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Tripartite relationship between gut microbiota, intestinal mucus and dietary fibers: towards preventive strategies against enteric infections

Tripartite relationship between gut microbiota, intestinal mucus and dietary fibers: towards... ABSTRACT The human gut is inhabited by a large variety of microorganims involved in many physiological processes and collectively referred as to gut microbiota. Disrupted microbiome has been associated with negative health outcomes and especially could promote the onset of enteric infections. To sustain their growth and persistence within the human digestive tract, gut microbes and enteric pathogens rely on two main polysaccharide compartments, namely dietary fibers and mucus carbohydrates. Several evidences suggest that the three-way relationship between gut microbiota, dietary fibers and mucus layer could unravel the capacity of enteric pathogens to colonise the human digestive tract and ultimately lead to infection. The review starts by shedding light on similarities and differences between dietary fibers and mucus carbohydrates structures and functions. Next, we provide an overview of the interactions of these two components with the third partner, namely, the gut microbiota, under health and disease situations. The review will then provide insights into the relevance of using dietary fibers interventions to prevent enteric infections with a focus on gut microbial imbalance and impaired-mucus integrity. Facing the numerous challenges in studying microbiota–pathogen–dietary fiber-mucus interactions, we lastly describe the characteristics and potentialities of currently available in vitro models of the human gut. dietary fibers, mucus, gut microbiota, enteric pathogens, in vitro gut models INTRODUCTION The human gastrointestinal tract (GIT) harbors a complex and diverse community of 10 trillion of microorganisms from almost all kingdoms of life consisting of bacteria, viruses, fungi, archaea and protozoa and collectively referred to as gut microbiota (Qin et al. 2010; Sender, Fuchs and Milo 2016). The healthy adult intestinal microbiota is composed of more than one hundred bacterial species per individual, mainly dominated by the Firmicutes and Bacteroidetes phyla followed by members from the Proteobacteria, Actinobacteria, Fusobacteria and Verrucomicrobia. This complex microbial ecosystem contributes to various essential functions for host physiology, including energy extraction from food through fermentation of dietary fibers (Morrison and Preston 2016), vitamin synthesis (Belzer et al. 2017) and development and maturation of the immune system (Kamada et al. 2013). Disruption in gut microbiota composition and activity (termed dysbiosis) can occur and have been associated with negative health outcomes, such as digestive or extra-intestinal diseases like for example inflammatory bowel disease (IBD) or metabolic syndrome (Lavelle and Sokol 2020). In particular, disrupted microbiome could promote the onset of enteric infections (Ghosh et al. 2011; Willing et al.2011) or at least increase their severity. Enteric disease has been and continues to be a major cause of morbidity and mortality worldwide, associated with high societal burden and economical losses (Buzby and Roberts 2009). Gram-negative bacteria, such as Escherichia coli, Salmonella enterica, and Campylobacter jejuni, are among the leading causes of human gastro-intestinal infections in the world (Kotloff 2017). Healthy intestinal microbiota contributes to host resistance to enteric infection through its involvement in the development of the host immune system and provision of colonization resistance. Mechanism of colonization resistance are not fully described yet but it is now acknowledged that commensal microorganisms can impede pathogen establishment by different means like secretion of antimicrobials, competition for carbon sources, micronutrients or intestinal niches, support of gut barrier integrity and induction of host immune responses (Chow, Tang and Mazmanian 2011; Kamada et al. 2013; McKenney and Pamer 2016). Interestingly, the process of infection itself results in disturbances of gut microbiota (Sekirov and Finlay 2009). Colonization resistance, microbiome community structure and niche occupation are crucial parameters during enteric infections that are modulated by two main drivers, namely mucus and diet (Sorbara and Pamer 2019). In order to colonize the intestinal epithelium, pathogens have to get through the mucus, a secreted gel layer produced by the specialized secretory goblet cells, providing a physical, chemical and biological line of defense for the host (Turner 2009; Peterson and Artis 2014). Furthermore, the mucus constitutes an endogenous source of energy substrates and acts as a biological niche for the mucus-associated microbiota, which greatly differs from the one found in the digestive lumen (Li et al. 2015). Due to its location at the interface between the intestinal lumen and the epithelium, an increasing number of studies have shown intestinal mucus act as a major modulator of human health (Martens, Neumann and Desai 2018). Diet also represents a key factor that directly shapes human gut microbiota (Makki et al. 2018). In particular, dietary fibers are defined as a source of carbohydrates resistant to digestion and absorption in the human small intestine that undergo partial or complete microbial breakdown and fermentation in the colon, thus providing a preferential dietary substrate for gut microbes (Kaoutari et al. 2013). Dietary interventions involving fibers have already shown their potential in humans in preventing/fighting disorders associated with gut microbial imbalance and/or impaired-mucus integrity such as inflammatory bowel diseases (IBD) (Wong, Harris and Ferguson 2016) and metabolic-associated disorders (Cotillard et al. 2013; Sonnenburg and Sonnenburg 2014). This review aims for the first time to give new insights into the potential use of dietary fibers as a mean to prevent enteric infections, by bringing together and critically discussing the new knowledge on inter-connections between three determinent factors of gut homeostasis, namely gut microbiota, dietary fibers and mucus layer. The first section of the review gives a general overview of dietary fibers and mucus polysaccharide structures and properties, highlighting their similarities and differences. The second section provides an overview of the interactions between dietary fibers, mucus and gut microbiota in health and disease situations. The following section sketches the current state of the art on the antagonistic properties of dietary fibers in human enteric infections. At last, the review discusses current challenges in this field of research and emphasizes the potential of in vitro human gut models to decipher the tripartite relationships between gut microbiota, mucus and dietary fibers. DIETARY FIBERS AND HUMAN MUCUS-ASSOCIATED POLYSACCHARIDES: CAN WE MAKE AN ANALOGY? Key differences and similarities between dietary fibers and mucus-polysaccharides are summarized in Table 1. Table 1. Similarities and differences between dietary fibers and mucus polysaccharides. . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability GH: Glycoside hydrolase; PUL: Polysaccharide utilization loci. Open in new tab Table 1. Similarities and differences between dietary fibers and mucus polysaccharides. . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability GH: Glycoside hydrolase; PUL: Polysaccharide utilization loci. Open in new tab Brief overview of dietary fibers and mucus polysaccharides structures and properties Dietary fibers Structure A variety of definitions for dietary fiber have been promulgated by scientific and regulatory agencies worldwide. According to the Codex Alimentarius, dietary fibers mean carbohydrate polymers with 10 or more monomeric units, which are not hydrolysed by the endogenous enzymes in the small intestine of humans (Codex Alimentarius 2010; Porter and Martens 2017). They include carbohydrate polymers naturally occurring in the food as consumed, as well as polymers obtained from food raw materials or chemically synthetized that have shown a physiological effect of benefit to health (Codex Alimentarius 2010; Jones 2014). The definition could be extented to oligosaccharides containing between 3–9 monomeric units, depending on national authorities’ recommendations (Codex Alimentarius 2010). Dietary fibers can be divided into subgroups according to their origin, structure and physicochemical properties (Porter and Martens 2017). Nevertheless, most dietary fibers consumed by humans are generally of plant origin and found in different proportions in fruits, vegetables, legumes, cereals, nuts and seeds. Some of them are also derived from animals, fungi or bacteria. This is the case for human-milk oligosaccharides (HMOs), mannans from yeasts, chitin from fungi and exopolysaccharides from bacteria, which are found in fermented foods such as bread, cheese or yogurt (Porter and Martens 2017). Dietary fibers can also be divided into either oligosaccharide (between 3 and 10 monomeric units) or polysaccharides. Among the latter, there are different types (I to V) of resistant starches. They are called this way because their constitutive α(1→4) linked D-glucose polymer cannot be hydrolyzed by human amylases in the time between ingestion and reaching the large intestine (Fuentes-Zaragova et al. 2010). Then, there are non-starch polysaccharides which comprise cellulose (polymer made of β(1→4) linked D-glucose units), hemicelluloses (set of branched polysaccharides based on xylose, mannose, arabinose, glucose), fructans like inulin (β(2→1) linked fructose units) and pectins (complex polysaccharides composed of mostly galacturonic acid, galactose, arabinose and rhamnose) (Deehan et al. 2017). Dietary fibers comprise also resistant oligosaccharides made of fructose (FOS), galactose (GOS), xylose (XOS), mixtures of arabinose and xylose (AXOS) or pectic sugars (POS) (Deehan et al. 2017). In consequence, there is a tremendous diversity of plant-derived dietary fibers that differ in their sugar composition, type of linkage between sugars, degree of polymerization or branching; these structural characteristics impact dietary fibers with various properties, notably crystallinity, viscosity or solubility. The latter is particularly relevant for efficient and rapid fermentation by microorganisms (Holscher 2017). Dietary fiber intake and health effects Dietary fibers intake varies substantially among countries. Westernised diets of industrialised countries are depleted in fibers in favor of animal protein, fat, sugar and starch, while non-industrialised rural communities have greater fibers intake through fibrous plant-rich diets (De Filippo et al. 2010; Schnorr et al. 2014). Investigations into dietary habits revealed that on average adults consume between 12–18 grams, 14 grams and 16–29 grams of fibers per day in the USA, United Kingdom and Europe, respectively (EFSA Panel on Dietetic Products 2010; King, Mainous and Lambourne 2012; Holscher 2017). These dietary amounts are below USDA's recommendation of 25 grams for women and 38 grams for men up to 50 years of age (Jones 2014; Holscher 2017). The beneficial effects of dietary fibers on health are now widely recognised. They have direct physiological benefits such as increasing the volume of faecal bulk, decreasing the intestinal transit time, lowering glycaemia and cholesterol levels as well as suppressing adiposity and the associated parameters of metabolic syndrome (Dhingra et al. 2012; Zou et al. 2018). Populations with higher dietary fibers intakes present a lower incidence of immune dysregulation, with a lower risk to develop asthma, allergies, IBD, diabetes and colorectal cancer (Burkitt et al. 1972; Sonnenburg and Sonnenburg 2014). Insufficient dietary intake in industrialised countries has been associated with a disrupted host-microbiota relationship leading to an increased incidence of inflammatory-related disorders (Makki et al. 2018; Zou et al. 2018). Intestinal mucus polysaccharides Structure Continuously produced and secreted mainly by goblet cells, intestinal mucus varies in terms of structure and composition according to the considered mammalian species (Hugenholtz & de Vos 2018; Etienne-Mesmin et al. 2019). In human, mucus is found throughout the entire GIT of human from the stomach to the large intestine, with its thickness and structure varying depending on the segment of the digestive tract considered, but also with cross-sectional differences. Especially, in the colon, the mucus layer shows a double-layer structure, with an inner layer firmly attached to the epithelium, and an outer layer, constantly shed into the lumen and showing an expended volume due to proteolytic activities provided by the host but also by commensal bacteria (Atuma et al. 2001; Ijssennagger, van der Meer and van Mil 2016). Mucus is a complex viscoelastic adherent secretion composed of water, electrolytes, lipids and proteins. The main structural components of mucus (around 5%) are large glycoproteins called mucins. The core of O-linked glycans is formed by a combination of three sugars, galactose, N-acetylgalactosamine and N-acetylglucosamine (Holmén Larsson et al. 2009; Juge 2012), to which different chains of glycans can be attached. The terminal monosaccharide is usually fucose or sialic acid (Holmén Larsson et al. 2009; Juge 2012). Oligosaccharide chains can also be sulfated, especially in colonic regions (Rho et al. 2005). The glycan moieties are conjugated to proteins, mostly by O-link to serine and threonine but also by N-link to asparagine (Porter and Martens 2017). To date, several MUC genes have been described in human and named based on their discovery's order. Some of them belong to the secreted gel-forming mucin family, while others are classified in the membrane-associated family. Host-secreted mucin 2 (MUC2) glycoprotein is a major constituent of human small intestinal and colonic mucus, while MUC1, MUC5AC, and MUC6 are predominant in the stomach (Sicard et al. 2017). Main functions The mucus barrier has several functions, a primary one being the lubrication of the epithelium helping the progress of food material along the GIT Mucin proteins are also glycosylated polymers that constitute a carbon and energy source for the growth of resident gut microbiota (Tailford et al. 2015). Accumulating evidences demonstrate a crucial role of the mucus layer in maintaining gut homeostasis (Martens, Neumann and Desai 2018). Notably, it contains a large variety of host antimicrobial molecules (e.g. α and β defensins, IgA and IgM) that are retained within the net-like polymer structure of mucin proteins. In close collaboration with the immune system and the gut microbiota, the mucus is the first line of defense against encroaching bacteria that can breach and persist on the epithelial surface (Johansson and Hansson 2016). In particular, bacteriophages, bacteria-killing viruses, are able to interact with mucus and studies in mice demonstrated that phage particles are 4-fold more concentrated in mucus layer compared to the lumen content (Barr et al. 2013). Recent studies showed that phages represent key players in limiting bacteria persistence close to the epithelium and may play an important role in gut microbiota homeostasis (Almeida et al. 2019; Rasmussen et al. 2020; Sausset et al. 2020). The mucus layer therefore has a dual role. On one hand, it lubricates the intestine and acts as a defensive barrier against harmful aggressors. On the other hand, it provides an ecological niche for bacteria by providing adhesion sites and nutrients, as described in section II (Interactions of dietary fibers and mucus-associated polysaccharides with human gut microbiota). Similarities and differences between dietary fibers and mucus carbohydrates Origin and metabolism The first major distinction between dietary fibers and mucus carbohydrates is their origin. While dietary fibers are provided only from the external environment through the diet, mucus polysaccharides originate from the host itself. Consequently, dietary fibers uptake is inconstant and varies in quantity and composition throughout daytime, life and individual, while mucus polysaccharides are chemically more homogeneous and always present as an energy source for the microbial ecosystem. Nonetheless, dietary fibers and mucus carbohydrates are both non-digestible by host enzymes but can be metabolized in the intestine by the resident members of the gut microbiota and further fermented to yield short chain fatty acids (SCFAs) (mainly acetate, butyrate and propionate) and gases (e.g. dihydrogen, carbon dioxide, methane and hydrogen sulfide) (Morrison and Preston 2016). As dietary fibers, mucus polysaccharides can also be fermented in the digestive lumen due to constant shedding of the mucus layer (Johansson 2012). Nevertheless, SCFAs, especially butyrate, resulting from mucin cross-feeding provide an energy source directly usable by nearby colonocytes (Ouwerkerk, de Vos and Belzer 2013). Structure As a result of different linkages and more than 20 possible numerous monomeric units, the structure of carbohydrates is amazingly diverse as illustrated by dietary fibers heterogeneity (Porter and Martens 2017). By comparison, mucus carbohydrates constitute a more restricted group of polysaccharides with only six possible monomeric sugar units (galactose, N-acetylgalactosamine, N-acetylglucosamine, mannose, fucose and sialic acid) (Etienne-Mesmin et al. 2019). However, the diversity of the mucus polysaccharide structures is huge and can offer structural similarities with dietary fibers (Porter and Martens 2017). While the sugar monomers and linkages are different, there is a structural similarity in term of polymerisation, high cross-linkage, with linkages solely and specifically broken down by certain bacteria. HMOs from human breast milk illustrate well the tight line between dietary fibers and mucus polysaccharide structure. They are composed of repeated and variably branched lactose or N–acetyl-lactosamine units often decorated with sialic acid and fucose monosaccharides (Kunz et al. 2000; Ninonuevo et al. 2006). These structures share common patterns with human blood group antigens, which can be recovered in the mucus (Etienne-Mesmin et al. 2019). Actually, most humans (e.g. 80% of North Americans and Europeans) called secretors, express the fut2 gene and consequently harbor blood groups antigens on mucin-O linked glycans (Kelly et al. 1995). During early infancy, HMOs can be considered as the sole source of dietary fibers (Koropatkin, Cameron and Martens 2012). Thus, at an early stage, HMOs intake initiate the use of mucus polysaccharides as a nutritive source by the infant gut microbiota (Koropaktin, Cameron and Martens 2012). Interactions of dietary fibers and mucus-associated polysaccharides with human gut microbiota Substrate accessibility and microbial niches Dietary fibers Substrate accessibility is the first determinant parameter in microbial colonisation of dietary fibers and subsequent degradation and fermentation of their constituting carbohydrates. Restricted to the intestinal transit time, dietary fibers fermentation in the gut can take place in-between 18 hours up to 60 hours (De Paepe et al. 2020). For effective dietary fibers fermentation, poly- or oligosaccharide accessibility is therefore crucial. Soluble fibers, such as oligosaccharides (e.g. FOS), are free and easily accessible to microbes in the lumen (Koropatkin, Cameron and Martens 2012). Thus, they can be easily metabolised in the proximal GIT (mainly ileum and proximal colon), especially in normal transit individuals (Koropatkin, Cameron and Martens 2012). Insoluble fibers consist of a complex tridimensional network of different polysaccharides (for example, plant cell wall particles made of cellulose, hemicellulose and pectins) that renders these carbohydrates less accessible to microorganisms. Hence, they are mainly hydrolysed and fermented later in the distal colon where the microbial bacteria richness is the highest (Koropatkin, Cameron and Martens 2012). By themselves, insoluble dietary fibers particles present in the intestine can be considered as microbial niches since they face an ecological succession of microbial colonisers able to degrade them gradually along their progression through the GIT (De Paepe et al. 2020). The colonising microbial actors are dietary fibers specific (Leitch et al. 2007) and in vitro study of these dynamic communities could be highly predictive of their fiber-degrading capacities (De Paepe et al. 2019). For instance, using anaerobic batch cultures of faecal microbiota, De Paepe and colleagues showed that colonization of wheat bran particles by Bacteroides ovatus/stercoris, Prevotella copri and Firmicutes was associated with an increase in fermentation activity (De Paepe et al. 2019). Similarly, Leitch and colleagues found that resistant starch particles were enriched in Ruminococcus bromii, a starch-colonizing and degrading bacterium (Leitch et al. 2007; Ze et al. 2012; Vital et al. 2018). Some coloniser species, such as Bacteroides thetaiotaomicron and Roseburia intestinalis could even form biofilms at the surface of dietary fibers particles in the luminal digestive content (Mirande et al. 2010; Li et al. 2015). Mucus polysaccharides The mucus layer is also considered a well-known microbial niche in the GIT where colonisation is necessary for resident microorganisms to maintain their presence (Ouwerkerk, de Vos and Belzer 2013). Bacterial mucinases, described both in commensal bacteria and in pathogenic strains, allow access to the mucus layer by proteolysis of the core of mucin proteins then enabling bacterial colonisation (Etienne-Mesmin et al. 2019). To counterbalance mucinase action and maintain its net-like structure that retains the microbiota, the mucus contains structural proteins including protease inhibitors that protect the mucus from extensive degradation (Bansil and Turner 2018). Numerous studies have demonstrated that microbiota communities from the digestive lumen differ in term of composition and abundance from the mucus-associated ones, supporting differences in term of nutrient availability including oxygen and carbohydrate substrates (Chassaing and Gewirtz 2019). Compared to the digestive lumen, the human colonic mucus layer displays a markedly higher level of Firmicutes, Actinobacteria and Proteobacteria and a lower level of Bacteroidetes (Donaldson, Lee and Mazmanian 2016; Richard et al. 2018; Chassaing and Gewirtz 2019; Vuik et al. 2019). Especially, mucosal communities are highly enriched in Bacteroides acidifaciens, Bacteroides fragilis, the mucin-degrader Akkermansia muciniphila and in species belonging to the Lachnospiraceae taxa (Donaldson, Lee and Mazmanian 2016; Pereira and Berry 2017). Niche accessibility also determines a gradient in microbial colonisation of the mucus layer from the digestive lumen to the intestinal epithelium. Densely colonised, the colonic outer layer has a rapid turnover rate, with a renewal in one hour in mouse colon (Johansson 2012; Johansson, Sjövall and Hansson 2013) and bacterial growth rate has to keep in pace for their mucosal prevalence (Rang et al. 1999). Firmly attached to the epithelial cells, the inner colonic layer has for long been believed to be devoid of bacteria in accordance with its more constraining physical properties (Johansson, Sjövall and Hansson 2013). However, single-cell imaging at tissue scale in mice recently revealed the presence of bacteria in close proximity of the epithelium (Earle et al. 2015). Among them, Segmented Filamentous Bacteria have been identified in many vertebrate intestines (humans, rodents and chickens) as commensal strains able to invade this mucus layer without invading the host (Chen et al. 2018; Hedblom et al. 2018; Ladinsky et al. 2019). Recognition and binding strategies Dietary fibers Among the fiber-degrading bacteria isolated from the human gut, the Bacteroides genus has been the most extensively studied. Several members of this genus (e.g. Bacteroides thetaiotaomicron, Bacteroides xylanisolvens, Bacteroides intestinalis, Bacteroides ovatus) are able to forage an important repertoire of glycans in the gut (Kaoutari et al. 2013). These bacteria produce cell-surface enzyme systems that allow them to convert dietary fibers into oligosaccharides that are then internalised into the cell and further hydrolysed into simple sugars. All of these enzyme systems have the same cellular organisation and operating mode as the Starch-Utilization System (Sus) of Bacteroides thetaiotaomicron in which substrate recognition is ensured by the cell-surface protein called SusD (Martens et al. 2009). Each enzyme system is dedicated to a specific polysaccharide and contains a SusD-like protein recognising fructans (Sonnenburg et al. 2010), xylans (Rogowski et al. 2015, Despres et al. 2016a), xyloglucans (Larsbrink et al. 2014), and pectins (Martens et al. 2011; Despres et al. 2016b). Among the Firmicutes, the fiber-degrading bacteria belonging to the Ruminococcus genus also rely on very complex enzyme complexes called cellulosomes (Ruminococcus champanellensis, Ruminococcus flavefaciens) or amylosomes (Ruminococcus bromii) for substrate recognition and binding (Ben David et al. 2015; Cann, Bernardi and Mackie 2016). Ruminococcus albus and Ruminococcus flavefaciens have also been shown to attach to cellulose via type IV pili (Rakotoarivonina et al. 2002; Vodovnik et al. 2013). Studies of complex polysaccharide degrading apparatus in Firmicutes species (other than Ruminococcus) are very limited. Recent studies have shown that Roseburia intestinalis and Monoglobus pectinilyticus belonging to the Firmicutes phylum display the appropriate gear to be mannan and pectin primary degraders, respectively (Kim et al. 2019; La Rosa et al. 2019). Sheridan and colleagues also reported that Roseburia spp. and Eubacterium rectale possess their own Gram-positive polysaccharide utilization loci allowing complex glycans degradation (Sheridan et al. 2016). Otherwise, Firmicutes species are known to rely on a diverse array of transporters (such as ABC transporters) to import smaller sugars for intracellular processing. In particular, ABC transporters own an extracellular substrate-binding site for sugar recognition (Chen 2013). Mucus polysaccharides Microorganisms have developed different binding strategies to mucin. As for dietary fibers, Bacteroides species recognise mucus polysaccharides via a SusD-like protein belonging to the enzyme system involved in mucin glycan degradation (Martens et al. 2009; Sonnenburg et al. 2010). Bacteria can also use specialised cell-surface adhesins or lectins. For instance, the well-known mucus-binding protein MUB, produced by Lactobacillus reuteri ATCC 53608, is able to interact with terminal sialic acid of mucus (Etzold et al. 2014). Another strategy is to employ appendages such as pili and flagella. Lactobacillus rhamnosus SpaC adhesins are localised along the complete length of the bacterial pili. This is supposed to reinforce mucin-binding strength (Reunanen et al. 2012). As their surface counterparts, these pili adhesins also recognise precise carbohydrate patterns (Troge et al. 2012). Interestingly, some adhesins have been shown to recognise patterns encountered in both mucins and dietary fibers, likely due to structural similarities (Cooling et al. 2015; Dotz and Wuhrer 2016; Taylor et al. 2018). Hence, in addition to binding to mucin, a Lactobacillus plantarum mannose-specific adhesin binds also to glycan structure on yeast cell wall and Bifidobacterium infantis adhesin recognises HMOs (Pretzer et al. 2005; Garrido et al. 2011). Carbohydrate metabolism by human gut microbiota Specialized carbohydrate-active enzymes Enzymes involved in carbohydrate metabolism are named CAZymes (for Carbohydrate-active enzymes) and represent 2.6% of the total enzymes encoded by the human gut microbiome (Turnbaugh et al. 2008). Of note, carbohydrate metabolism is almost exclusively supported by the gut microbiome, with around 10 000 CAZymes found in the genome of 177 reference gut bacteria, compared to only 8 to 17 CAZymes in the human genome (Kaoutari et al. 2013; Kaoutari et al. 2014). In the CAZyme super family, glycoside hydrolases (GHs) hydrolyse the glycosidic bond between two or more carbohydrates or between a carbohydrate and a non-carbohydrate moiety, whereas polysaccharide lyases (PLs) cleave uronic-acid containing polysaccharides via a β-elimination mechanism and carbohydrate esterases (CEs) catalyze the de-O or de-N-acylation of substituted saccharides (Kaoutari et al. 2013). Based on their sequences, GHs are classified into 167 families, PLs into 40 families and CEs in 17 families (http://www.cazy.org/). CAZymes are highly specific and often associated with the degradation of one type of linkage (Snart et al. 2006, Chassard et al. 2010; Hamaker and Tuncil 2014). In addition to catalytic modules, CAZymes often contain carbohydrate-binding modules (CBM) that keep them bound to the substrate (Bolam et al. 1998; Boraston et al. 2004). CBMs have been classified into 86 families according to their amino acid sequence and their substrate specificity (http://www.cazy.org/). Some families contain plant dietary fibers specialised CAZymes (e.g. GH5, GH6, GH9, GH10, GH11, GH12, GH28, GH44, GH45, GH74, GH88, GH105, PL1, PL2, PL3, PL4, PL9, PL10, PL11, PL15) while other contain mucus polysaccharide specialised ones (e.g. GH20, GH29, GH33, GH42, GH84, GH85, GH89, GH95, GH98, GH101, GH112, GH129) (Hamaker and Tuncil 2014). CAZymes relative to dietary fibers utilization are well characterised (White et al. 2014, Grondin et al. 2017). CAZymes involved in mucin metabolism have also been functionally characterised in resident members of the gut microbiota able to feed on mucins, including Akkermansia muciniphila, Bacteroides thetaiotaomicron, Bacteroides fragilis, Bifidobacterium bifidum and Ruminococcus gnavus, as recently reviewed (Tailford et al. 2015, Ndeh and Gilbert 2018). Of note, β-galactosidases from the GH2 family has been associated with the degradation of both mucus polysaccharides and dietary fibers (Turnbaugh et al. 2009). If most CBMs are involved in enzyme binding to dietary fibers polysaccharides, CBM in families 32, 40, 47 and 51 also recognise mucin carbohydrates (as reviewed in Ficko-Blean and Boraston 2012). Vertical ecological relationships in carbohydrate degradation Dietary fibers According to the degree of dietary fibers complexity, several CAZymes are needed for their complete hydrolysis (Martens et al. 2011) and the required time for their degradation in the human gut will vary (Sanchez et al. 2009). Such degradation process can be sequential and involves several different microorganisms. For example, Bifidobacterium spp. commonly need primary degradation of starch and xylan by species like Ruminoccocus bromii and Bacteroides ovatus to use the resulting malto- and xylo- oligosaccharides, respectively (Turroni et al. 2018). The relationship by which one microorganism allows another to feed is called cross-feeding (Falony et al. 2006). This mechanism is possible since GHs, PLs and CEs are typically secreted or cell surface-associated enzymes whose activity results in the availability of the released mono- or oligosaccharides for uptake by the hydrolase-producing organism itself but also by nearby bacteria. In the cross-feeding chain, microorganisms required to initiate the degradation are called primary degraders and are defined as ‘bacteria that are able to detect and degrade a complex carbohydrate owing to enzymatic equipment that is missing in other species’ (Kaoutari et al. 2013). If a primary degrader outcompetes the other organisms by being the most efficient in degrading a particular polysaccharide, hence being essential for further degradation by the resident microbiota, it is called bacteria with keystone functions or keystone species (Ze et al. 2012). For example, Ruminoccocus bromii has been regularly described as a resistant starch keystone species, and its absence within the ecosystem is associated with resistant starch indigestibility by the host (Ze et al. 2012; Vital et al. 2018). Mucus polysaccharides Mucus polysaccharides are also concerned by this cross feeding strategy (Png et al. 2010; Marcobal et al. 2013; Egan et al. 2014), since a combination of enzymatic activities from several mucolytic bacteria is required to complete mucin degradation (Derrien et al. 2010; Marcobal et al. 2013). As the O-glycans are covalently attached to the mucin peptides, the peripheral residues are the first targets for GH enzymes. Removal of sialic acid, fucose and glycosulfate is necessary before degradation of O-glycan chains (Corfield 2018). Bacteroides thetaiotaomicron, Bacteroides ovatus, Prevotella spp. strain RS2, Bifidobacterium breve UCC2003, or Bacteroides fragilis all possess mucin-desulfating sulfatases or glycosulfatases and are thus potential primary degraders (Salyers et al. 1977, Berteau et al. 2006, Benjdia et al. 2011; Egan et al. 2016, Praharaj et al. 2018). Facing the huge amount of constantly renewed substrate, there should exist some redundancies in mucus degrading capabilities between species. This is proven by the high numbers of primary degraders. Akkermansia muciniphila could be considered as a species that fulfills a keystone function in mucin degradation. Once the peripheral residues have been removed, the remainders of the O-glycan chains can be hydrolysed. The released saccharides, such as N-acetylglucosamine, N-acetylgalactosamine, galactose, fucose and N-acetylneuraminic acid (sialic acid) can be used by the bacterial degrader itself or by other resident bacteria (Bjursell, Martens and Gordon 2006; Martens, Chiang and Gordon 2008; Sonnenburg et al. 2010). Commensal Escherichia coli and Enterococcus are examples of cross-feeders unable to feed on mucin without microbial pre-digestion (Sicard et al. 2017). Horizontal ecological relationships in carbohydrate degradation Inside the ecological niche, microorganisms can also be classified as generalists or specialists based on their CAZyme equipment. Generalists can use a large number of different carbohydrate structures. When comparing the two main phyla inhabiting the human gut, Bacteroidetes are usually considered more generalists than Firmicutes (Kaoutari et al. 2013). With 308 CAZyme genes, Bacteroidetes thetaiotaomicron is a good example of a generalist species (Martens et al. 2008). On the opposite, other bacteria using relatively few polysaccharides, such as Ruminoccocus bromii (starch degrader only) and Roseburia inulinivorans (inulin degrader), are termed as ‘specialists’ (Koropatkin, Cameron and Martens 2012). Thanks to their CAZyme arsenal, generalist microorganisms can shift their metabolism depending on the diet, and are thought to be highly adaptable to different conditions depending on dietary fibers availability (Koropatkin, Cameron and Martens 2012). When several carbon sources are available, generalists exhibit hierarchical polysaccharide preferences (Rogers et al. 2013). For instance, Bacteroides thetaiotaomicron prioritises dietary fiber over mucus polysaccharide consumption (Kashyap et al. 2013), but this sense of priority is not shared by all microorganisms. Inversely, Bacteroides massiliensis and Bacteroides fragilis are more oriented towards mucosa-associated glycans (Pudlo et al. 2015). Then, large differences can be observed between species of a same genus. As an example, Bacteroides thetaiotaomicron and Bacteroides ovatus, which have 96.5% identity in their 16S rRNA gene sequences have less than one-third of their sus-like systems genes in common (Martens et al. 2011). Some generalists can even switch between dietary fibers and mucus polysaccharides (Sonnenburg 2005). This substrate versatility has been primarily described for Bacteroides species because of their large repertoire of CAZymes. In particular, a fiber-deprived diet forces the versatile species to use the pool of indigenous host glycans present in the mucus (Earle et al. 2015; Desai et al. 2016). This implies that, driven by the increase in selection pressure, strains can rapidly adapt to the mucus niche by switching their transcriptional repertoire to mucus polysaccharides consumption and/or acquiring new mucus polysaccharide degrading functions (Li et al. 2015). Low-fiber diets increase the expression of microbiota O-glycan CAZymes (Sonnenburg 2005), as well as mucinases (Desai et al. 2016). This results in increased inner mucus layer permeability as illustrated in murine models (Schroeder et al. 2018). Studies have shown that dietary fibers supplementation can reverse this loss of mucus integrity (Schroeder et al. 2018). Lastly, ‘versatile’ species can be opposed to ‘mucus specialists’ which rely on mucus polysaccharides as sole carbon source (Cockburn and Koropatkin 2016). Akkermansia muciniphila is a good example of a mucus specialist (Derrien, Belzer and de Vos 2017). Tailford and colleagues have reviewed bacteria with known mucus-degrading capabilities (Tailford et al. 2015). Effect of carbohydrates on gut microbiota composition and sources of variability Well-known effect of dietary fibers on the gut microbiota Large observational studies taught us that dietary fibers consumption affects human gut microbiota composition by evolutionary means (Yatsunenko et al. 2012; Clemente et al. 2015; Smits et al. 2017). The effect of short-term intervention studies appears much more modest, less permanent and with higher inter-subject variability, suggesting a day-to-day adaptation of the gut microbiota to the diet and dietary fibers in particular (Turnbaugh et al. 2009; Wu et al. 2011; Cotillard et al. 2013). Interestingly, most of these studies have focused on the effect of a specific fiber rather than using a rich/low fiber diet. The reported effects vary widely depending on the type of fiber investigated (Martínez et al. 2010), its crystalline form (Tester, Karkalas and Qi 2004; Lesmes et al. 2008), the degree of polymerisation (Hughes et al. 2008; Sanchez et al. 2009; Van den Abbeele et al. 2011; Zhu et al. 2017) and the dose (Bouhnik et al. 1999; Davis et al. 2011). Nevertheless, it is very tempting to associate specific microbiota variations to enrichment of microbial groups with the corresponding dietary fibers degradation capabilities. For instance, resistant starch supplementation has been found to increase Ruminoccocus bromii population, a well-known resistant starch degrader, in human faeces (Salonen et al. 2014; Vital et al. 2018). However, fiber consumption can influence microbiota composition by other indirect physiological effects. For instance, dietary fibers fermentation generates SCFAs leading to a lower colonic pH. Thus, selecting microbial groups resistant to low pH (Scott, Duncan and Flint 2008; Duncan et al. 2009). Dietary fibers are also able to trap bile salts (Story and Kritchevsky 1978), slow glucose absorption and modulate the immune system (Hooper, Littman and Macpherson 2012), mechanisms by which the microbiota composition is in turn affected. There is a huge discrepancy between individuals in terms of fiber-degrading capacities and effects of dietary fibers on their microbiota and this mainly relies on dietary habits (Ze et al. 2012). Multiple independent studies in humans have demonstrated stark differences in terms of microbiota composition and activity between urbanised populations consuming low fiber diets and rural populations, westernisation being characterized by a lower bacterial diversity, a lower Prevotella/Bacteroides ratio and a loss of CAZymes genes (Yatsunenko et al. 2012; Clemente et al. 2015; Martínez et al. 2015; Smits et al. 2017; Makki et al. 2018). Studies have shown that even rarely ingested dietary fibers (Kitahara et al. 2005; Hehemann et al. 2010; Hehemann et al. 2012) or long-considered unfermentable ones (De Filippo et al. 2010) can be catabolised by the gut microbiota of accustomed populations. Japanese consuming diets enriched in uncooked seaweed possess in their microbiota very rare genes (acquired from the environmental bacterium Bacteroides plebeius) encoding porphyranase and agarase enzymes enabling their digestion (Kitahara et al. 2005; Hehemann et al. 2010; Hehemann et al. 2012). Likewise, long-term over-generational consumption of (previously) indigestible dietary fibers can select for new specific degrading capabilities of the microbiota in a specific population (Hehemann et al. 2012). First evidences of a link between mucus polysaccharides and gut microbiota composition? Few pieces of evidences point out the influence of mucus polysaccharides on gut microbiota composition. Mice deficient in core 1-derived O-glycans exhibit a dysbiotic faecal microbiota (Sommer et al. 2014) and mice deficient in core 1- and core 2-derived O-glycans develop microbiota-dependent colitis (Bergstrom et al. 2016). However, since modifications of mucin glycosylation patterns affect mucus barrier function, it appears challenging to decipher whether this dysbiotic microbiota results from direct modulation of microbial communities or from other induced phenomenon, such as inflammation. More interestingly, Wacklin and colleagues have shown that human ABO blood groups, expressed in mucus O-linked glycans, are also involved in intestinal microbiota composition differences (Wacklin et al. 2011). Specifically, faecal microbiota from individuals harboring the B antigen on their mucosal surface (secretor B and AB) differed from the non-B antigen groups (Mäkivuokko et al. 2012). A study performed in mice confirmed these observations with differences in microbiota composition according to the presence or not of blood groups antigens, but also gave additional information on the effect of dietary fibers. Differences in blood group antigen microbiota were noticed only when mice diet was depleted in dietary fibers, suggesting the impact of mucus glycosylation on microbiota composition gains importance when mucus polysaccharides are the sole carbohydrate type left (Kashyap et al. 2013). GUT MICROBIOTA, DIETARY FIBERS AND INTESTINAL MUCUS: FROM HEALTH TO DISEASES? A number of studies highlight the crucial role of gut microbiota in human health and disease. A persistent imbalance in gut microbial communities termed dysbiosis has been associated with many diseases, including infections, allergy, asthma, IBD, obesity, diabetes, liver disease and colorectal cancer (Gong and Yang 2012). For inflammatory-related disorders (such as metabolic disorders, IBD or colorectal cancer), it remains challenging to identify common features in the observed dysbiosis. Within a specified pathology, results in terms of microbiota composition varied between the studies since microbiota analysis is highly dependent on the sampling, e.g. type of population, gastrointestinal location or disease stage (Lucas, Barnich and Nguyen 2017; Cuevas-Sierra et al. 2019). Still, lower microbiota diversity and shift in microbial populations are recurrent factors. Disease susceptibility can be transferred in axenic rodent by microbiota transplantation, highlighting the importance of dysbiosis in the onset of certain pathologies (Bäckhed et al. 2007; Turnbaugh et al. 2008; Ferreira, Willing and Finlay 2011; Vrieze et al. 2012; Liou et al. 2013; Zackular et al. 2013). However, the mechanisms by which the intestinal microbiota participate in these pathologies are still debated; some hypotheses have been proposed including altered energy supplies for the colonocytes, stool bulking, intestinal transit, modulation of the immune system, human gene expression and cell differentiation (Brownawell et al. 2012). In addition, regarding the thin equilibrium between mucus as a protective barrier and its host, defects in mucus integrity have been associated with many of these pathologies including the aforementioned inflammatory-related diseases (Ouwerkerk, de Vos and Belzer 2013, Corfield 2018, Etienne-Mesmin et al. 2019). As detailed below, increased risks of metabolic disorders, IBD and colorectal cancer have been inversely correlated to dietary fibers intakes. Although only little mechanistic data explain how fibers can prevent these pathologies, it is a worthy strategy to explore. One means by which dietary fibers supplementation could improve these conditions is by supporting microbiota diversity (Brownawell et al. 2012). Another hypothesis is related to the positive link between dietary fibers intakes and mucus barrier integrity. First, insoluble dietary fibers mechanically stimulate the intestinal epithelium to secrete mucus (McRorie and McKeown 2017). Second, SCFAs produced during dietary fibers fermentation also play a role in maintaining a balanced mucus production (Wrzosek et al. 2013). Finally, by preventing the ‘versatile’ part of the gut microbiota from shifting towards the utilization of mucus polysaccharides, dietary fibers intakes also act to maintain the mucus layer integrity (Desai et al. 2016; Schroeder et al. 2018; Zou et al. 2018). Current evidences for the relationship between dietary fibers, mucus and intestinal-inflammatory-related disorders Considering the close relationship between dietary fibers and mucus polysaccharides in the gut homeostasis, this section gives a current state of the art on their role in the frame of three intestinal-inflammatory-related pathologies, namely, obesity and metabolic disorders, IBD and colorectal cancer. Obesity and metabolic-related disorders Dietary fibers Metabolic disorders and obesity have been associated with dietary fibers intakes in humans (Fuller et al. 2016; Makki et al. 2018) and supplementation with dietary fibers improves the symptoms (Fechner, Kiehntopf and Jahreis 2014; Myhrstad et al. 2020). Interestingly, individual response to dietary fibers intervention depends on gut microbiota diversity prior to intervention, low response being associated with low microbiota diversity (Cotillard et al. 2013; Zeevi et al. 2015). These pathologies have also been linked to altered representation of bacterial genes and metabolic pathways involved in the processing of carbohydrates, including CAZymes (Turnbaugh et al. 2008). Even if dietary fibers degrading bacteria are depleted in metabolic disorders (Makki et al. 2018), the gut microbiome of genetically-induced obese mice is still more efficient in extracting energy from food compared to the microbiota of wild-type mice fed the same diet (Turnbaugh et al. 2006). In obese humans, increase proportion in the food of more easily degradable/fermentable substrates (together with reduced fiber intakes) may give a benefit to certain microbes, in relation to the gut microbiota dysbiotic state (Zmora et al. 2019). The improvement in metabolic disorders and obesity induced by dietary fibers supplementation could thus result from multiple effects in relation to microbiota modulation, notably SCFAs generation. Administration of SCFAs inhibits diet-induced obesity and improves metabolic syndrome in mice (Kimura et al. 2013; Den Besten et al. 2015; De Vadder et al. 2016), However, the beneficial effect of SCFAs on metabolic disorders is still debated as SCFAs are notably suggested to participate in energy uptake regulation (Janssen and Kersten 2015; Dabke, Hendrick and Devkota 2019). Mucus polysaccharides High-fat/low fiber diets have been shown to increase plasma lipopolysaccharide levels in mice (Cani et al. 2007) and humans (Romaní-Pérez, Agusti and Sanz 2017) which could incriminate epithelial barrier dysfunction. Studies investigating more precisely mucus integrity during obesity and metabolic disorders revealed decreased thickness and increased mucus permeability and microbiota encroachment (Chassaing, Ley and Gewirtz 2014; Chassaing et al. 2015; Tomas et al. 2016; Chassaing et al. 2017a). Some additional evidences point towards microbiota involvement in these observed mucus defect, as illustrated by the high number of studies involving the mucin specialist Akkermansia municiphila. First, Akkermansia muciniphila is less abundant in the intestinal microbiota of both genetic and diet-induced obese and diabetic mice, as well as in obese patients when compared to the faecal microbiota of healthy individuals (Everard et al. 2013; Shin et al. 2014). In mouse models of obesity and metabolic disorders, Akkermansia muciniphila treatment or oral administration of the Amuc_1100 bacterial outer-membrane protein from Akkermansia muciniphila restored the epithelial barrier defects and improved weight control (Plovier et al. 2017). These positive effects of Akkermansia muciniphila supplementation have recently been confirmed in overweight/obese insulin-resistant human individuals (Depommier et al. 2019). A recent mechanistic study in mice revealed that pasteurized Akkermansia muciniphila was able to increase faecal energy contents in decreasing gene expression of glucose and fructose intestinal transporters (Depommier et al. 2020). Of great interest, administration of Akkermansia muciniphila also increased goblet cells numbers and mucus production in the gut of mice fed a high fat diet (Shin et al. 2014). This has been highlighted as a probable means for the bacteria to maintain their carbon energy source in the gut (Van den Abbeele et al. 2011). Taken together, these data imply that specific gut bacteria enrichment or depletion could be intimately linked to the mucus defect observed when consuming a low fiber diet, and suggest that a long term low fiber diet pushes microorganisms toward mucus consumption, leading to mucus erosion. Some evidence has been already obtained in mice where a low-fiber diet drove a dysbiosis responsible for mucus defects (Schroeder et al. 2018; Zou et al. 2018). These defects could be prevented by transplanting a non-dysbiotic microbiota from fiber-fed mice (Schroeder et al. 2018) or by inulin supplementation in a microbiota-dependent manner (Zou et al. 2018). Inhibiting mucus consumption by reverting to adequate dietary fibers intakes could be a proper strategy for obese or metabolic syndrome patients whose microbiota diversity is not yet beyond reach. Inflammatory bowel diseases Dietary fibers Low dietary fibers intakes exacerbate colitis in mice and dietary fibers supplementation has beneficial effects limiting colitis development (Macia et al. 2015). Accordingly, in humans, low dietary fibers intakes are relatively consistent with IBD prevalence (Kakodkar and Mutlu 2017). In a prospective study following 170 776 women, intake of the highest quintile of dietary fibers (median of 24.3 g/day) was associated with a 40% reduction of Crohn's disease risk compared to the lowest quintile (median of 12.7 g/day) (Ananthakrishnan et al. 2013). As for metabolic disorders, the microbiome of IBD patients encodes fewer pathways related to carbohydrate metabolism (Morgan et al. 2012), together with a decrease in SCFAs production and SCFA producing-bacteria (Thibault et al. 2010; Vinolo et al. 2011, Machiels et al. 2014; Ríos-Covián et al. 2016). The beneficial therapeutic effects of SCFAs have been already observed in ulcerative colitis patients (Breuer et al. 1997; Scheppach and German-Austrian Scfa Study Group 1996, Vernia et al. 2003; Vernia et al. 2007) and this effect could be mediated by regulation of the host immune system and metabolism (Galvez, Rodríguez-Cabezas and Zarzuelo 2005; Wikoff et al. 2009). The use of butyrate enemas especially has shown promising results on ulcerative colitis patients' symptoms, but further clinical investigations will be required to overcome variations in studies outcomes and to conclude on their clinical effectiveness in human therapy (Sossai 2012). Specific sulfate-reducing bacteria may be involved in the induction of IBD upon low fiber/high fat–high protein diets. Indeed, low fiber animal-based food enriches the mouse microbiota in bile-tolerant microorganism, such as Bilophila wadsworthia, a sulfate-reducing bacteria that is incriminated to trigger inflammatory responses in the intestine (Devkota et al. 2012; David et al. 2014). This result could be a first clue in favor of dietary fibers effect on colorectal cancer. Human studies have confirmed an increase in sulfate-reducing bacteria in IBD patients (Ijssennagger, van der Meer and van Mil 2016). The produced sulfide could take part in the disease etiology by reducing disulfide bonds thus promoting permeability of the mucus network. Mucus polysaccharides When compared to healthy volunteers, the mucus layer of IBD patients is often thinner and more discontinuous (Strugala, Dettmar and Pearson 2008). The intestinal pattern of MUC genes and the glycosylation mucus profiles are also altered (Corfield 2018). Interestingly, mutations in the fut2 gene, responsible for the secretion of blood group antigens in the mucus layer or in ATG16L1 or XBP1 genes associated to goblet cell function are well-known IBD susceptibility factors (Prescott et al. 2007, Kaser et al. 2008, Cadwell et al. 2010; Rausch et al. 2011; Mohanan et al. 2018). In line with the close interactions between mucus and microbiota, the mucus-associated microbiota has been proposed to participate in IBD aetiology and/or severity. In biopsies from IBD patients, mucosal bacteria are found in greater number, in closer proximity to the intestinal epithelium and in denser biofilms (Schultsz et al. 1999; Swidsinski et al. 2002; Swidsinski et al. 2005; Swidsinski et al. 2007). These mucosal bacteria could show pathogenic properties as Bacteroides fragilis accounts for most of the biofilm mass (Swidsinski et al. 2005). Concerning mucin degrading-bacteria, in faecal samples and colon mucus-associated microbiota, an increased prevalence of Ruminococcus gnavus and Ruminococcus torques was associated to IBD (Png et al. 2010; Hall et al. 2017; Schirmer et al. 2018), whereas Akkermansia muciniphila has been negatively correlated with these pathologies (Png et al. 2010). Of note, these bacteria both degrade and stimulate intestinal mucus production (Hata and Smith 2004; Cervera-Tison et al. 2012; Crost et al. 2013; Lee and Ko 2014; Shin et al. 2014; Graziani et al. 2016) and whether their role is beneficial or not in IBD remains unclear (Derrien, Belzer and de Vos 2017; Seregin et al. 2017; Bian et al. 2019). As fiber-free diet leads to mucus penetrability, microbiota encroachment and low-grade inflammation (Zou et al. 2018), it should be relevant to further investigate if dietary fibers could play a decisive role in IBD prevention. Colorectal cancer Dietary fibers The development of colorectal cancer could be stackable with the events occurring during IBD. Thus, it is not surprising to identify commonly shared predisposition factors or physiological features between these two pathologies, and IBD prevention should logically impacts colorectal cancer prevalence. As for IBD, lower dietary fibers intake and lower fiber-degrading microbiota abundance are associated with increased colorectal cancer incidence (Wang et al. 2012; Aune et al. 2016). Of note, a recent meta-analysis covering 185 prospective trials and 58 clinical studies provided convincing evidence for an inverse correlation between dietary fibers intake and colorectal cancer risk (Reynolds et al. 2019). More surprisingly, increasing fiber intakes after diagnosis is associated with a better survival (Song et al. 2018). Both in vitro and in vivo studies have shown that some types of fibers (e.g. inulin, pectin, cellulose or resistant starch) may play a major role in colorectal cancer prevention (Reddy et al. 1989; Hylla et al. 1998; Buddington, Donahoo and Buddington 2002; Willats, Knox and Mikkelsen 2006; Fuentes-Zaragoza et al. 2010). These effects could be mediated by regulation of intestinal epithelial cell proliferation, inhibition of secondary bile acid production and anti-oxidant effects. However, to date investigations about the role of gut microbiota in the latter observations are preliminary (Fuller et al. 2016; Ocvirk et al. 2019). Nevertheless, a recent prospective cohort study identified an interesting inverse correlation between high-fiber diet and colorectal cancer positive for Fusobacterium nucleatum, a colonic tumorigenesis associated bacterium (Mehta et al. 2017). Fusobacterium species invade colonic epithelial cells to drive inflammation and tumorigenesis (Kostic et al. 2013; Rubinstein et al. 2013) and this result could be a first clue in favor of dietary fibers effect on colorectal cancer through microbiota modulation. The role of SCFAs, in particular butyric acid, resulting from fiber metabolism remains unclear (Donohoe et al. 2012). Apart from its role as an energy substrate for normal colonocytes, butyrate could be a potent inducer of apoptosis in cancer cells (Wu et al. 2018). Mucus polysaccharides Other potential bacterial colorectal cancer drivers have been identified, such as Helicobacter pylori, Streptococcus bovis or Clostridium septicum that need access to the epithelium to infect (Grahn et al. 2005; Mirza, McCloud and Cheetham 2009; Wang et al. 2012; Krishnan and Eslick 2014). Thus, when bacterial access to the epithelium is involved in colorectal cancer aetiology, we can rightly suppose that mucus barrier defects could increase the risk for colorectal cancer development. Moreover, colorectal cancer is characterized by mucin expression modifications and abnormal glycosylation patterns that progress with the tumor stages (Corfield et al. 2018). These local defects in colonic mucus barrier allow a close contact of microbiota with mucosal epithelial cells and lead to inflammatory responses (Corfield et al. 2018). In addition, in a mouse model of chemically induced carcinogenesis, the number and severity of the lesions were inversely correlated to the number of goblet cells, clearly supporting a role of mucus integrity in colorectal cancer prevention (Novaes et al. 2016). Altogether, as for IBD, these results strongly highlight the need for additional mechanistic studies to investigate if mucus deterioration may be prevented by high dietary fibers intakes in a colorectal cancer context. HOW ENTERIC PATHOGENS CAN INTERACT WITH MUCUS AND DIETARY FIBERS IN A COMPLEX MICROBIAL BACKGROUND? Mucus-associated polysaccharides: from interactions with enteric pathogens to a cue for their virulence? Pathogens binding to mucus Binding structures Most of the enteric pathogens including Enterobacteriaceae have to reach the intestinal epithelium and invade the mucosal barrier to promote their colonisation or persistence. Binding to mucus is, therefore, the primary colonisation challenge for pathogens (Sicard et al. 2017) but it can also favor subsequent bacterial adhesion. In vitro adherence of Salmonellae enterica serovar Typhimurium and Enterohemorrhagic Escherichia coli (EHEC) is higher on high-mucus producing cells (e.g. Ht29-MTX or LS174T) than in non- or low-mucus producing cells (e.g. Caco-2 or HT29) (Gagnon et al. 2013; Hews et al. 2017). As for commensals, pathogens use surface-associated appendages (adhesins, fimbriae and flagella) to bind to mucus polysaccharides. For instance, the close relatives Helicobacter pylori and Campylobacter jejuni possess several characterised adhesins that notably bind to blood group antigens and to sialic acid (Mahdavi 2002; Avril et al. 2006; Heikema et al. 2010; Moran, Gupta and Joshi 2011, Kenny et al. 2012; Rossez et al. 2014) while GbpA from Vibrio cholerae binds to N-acetylglucosamine (Bhowmick et al. 2008; Wong et al. 2012). Flagellar subunits of Campylobacter jejuni (Sicard et al2017), enteropathogenic Escherichia coli (Erdem et al. 2007) and Clostridioides difficile are all able to bind mucus polysaccharides. Enterobacteriaceae can interact with mucus glycans via various appendanges like type 1 pili, which harbors an adhesin, FimH, at the tip of fimbriae responsible for mannose-specific adhesive interactions (Abraham et al. 1983; Sokurenko et al. 1998; Schembri et al. 2001; Aprikian et al. 2007). Std fimbriae from Salmonella enterica serovar Typhimurium interacts with terminal fucose (Chessa et al. 2009) and mannose residues (Vimal et al. 2000) Sources of variations As described above, pathogen-mucus interactions are built on the recognition of specific saccharide patterns. As mucus polysaccharide composition changes all along the human GIT, it could be a strategy for precise site targeting in the gut (Owen et al. 2017). The pathogens also have to deal with host-related parameters known to induce variations in mucus structure and composition, such as genetics, diet, degradation by host microbiota and diseases. Illustrating this pathogen pattern dependency, Helicobacter pylori infections were found most prevalent in individuals from O than A group, suggesting a preferred attachment of the bacteria to O- blood group antigen present in the mucus (Kościelak 2012). On the contrary, Enterotoxigenic Escherichia coli (ETEC) seem to have a predilection for individuals from A group (Qadri et al. 2007; Ahmed et al. 2009). Some pathogenic bacteria as Shigella flexneri, Helicobacter pylori and Citrobacter rodentium are even able to reshape mucin glycosylation patterns (Sperandio et al. 2013; Pham et al. 2014; Magalhães et al. 2015). These modifications may adjust the expression of bacterial receptors (Barnich et al. 2007; Corfield et al. 2018) or impact the gut microbiota colonisation barrier (Pham et al. 2014). For instance, Helicobacter pylori infection affects host expression resulting in increased sialylation patterns that favor Helicobacter pylori SabA-mediated adhesion (Magalhães et al. 2015). Mucus degradation by pathogens Bacterial mucinases To face the mucus net-like properties, pathogens possess proteases called mucinases. These mucinases are classified according to the functional group involved in catalysis (e.g. metallo, serine and aspartic proteases), their site of action (endo- or exo- proteases) and their evolutionary relationships related to their amino acid sequence (Carroll 2013). Even if some mucinases, as SslE, are known to exist in both secreted and surface-associated forms, most of the characterised mucinases are secreted in the external environment by pathogens, probably for a wider impact on the mucus structure (Etienne-Mesmin et al. 2019). Mucinases have been well characterised in Enterobacteriaceae, in particular in ETEC and EHEC. These Escherichia coli pathovars are well armed with a diverse arsenal of mucinases, such as SslE, StcE, Hbp, YghJ and EatA (Dutta et al. 2002; Lathem et al. 2002; Leyton et al. 2003; Grys et al. 2005; Kumar et al. 2014). In Adherent Invasive Escherichia coli (AIEC), mucinase Vat-AIEC is over-expressed in the presence of bile salts and mucin, and contribute to bacteria penetration in the mucus layer to establish gut colonisation (Gibold et al. 2016). Mucinases have also been evidenced in Vibrio cholerae (Szabady et al. 2011), Yersinia enterocolitica (Mantle and Rombough 1993) and Clostridioides difficile (Janoir et al. 2007), suggesting the involvement of mucus depolymerisation during infection processes. For instance, EatA and YghJ help the delivery of ETEC toxins to the cell surface by degrading the mucus layer (Kumar et al. 2014; Luo et al. 2014) while StcE by reducing the colonic inner mucus layer promotes EHEC adherence (Hews et al. 2017). It is noteworthy that some commensal bacteria also possess mucinases, highlighting the fine line between pathogenicity and commensalism in the GIT. As an example, SslE is found both in commensal Escherichia coli and in ETEC and EHEC pathogenic strains (Etienne-Mesmin et al. 2019; Tapader, Basu and Pal 2019). Nevertheless, differences between commensal and pathogen mucinases reside at least in their expression levels. For example, pathogenic Escherichia coli generate significant amounts of YghJ compared to their commensal counterparts, while there is no difference in the putative catabolic amino acid sequences (Luo et al. 2014). Lastly, as for CAZymes, mucinases seem to have substrate specificities. For example, StcE preferentially cleaves MUC2 compared to MUC5AC (Hews et al. 2017) and YghJ targets MUC2 and MUC3 (Luo et al. 2013). Glycosyl hydrolases By their degrading potential, CAZymes, and notably GHs, could be another way to cleave mucus but this activity has been poorly described in pathogens. To date, pathogen GHs, as commensal ones, have been preferentially studied as feeding tools rather than mucus-degrading enzymes. As a nice example, Salmonella contains 47 GHs that may degrade glycans. During infection in mice, specific deletion of nanH and malS genes impedes bacterial invasion, suggesting that these GHs may be considered as new virulence factors (Arabyan et al. 2016). Bacteroides fragilis has also been shown to require special polysaccharide utilization loci (containing GH along other CAZymes) for crypt colonisation, and mutants strains deficient for these loci failed to occupy crypts (Lee et al. 2013). However, it is not possible to decipher if these GH knock-out defects in colonisation can be attributed to mucus-degrading defect or to loss of feeding capabilities on other carbohydrate sources. Mucus-based feeding of pathogens Primary degraders or cross-feeding strategies CAZymes are also used by some pathogens to release mucus-derived sugars for their own consumption (Mondal et al. 2014; Arabyan et al. 2016). Salmonella enterica serovar Typhimurium has the ability to release carbohydrates from mucus by using its sialidase (Hoyer et al. 1992). Interestingly, Vibrio cholerae uses its chitinase ChiA2 to feed on both chitin fibers found in the aquatic environment and mucins in the gut (Huq et al. 1983; Meibom et al. 2004; Hunt et al. 2008; Mondal et al. 2014), most probably because of their structural similarities (chain polymers of β-1,4 linked N-acetylglucosamine residues). In line with this observation, mutants for chitin utilisation pathway display less capacity to penetrate mucus and are hypovirulent in a mouse model (Chourashi et al. 2016). Besides these examples, pathogens usually behave as non-primary degraders. They have limited CAZymes arsenal and often count on other mucin degraders to cross-feed. Escherichia coli pathogens represent a good example of this strategy. Indeed, they colonise the mouse large intestine by growing in intestinal mucus, but as they do not secrete extracellular GHs, they cannot degrade mucin-derived oligo- and polysaccharides and depend on other microbes which feed them with small saccharides and promote their own growth (Conway and Cohen 2015). In a gnotobiotic mouse model, EHEC colonise the mucus layer within the cooperation of local bacterial communities including Bacteroides thetaiotaomicron that cleaves host glycan-derived sugars and produces fucose (Pacheco et al. 2012). Similarly, Bacteroides thetaiotaomicron is also able to release free sialic acid from colon mucus glycans that can be further used by Clostridioides difficile and Salmonella enterica serovar Typhimurium to promote their own colonisation and persistence in the gnotobiotic mice gut (Ng et al. 2013). To date, more investigations are required to decipher if these cross-feed relationships also exist in the human gut. Importance of microbial background When gut microbiota is not disturbed, pathogens have to compete with commensal non-primary feeders to use mucus carbohydrates. Conway and Cohen (2015) showed that when gnotobiotic mice are pre-colonised with only three commensal Escherichia coli strains, these strains use all the mucus monosaccharides uptake possibilities to outcompete the pathogenic EHEC strain, leading to pathogen elimination (Leatham et al. 2009). In response, EHEC can utilize a large panel of mucus-derived monosaccharides and thereby compete with commensal Escherichia coli (Fabich et al. 2008). The metabolic flexibility of some pathogenic strains to use both glycolytic and gluconeogenic nutrients from the host may also represent a competitive advantage (Bertin et al. 2013). To outcompete the native microbiota, pathogens can benefit from gut disturbance that will leave free ecological niches. For instance, in human, antibiotic use is one of the leading risk factors for enteric diseases associated with Salmonella and Clostridioides difficile infections (Pavia et al. 1990; Kelly et al. 1994; Pépin et al. 2005; Doorduyn et al. 2006; Dethlefsen et al. 2008). Of interest, antibiotic treatment is also one of the drivers modulating mucin carbohydrates availability. Studies in mice showed that antibiotic treatment induced a spike in mucus-derived monosaccharides such as sialic acid, and these high concentrations of free monosaccharides facilitated the expansion of Salmonella enterica serovar Typhimurium and Clostridioides difficile (Ng et al. 2013). As further evidence, colonisation of gnotobiotic mice with a sialidase-deficient mutant of Bacteroides thetaiotaomicron induces reduction of free sialic acid levels impairing expansion of Clostridioides difficile. These transient effects could be reversed by exogenous dietary administration of free sialic acid (Ng et al. 2013). Pathogens and inflammation in a mucus-altered context There is scarce but promising evidence that inflammation driven by mucus alterations may support pathogen infection. First, in mouse models, defects in mucus glycosylation are clearly associated with inflammation (An et al. 2007; Stone et al. 2009; Burger-van Paassen et al. 2011). This inflammation occurs only when gut microbiota is present, suggesting that the close proximity between microbes and the epithelial brush border drives the response (Bergstrom et al. 2016). Besides, mice with genetically impaired mucus layer are more susceptible to pathogens such as Salmonella enterica (Bergstrom et al. 2010; Zarepour et al. 2013; Hecht et al. 2017). Altogether, mucus defects appear to be involved both in inflammation and pathogen susceptibility. As mucus over-degradation triggers an inflammatory state, we may hypothesise that mucus-degrading microorganisms or microorganisms benefiting from mucus degradation would be more adapted to an inflammatory environment. In this sense, colitis-induced with dextran sodium sulfate seemed to favor microorganisms expressing genes involved in mucus polysaccharide utilisation (Schwab et al. 2014). In the same way, recent studies suggest that pathogens could also benefit from this pro-inflammatory state. In both human and mice, inflamed microbiota is characterised by a reduced abundance of obligate anaerobic bacteria and expansion of facultative anaerobic bacteria from Proteobacteria phylum, mostly members of the Enterobacteriaceae family (Seksik 2003; Gophna et al. 2006; Baumgart et al. 2007; Lupp et al. 2007; Walker et al. 2011; Gevers et al. 2014, Chiodini et al. 2015). Interestingly, Enterobacteriaceae may also support this inflammatory state, thus promoting their own persistence in the gut (Garrett et al. 2010). Lastly, pathogens such as Salmonella have adapted their own metabolism and triggers inflammation-induced mucus fucosylation, allowing the pathogen to feed on fucose (Ansong et al. 2012; Bäumler and Sperandio 2016) in an inflammatory state. Salmonella enterica serovar Typhimiurium also benefits from inflammation-derived electron acceptors that facilitates utilization of microbiota-derived succinate as a carbon source (Spiga et al. 2017). Modulation of virulence genes by mucus-degradation products In addition to acting as binding sites or carbon sources for pathogens, mucin glycoproteins can influence the expression of different pathogen virulence genes, as shown by many in vitro studies (Vogt, Peña-Díaz and Finlay 2015). Many virulence genes of Campylobacter jejuni are upregulated in vitro in the presence of MUC2 glycoprotein (Tu, McGuckin and Mendz 2008) and fucose especially influences chemotaxis and biofilm formation that are important during gut infection (Dwivedi et al. 2016). In response to mucins, Vibrio cholerae also downregulates polysaccharide synthesis pathways involved in biofilm formation, thus promoting its motility within the mucus (Liu et al. 2015). Released monosaccharides from mucin O-glycan degradation can also act as a chemical cue to help pathogens to sense their environment and adapt accordingly. As illustrated with EHEC, fucose represses EHEC LEE expression involved in the formation of attachment and effacement lesions (Pacheco et al. 2012; Cameron and Sperandio 2015). The study postulates that gene repression through fucose-sensing may prevent energy expense in EHEC during LEE production before reaching the epithelial surface, where free fucose is not present (Pacheco et al. 2012, Cameron and Sperandio 2015). N-acetylglucosamine and sialic acid have also a negative effect on LEE expression under aerobic conditions (Le Bihan et al. 2017) but stimulate the production of a LEE effector (EspB) under micro-aerobic conditions, which are those found at a close proximity of the intestinal epithelium (Carlson-Banning and Sperandio 2016). Therefore, the availability of free monosaccharides is not the sole determinant factor in pathogen virulence regulation, but other parameters associated to bacterial localisation, such as oxygen conditions, must be considered. How can dietary fiber modulate enteric pathogen virulence? An overview of in vitro and in vivo studies investigating the potential of dietary fibers against human enteric pathogens is provided in Table 2. Table 2. In vitro and in vivo studies investigating the potential of dietary fibers against human enteric pathogens Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) AIEC: Adherent Invasive Escherichia coli, CCL: chemokine (C-C motif) ligand, CXLCL : chemokine (C-X-C motif) ligand, EHEC: enterohemorrhagic Escherichia coli, ELISA: Enzyme-Linked Immuno Sorbent Assay, EPEC: enteropathogenic Escherichia coli, ETEC: enterotoxigenic Escherichia coli, Gb 3: globotriosylceramide, GM : monosialotetrahexosylganglioside, IL: Interleukin, GM-CSF: Granulocyte Macrophage Colony Stimulating Factor, LT: heat-labile toxin, M-SHIME®: Mucosal Simulator of the Human Intestinal Microbial Ecosystem, Stx: Shiga toxin, ST:heat-stable toxin, TNF-α: Tumor Necrosis Factor Alpha, TLR: Toll like receptor. Open in new tab Table 2. In vitro and in vivo studies investigating the potential of dietary fibers against human enteric pathogens Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) AIEC: Adherent Invasive Escherichia coli, CCL: chemokine (C-C motif) ligand, CXLCL : chemokine (C-X-C motif) ligand, EHEC: enterohemorrhagic Escherichia coli, ELISA: Enzyme-Linked Immuno Sorbent Assay, EPEC: enteropathogenic Escherichia coli, ETEC: enterotoxigenic Escherichia coli, Gb 3: globotriosylceramide, GM : monosialotetrahexosylganglioside, IL: Interleukin, GM-CSF: Granulocyte Macrophage Colony Stimulating Factor, LT: heat-labile toxin, M-SHIME®: Mucosal Simulator of the Human Intestinal Microbial Ecosystem, Stx: Shiga toxin, ST:heat-stable toxin, TNF-α: Tumor Necrosis Factor Alpha, TLR: Toll like receptor. Open in new tab Direct antagonistic effect of dietary fibers on pathogens Bacteriostatic effect Some dietary fibers such as chitosan (derived from chitin) have shown a direct bacteriostatic effect by inhibiting the growth of various pathogens, and especially EHEC (Chantarasataporn et al. 2014; Ma et al. 2016; Vardaka, Yehia and Savvaidis 2016; Garrido-Maestu et al. 2018). Chitosan antimicrobial activity probably results from the intracellular leakage via binding positively charged chitosan to negatively charged bacterial surface, leading membrane permeability alteration causing cell death (Jeon et al. 2014). Of interest, the broad in vitro effect of chitosan is also conserved in vivo for ETEC, EHEC and others animal pathogens, by decreasing pathogen colonisation (Jeong et al. 2011; Xiao et al. 2014; Jeon et al. 2016; Liu et al. 2016). Inhibition of cell adhesion Dietary fibers from different sources have proven efficiency in reducing pathogenic Escherichia coli adhesion to intestinal epithelial cells. Many of these fibers have a plant origin (Rhoades et al. 2008; Roubos-van den Hil et al. 2009; Roubos-van den Hil et al. 2010; González-Ortiz et al. 2013; Di et al. 2017). For example, soluble fiber extract from plantain bananas reduce adhesion of AIEC, ETEC and Shigella strains to intestinal epithelial cells (Martin et al. 2004; Roberts et al. 2010). Dietary fibers can be also produced by microorganisms. β-galactomannan from yeasts are able to decrease ETEC adhesion on Caco-2 cells (Jeon et al. 2012). Yeasts also harbor numerous oligomannosides on cell wall able to interact with FimH adhesin of type 1 pili and represent an interesting anti-adherence strategy in reducing pathogenic E. coli adhesion (Roussel et al. 2018b; Sivignon et al. 2015; Ganner and schatzmayr 2012). Bacterial exopolysaccharides from Lactobacillus spp. also inhibited EHEC adhesion on HT29 cells as well as biofilm formation (Kim, oh and Kim 2009, Liu et al. 2017). These exopolysaccharides do not necessarily contain mannose supporting other possible inhibitory effects (Liu et al. 2017). Lastly, dietary fibers can derive from milk. Adhesion of ETEC strains to intestinal Caco-2 cells was reduced by addition of human HMOs (Idota and Kawakami 1995; Salcedo et al. 2013) and goat milk oligosaccharides were also proven to decrease adhesion of human enteric pathogen as Escherichia coli and Salmonella enterica serovar Typhimurium in a Caco-2 cells model (Leong et al. 2019). Reduction of bacteria adhesion could be explained by shared patterns between mucin polysaccharides and dietary fibers, resulting in dietary fibers acting as a decoy for bacteria which escape from the mucus compartment. Inhibition of toxin binding and activity Interestingly, dietary fibers from human milk have also a direct inhibitory effect on pathogen toxins. Sialyl lactose contained in milk was able to inhibit cholera toxin binding to its receptor the monosialoganglioside 1 GM1 (Idota et al. 1995). GM1 is also the receptor of the heat-labile toxin (LT) from ETEC and, in rabbit small intestine loops, the ganglioside fraction of human milk was reported to inhibit LT toxin activity, probably by sharing similarities with GM1 (Otnaess, Laegreid and Ertresvåg 1983). Another human milk component, certainly a fucosylated oligosaccharide, is able to inhibit the ability of ETEC heat-stable toxin (ST) to induce diarrhea in mice and the binding of the extracellular domain of guanylate cyclase, the ST receptor, to fucosylated oligosaccharides was the mechanism involved (Newburg et al. 1990; Crane et al. 1994). In line with this, it seems that milk oligosaccharide richness is associated with infant resistance to many pathogens, notably ETEC (Newburg, Ruiz-Palacios and Morrow 2005). Using the direct inhibitory potential of enterotoxin by saccharides, genetically modified probiotics expressing surface oligosaccharides that effectively bind and inhibit LT from ETEC and Shiga toxins from EHEC have been designed (Paton, Morona and Paton 2000; Paton et al. 2005). One of these probiotics was capable of adsorbing LT toxin (approximately 5% of its own weight) that results in significant protection from LT–induced fluid secretion in rabbit ligated ileal loop assays (Paton et al. 2005). Indirect effect of dietary fibers through gut microbiota modulation Modulation of microbiota composition The resident microbiota is now widely recognised as a significant barrier to pathogen colonisation. This protective role is supported by many studies showing that commensal strains from gut microbiota promote inhibition mechanisms towards pathogens. Direct inhibitory effects are mediated by acid production, secretion of inhibitory molecules like bacteriocin or production of (mostly) unknown compounds able to repress virulence genes (Corr, Gahan and Hill 2007; Schoster et al. 2013; Sikorska and Smoragiewicz 2013). Therefore, microbiota modulation with dietary fibers may be a relevant means to prevent enteric infections (Conway and Cohen 2015). However, demonstrating a positive effect mediated by microbiota modulation is not easy. Even if a dietary fibers supplementation does modify the microbiota and has anti-infectious properties, how to prove that the beneficial effect results from the increase or decrease of specific microbial groups? Some clues can emerge from the simultaneous administration of probiotic strains and dietary fibers to specifically support the probiotic growth (resulting in a prebiotic effect for dietary fibers). In 2001, Asahara and colleagues showed that pre-colonisation of mice with probiotic Bifidobacterium breve inhibited Salmonella enterica serovar Typhimurium growth and translocation in others organs (Asahara et al. 2001). This effect was strengthened by co-administration of Bifidobacterium breve with prebiotic GOS, while GOS alone did not show any anti-infectious properties. However, the authors did not prove any change in Bifidobacterium breve proportion or activity by GOS administration (Asahara et al. 2001). More recently, the continuous oral administration of the probiotic Bifodobacterium breve strain Yakult inhibited mice infection by multidrug-resistant strain of Acinetobacter baumannii and GOS markedly potentiated the probiotic effect without providing any protection alone (Asahara et al. 2016). Another mouse study showed that the second generation probiotic Faecalibacterium prausnitzii plus potato starch reduced Clostridioides difficile colonisation, the combined effect being slightly better than the individual one (Roychowdhury et al. 2018). In a continuous anaerobic fermentation system inoculated with human faeces, combination of Lactobacillus plantarum 0407 and Bifidobacterium bifidum Bb12 together with oligofructose and XOS reduced Campylobacter jejuni growth whatever the mode of administration (prophylaxis treatment or co-administration with the pathogen). The dietary fibers alone failed to reproduce the combined effect of dietary fibers and probiotics but the dietary fibers did increase bifidobacteria counts, supporting a prebiotic effect (Fooks and Gibson 2003). Taken together, these studies in rodent models support that prevention of enteric infections by dietary fibers supplementation may be achievable. Nevertheless, the beneficial effect firstly depends on the previous identification of a specific probiotic group that can act in synergy with dietary fibers, without obvious associated prebiotic effect. Some evidences of dietary fibers efficiency against enteric infections are also available in humans, with the well-known prebiotics FOS and GOS. A study on 281 healthy infants reported that supplementation with GOS and/or FOS resulted in fewer episodes of acute diarrhea. Another study on 342 infants reported a lower incidence of gastroenteritis in the supplemented group with GOS and FOS compared to controls and reduced antibiotic courses per year (Bruzzese et al. 2009). Nevertheless, interpretation of these results are impeded by the lack of pathogen identification and in depth gut microbiota characterisation. Modulation of gut microbiota activity Microbial metabolites resulting from dietary fibers fermentation, such as SCFAs can also modulate pathogen virulence. Acetate at the concentration found in the human ileum stimulates the expression of Type III secretion System (T3SS) from Salmonella enterica serovar Typhimurium, while propionate added at the typical concentration of the human colon, represses T3SS expression (Lawhon et al. 2002). Contradictory results have been obtained for butyrate (at concentrations found in the human colon) with repression or over-expression of T3SS depending on the studies (Lawhon et al. 2002; Takao, Yen and Tobe 2014). Mice fed a diet rich in highly fermentable guar gum exhibited a 10- to 100-fold increase in EHEC colonisation and developed illness compared to the control group fed with cellulose, which is considered as non-fermentable fiber (Zumbrun et al. 2013). This increased pathogenicity was associated to a rise in globotriaosylceramide expression (Shiga-toxin receptor), upregulated due to increase in butyrate concentrations (Zumbrun et al. 2013). Acetate produced by bifidobacteria seemed to protect mice from EHEC toxic effect by increasing intestinal epithelium barrier function (Fukuda et al. 2011). Lastly, an elegant gnotobiotic mouse study showed that a dietary fiber-rich diet could promote Clostridioides difficile colonisation in presence of succinate produced by Bacteroides thetaiotaomicron (Ferreyra et al. 2014). Of note, such a study must be interpreted cautiously since the experiments have been conducted in gnotobiotic mice lacking a competitive microbiota that would normally occupy the succinate-feeding niche. These examples illustrate the complexity in dietary fibers-microbiota-pathogens interactions and the need to investigate in depth pathogen specificities before assuming any dietary recommendation. Inhibition of pathogen interactions with mucus: a new mode of dietary fibers action? Figure 1 summarizes the potential role of dietary fibers in enteric infections, with an emphasis on mucus layer interactions. Figure 1. Open in new tabDownload slide Overview of the potential role of dietary fibers in preventing enteric infectionsReliable and converging data from scientific litterature are represented with numbers in circles, while data more hypothetical needing further investigations are represented with numbers in square. (1) Some dietary fibers exhibit direct bacteriostatic effects against pathogens. (2) Dietary fibers degradation lead to short-chain fatty acids (SCFAs) production that can modulate pathogens' virulence. (3) By presenting structure similarities with receptors, some dietary fibers can prevent pathogen adhesin binding to their receptors. (4) By the same competition mechanism, dietary fibers can also prevent toxin binding to their receptors. (5) Dietary fibers are able to promote gut microbiota diversity. (6) Dietary fibers may promote the growth of specific strains with probiotic properties and therefore exhibit anti-infectious properties. (7) Suitable dietary fibers intake prevents microbiota's switch to mucus consumption, limiting subsequent commensal microbiota encroachement and associated-intestinal inflammation. (8) Dietary fibers may prevent pathogen cross-feeding on mucus by limiting mucus degradation and/or by preserving the diversity of competing bacterial species. (9) By preventing mucus over-degradation by switchers microbes, dietary fibers can hamper pathogen progression close to the epithelial brush border and further restrict subsequent inflammation. Figure 1. Open in new tabDownload slide Overview of the potential role of dietary fibers in preventing enteric infectionsReliable and converging data from scientific litterature are represented with numbers in circles, while data more hypothetical needing further investigations are represented with numbers in square. (1) Some dietary fibers exhibit direct bacteriostatic effects against pathogens. (2) Dietary fibers degradation lead to short-chain fatty acids (SCFAs) production that can modulate pathogens' virulence. (3) By presenting structure similarities with receptors, some dietary fibers can prevent pathogen adhesin binding to their receptors. (4) By the same competition mechanism, dietary fibers can also prevent toxin binding to their receptors. (5) Dietary fibers are able to promote gut microbiota diversity. (6) Dietary fibers may promote the growth of specific strains with probiotic properties and therefore exhibit anti-infectious properties. (7) Suitable dietary fibers intake prevents microbiota's switch to mucus consumption, limiting subsequent commensal microbiota encroachement and associated-intestinal inflammation. (8) Dietary fibers may prevent pathogen cross-feeding on mucus by limiting mucus degradation and/or by preserving the diversity of competing bacterial species. (9) By preventing mucus over-degradation by switchers microbes, dietary fibers can hamper pathogen progression close to the epithelial brush border and further restrict subsequent inflammation. Binding to mucus: dietary fibers acting as a decoy Mucus polysaccharide patterns represent potential binding sites for intestinal pathogens and this observation can be extended to all mucosa surface-associated carbohydrates. Interestingly, saccharide-binding patterns are also found in dietary fibers and the hypothesis here is that dietary fibers can lure pathogens from mucus polysaccharides-associated patterns by presenting similar binding sites. The chitin-binding protein GbpA of Vibrio cholerae has been described as a common adherence factor for both chitin and intestinal surface, including mucus polysaccharides (Kirn, Jude and Taylor 2005; Wong et al. 2012; Younes and Rinaudo 2015). F17 fimbriae produced by ETEC strains recognizes N-acetylglucosamine-presenting receptors on the mucosa and this binding is inhibited by N-acetylglucosamine as well as N-acetylglucosamine oligomers (Buts et al. 2004). Blood group antigens on soluble glycans such as mucins or HMOs may serve as decoy receptors in pathogen defense (Pendu et al. 1983; Renkonen 2000; Yu et al. 2001). Owing to the commonly shared pattern between HMO and human blood groups epitope on mucus polysaccharides, it was shown that HMOs have the potential to inhibit many pathogens binding to mucus. These results are relevant for both pathogens with a tropism to ileum and colon since over 90% of ingested HMOs survive transit throughout the gut (Chaturvedi et al. 2001). HMO supplementation inhibited Campylobacter colonization of mice in vivo and human intestinal mucosa ex vivo (Ruiz-Palacios et al. 2003). Specifically, Campylobacter jejuni binds to fucosylated carbohydrates containing the H(O) blood group epitope and this binding is inhibited by HMOs. First evidences of HMO relevance in human enteric infection prevention come from breastfed infants who are at a 6-fold to 10-fold lower risk of developing necrotising enterocolitis than formula-fed ones (Lucas and Cole 1990; Schanler 2005; Meinzen-Derr et al. 2009). The infant protection would depend on HMO composition of the milk (Autran et al. 2018). Inhibition of mucus degradation by dietary fibers The gut microbiota ability to switch to mucus polysaccharides consumption when fiber intake is low is a relatively new discovery (Sonnenburg 2005). Desai and colleagues were pioneers in extending this notion to enteric pathogen (Desai et al. 2016). In a gnotobiotic mice model colonised by a synthetic human microbiota of 14 species, they showed that a low-fiber diet led the microbiota to switch to mucus polysaccharides consumption, and to enrichment in mucus degrading bacteria and mucus erosion. This greater penetrability induced a lethal susceptibility to the murine pathogen Citrobacter rodentium (Desai et al. 2016). Avoidance of mucus polysaccharides over degradation with adequate dietary fibers intake should allow a safe mucus-consuming microbiota to maintain, prevention of inflammatory reactions and therefore increased barrier to pathogen colonisation (Leatham et al. 2009). Furthermore, to maintain in the intestinal mucus layer, pathogens generally rely on cross-feeding (Pacheco et al. 2012; Ng et al. 2013). Distracting the versatile part of the microbiota from mucus degradation could prevent their adaptation to mucus consumption (Desai et al. 2016), thus avoiding them to feed pathogens in the mucus niche. On the contrary, other studies have reported that dietary fibers rich diet could promote pathogen colonisation by cross-feeding on fiber-derived metabolites from the lumen (Ferreyra et al. 2014). However, these studies have been conducted in antibiotic-treated mice, and we can argue that in a more complex physiological situation, other commensal microorganisms could have outcompeted with pathogens for fiber metabolites (Ferreyra et al. 2014). Altogether, these results indicate that other investigations are needed to address the question of whether enteric infections may benefit from dietary fibers intake or not. This would necessarily depend on fiber characteristics (fermentable or not), but also on the studied microbiota (e.g. selected strains or complex microbiota, antibiotic treatment, inflammation or not…) and type of models used. In any way, it should be interesting to evaluate dietary fibers anti-infectious properties under dysbiotic conditions (e.g. following antibiotic treatment, inflammation, metabolic disorders) to anticipate the effects due to the lack of competition by a diverse long-term resident microbiota. HUMAN IN VITRO GUT MODELS TO DECIPHER THE ROLE OF DIETARY FIBERS AND MUCUS IN ENTERIC INFECTIONS: INTEREST AND LIMITATIONS? Main scientific challenges to be addressed Recent studies have shown that fiber-deprived diets lead to defects of the intestinal mucus layer and correlates with increased pathogen susceptibility and negative outcomes such as inflammatory-related disorders. Nevertheless, a number of challenges need to be addressed before any fiber intake recommendation to prevent enteric infections can be made. First, beneficial effects appear to be fiber-dependent. The wide variety of fiber sources, chemical structure, physico-chemical properties (especially solubility), but also processing and preparation (Hernot et al. 2008), make studies challenging to interpret. As an example, Zumbrun and colleagues showing that guar gum strengthens the EHEC physiopathology in mice, which demonstrate that any deleterious effect observed for one specific type of fiber cannot be extrapolated to all others (Zumbrun et al. 2013). In addition, recent studies caution that processed foods enriched in refined fermentable dietary fibers could have side effects by increasing the risk of liver-related diseases and worsening colitis (Singh et al. 2018; Singh et al. 2019). Caution should be paid when choosing dietary fibers.Fibers with targeted properties should be favored in order to limit potential side effects (e.g. chitosan has shown a broad-spectrum antimicrobial activity) (Raafat and Sahl 2009). Second, utilising fibers for their antagonistic properties against enteric pathogens implies to get a better knowledge of the pathogen itself and to decipher meticulously molecular mechanisms involved in virulence. To establish effective anti-adhesion strategies, pathogen adhesins, their recognised motifs, as well as their distribution throughout human microbiota must be extensively characterized. In the same way, mucinase genes present in enteric pathogens should be characterised in depth. Their importance in pathogen virulence, as well as their mechanisms of action (e.g. recognition patterns), should be addressed. Of note, it would also be interesting to increase our knowledge on the few characterised GH from pathogens and their role during the infection process, especially their ability to degrade mucus. Data about pathogen feeding strategies are missing, especially in a complex microbial background, which would allow a better prediction of pathogen response to DF supplementation. Lastly, at the host level, throughout the GIT, enteric pathogens have to face a succession of different environmental conditions (e.g. pH, bile salts, oxygen and nutrient availability, mucus, and interactions with other resident microbes) that widely vary among individuals (Guerra et al. 2012). In particular, large-scale microbiome studies have confirmed a high degree of variability in microbiota composition among individuals, and dietary interventions in human studies clearly emphasised the inter-individual response of gut microbiota (Cotillard et al. 2013; Salonen et al. 2014; Hughes et al. 2019). In a human metabolic disorder context, individual responses to dietary fiber interventions seem to depend on gut microbiota diversity prior to intervention (baseline), with low responses being associated with low microbiota diversity (Cotillard et al. 2013; Zeevi et al. 2015), making it difficult to extrapolate the results from one individual to the general population. Differences in intervention studies outcomes are exacerbated by the absence of standardised protocols that results in important variations and outweigh biological differences (Lozupone et al. 2012). In particular, studies have shown that composition of the faecal bacterial community can be affected by experimental design and procedures, including sampling, storage or DNA extraction method, but also depends on 16S rRNA gene region targeted and sequencing platforms (Rintala et al. 2017; Panek et al. 2018; Chen et al. 2019). However, modulation of the gut microbiota through dietary fibers interventions still represent an attractive approach for promoting health through enteric disease prevention. In particular, using dietary fibers to sustain the growth of certain bacteria while limiting the expansion of pathogens or maintaining mucosal barrier integrity remain an achievable goal. Nevertheless, to date, only few studies have characterised the underlying mechanisms involved in the inter-relationship between gut microbiota community (including commensals and pathogens) and dietary fibers, considering the wide range of host shaping factors. Research in this field is clearly required to identify gut microbiota keystone species utilising or responding to specific fiber sources and to evaluate in-depth the metabolic cross-feeding mechanisms between microbial species. Several questions remain unresolved such as why certain microbes elicit mucosal barrier strengthening, while some other exhibit mucus-degrading activities. Of note, all these questions should be investigated in healthy individuals but also in patients. A pathogen response to dietary fibers intervention could greatly vary according to the host individual but also to its health status, closely related to its microbiota structure and functionalities (dysbiotic or non-dysbiotic microbiota). In particular, the possible exploitation of host inflammation by pathogens and the mechanisms involved should be investigated more thoroughly. Such studies could help to develop personalised dietary fibers interventions and maximise their beneficial effects. In vitro human gut models as a relevant alternative to in vivo studies In vivo approaches in humans obviously represent the gold standard to investigate the interactions between dietary fibers, gut microbiota and enteric pathogens. However, the biological interpretation is complicated due to a myriad of factors among which inter-individual variability is one of the main challenges. In human clinical trials, there is a huge discrepancy between the studies due to dietary habits, genetic background, lifestyle and geographical origin of participants, as well as the quality and quantity of dietary fibers tested. Strict compliance of participants to the tested diet in interventional studies is also a factor difficult to monitor. Thus, any specific effect related to dietary fibers interventions is difficult to measure in healthy people. Moreover, for evident ethical reasons, access to the different segments of the GIT (from the stomach to the distal colon) is very limited and collection of mucus layer from human biopsies remains difficult (Hansson 2012). To minimise invasive procedures, human gut microbiota studies are usually performed using faecal samples and measured as endpoints, thus making it difficult to decipher where in the GIT the effects of a specific treatment occur (Riva et al. 2019). Lastly, human clinical intervention studies are limited in scope or are even impossible, depending on the pathogenic microorganisms involved. A widespread alternative to clinical studies is the use of in vivo animal models. Animal models are undoubtedly very useful to study physiological or pathological conditions at the level of the entire organism. For decades, their use has been essential for a better understanding of various infectious diseases. To investigate the involvement of gut microbiota on host functions, the use of gnotobiotic animals is particularly relevant, even if these experiments remain expensive and time-consuming (Kirk 2012). Nevertheless, more and more attention should be paid to reduce dependence on animal studies considering the societal demand to limit experiments on animals and the increasing ethical constraints. Also, important caution should be applied when translating data obtained in animal models to humans. Importantly, in vivo approaches involving laboratory animals can be hampered by differences between animal and human digestive physiology including resident microbiota and susceptibility to infection by pathogens (Hugenholtz and de Vos 2018). Concerning dietary fibers, rats have a lower capacity to digest polysaccharides from fibers than human (Knudsen et al. 1994). Another alternative is the use of in vitro models simulating the human digestive environment. Such models can provide a timely and cost-efficient alternative to in vivo assays to perform mechanistic studies on the impact of dietary fibers on human microbiome under controlled conditions of health and disease. Indeed, in vitro approaches enable a high level of control excluding confounding environmental or dietary habits that typically impede the interpretation of in vivo studies and particularly enable to investigate the direct interactions of dietary fibers with gut microbiota, independently from the host. Compared to in vivo approaches, those models offer technical flexibility, accuracy, reproducibility, and are not limited by ethical constraints nor safety concerns, making them doubtlessusefull when working with pathogens to investigate human infectious. Nevertheless, these in vitro models are obviously limited by the lack of nervous or endocrinal systems, but also host immune responses meaning it impossible to monitor host-microbe based colonisation resistance determinants (Payne et al. 2012; Etienne-Mesmin et al. 2019). Importantly, diversity measures are always lower in in vitro gut models than in human faecal samples, suggesting that they are not yet capable of supporting the full range of species that are living in the human gut (Van de Wiele et al. 2015; Pham and Mohajeri 2018). Similarly, SCFAs that play a major role in gut homeostasis are not absorbed in most of in vitro models, or only by passive mechanisms, which may have an impact on gut microbiota or tested pathogenic microorganisms (Pham and Mohajeri 2018). Actually, a broad range of in vitro gut systems is available to reproduce the human GIT, from static mono-compartmental to dynamic multi-compartmental models (Guerra et al. 2012; Payne et al. 2012; Pham and Mohajeri 2018). The last ones are particularly relevant because they enable studying the complex and successive multistage processes of human digestion. They integrate key physicochemical and microbial parameters of the human gut, such as temperature, pH, transit time, digestive enzymes and bile salts, complex, metabolically active and regionalised resident gut microbiota from human origin, and anaerobiosis mainly in the colon compartments. Their spatial compartmentalisation allows sample collection over time and in the desired segment of the digestive tract. In this sense, they can be especially useful to answer research questions related to enteric pathogens with different sites of colonisation (e.g. stomach for Helicobacter pylori, distal small intestine for ETEC and EHEC or large intestine for EHEC). Among dynamic multi-compartmental models, the well-known and validated systems are the TNO gastro-Intestinal Model, namely TIM-1 for the gastric and small intestinal model and TIM-2 for the colon system (Minekus 2015), the continuous three-stage colon systems developed by Gibson, Cummings and MacFarlane (Gibson, Cummings and Macfarlane 1988) or the PolyFermS (Payne et al. 2012), and the Simulator of the Human Intestinal Microbial Ecosystem SHIME® that includes all the compartments from the stomach to the colon (Molly, Vande Woestyne and Verstraete 1993; Van de Wiele et al. 2015). Interestingly, these devices have been recently extended to mimicking specific conditions encountered within the GIT of young children or elderly people, that can be the at-risk population for enteric infections (Cinquin et al. 2006; Denis et al. 2016; Roussel et al. 2018a). In vitro gut models to decipher the key role of digestive secretions, mucus and gut microbiota Despite the obvious limitations of in vitro tools, i.e. no input from nervous, endocrine or immune systems, multi-scale human gut models represent a powerful platform to investigate pathogen survival, regulation of virulence factors (including toxins and adhesins), and interactions with gut microbiota, and decipher how dietary fibers can modulate these parameters to prevent enteric infections. In vitro models of the upper gut, mainly the TIM-1 model, have already shown their value to study the behavior of E. coli pathotypes, such as EHEC or ETEC, in the stomach and the three compartments of the small intestine, and the impact of both serotypes and food components (Etienne-Mesmin et al. 2011; Miszczycha et al. 2014; Roussel et al. 2018b). Despite the absence of metabolisation of dietary fibers in the stomach and small intestine, their viscosity and water holding capacity have to be considered (Taghipoor et al. 2014). Therefore, evaluating the detrimental or beneficial influence of dietary fibers on pathogen survival and/or virulence in the stomach and small intestine would be a future challenge. In the same way, by adding mucus secretion in the upper gut models, the effect of mucins on pathogen survival and virulence is relevant to assess. Besides, it has been shown that dietary fibers bind to bile salts which can subsequently escape re-absorption in the small intestine, increasing their concentration in the digestive lumen (Capuano 2017). Since bile salts have a well-known bactericidal effect, this observation opens the road for many investigations. At least, this hypothesis can easily be tested using in vitro models of the upper gut reproducing passive absorption phenomenon (like in TIM-1 displaying dialysis through hollow fibers). In vitro models of the lower gut are suitable tools to investigate the effect of enteric pathogens, with or without dietary fibers, as sole modulators of gut microbiota composition and metabolic activities. These colon models are inoculated with human faecal samples, and range from batch to continuous fermentation systems. The rapidity and high throughput of batch models render them very useful for large screening studies of dietary fibers (Pham and Mohajeri 2018), but this approach is limited by short-time fermentation (24 to 48h), but also accumulation of metabolites and pH decrease that could impede microbial activities (Payne et al. 2012). In continuous fermentation models, reproducing one or several parts of the human colon, faecal microbiota rapidly shift to adapt to the experimental conditions of the designated colon segment (Aguirre and Venema 2017). These models allow long-term dietary fibers supplementation studies, in accordance with data from clinical trials showing that changes in response to fiber intake could take up to several months to stabilise (Reimer et al. 2014). Several lines of evidence have already demonstrated the ability of dietary fibers to limit pathogen expansion in continuous fermentation models (Pham and Mohajeri 2018). For instance, the SHIME model has been used to demonstrate the antagonistic effects of long-chain arabinoxylans or inulin towards colonisation by opportunistic AIEC pathobiont (Van den Abbeele et al. 2016). Conversely, in the PolyFermS system, a detrimental effect of dietary fibers was demonstrated, since addition of inulin stimulated the growth of Salmonella in the distal colon (Zihler et al. 2010). In vitro colon models could be also advantageously used to assess the effect of dietary fibers on pathogen virulence factors in a complex microbial background. Of particular interest, specific configurations of in vitro colon models have been recently developed to obtain a more realistic view on processes that drive the gastrointestinal microbiome. Some in vitro gut models, such as the Mucosal-SHIME (M-SHIME®), now integrate the mucosal environment which represent a colonisation niche for some bacterial species, including pathogens (Van den Abbeele et al. 2016; Van Herreweghen et al. 2018). The Dietary Particle-Mucosal SHIME (DP-M-SHIME®) allows the incorporation of insoluble food particles, colonized by a specific subset of bacteria, then reproducing the fine-scale spatial organisation of the human gut (De Paepe et al. 2018; De Paepe et al. 2019; De Paepe et al. 2020). These models provide a platform to study gut microbiota functionality and niche differentiation, during treatments with dietary fibers and/or pathogens. However, one of the limitations is the nature and origin of mucins (gastric porcine mucins) used to assess the interactions with gut bacteria doubled by the inability to reproduce a colonic mucus gel recapitulating the in vivo situation. Mucin glycosylation that also plays a critical role in the interaction between gut bacteria and mucus cannot be reproduced in vitro. In vitro colon fermentation models allow the operation of several bioreactors in parallel inoculated with either (i) a same faecal sample to test different dietary fibers/pathogen conditions on the same microbiota or (ii) different faecal samples collected from various donors to evaluate inter-individual variations upon one treatment. Considering inter-individual variations is of high importance as gut microbiota response to any dietary intervention varies widely and depends on starting levels of bacterial species present within the established gut microbiota (Cotillard et al. 2013, Zeevi et al. 2015, Makki et al. 2018). As illustrated with the PolyFermS in vitro system, Lacroix and colleagues investigated the metabolic cross-feeding mechanism and showed that soluble dietary fibers supplementation (β-glucan, XOS, α-GOS and inulin) induced different metabolic and microbial responses depending on an individual's specific microbiota (Poeker et al. 2018). Similar inter-individual differences were observed in the SHIME model supplemented with wheat bran particles (De Paepe et al. 2019). Since cross-feeding relationships are complex and take time to establish and stabilise in vivo, the use of in vitro controlled laboratory settings is suitable to better understand the role played by keystone bacterial species. In particular, these in vitro tools will further help to better manipulate the gut microbiota with personalised dietary interventions. Indeed, the effect of dietary fibers on gut microbiota composition and metabolic activity can be easily monitored when considering inter-individual variability (testing different donor stools), especially with low or high microbial diversity associated with different dietary intakes or even pathological situations (with stool from patients). Additional evidences also suggest that gut-derived metabolites are important modulators of host pathophysiology, among them SCFAs are derived from microbial fermentation of dietary fibers. One main advantage of in vitro continuous models is the possibility to follow SCFA production over time in each colon compartment, and how it can be modulated by dietary fibers and/or pathogen infection (Poeker et al. 2018; De Paepe et al. 2020). In the TIM-2 model, Van Nuenen and colleagues demonstrated the potential of inulin to shift the metabolic activity of the human colonic microbiota (mainly branched-chain fatty acids) infected by Clostridioides difficile (van Nuenen, Diederick Meyer and Venema 2003). Non-targeted approaches can also be used to investigate the impact of dietary fibers or pathogens on gut microbiota activity, such as NMR-based metabolomics technique (Lamichhane et al. 2014) or volatolomics (Giannoukos et al. 2019). Of interest, recent studies have revealed that analysis of the microbial volatolome is a promising approach to detect an imbalance of microbial activity (Sagar et al. 2015, Cruz et al. 2020) and to diagnose metabolism changes in response to physiological stresses (Berkhout et al. 2018). Toward an integration of host responses In order to get closer to the in vivo situation by integrating host-microbiota interactions, current technological challenges aim to couple in vitro colon models to intestinal epithelial cells (Bahrami et al. 2011; Marzorati et al. 2014; Tovaglieri et al. 2019) or Toll-Like Receptor reporter cells (Chassaing et al. 2017b). This would allow a better understanding of how dietary fibers can modulate pathogen-induced inflammatory pathways in the presence of the complex colonic microbiota. In vitro gut models can also be coupled to more complex units, such as the HMI module (Marzorati et al. 2014) or the HuMiX gut-on-a-chip model (Greenhalgh et al. 2019). The HMI module has been specifically designed to be connected to continuous fermentation models such as the SHIME model and incorporates (micro)environmental from the mucosa such as microaerophilic conditions and shear forces. These conditions are extremely important for opportunistic pathogen colonisation and virulence as demonstrated for Salmonella, Shigella and E. coli (De Weirdt and Van de Wiele 2015). Challenge of HMI module with colonic microbiota originating from the SHIME model treated with dried-fermentable yeast induced a decrease of pro-inflammatory IL-8 production (Marzorati et al. 2014). Efforts should be pursued on better simulating the mechanical deformations resulting from peristalsis that could play an important role in holding pathogens exclusion as shown in vivo (Quigley 2011). Interestingly, to further investigate the mechanistic host–microbiome crosstalk in intestinal inflammation, gut-on-a-chip devices have been developed to model intestinal inflammation (Shin and Kim 2018). This is of particular interest since the role of inflammation in enteric infections needs to be unraveled. Recent upgrades in those chips have integrated the oxygen gradient microenvironment (Jalili-Firoozinezhad et al. 2019; Shin et al. 2019). Advanced Organ-on-a-Chip devices have also been engineered to investigate communications between gut microbiota and other organs, as illustrated for liver (Boeri et al. 2019). To study the bi-directional host-microbiota interactions in depth, colonic samples collected from in vitro gut fermentation models could be transferred to germ-free mice (Chassaing et al. 2017b) to see if dietary fibers-induced modifications of gut microbiota have the potential to influence the host and if those modifications can persist. From health to disease conditions The ultimate goal of most biomedical research is to gain greater insight into mechanisms of human diseases in order to develop new preventive strategies, including dietary strategies based on dietary fibers intakes. A major scientific and technical challenge would be then to optimise in vitro colon models to reproduce disease conditions, especially associated with inflammation-related disorders such as obesity, IBD or colorectal cancer. These models will be inoculated with faeces collected from patients, and the main objective would be to maintain for a long period in the bioreactor gut microbiota dysbiosis considered as a characteristic feature of the pathology (Leocádio et al. 2020). Dysbiosis patterns have been associated with an increase in the proportion of several potentially pathogenic bacteria in colorectal cancer patients and autists and have been widely postulated in obesity-related disorders and IBD (DeGruttola et al. 2016). Up to now, a unique study described the adaptation of the TIM-2 colon model to obese conditions (Aguirre, Bussolo de Souza and Venema 2016). Aguirre and colleagues showed by using the TIM-2 model inoculated with faecal samples from lean or obese patients that fermentable carbohydrates (arabinogalactan and inulin) are differently used by the microbiota from the two populations, with higher amount of energy extracted after fermentation by obese microbiota (Aguirre, Bussolo de Souza and Venema 2016). However, this study is hampered by the lack of adaptation of physicochemical parameters (e.g. pH, transit time) to specific digestive conditions found in obese patients. Therefore, more research is warranted in this field to fully determine specific digestive conditions of at-risk populations that can be implemented in the diseased in vitro colon models. This will help scientists to understand better how physicochemical parameters of the digestive tract could by themselves shape the resident microbiota. Conflicts of Interest None declared. REFERENCES Abraham SN , Hasty DL, Simpson WA et al. Antiadhesive properties of a quaternary structure-specific hybridoma antibody against type 1 fimbriae of Escherichia coli . J Exp Med . 1983 ; 158 : 1114 – 28 . Google Scholar Crossref Search ADS PubMed WorldCat Aguirre M , Bussolo de Souza C, Venema K. The Gut Microbiota from Lean and Obese Subjects Contribute Differently to the Fermentation of Arabinogalactan and Inulin . PLoS One . 2016 ; 11 : e0159236 . Google Scholar Crossref Search ADS PubMed WorldCat Aguirre M , Venema K. Challenges in simulating the human gut for understanding the role of the microbiota in obesity . Beneficial Microbes . 2017 ; 8 : 31 – 53 . Google Scholar Crossref Search ADS PubMed WorldCat Ahmed T , Lundgren A, Arifuzzaman M et al. Children with the Le(a+b−) Blood Group Have Increased Susceptibility to Diarrhea Caused by Enterotoxigenic Escherichia coli Expressing Colonization Factor I Group Fimbriae . IAI . 2009 ; 77 : 2059 – 64 . Google Scholar Crossref Search ADS WorldCat Almeida GMF , Laanto E, Ashrafi R et al. Bacteriophage Adherence to Mucus Mediates Preventive Protection against Pathogenic Bacteria . mBio . 2019 ; 10 : e01984 – 19 . Google Scholar Crossref Search ADS PubMed WorldCat Ananthakrishnan AN , Khalili H, Konijeti GG et al. A Prospective Study of Long-term Intake of Dietary Fiber and Risk of Crohn's Disease and Ulcerative Colitis . Gastroenterology . 2013 ; 145 : 970 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Andrés-Barranco S , Vico JP, Grilló MJ et al. Reduction of subclinical Salmonella infection in fattening pigs after dietary supplementation with a ß-galactomannan oligosaccharide . J Appl Microbiol . 2015 ; 118 : 284 – 94 . Google Scholar Crossref Search ADS PubMed WorldCat An G , Wei B, Xia B et al. Increased susceptibility to colitis and colorectal tumors in mice lacking core 3–derived O-glycans . J Exp Med . 2007 ; 204 : 1417 – 29 . Google Scholar Crossref Search ADS PubMed WorldCat Ansong C , Deatherage BL, Hyduke D et al. Studying Salmonellae and Yersiniae Host–Pathogen Interactions Using Integrated ‘Omics and Modeling . Systems Biology . 2012 ; 21 – 41 . Google Scholar OpenURL Placeholder Text WorldCat Aprikian P , Tchesnokova V, Kidd B et al. Interdomain Interaction in the FimH Adhesin of Escherichia coli Regulates the Affinity to Mannose . J Biol Chem . 2007 ; 282 : 23437 – 46 . Google Scholar Crossref Search ADS PubMed WorldCat Arabyan N , Park D, Foutouhi S et al. Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling . Sci Rep . 2016 ; 6 : 29525 . Google Scholar Crossref Search ADS PubMed WorldCat Asahara T , Nomoto K, Shimizu K et al. Increased resistance of mice to Salmonella enterica serovar Typhimurium infection by synbiotic administration of Bifidobacteria and transgalactosylated oligosaccharides . J Appl Microbiol . 2001 ; 91 : 985 – 96 . Google Scholar Crossref Search ADS PubMed WorldCat Asahara T , Takahashi A, Yuki N et al. Protective Effect of a Synbiotic against Multidrug-Resistant Acinetobacter baumannii in a Murine Infection Model . Antimicrob Agents Chemother . 2016 ; 60 : 3041 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Atuma C , Strugala V, Allen A et al. The adherent gastrointestinal mucus gel layer: thickness and physical state in vivo . Am J Physiol-Gastro Liver Physiol . 2001 ; 280 : G922 – 9 . Google Scholar Crossref Search ADS WorldCat Aune D , Keum N, Giovannucci E et al. Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies . BMJ . 2016 : i2716 . Google Scholar OpenURL Placeholder Text WorldCat Autran CA , Kellman BP, Kim JH et al. Human milk oligosaccharide composition predicts risk of necrotising enterocolitis in preterm infants . Gut . 2018 ; 67 : 1064 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Avril T , Wagner ER, Willison HJ et al. Sialic Acid-Binding Immunoglobulin-Like Lectin 7 Mediates Selective Recognition of Sialylated Glycans Expressed on Campylobacter jejuni Lipooligosaccharides . IAI . 2006 ; 74 : 4133 – 41 . Google Scholar Crossref Search ADS WorldCat Badia R , Zanello G, Chevaleyre C et al. Effect of Saccharomyces cerevisiae var. Boulardii and beta-galactomannan oligosaccharide on porcine intestinal epithelial and dendritic cells challenged in vitro with Escherichia coli F4 (K88) . Vet Res . 2012 ; 43 : 4 . Google Scholar Crossref Search ADS PubMed WorldCat Bahrami B , Child MW, Macfarlane S et al. Adherence and Cytokine Induction in Caco-2 Cells by Bacterial Populations from a Three-Stage Continuous-Culture Model of the Large Intestine . Appl Environ Microbiol . 2011 ; 77 : 2934 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Bansil R , Turner BS. The biology of mucus: Composition, synthesis and organization . Adv Drug Deliv Rev . 2018 ; 124 : 3 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Barnich N , Carvalho FA, Glasser A-L et al. CEACAM6 acts as a receptor for adherent-invasive E. coli, supporting ileal mucosa colonization in Crohn disease . J Clin Invest . 2007 ; 117 : 1566 – 74 . Google Scholar Crossref Search ADS PubMed WorldCat Barr JJ , Auro R, Furlan M et al. Bacteriophage adhering to mucus provide a non-host-derived immunity . Proc Natl Acad Sci USA . 2013 ; 110 : 10771 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Baumgart M , Dogan B, Rishniw M et al. Culture independent analysis of ileal mucosa reveals a selective increase in invasive Escherichia coli of novel phylogeny relative to depletion of Clostridiales in Crohn's disease involving the ileum . ISME J . 2007 ; 1 : 403 – 18 . Google Scholar Crossref Search ADS PubMed WorldCat Belzer C , Chia LW, Aalvink S et al. Microbial Metabolic Networks at the Mucus Layer Lead to Diet-Independent Butyrate and Vitamin B12 Production by Intestinal Symbionts . mBio . 2017 ; 8 : mBio.00770-17 , e00770 – 17 . Google Scholar Crossref Search ADS PubMed WorldCat Ben David Y , Dassa B, Borovok I et al. Ruminococcal cellulosome systems from rumen to human: Human ruminococcal cellulosome . Environ Microbiol . 2015 ; 17 : 3407 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Benjdia A , Martens EC, Gordon JI et al. Sulfatases and a Radical S -Adenosyl-l-methionine (AdoMet) Enzyme Are Key for Mucosal Foraging and Fitness of the Prominent Human Gut Symbiont , Bacteroides thetaiotaomicron J Biol Chem . 2011 ; 286 : 25973 – 82 . Google Scholar Crossref Search ADS PubMed WorldCat Bergstrom K , Kissoon-Singh V, Gibson DL et al. Muc2 Protects against Lethal Infectious Colitis by Disassociating Pathogenic and Commensal Bacteria from the Colonic Mucosa . PLoS Pathog . 2010 ; 6 : e1000902 . Google Scholar Crossref Search ADS PubMed WorldCat Bergstrom K , Liu X, Zhao Y et al. Defective Intestinal Mucin-Type O-Glycosylation Causes Spontaneous Colitis-Associated Cancer in Mice . Gastroenterology . 2016 ; 151 : 152 – 164.e11 . Google Scholar Crossref Search ADS PubMed WorldCat Berkhout DJC , Niemarkt HJ, de Boer NKH et al. The potential of gut microbiota and fecal volatile organic compounds analysis as early diagnostic biomarker for necrotizing enterocolitis and sepsis in preterm infants . Expert Review of Gastroenterology & Hepatology . 2018 ; 12 : 457 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Berteau O , Guillot A, Benjdia A et al. A New Type of Bacterial Sulfatase Reveals a Novel Maturation Pathway in Prokaryotes . J Biol Chem . 2006 ; 281 : 22464 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Bertin Y , Chaucheyras-Durand F, Robbe-Masselot C et al. Carbohydrate utilization by enterohaemorrhagic Escherichia coli O157:H7 in bovine intestinal content: Carbon nutrition of EHEC O157:H7 in the bovine intestine . Environ Microbiol . 2013 ; 15 : 610 – 22 . Google Scholar Crossref Search ADS PubMed WorldCat Bhowmick R , Ghosal A, Das B et al. Intestinal Adherence of Vibrio cholerae Involves a Coordinated Interaction between Colonization Factor GbpA and Mucin . IAI . 2008 ; 76 : 4968 – 77 . Google Scholar Crossref Search ADS WorldCat Bian X , Wu W, Yang L et al. Administration of Akkermansia muciniphila Ameliorates Dextran Sulfate Sodium-Induced Ulcerative Colitis in Mice . Front Microbiol . 2019 ; 10 : 2259 . Google Scholar Crossref Search ADS PubMed WorldCat Bjursell MK , Martens EC, Gordon JI. Functional Genomic and Metabolic Studies of the Adaptations of a Prominent Adult Human Gut Symbiont, Bacteroides thetaiotaomicron, to the Suckling Period . J Biol Chem . 2006 ; 281 : 36269 – 79 . Google Scholar Crossref Search ADS PubMed WorldCat Boeri L , Izzo L, Sardelli L et al. Advanced Organ-on-a-Chip Devices to Investigate Liver Multi-Organ Communication: Focus on Gut, Microbiota and Brain . Bioengineering . 2019 ; 6 : 91 . Google Scholar Crossref Search ADS WorldCat Bolam DN , Ciruela A, McQUEEN-MASON S et al. Pseudomonas cellulose-binding domains mediate their effects by increasing enzyme substrate proximity . Biochem J . 1998 ; 331 : 775 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Boraston AB , Bolam DN, Gilbert HJ et al. Carbohydrate-binding modules: fine-tuning polysaccharide recognition . Biochem J . 2004 ; 382 : 769 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Bouhnik Y , Vahedi K, Achour L et al. Short-Chain Fructo-Oligosaccharide Administration Dose-Dependently Increases Fecal Bifidobacteria in Healthy Humans . J Nutr . 1999 ; 129 : 113 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Bovee-Oudenhoven IM , Termont DS, Heidt PJ et al. Increasing the intestinal resistance of rats to the invasive pathogen Salmonella enteritidis: additive effects of dietary lactulose and calcium . Gut . 1997 ; 40 : 497 – 504 . Google Scholar Crossref Search ADS PubMed WorldCat Breuer RI , Soergel KH, Lashner BA et al. Short chain fatty acid rectal irrigation for left-sided ulcerative colitis: a randomised, placebo controlled trial . Gut . 1997 ; 40 : 485 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat Brownawell AM , Caers W, Gibson GR et al. Prebiotics and the Health Benefits of Fiber: Current Regulatory Status, Future Research, and Goals . J Nutr . 2012 ; 142 : 962 – 74 . Google Scholar Crossref Search ADS PubMed WorldCat Bruzzese E , Volpicelli M, Squeglia V et al. A formula containing galacto- and fructo-oligosaccharides prevents intestinal and extra-intestinal infections: An observational study . Clin Nutr . 2009 ; 28 : 156 – 61 . Google Scholar Crossref Search ADS PubMed WorldCat Buddington KK , Donahoo JB, Buddington RK. Dietary Oligofructose and Inulin Protect Mice from Enteric and Systemic Pathogens and Tumor Inducers . J Nutr . 2002 ; 132 : 472 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Burger-van Paassen N , van der Sluis M, Bouma J et al. Colitis development during the suckling-weaning transition in mucin Muc2-deficient mice . Am J Physiol-Gastro Liver Physiol . 2011 ; 301 : G667 – 78 . Google Scholar Crossref Search ADS WorldCat Burkitt DP , Walker ARP, Painter NS. Effect of dietary fiber on stools and transit-times, and its role in the causation of disease . Lancet North Am Ed . 1972 ; 300 : 1408 – 11 . Google Scholar Crossref Search ADS WorldCat Buts L , Bouckaert J, De Genst E et al. The fimbrial adhesin F17-G of enterotoxigenic Escherichia coli has an immunoglobulin-like lectin domain that binds N-acetylglucosamine: F-17G lectin domain structure . Mol Microbiol . 2004 ; 49 : 705 – 15 . Google Scholar Crossref Search ADS WorldCat Buzby JC , Roberts T. The Economics of Enteric Infections: Human Foodborne Disease Costs . Gastroenterology . 2009 ; 136 : 1851 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Bäckhed F , Manchester JK, Semenkovich CF et al. Mechanisms underlying the resistance to diet-induced obesity in germ-free mice . Proc Natl Acad Sci . 2007 ; 104 : 979 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Bäumler AJ , Sperandio V. Interactions between the microbiota and pathogenic bacteria in the gut . Nature . 2016 ; 535 : 85 – 93 . Google Scholar Crossref Search ADS PubMed WorldCat Cadwell K , Patel KK, Maloney NS et al. Virus-Plus-Susceptibility Gene Interaction Determines Crohn's Disease Gene Atg16L1 Phenotypes in Intestine . Cell . 2010 ; 141 : 1135 – 45 . Google Scholar Crossref Search ADS PubMed WorldCat Cameron EA , Sperandio V. Frenemies: Signaling and Nutritional Integration in Pathogen-Microbiota-Host Interactions . Cell Host & Microbe . 2015 ; 18 : 275 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Cani PD , Amar J, Iglesias MA et al. Metabolic Endotoxemia Initiates Obesity and Insulin Resistance . Diabetes . 2007 ; 56 : 1761 – 72 . Google Scholar Crossref Search ADS PubMed WorldCat Cann I , Bernardi RC, Mackie RI. Cellulose degradation in the human gut: Ruminococcus champanellensis expands the cellulosome paradigm: Ruminococcus champanellensis celulosome . Environ Microbiol . 2016 ; 18 : 307 – 10 . Google Scholar Crossref Search ADS PubMed WorldCat Capuano E. The behavior of dietary fiber in the gastrointestinal tract determines its physiological effect . Crit Rev Food Sci Nutr . 2017 ; 57 : 3543 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Carlson-Banning KM , Sperandio V. Catabolite and Oxygen Regulation of Enterohemorrhagic Escherichia coli Virulence . mBio . 2016 ; 7 : e01852 – 16 . Google Scholar Crossref Search ADS PubMed WorldCat Carroll IM. Enteric bacterial proteases in inflammatory bowel disease- pathophysiology and clinical implications . WJG . 2013 ; 19 : 7531 . Google Scholar Crossref Search ADS PubMed WorldCat Cervera-Tison M , Tailford LE, Fuell C et al. Functional Analysis of Family GH36 α-Galactosidases from Ruminococcus gnavus E1: Insights into the Metabolism of a Plant Oligosaccharide by a Human Gut Symbiont . Appl Environ Microbiol . 2012 ; 78 : 7720 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat Chantarasataporn P , Tepkasikul P, Kingcha Y et al. Water-based oligochitosan and nanowhisker chitosan as potential food preservatives for shelf-life extension of minced pork . Food Chem . 2014 ; 159 : 463 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Gewirtz AT. Identification of Inner Mucus-Associated Bacteria by Laser Capture Microdissection . Cell Mol Gastroenterol Hepatol . 2019 ; 7 : 157 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Koren O, Goodrich JK et al. Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome . Nature . 2015 ; 519 : 92 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Ley RE, Gewirtz AT. Intestinal Epithelial Cell Toll-like Receptor 5 Regulates the Intestinal Microbiota to Prevent Low-Grade Inflammation and Metabolic Syndrome in Mice . Gastroenterology . 2014 ; 147 : 1363 – 77 ..e17. Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Raja SM, Lewis JD et al. Colonic Microbiota Encroachment Correlates With Dysglycemia in Humans . Cell Mol Gastroenterol Hepatol . 2017a ; 4 : 205 – 21 . Google Scholar Crossref Search ADS WorldCat Chassaing B , Van de Wiele T, De Bodt J et al. Dietary emulsifiers directly alter human microbiota composition and gene expression ex vivo potentiating intestinal inflammation . Gut . 2017b ; 66 : 1414 – 27 . Google Scholar Crossref Search ADS WorldCat Chassard C , Delmas E, Robert C et al. The cellulose-degrading microbial community of the human gut varies according to the presence or absence of methanogens: Cellulolytic microbiota and CH4 production in the human gut . FEMS Microbiol Ecol . 2010 ; 74 : 205 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Chaturvedi P , Warren CD, Buescher CR et al. Survival of Human Milk Oligosaccharides in the Intestine of Infants . Bioactive Components of Human Milk . 2001 ; 34 : 315 – 23 . Google Scholar Crossref Search ADS WorldCat Chen B , Chen H, Shu X et al. Presence of Segmented Filamentous Bacteria in Human Children and Its Potential Role in the Modulation of Human Gut Immunity . Front Microbiol . 2018 ; 9 : 1403 . Google Scholar Crossref Search ADS PubMed WorldCat Chen J. Molecular mechanism of the Escherichia coli maltose transporter . Curr Opin Struct Biol . 2013 ; 23 : 492 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Chen XY , Woodward A, Zijlstra RT et al. Exopolysaccharides Synthesized by Lactobacillus reuteri Protect against Enterotoxigenic Escherichia coli in Piglets . Appl Environ Microbiol . 2014 ; 80 : 5752 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Chen Z , Hui PC, Hui M et al. Impact of Preservation Method and 16S rRNA Hypervariable Region on Gut Microbiota Profiling . mSystems . 2019 ; 4 . Google Scholar OpenURL Placeholder Text WorldCat Chessa D , Winter MG, Jakomin M et al. Salmonella enterica serotype Typhimurium Std fimbriae bind terminal α(1,2)fucose residues in the cecal mucosa . Mol Microbiol . 2009 ; 71 : 864 – 75 . Google Scholar Crossref Search ADS PubMed WorldCat Chiodini RJ , Dowd SE, Chamberlin WM et al. Microbial Population Differentials between Mucosal and Submucosal Intestinal Tissues in Advanced Crohn's Disease of the Ileum . PLoS One . 2015 ; 10 : e0134382 . Google Scholar Crossref Search ADS PubMed WorldCat Chourashi R , Mondal M, Sinha R et al. Role of a sensor histidine kinase ChiS of Vibrio cholerae in pathogenesis . Int J Med Microbiol . 2016 ; 306 : 657 – 65 . Google Scholar Crossref Search ADS PubMed WorldCat Chow J , Tang H, Mazmanian SK. Pathobionts of the gastrointestinal microbiota and inflammatory disease . Curr Opin Immunol . 2011 ; 23 : 473 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Cilieborg MS , Sangild PT, Jensen ML et al. α1,2-Fucosyllactose Does Not Improve Intestinal Function or Prevent Escherichia coli F18 Diarrhea in Newborn Pigs . J Pediatr Gastroenterol Nutr . 2017 ; 64 : 310 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Cinquin C , Le Blay G, Fliss I et al. New three-stage in vitro model for infant colonic fermentation with immobilized fecal microbiota: Model for infant colon fermentation . FEMS Microbiol Ecol . 2006 ; 57 : 324 – 36 . Google Scholar Crossref Search ADS PubMed WorldCat Clemente JC , Pehrsson EC, Blaser MJ et al. The microbiome of uncontacted Amerindians . Sci Adv . 2015 ; 1 : e1500183 . Google Scholar Crossref Search ADS PubMed WorldCat Cockburn DW , Koropatkin NM. Polysaccharide Degradation by the Intestinal Microbiota and Its Influence on Human Health and Disease . J Mol Biol . 2016 ; 428 : 3230 – 52 . Google Scholar Crossref Search ADS PubMed WorldCat CODEX Alimentarius Commission . CODEX Alimentarius (CODEX) Guidelines on Nutrition Labeling CAC/GL 2–1985 as Last Amended 2010 . Rome : FAO ; 2010 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Conway T , Cohen PS. Commensal and Pathogenic Escherichia coli Metabolism in the Gut . Microbiology Spectrum . 2015 ; 3 . Google Scholar OpenURL Placeholder Text WorldCat Coppa GV , Zampini L, Galeazzi T et al. Human Milk Oligosaccharides Inhibit the Adhesion to Caco-2 Cells of Diarrheal Pathogens: Escherichia c oli, Vibrio cholerae, and Salmonella fyris . Pediatr Res . 2006 ; 59 : 377 – 82 . Google Scholar Crossref Search ADS PubMed WorldCat Corfield AP. The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human . Microorganisms . 2018 ; 6 : 78 . Google Scholar Crossref Search ADS WorldCat Corfield AP . The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human . Microorganisms . 2018 ; 6 : 78 . Google Scholar Crossref Search ADS WorldCat Corr SC , Gahan CGM, Hill C. Impact of selected Lactobacillus and Bifidobacterium species on Listeria monocytogenes infection and the mucosal immune response . FEMS Immunol Med Microbiol . 2007 ; 50 : 380 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Cotillard A , Kennedy SP, Kong LC et al. Dietary intervention impact on gut microbial gene richness . Nature . 2013 ; 500 : 585 – 88 . Google Scholar Crossref Search ADS PubMed WorldCat Crane JK , Azar SS, Stam A et al. Oligosaccharides from Human Milk Block Binding and Activity of the Escherichia coli Heat-Stable Enterotoxin (STa) in T84 Intestinal Cells . J Nutr . 1994 ; 124 : 2358 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Cravioto A , Tello A, Villafan H et al. Inhibition of Localized Adhesion of Enteropathogenic Escherichia coli to HEp-2 Cells by Immunoglobulin and Oligosaccharide Fractions of Human Colostrum and Breast Milk . J Infect Dis . 1991 ; 163 : 1247 – 55 . Google Scholar Crossref Search ADS PubMed WorldCat Crost EH , Tailford LE, Le Gall G et al. Utilisation of Mucin Glycans by the Human Gut Symbiont Ruminococcus gnavus Is Strain-Dependent . PLoS One . 2013 ; 8 : e76341 . Google Scholar Crossref Search ADS PubMed WorldCat Cruz R , Palmeira JD, Martins ZE et al. Multidisciplinary approach to determine the effect of polybrominated diphenyl ethers on gut microbiota . Environ Pollut . 2020 ; 260 : 113920 . Google Scholar Crossref Search ADS PubMed WorldCat Cuevas-Sierra A , Ramos-Lopez O, Riezu-Boj JI et al. Diet, Gut Microbiota, and Obesity: Links with Host Genetics and Epigenetics and Potential Applications . Adv Nutr . 2019 ; 10 : S17 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Dabke K , Hendrick G, Devkota S. The gut microbiome and metabolic syndrome . J Clin Invest . 2019 ; 129 : 4050 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat David LA , Maurice CF, Carmody RN et al. Diet rapidly and reproducibly alters the human gut microbiome . Nature . 2014 ; 505 : 559 – 63 . Google Scholar Crossref Search ADS PubMed WorldCat Davis LMG , Martínez I, Walter J et al. Barcoded Pyrosequencing Reveals That Consumption of Galactooligosaccharides Results in a Highly Specific Bifidogenic Response in Humans . PLoS One . 2011 ; 6 : e25200 . Google Scholar Crossref Search ADS PubMed WorldCat Deehan EC , Duar RM, Armet AM et al. Modulation of the Gastrointestinal Microbiome with Nondigestible Fermentable Carbohydrates To Improve Human Health . Microbiol Spectrum . 2017 ; 5 : BAD – 0019 . Google Scholar OpenURL Placeholder Text WorldCat De Filippo C , Cavalieri D, Di Paola M et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa . Proc Natl Acad Sci . 2010 ; 107 : 14691 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat DeGruttola AK , Low D, Mizoguchi A et al. Current Understanding of Dysbiosis in Disease in Human and Animal Models . Inflamm Bowel Dis . 2016 ; 22 : 1137 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Den Besten G , Bleeker A, Gerding A et al. Short-Chain Fatty Acids Protect Against High-Fat Diet–Induced Obesity via a PPARγ-Dependent Switch From Lipogenesis to Fat Oxidation . Diabetes . 2015 ; 64 : 2398 – 408 . Google Scholar Crossref Search ADS PubMed WorldCat Denis S , Sayd T, Georges A et al. Digestion of cooked meat proteins is slightly affected by age as assessed using the dynamic gastrointestinal TIM model and mass spectrometry . Food Funct . 2016 ; 7 : 2682 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat De Paepe K , Verspreet J, Courtin CM et al. Microbial succession during wheat bran fermentation and colonisation by human faecal microbiota as a result of niche diversification . ISME J . 2020 ; 14 : 584 – 96 . Google Scholar Crossref Search ADS PubMed WorldCat De Paepe K , Verspreet J, Rezaei MN et al. Isolation of wheat bran-colonizing and metabolizing species from the human fecal microbiota . PeerJ . 2019 ; 7 : e6293 . Google Scholar Crossref Search ADS PubMed WorldCat De Paepe K , Verspreet J, Verbeke K et al. Introducing insoluble wheat bran as a gut microbiota niche in an in vitro dynamic gut model stimulates propionate and butyrate production and induces colon region specific shifts in the luminal and mucosal microbial community: Long-term wheat bran intervention in the SHIME . Environ Microbiol . 2018 ; 20 : 3406 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Depommier C , Everard A, Druart C et al. Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: a proof-of-concept exploratory study . Nat Med . 2019 ; 25 : 1096 – 103 . Google Scholar Crossref Search ADS PubMed WorldCat Depommier C , Van Hul M, Everard A et al. Pasteurized Akkermansia muciniphila increases whole-body energy expenditure and fecal energy excretion in diet-induced obese mice . Gut Microbes . 2020 : 1 – 15 . Google Scholar OpenURL Placeholder Text WorldCat Derrien M , Belzer C, de Vos WM. Akkermansia muciniphila and its role in regulating host functions . Microb Pathog . 2017 ; 106 : 171 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Derrien M , van Passel MWJ, van de Bovenkamp JHB et al. Mucin-bacterial interactions in the human oral cavity and digestive tract . Gut Microbes . 2010 ; 1 : 254 – 68 . Google Scholar Crossref Search ADS PubMed WorldCat Desai MS , Seekatz AM, Koropatkin NM et al. A Dietary Fiber-Deprived Gut Microbiota Degrades the Colonic Mucus Barrier and Enhances Pathogen Susceptibility . Cell . 2016 ; 167 : 1339 – 1353.e21 . Google Scholar Crossref Search ADS PubMed WorldCat Despres J , Forano E, Lepercq P et al. Unraveling the pectinolytic function of Bacteroides xylanisolvens using a RNA-seq approach and mutagenesis . BMC Genomics . 2016a ; 17 : 147 . Google Scholar Crossref Search ADS WorldCat Despres J , Forano E, Lepercq P et al. Xylan degradation by the human gut Bacteroides xylanisolvens XB1AT involves two distinct gene clusters that are linked at the transcriptional level . BMC Genomics . 2016b ; 17 : 326 . Google Scholar Crossref Search ADS WorldCat Dethlefsen L , Huse S, Sogin ML et al. The Pervasive Effects of an Antibiotic on the Human Gut Microbiota, as Revealed by Deep 16S rRNA Sequencing . PLoS Biol . 2008 ; 6 : e280 . Google Scholar Crossref Search ADS PubMed WorldCat De Vadder F , Kovatcheva-Datchary P, Zitoun C et al. Microbiota-Produced Succinate Improves Glucose Homeostasis via Intestinal Gluconeogenesis . Cell Metab . 2016 ; 24 : 151 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Devkota S , Wang Y, Musch MW et al. Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10−/− mice . Nature . 2012 ; 487 : 104 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat De Weirdt R , Van de Wiele T. Micromanagement in the gut: microenvironmental factors govern colon mucosal biofilm structure and functionality . npj Biofilms Microbiomes . 2015 ; 1 : 15026 . Google Scholar Crossref Search ADS PubMed WorldCat Dhingra D , Michael M, Rajput H et al. Dietary fibre in foods: a review . J Food Sci Technol . 2012 ; 49 : 255 – 66 . Google Scholar Crossref Search ADS PubMed WorldCat Diez-Gonzalez F , Callaway TR, Kizoulis MG et al. Grain feeding and the dissemination of acid-resistant Escherichia coli from cattle . Science . 1998 ; 281 : 1666 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Di R , Vakkalanka MS, Onumpai C et al. Pectic oligosaccharide structure-function relationships: Prebiotics, inhibitors of Escherichia coli O157:H7 adhesion and reduction of Shiga toxin cytotoxicity in HT29 cells . Food Chem . 2017 ; 227 : 245 – 54 . Google Scholar Crossref Search ADS PubMed WorldCat Donaldson GP , Lee SM, Mazmanian SK. Gut biogeography of the bacterial microbiota . Nat Rev Microbiol . 2016 ; 14 : 20 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat Donohoe DR , Collins LB, Wali A et al. The Warburg Effect Dictates the Mechanism of Butyrate-Mediated Histone Acetylation and Cell Proliferation . Mol Cell . 2012 ; 48 : 612 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Doorduyn Y , Van Den Brandhof WE, Van Duynhoven Y et al. Risk factors for Salmonella Enteritidis and Typhimurium (DT104 and non-DT104) infections in The Netherlands: predominant roles for raw eggs in Enteritidis and sandboxes in Typhimurium infections . Epidemiol Infect . 2006 ; 134 : 617 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Dotz V , Wuhrer M. Histo-blood group glycans in the context of personalized medicine . Biochimica et Biophysica Acta (BBA) - General Subjects . 2016 ; 1860 : 1596 – 607 . Google Scholar Crossref Search ADS WorldCat Duncan SH , Louis P, Thomson JM et al. The role of pH in determining the species composition of the human colonic microbiota . Environ Microbiol . 2009 ; 11 : 2112 – 22 . Google Scholar Crossref Search ADS PubMed WorldCat Dutta PR , Cappello R, Navarro-García F et al. Functional Comparison of Serine Protease Autotransporters of Enterobacteriaceae . IAI . 2002 ; 70 : 7105 – 13 . Google Scholar Crossref Search ADS WorldCat Dwivedi R , Nothaft H, Garber J et al. L-fucose influences chemotaxis and biofilm formation in Campylobacter jejuni: L-fucose influence on C. jejuni . Mol Microbiol . 2016 ; 101 : 575 – 89 . Google Scholar Crossref Search ADS PubMed WorldCat Earle KA , Billings G, Sigal M et al. Quantitative Imaging of Gut Microbiota Spatial Organization . Cell Host & Microbe . 2015 ; 18 : 478 – 88 . Google Scholar Crossref Search ADS PubMed WorldCat EFSA Panel on Dietetic Products . Scientific Opinion on the substantiation of health claims related to dietary fibre (ID 744, 745, 746, 748, 749, 753, 803, 810, 855, 1415, 1416, 4308, 4330) pursuant to Article 13(1) of Regulation (EC) No 1924/2006 . EFSA Journal : 23 . OpenURL Placeholder Text WorldCat Egan M , Jiang H, O'Connell Motherway M et al. Glycosulfatase-Encoding Gene Cluster in Bifidobacterium breve UCC2003 . Appl Environ Microbiol . 2016 ; 82 : 6611 – 23 . Google Scholar Crossref Search ADS PubMed WorldCat Egan M , O'Connell Motherway M, Kilcoyne M et al. Cross-feeding by Bifidobacterium breve UCC2003 during co-cultivation with Bifidobacterium bifidum PRL2010 in a mucin-based medium . BMC Microbiol . 2014 ; 14 : 282 . Google Scholar Crossref Search ADS PubMed WorldCat Erdem AL , Avelino F, Xicohtencatl-Cortes J et al. Host Protein Binding and Adhesive Properties of H6 and H7 Flagella of Attaching and Effacing Escherichia coli . JB . 2007 ; 189 : 7426 – 35 . Google Scholar Crossref Search ADS WorldCat Etienne-Mesmin L , Chassaing B, Desvaux M et al. Experimental models to study intestinal microbes–mucus interactions in health and disease . FEMS Microbiol Rev . 2019 ; 43 : 457 – 89 . Google Scholar Crossref Search ADS PubMed WorldCat Etienne-Mesmin L , Livrelli V, Privat M et al. Effect of a New Probiotic Saccharomyces cerevisiae Strain on Survival of Escherichia coli O157:H7 in a Dynamic Gastrointestinal Model . Appl Environ Microbiol . 2011 ; 77 : 1127 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Etzold S , MacKenzie DA, Jeffers F et al. Structural and molecular insights into novel surface-exposed mucus adhesins from Lactobacillus reuteri human strains: A novel mucus adhesin from Lactobacillus reuteri . Mol Microbiol . 2014 ; 92 : 543 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Everard A , Belzer C, Geurts L et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity . Proc Natl Acad Sci . 2013 ; 110 : 9066 – 71 . Google Scholar Crossref Search ADS PubMed WorldCat Fabich AJ , Jones SA, Chowdhury FZ et al. Comparison of Carbon Nutrition for Pathogenic and Commensal Escherichia coli Strains in the Mouse Intestine . IAI . 2008 ; 76 : 1143 – 52 . Google Scholar Crossref Search ADS WorldCat Falony G , Vlachou A, Verbrugghe K et al. Cross-Feeding between Bifidobacterium longum BB536 and Acetate-Converting, Butyrate-Producing Colon Bacteria during Growth on Oligofructose . AEM . 2006 ; 72 : 7835 – 41 . Google Scholar Crossref Search ADS WorldCat Fechner A , Kiehntopf M, Jahreis G. The Formation of Short-Chain Fatty Acids Is Positively Associated with the Blood Lipid–Lowering Effect of Lupin Kernel Fiber in Moderately Hypercholesterolemic Adults . J Nutr . 2014 ; 144 : 599 – 607 . Google Scholar Crossref Search ADS PubMed WorldCat Ferreira RBR , Willing BP, Finlay BB. Bringing Koch's Postulates to the Table in IBD . Cell Host & Microbe . 2011 ; 9 : 353 – 4 . Google Scholar Crossref Search ADS PubMed WorldCat Ferreyra JA , Wu KJ, Hryckowian AJ et al. Gut Microbiota-Produced Succinate Promotes C. difficile Infection after Antibiotic Treatment or Motility Disturbance . Cell Host & Microbe . 2014 ; 16 : 770 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Ficko-Blean E , Boraston AB. Insights into the recognition of the human glycome by microbial carbohydrate-binding modules . Curr Opin Struct Biol . 2012 ; 22 : 570 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Fooks LJ , Gibson GR. Mixed culture fermentation studies on the effects of synbiotics on the human intestinal pathogens Campylobacter jejuni and Escherichia coli . Anaerobe . 2003 ; 9 : 231 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Fuentes-Zaragoza E , Riquelme-Navarrete MJ, Sánchez-Zapata E et al. Resistant starch as functional ingredient: A review . Food Res Int . 2010 ; 43 : 931 – 42 . Google Scholar Crossref Search ADS WorldCat Fukuda S , Toh H, Hase K et al. Bifidobacteria can protect from enteropathogenic infection through production of acetate . Nature . 2011 ; 469 : 543 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Fuller S , Beck E, Salman H et al. New Horizons for the Study of Dietary Fiber and Health: A Review . Plant Foods Hum Nutr . 2016 ; 71 : 1 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Gagnon M , Zihler Berner A, Chervet N et al. Comparison of the Caco-2, HT-29 and the mucus-secreting HT29-MTX intestinal cell models to investigate Salmonella adhesion and invasion . J Microbiol Methods . 2013 ; 94 : 274 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Galvez J , Rodríguez-Cabezas ME, Zarzuelo A. Effects of dietary fiber on inflammatory bowel disease . Mol Nutr Food Res . 2005 ; 49 : 601 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Ganner A , Schatzmayr G. Capability of yeast derivatives to adhere enteropathogenic bacteria and to modulate cells of the innate immune system . Appl Microbiol Biotechnol . 2012 ; 95 : 289 – 97 . Google Scholar Crossref Search ADS PubMed WorldCat Garrett WS , Gallini CA, Yatsunenko T et al. Enterobacteriaceae Act in Concert with the Gut Microbiota to Induce Spontaneous and Maternally Transmitted Colitis . Cell Host & Microbe . 2010 ; 8 : 292 – 300 . Google Scholar Crossref Search ADS PubMed WorldCat Garrido-Maestu A , Ma Z, Paik S-Y-R et al. Engineering of chitosan-derived nanoparticles to enhance antimicrobial activity against foodborne pathogen Escherichia coli O157:H7 . Carbohydr Polym . 2018 ; 197 : 623 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Garrido D , Kim JH, German JB et al. Oligosaccharide Binding Proteins from Bifidobacterium longum subsp. infantis Reveal a Preference for Host Glycans . PLoS One . 2011 ; 6 : e17315 . Google Scholar Crossref Search ADS PubMed WorldCat Gevers D , Kugathasan S, Denson LA et al. The Treatment-Naive Microbiome in New-Onset Crohn’s Disease . Cell Host & Microbe . 2014 ; 15 : 382 – 92 . Google Scholar Crossref Search ADS PubMed WorldCat Ghosh S , Dai C, Brown K et al. Colonic microbiota alters host susceptibility to infectious colitis by modulating inflammation, redox status, and ion transporter gene expression . Am J Physiol-Gastro Liver Physiol . 2011 ; 301 : G39 – 49 . Google Scholar Crossref Search ADS WorldCat Giannoukos S , Agapiou A, Brkić B et al. Volatolomics: A broad area of experimentation . J Chromatogr B . 2019 ; 1105 : 136 – 47 . Google Scholar Crossref Search ADS WorldCat Gibold L , Garenaux E, Dalmasso G et al. The Vat-AIEC protease promotes crossing of the intestinal mucus layer by Crohn's disease-associated Escherichia coli: Vat-AIEC Favours Mucus Layer's Crossing by LF82 E. coli . Cell Microbiol . 2016 ; 18 : 617 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Gibson GR , Cummings JH, Macfarlane GT. Use of a three-stage continuous culture system to study the effect of mucin on dissimilatory sulfate reduction and methanogenesis by mixed populations of human gut bacteria . Appl Environ Microbiol . 1988 ; 54 : 2750 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Gilbert RA , Denman SE, Padmanabha J et al. Effect of diet on the concentration of complex Shiga toxin-producing Escherichia coli and EHEC virulence genes in bovine faeces, hide and carcass . Int J Food Microbiol . 2008 ; 121 : 208 – 16 . Google Scholar Crossref Search ADS PubMed WorldCat Gong J , Yang C. Advances in the methods for studying gut microbiota and their relevance to the research of dietary fiber functions . Food Res Int . 2012 ; 48 : 916 – 29 . Google Scholar Crossref Search ADS WorldCat González-Ortiz G , Hermes RG, Jiménez-Díaz R et al. Screening of extracts from natural feed ingredients for their ability to reduce enterotoxigenic Escherichia coli (ETEC) K88 adhesion to porcine intestinal epithelial cell-line IPEC-J2 . Vet Microbiol . 2013 ; 167 : 494 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat González-Ortiz G , Pérez JF, Hermes RG et al. Screening the ability of natural feed ingredients to interfere with the adherence of enterotoxigenic Escherichia coli (ETEC) K88 to the porcine intestinal mucus . Br J Nutr . 2014 ; 111 : 633 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Gophna U , Sommerfeld K, Gophna S et al. Differences between Tissue-Associated Intestinal Microfloras of Patients with Crohn's Disease and Ulcerative Colitis . J Clin Microbiol . 2006 ; 44 : 4136 – 41 . Google Scholar Crossref Search ADS PubMed WorldCat Grahn N , Hmani-Aifa M, Fransén K et al. Molecular identification of Helicobacter DNA present in human colorectal adenocarcinomas by 16S rDNA PCR amplification and pyrosequencing analysis . J Med Microbiol . 2005 ; 54 : 1031 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Graziani F , Pujol A, Nicoletti C et al. Ruminococcus gnavus E1 modulates mucin expression and intestinal glycosylation . J Appl Microbiol . 2016 ; 120 : 1403 – 17 . Google Scholar Crossref Search ADS PubMed WorldCat Greenhalgh K , Ramiro-Garcia J, Heinken A et al. Integrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells . Cell Rep . 2019 ; 27 : 1621 – 32 ..e9. Google Scholar Crossref Search ADS PubMed WorldCat Grondin JM , Tamura K, Déjean G et al. Polysaccharide Utilization Loci: Fueling Microbial Communities . J Bacteriol . 2017 ; 199 : e00860 – 16 ., e00860-16 . Google Scholar Crossref Search ADS PubMed WorldCat Grys TE , Siegel MB, Lathem WW et al. The StcE Protease Contributes to Intimate Adherence of Enterohemorrhagic Escherichia coli O157:H7 to Host Cells . IAI . 2005 ; 73 : 1295 – 303 . Google Scholar Crossref Search ADS WorldCat Guerra-Ordaz AA , González-Ortiz G, La Ragione RM et al. Lactulose and Lactobacillus plantarum, a Potential Complementary Synbiotic To Control Postweaning Colibacillosis in Piglets . Appl Environ Microbiol . 2014 ; 80 : 4879 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Guerra A , Etienne-Mesmin L, Livrelli V et al. Relevance and challenges in modeling human gastric and small intestinal digestion . Trends Biotechnol . 2012 ; 30 : 591 – 600 . Google Scholar Crossref Search ADS PubMed WorldCat Halas D , Hansen CF, Hampson DJ et al. Effect of dietary supplementation with inulin and/or benzoic acid on the incidence and severity of post-weaning diarrhoea in weaner pigs after experimental challenge with enterotoxigenic Escherichia coli . Arch Anim Nutr . 2009 ; 63 : 267 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Hall AB , Yassour M, Sauk J et al. A novel Ruminococcus gnavus clade enriched in inflammatory bowel disease patients . Genome Med . 2017 ; 9 : 103 . Google Scholar Crossref Search ADS PubMed WorldCat Hamaker BR , Tuncil YE. A Perspective on the Complexity of Dietary Fiber Structures and Their Potential Effect on the Gut Microbiota . J Mol Biol . 2014 ; 426 : 3838 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Hansson GC. Role of mucus layers in gut infection and inflammation . Curr Opin Microbiol . 2012 ; 15 : 57 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Hata DJ , Smith DS. Blood Group B Degrading Activity of Ruminococcus gnavus α-Galactosidase . Artificial Cells, Blood Substitutes, and Biotechnology . 2004 ; 32 : 263 – 74 . Google Scholar Crossref Search ADS WorldCat Hayden UL , McGuirk SM, West SE et al. Psyllium improves fecal consistency and prevents enhanced secretory responses in jejunal tissues of piglets infected with ETEC . Dig Dis Sci . 1998 ; 43 : 2536 – 41 . Google Scholar Crossref Search ADS PubMed WorldCat Hecht AL , Casterline BW, Choi VM et al. A Two-Component System Regulates Bacteroides fragilis Toxin to Maintain Intestinal Homeostasis and Prevent Lethal Disease . Cell Host & Microbe . 2017 ; 22 : 443 – 8 ..e5. Google Scholar Crossref Search ADS PubMed WorldCat Hedblom GA , Reiland HA, Sylte MJ et al. Segmented Filamentous Bacteria – Metabolism Meets Immunity . Front Microbiol . 2018 ; 9 : 1991 . Google Scholar Crossref Search ADS PubMed WorldCat Hehemann J-H , Correc G, Barbeyron T et al. Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota . Nature . 2010 ; 464 : 908 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Hehemann J-H , Kelly AG, Pudlo NA et al. Bacteria of the human gut microbiome catabolize red seaweed glycans with carbohydrate-active enzyme updates from extrinsic microbes . Proc Natl Acad Sci . 2012 ; 109 : 19786 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat Heikema AP , Bergman MP, Richards H et al. Characterization of the Specific Interaction between Sialoadhesin and Sialylated Campylobacter jejuni Lipooligosaccharides . IAI . 2010 ; 78 : 3237 – 46 . Google Scholar Crossref Search ADS WorldCat Hernot DC , Boileau TW, Bauer LL et al. In Vitro Digestion Characteristics of Unprocessed and Processed Whole Grains and Their Components . J Agric Food Chem . 2008 ; 56 : 10721 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Hews CL , Tran S-L, Wegmann U et al. The StcE metalloprotease of enterohaemorrhagic Escherichia coli reduces the inner mucus layer and promotes adherence to human colonic epithelium ex vivo . Cell Microbiol . 2017 ; 19 : e12717 . Google Scholar Crossref Search ADS WorldCat Holmén Larsson JM , Karlsson H, Sjövall H et al. A complex, but uniform O-glycosylation of the human MUC2 mucin from colonic biopsies analyzed by nanoLC/MSn . Glycobiology . 2009 ; 19 : 756 – 66 . Google Scholar Crossref Search ADS PubMed WorldCat Holscher HD. Dietary fiber and prebiotics and the gastrointestinal microbiota . Gut Microbes . 2017 ; 8 : 172 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Hoyer LL , Hamilton AC, Steenbergen SM et al. Cloning, sequencing and distribution of the Salmonella typhimurium LT2 siaiidase gene, nanH, provides evidence for interspecies gene transfer . Mol Microbiol . 1992 ; 6 : 873 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Hugenholtz F , de Vos WM. Mouse models for human intestinal microbiota research: a critical evaluation . Cell Mol Life Sci . 2018 ; 75 : 149 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Hughes RL , Marco ML, Hughes JP et al. The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models-Part I: Overview of Current Methods . Adv Nutr . 2019 ; 10 : 953 – 78 . Google Scholar Crossref Search ADS PubMed WorldCat Hughes SA , Shewry PR, Gibson GR et al. In vitro fermentation of oat and barley derived β-glucans by human faecal microbiota . FEMS Microbiol Ecol . 2008 ; 64 ; 482 – 93 . Google Scholar Crossref Search ADS PubMed WorldCat Hunt DE , Gevers D, Vahora NM et al. Conservation of the Chitin Utilization Pathway in the Vibrionaceae . AEM . 2008 ; 74 : 44 – 51 . Google Scholar Crossref Search ADS WorldCat Huq A , Small EB, West PA et al. Ecological relationships between Vibrio cholerae and planktonic crustacean copepods . Appl Environ Microbiol . 1983 ; 45 : 275 – 83 . Google Scholar Crossref Search ADS PubMed WorldCat Hylla S , Gostner A, Dusel G et al. Effects of resistant starch on the colon in healthy volunteers: possible implications for cancer prevention . Am J Clin Nutr . 1998 ; 67 : 136 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Idota T , Kawakami H, Murakami Y et al. Inhibition of Cholera Toxin by Human Milk Fractions and Sialyllactose . Biosci Biotechnol Biochem . 1995 ; 59 : 417 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Idota T , Kawakami H. Inhibitory Effects of Milk Gangliosides on the Adhesion of Escherichia coli to Human Intestinal Carcinoma Cells . Biosci Biotechnol Biochem . 1995 ; 59 : 69 – 72 . Google Scholar Crossref Search ADS PubMed WorldCat Ijssennagger N , van der Meer R, van Mil SWC. Sulfide as a Mucus Barrier-Breaker in Inflammatory Bowel Disease? Trends Mol Med . 2016 ; 22 : 190 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Jalili-Firoozinezhad S , Gazzaniga FS, Calamari EL et al. A complex human gut microbiome cultured in an anaerobic intestine-on-a-chip . Nat Biomed Eng . 2019 ; 3 : 520 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Janoir C , Péchiné S, Grosdidier C et al. Cwp84, a Surface-Associated Protein of Clostridium difficile, Is a Cysteine Protease with Degrading Activity on Extracellular Matrix Proteins . JB . 2007 ; 189 : 7174 – 80 . Google Scholar Crossref Search ADS WorldCat Janssen AWF , Kersten S. The role of the gut microbiota in metabolic health . FASEB J . 2015 ; 29 : 3111 – 23 . Google Scholar Crossref Search ADS PubMed WorldCat Jazi V , Mohebodini H, Ashayerizadeh A et al. Fermented soybean meal ameliorates Salmonella Typhimurium infection in young broiler chickens . Poult Sci . 2019 ; 98 : 5648 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Jeong KC , Kang MY, Kang J et al. Reduction of Escherichia coli O157:H7 Shedding in Cattle by Addition of Chitosan Microparticles to Feed . Appl Environ Microbiol . 2011 ; 77 : 2611 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Jeon SJ , Ma Z, Kang M et al. Application of chitosan microparticles for treatment of metritis and in vivo evaluation of broad spectrum antimicrobial activity in cow uteri . Biomaterials . 2016 ; 110 : 71 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Jeon SJ , Oh M, Yeo W-S et al. Underlying Mechanism of Antimicrobial Activity of Chitosan Microparticles and Implications for the Treatment of Infectious Diseases . PLoS One . 2014 ; 9 : e92723 . Google Scholar Crossref Search ADS PubMed WorldCat Johansson MEV , Hansson GC. Immunological aspects of intestinal mucus and mucins . Nat Rev Immunol . 2016 ; 16 : 639 – 49 . Google Scholar Crossref Search ADS PubMed WorldCat Johansson MEV , Sjövall H, Hansson GC. The gastrointestinal mucus system in health and disease . Nat Rev Gastroenterol Hepatol . 2013 ; 10 : 352 – 61 . Google Scholar Crossref Search ADS PubMed WorldCat Johansson MEV. Fast Renewal of the Distal Colonic Mucus Layers by the Surface Goblet Cells as Measured by In Vivo Labeling of Mucin Glycoproteins . PLoS One . 2012 ; 7 : e41009 . Google Scholar Crossref Search ADS PubMed WorldCat Jones JM. CODEX-aligned dietary fiber definitions help to bridge the ‘fiber gap .’ Nutr J . 2014 ; 13 : 34 . Google Scholar Crossref Search ADS PubMed WorldCat Juge N . Microbial adhesins to gastrointestinal mucus . Trends Microbiol . 2012 ; 20 : 30 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Kakodkar S , Mutlu EA. Diet as a Therapeutic Option for Adult Inflammatory Bowel Disease . Gastroenterol Clin North Am . 2017 ; 46 : 745 – 67 . Google Scholar Crossref Search ADS PubMed WorldCat Kamada N , Chen GY, Inohara N et al. Control of pathogens and pathobionts by the gut microbiota . Nat Immunol . 2013 ; 14 : 685 – 90 . Google Scholar Crossref Search ADS PubMed WorldCat Kaoutari AE , Armougom F, Gordon JI et al. The abundance and variety of carbohydrate-active enzymes in the human gut microbiota . Nat Rev Microbiol . 2013 ; 11 : 497 – 504 . Google Scholar Crossref Search ADS PubMed WorldCat Kaoutari AE , Armougom F, Raoult D et al. Le microbiote intestinal et la digestion des polysaccharides . Med Sci (Paris) . 2014 ; 30 : 259 – 65 . Google Scholar Crossref Search ADS PubMed WorldCat Kaser A , Lee A-H, Franke A et al. XBP1 Links ER Stress to Intestinal Inflammation and Confers Genetic Risk for Human Inflammatory Bowel Disease . Cell . 2008 ; 134 : 743 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Kashyap PC , Marcobal A, Ursell LK et al. Genetically dictated change in host mucus carbohydrate landscape exerts a diet-dependent effect on the gut microbiota . Proc Natl Acad Sci . 2013 ; 110 : 17059 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Kelly CP , Pothoulakis C, LaMont JT. Clostridium difficile Colitis . N Engl J Med . 1994 ; 330 ; 257 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Kelly RJ , Rouquier S, Giorgi D et al. Sequence and Expression of a Candidate for the Human Secretor Blood Group α(1,2)Fucosyltransferase Gene (FUT2) . J Biol Chem . 1995 ; 270 : 4640 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Kenny DT , Skoog EC, Lindén SK et al. Presence of terminal N-acetylgalactosamineβ1-4N-acetylglucosamine residues on O-linked oligosaccharides from gastric MUC5AC: Involvement in Helicobacter pylori colonization? Glycobiology . 2012 ; 22 : 1077 – 85 . Google Scholar Crossref Search ADS PubMed WorldCat Kim CC , Healey GR, Kelly WJ et al. Genomic insights from Monoglobus pectinilyticus: a pectin-degrading specialist bacterium in the human colon . ISME J . 2019 ; 13 : 1437 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Kimura I , Ozawa K, Inoue D et al. The gut microbiota suppresses insulin-mediated fat accumulation via the short-chain fatty acid receptor GPR43 . Nat Commun . 2013 ; 4 : 1829 . Google Scholar Crossref Search ADS PubMed WorldCat Kim Y , oh S, Kim SH. Released exopolysaccharide (r-EPS) produced from probiotic bacteria reduce biofilm formation of enterohemorrhagic Escherichia coli O157:H7 . Biochem Biophys Res Commun . 2009 ; 379 : 324 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat King DE , Mainous AG, Lambourne CA. Trends in Dietary Fiber Intake in the United States, 1999–2008 . J Acad Nutrition Dietetics . 2012 ; 112 : 642 – 8 . Google Scholar Crossref Search ADS WorldCat Kirk RGW . “Life in a Germ-Free World”: Isolating Life from the Laboratory Animal to the Bubble Boy . Bull Hist Med . 2012 ; 86 : 237 – 75 . Google Scholar Crossref Search ADS PubMed WorldCat Kirn TJ , Jude BA, Taylor RK. A colonization factor links Vibrio cholerae environmental survival and human infection . Nature . 2005 ; 438 : 863 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Kitahara M , Sakamoto M, Ike M et al. Bacteroides plebeius sp. nov. and Bacteroides coprocola sp. nov., isolated from human faeces . Int J Syst Evol Microbiol . 2005 ; 55 : 2143 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Knudsen KEB , Wisker E, Daniel M et al. Digestibility of energy, protein, fat and non-starch polysaccharides in mixed diets: Comparative studies between man and the rat . Br J Nutr . 1994 ; 71 : 471 – 87 . Google Scholar Crossref Search ADS PubMed WorldCat Koropatkin NM , Cameron EA, Martens EC. How glycan metabolism shapes the human gut microbiota . Nat Rev Microbiol . 2012 ; 10 : 323 – 35 . Google Scholar Crossref Search ADS PubMed WorldCat Kostic AD , Chun E, Robertson L et al. Fusobacterium nucleatum Potentiates Intestinal Tumorigenesis and Modulates the Tumor-Immune Microenvironment . Cell Host & Microbe . 2013 ; 14 : 207 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Kotloff KL . The Burden and Etiology of Diarrheal Illness in Developing Countries . Pediatr Clin North Am . 2017 ; 64 : 799 – 814 . Google Scholar Crossref Search ADS PubMed WorldCat Kościelak J. The Hypothesis on Function of Glycosphingolipids and ABO Blood Groups Revisited . Neurochem Res . 2012 ; 37 : 1170 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Krishnan S , Eslick GD. Streptococcus bovis infection and colorectal neoplasia: a meta-analysis . Colorectal Dis . 2014 ; 16 : 672 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Kuda T , Hirano S, Yokota Y et al. Effect of depolymerized sodium alginate on Salmonella Typhimurium infection in human enterocyte-like HT-29-Luc cells and BALB/c mice . J Funct Foods . 2017 ; 28 : 122 – 6 . Google Scholar Crossref Search ADS WorldCat Kudva IT , Hunt CW, Williams CJ et al. Evaluation of dietary influences on Escherichia coli O157:H7 shedding by sheep . Appl Environ Microbiol . 1997 ; 63 : 3878 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Kumar P , Luo Q, Vickers TJ et al. EatA, an Immunogenic Protective Antigen of Enterotoxigenic Escherichia coli, Degrades Intestinal Mucin . Infect Immun . 2014 ; 82 : 500 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Kunz C , Rudloff S, Baier W et al. OLIGOSACCHARIDES IN HUMAN MILK : Structural, Functional, and Metabolic Aspects . Annu Rev Nutr . 2000 ; 20 : 699 – 722 . Google Scholar Crossref Search ADS PubMed WorldCat Ladinsky MS , Araujo LP, Zhang X et al. Endocytosis of commensal antigens by intestinal epithelial cells regulates mucosal T cell homeostasis . Science . 2019 ; 363 : eaat4042 . Google Scholar Crossref Search ADS PubMed WorldCat Lamichhane S , Yde CC, Forssten S et al. Impact of Dietary Polydextrose Fiber on the Human Gut Metabolome . J Agric Food Chem . 2014 ; 62 : 9944 – 51 . Google Scholar Crossref Search ADS PubMed WorldCat La Rosa SL , Leth ML, Michalak L et al. The human gut Firmicute Roseburia intestinalis is a primary degrader of dietary β-mannans . Nat Commun . 2019 ; 10 : 905 . Google Scholar Crossref Search ADS PubMed WorldCat Larsbrink J , Rogers TE, Hemsworth GR et al. A discrete genetic locus confers xyloglucan metabolism in select human gut Bacteroidetes . Nature . 2014 ; 506 : 498 – 502 . Google Scholar Crossref Search ADS PubMed WorldCat Lathem WW , Grys TE, Witowski SE et al. StcE, a metalloprotease secreted by Escherichia coli O157:H7, specifically cleaves C1 esterase inhibitor . Mol Microbiol . 2002 ; 45 : 277 – 88 . Google Scholar Crossref Search ADS PubMed WorldCat Lavelle A , Sokol H. Gut microbiota-derived metabolites as key actors in inflammatory bowel disease . Nat Rev Gastroenterol Hepatol . 2020 ; 17 : 223 – 37 . Google Scholar Crossref Search ADS PubMed WorldCat Lawhon SD , Maurer R, Suyemoto M et al. Intestinal short-chain fatty acids alter Salmonella typhimurium invasion gene expression and virulence through BarA/SirA: Short-chain fatty acids and Salmonella invasion . Mol Microbiol . 2002 ; 46 : 1451 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Leatham MP , Banerjee S, Autieri SM et al. Precolonized Human Commensal Escherichia coli Strains Serve as a Barrier to E. coli O157:H7 Growth in the Streptomycin-Treated Mouse Intestine . IAI . 2009 ; 77 : 2876 – 86 . Google Scholar Crossref Search ADS WorldCat Le Bihan G , Sicard J-F, Garneau P et al. The NAG Sensor NagC Regulates LEE Gene Expression and Contributes to Gut Colonization by Escherichia coli O157:H7 . Front Cell Infect Microbiol . 2017 ; 7 : 134 . Google Scholar Crossref Search ADS PubMed WorldCat Lee H , Ko G. Effect of Metformin on Metabolic Improvement and Gut Microbiota . Appl Environ Microbiol . 2014 ; 80 : 5935 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Lee SM , Donaldson GP, Mikulski Z et al. Bacterial colonization factors control specificity and stability of the gut microbiota . Nature . 2013 ; 501 : 426 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Leitch ECM , Walker AW, Duncan SH et al. Selective colonization of insoluble substrates by human faecal bacteria . Environ Microbiol . 2007 ; 9 : 667 – 79 . Google Scholar Crossref Search ADS PubMed WorldCat Lema M , Williams L, Walker L et al. Effect of dietary fiber on E. coli O157:H7 shedding in lambs . Small Ruminant Research . 2002 : 7 . Google Scholar OpenURL Placeholder Text WorldCat Leocádio PCL , Oriá RB, Crespo-Lopez ME et al. Obesity: More Than an Inflammatory, an Infectious Disease? Front Immunol . 2020 ; 10 : 3092 . Google Scholar Crossref Search ADS PubMed WorldCat Leong A , Liu Z, Almshawit H et al. Oligosaccharides in goats’ milk-based infant formula and their prebiotic and anti-infection properties . Br J Nutr . 2019 ; 122 : 441 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Lesmes U , Beards EJ, Gibson GR et al. Effects of Resistant Starch Type III Polymorphs on Human Colon Microbiota and Short Chain Fatty Acids in Human Gut Models . J Agric Food Chem . 2008 ; 56 : 5415 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Leyton DL , Sloan J, Hill RE et al. Transfer Region of pO113 from Enterohemorrhagic Escherichia coli: Similarity with R64 and Identification of a Novel Plasmid-Encoded Autotransporter, EpeA . IAI . 2003 ; 71 : 6307 – 19 . Google Scholar Crossref Search ADS WorldCat Li H , Limenitakis JP, Fuhrer T et al. The outer mucus layer hosts a distinct intestinal microbial niche . Nat Commun . 2015 ; 6 : 8292 . Google Scholar Crossref Search ADS PubMed WorldCat Liou AP , Paziuk M, Luevano J-M et al. Conserved Shifts in the Gut Microbiota Due to Gastric Bypass Reduce Host Weight and Adiposity . Sci Transl Med . 2013 ; 5 : 178ra41 . Google Scholar Crossref Search ADS PubMed WorldCat Liu G , Chen S, Guan G et al. Chitosan Modulates Inflammatory Responses in Rats Infected with Enterotoxigenic Escherichia coli . Mediators Inflamm . 2016 ; 2016 : 1 – 6 . Google Scholar OpenURL Placeholder Text WorldCat Liu XF , Guan YL, Yang DZ et al. Antibacterial action of chitosan and carboxymethylated chitosan . J Appl Polym Sci . 2000 ; 79 : 1324 – 35 . Google Scholar OpenURL Placeholder Text WorldCat Liu Z , Wang Y, Liu S et al. Vibrio cholerae Represses Polysaccharide Synthesis To Promote Motility in Mucosa . Infect Immun . 2015 ; 83 : 1114 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Liu Z , Zhang Z, Qiu L et al. Characterization and bioactivities of the exopolysaccharide from a probiotic strain of Lactobacillus plantarum WLPL04 . J Dairy Sci . 2017 ; 100 : 6895 – 905 . Google Scholar Crossref Search ADS PubMed WorldCat Lozupone CA , Stombaugh JI, Gordon JI et al. Diversity, stability and resilience of the human gut microbiota . Nature . 2012 ; 489 : 220 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Lucas A , Cole TJ. Breast milk and neonatal necrotising enterocolitis . Lancet North Am Ed . 1990 ; 336 : 1519 – 23 . Google Scholar Crossref Search ADS WorldCat Lucas C , Barnich N, Nguyen H. Microbiota, Inflammation and Colorectal Cancer . IJMS . 2017 ; 18 : 1310 . Google Scholar Crossref Search ADS WorldCat Luo Q , Kumar P, Vickers TJ et al. Enterotoxigenic Escherichia coli Secretes a Highly Conserved Mucin-Degrading Metalloprotease To Effectively Engage Intestinal Epithelial Cells . Infect Immun . 2014 ; 82 : 509 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Lupp C , Robertson ML, Wickham ME et al. Host-Mediated Inflammation Disrupts the Intestinal Microbiota and Promotes the Overgrowth of Enterobacteriaceae . Cell Host & Microbe . 2007 ; 2 : 119 – 29 . Google Scholar Crossref Search ADS PubMed WorldCat Machiels K , Joossens M, Sabino J et al. A decrease of the butyrate-producing species Roseburia hominis and Faecalibacterium prausnitzii defines dysbiosis in patients with ulcerative colitis . Gut . 2014 ; 63 : 1275 – 83 . Google Scholar Crossref Search ADS PubMed WorldCat Macia L , Tan J, Vieira AT et al. Metabolite-sensing receptors GPR43 and GPR109A facilitate dietary fibre-induced gut homeostasis through regulation of the inflammasome . Nat Commun . 2015 ; 6 : 6734 . Google Scholar Crossref Search ADS PubMed WorldCat Magalhães A , Marcos-Pinto R, Nairn AV et al. Helicobacter pylori chronic infection and mucosal inflammation switches the human gastric glycosylation pathways . Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease . 2015 ; 1852 : 1928 – 39 . Google Scholar Crossref Search ADS WorldCat Magalhães A , Marcos-Pinto R, Nairn AV et al. Helicobacter pylori chronic infection and mucosal inflammation switches the human gastric glycosylation pathways . Biochim Biophys Acta Mol Basis Dis . 2015 ; 1852 : 1928 – 39 . Google Scholar Crossref Search ADS WorldCat Mahdavi J. Helicobacter pylori SabA Adhesin in Persistent Infection and Chronic Inflammation . Science . 2002 ; 297 : 573 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Makki K , Deehan EC, Walter J et al. The Impact of Dietary Fiber on Gut Microbiota in Host Health and Disease . Cell Host & Microbe . 2018 ; 23 : 705 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Mantle M , Rombough C. Growth in and breakdown of purified rabbit small intestinal mucin by Yersinia enterocolitica . Infect Immun . 1993 ; 61 : 4131 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Marcobal A , Southwick AM, Earle KA et al. A refined palate: Bacterial consumption of host glycans in the gut . Glycobiology . 2013 ; 23 : 1038 – 46 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Chiang HC, Gordon JI. Mucosal Glycan Foraging Enhances Fitness and Transmission of a Saccharolytic Human Gut Bacterial Symbiont . Cell Host & Microbe . 2008 ; 4 : 447 – 57 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Koropatkin NM, Smith TJ et al. Complex Glycan Catabolism by the Human Gut Microbiota: The Bacteroidetes Sus-like Paradigm . J Biol Chem . 2009 ; 284 : 24673 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Lowe EC, Chiang H et al. Recognition and Degradation of Plant Cell Wall Polysaccharides by Two Human Gut Symbionts . PLoS Biol . 2011 ; 9 : e1001221 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Neumann M, Desai MS. Interactions of commensal and pathogenic microorganisms with the intestinal mucosal barrier . Nat Rev Microbiol . 2018 ; 16 : 457 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Martin HM , Campbell BJ, Hart CA et al. Enhanced Escherichia coli adherence and invasion in Crohn's disease and colon cancer . Gastroenterology . 2004 ; 127 : 80 – 93 . Google Scholar Crossref Search ADS PubMed WorldCat Martínez I , Kim J, Duffy PR et al. Resistant Starches Types 2 and 4 Have Differential Effects on the Composition of the Fecal Microbiota in Human Subjects . PLoS One . 2010 ; 5 : e15046 . Google Scholar Crossref Search ADS PubMed WorldCat Martínez I , Stegen JC, Maldonado-Gómez MX et al. The Gut Microbiota of Rural Papua New Guineans: Composition, Diversity Patterns, and Ecological Processes . Cell Rep . 2015 ; 11 : 527 – 38 . Google Scholar Crossref Search ADS PubMed WorldCat Marzorati M , Vanhoecke B, De Ryck T et al. The HMITM module: a new tool to study the Host-Microbiota Interaction in the human gastrointestinal tract in vitro . BMC Microbiol . 2014 ; 14 : 133 . Google Scholar Crossref Search ADS PubMed WorldCat Ma Z , Kim D, Adesogan AT et al. Chitosan Microparticles Exert Broad-Spectrum Antimicrobial Activity against Antibiotic-Resistant Micro-organisms without Increasing Resistance . ACS Appl Mater Interfaces . 2016 ; 8 : 10700 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat McKenney PT , Pamer EG. From Hype to Hope: The Gut Microbiota in Enteric Infectious Disease . Cell . 2015 ; 163 : 1326 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat McRorie JW , McKeown NM. Understanding the Physics of Functional Fibers in the Gastrointestinal Tract: An Evidence-Based Approach to Resolving Enduring Misconceptions about Insoluble and Soluble Fiber . J Acad Nutrition and Dietetics . 2017 ; 117 : 251 – 64 . Google Scholar Crossref Search ADS WorldCat Mehta RS , Nishihara R, Cao Y et al. Association of Dietary Patterns With Risk of Colorectal Cancer Subtypes Classified by Fusobacterium nucleatum in Tumor Tissue . JAMA Oncol . 2017 ; 3 : 921 . Google Scholar Crossref Search ADS PubMed WorldCat Meibom KL , Li XB, Nielsen AT et al. The Vibrio cholerae chitin utilization program . Proc Natl Acad Sci . 2004 ; 101 : 2524 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Meinzen-Derr J , Poindexter B, Wraje L et al. Role of human milk in extremely low birth weight infants’ risk of necrotizing enterocolitis or death . J Perinatol . 2009 ; 29 : 57 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Minekus M . The TNO Gastro-Intestinal Model (TIM) . In: Verhoeckx K, Cotter P, López-Expósito I et al. (eds). The Impact of Food Bioactives on Health . Cham : Springer International Publishing , 2015 , 37 – 46 . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Mirande C , Kadlecikova E, Matulova M et al. Dietary fibre degradation and fermentation by two xylanolytic bacteria Bacteroides xylanisolvens XB1A T and Roseburia intestinalis XB6B4 from the human intestine . J Appl Microbiol . 2010 ; 109 : 451 – 60 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Mirza NN , McCloud JM, Cheetham MJ. Clostridium septicum sepsis and colorectal cancer - a reminder . World J Surg Onc . 2009 ; 7 : 73 . Google Scholar Crossref Search ADS WorldCat Miszczycha SD , Thévenot J, Denis S et al. Survival of Escherichia coli O26:H11 exceeds that of Escherichia coli O157:H7 as assessed by simulated human digestion of contaminated raw milk cheeses . Int J Food Microbiol . 2014 ; 172 : 40 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Mohanan V , Nakata T, Desch AN et al. C1orf106 is a colitis risk gene that regulates stability of epithelial adherens junctions . Science . 2018 ; 359 : 1161 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Molly K , Vande Woestyne M, Verstraete W. Development of a 5-step multi-chamber reactor as a simulation of the human intestinal microbial ecosystem . Appl Microbiol Biotechnol . 1993 ; 39 : 254 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Mondal M , Nag D, Koley H et al. The Vibrio cholerae Extracellular Chitinase ChiA2 Is Important for Survival and Pathogenesis in the Host Intestine . PLoS One . 2014 ; 9 : e103119 . Google Scholar Crossref Search ADS PubMed WorldCat Moran AP , Gupta A, Joshi L. Sweet-talk: role of host glycosylation in bacterial pathogenesis of the gastrointestinal tract . Gut . 2011 ; 60 : 1412 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat Morgan XC , Tickle TL, Sokol H et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment . Genome Biol . 2012 ; 13 : R79 . Google Scholar Crossref Search ADS PubMed WorldCat Morrison DJ , Preston T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism . Gut Microbes . 2016 ; 7 : 189 – 200 . Google Scholar Crossref Search ADS PubMed WorldCat Myhrstad MCW , Tunsjø H, Charnock C et al. Dietary Fiber, Gut Microbiota, and Metabolic Regulation—Current Status in Human Randomized Trials . Nutrients . 2020 ; 12 : 859 . Google Scholar Crossref Search ADS WorldCat Mäkivuokko H , Lahtinen SJ, Wacklin P et al. Association between the ABO blood group and the human intestinal microbiota composition . BMC Microbiol . 2012 ; 12 : 94 . Google Scholar Crossref Search ADS PubMed WorldCat Ndeh D , Gilbert HJ. Biochemistry of complex glycan depolymerisation by the human gut microbiota . FEMS Microbiol Rev . 2018 ; 42 : 146 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Newburg DS , Pickering LK, McCluer RH et al. Fucosylated Oligosaccharides of Human Milk Protect Suckling Mice from Heat-Stabile Enterotoxin of Escherichia coli . J Infect Dis . 1990 ; 162 : 1075 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Newburg DS , Ruiz-Palacios GM, Morrow AL. Human Milk Glycans Protect Infants Against Enteric Pathogens . Annu Rev Nutr . 2005 ; 25 : 37 – 58 . Google Scholar Crossref Search ADS PubMed WorldCat Ng KM , Ferreyra JA, Higginbottom SK et al. Microbiota-liberated host sugars facilitate post-antibiotic expansion of enteric pathogens . Nature . 2013 ; 502 : 96 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Ninonuevo MR , Park Y, Yin H et al. A Strategy for Annotating the Human Milk Glycome . J Agric Food Chem . 2006 ; 54 : 7471 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Novaes RD , Sequetto PL, Vilela Gonçalves R et al. Depletion of enteroendocrine and mucus-secreting cells is associated with colorectal carcinogenesis severity and impaired intestinal motility in rats: CELLS AND COLORECTAL CARCINOGENESIS . Microsc Res Tech . 2016 ; 79 : 3 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Ocvirk S , Wilson AS, Appolonia CN et al. Fiber, Fat, and Colorectal Cancer: New Insight into Modifiable Dietary Risk Factors . Curr Gastroenterol Rep . 2019 ; 21 : 62 . Google Scholar Crossref Search ADS PubMed WorldCat Otnaess AB , Laegreid A, Ertresvåg K. Inhibition of enterotoxin from Escherichia coli and Vibrio cholerae by gangliosides from human milk . Infect Immun . 1983 ; 40 : 563 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Ouwerkerk JP , de Vos WM, Belzer C. Glycobiome: Bacteria and mucus at the epithelial interface . Best Practice & Research Clinical Gastroenterology . 2013 ; 27 : 25 – 38 . Google Scholar Crossref Search ADS PubMed WorldCat Owen CD , Tailford LE, Monaco S et al. Unravelling the specificity and mechanism of sialic acid recognition by the gut symbiont Ruminococcus gnavus . Nat Commun . 2017 ; 8 : 2196 . Google Scholar Crossref Search ADS PubMed WorldCat Pacheco AR , Curtis MM, Ritchie JM et al. Fucose sensing regulates bacterial intestinal colonization . Nature . 2012 ; 492 : 113 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Panek M , Čipčić Paljetak H, Barešić A et al. Methodology challenges in studying human gut microbiota - effects of collection, storage, DNA extraction and next generation sequencing technologies . Sci Rep . 2018 ; 8 : 5143 . Google Scholar Crossref Search ADS PubMed WorldCat Paton AW , Jennings MP, Morona R et al. Recombinant Probiotics for Treatment and Prevention of Enterotoxigenic Escherichia coli Diarrhea . Gastroenterology . 2005 ; 128 : 1219 – 28 . Google Scholar Crossref Search ADS PubMed WorldCat Paton AW , Morona R, Paton JC. A new biological agent for treatment of Shiga toxigenic Escherichia coli infections and dysentery in humans . Nat Med . 2000 ; 6 : 265 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Pavia AT , Shipman LD, Wells JG et al. Epidemiologic Evidence that Prior Antimicrobial Exposure Decreases Resistance to Infection by Antimicrobial-Sensitive Salmonella . J Infect Dis . 1990 ; 161 : 255 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Payne AN , Zihler A, Chassard C et al. Advances and perspectives in in vitro human gut fermentation modeling . Trends Biotechnol . 2012 ; 30 : 17 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat Pendu JL , Lemieux RU, Dalix AM et al. Competition between ABO and Le Gene Specified Enzymes . Vox Sang . 1983 ; 45 : 349 – 58 . Google Scholar Crossref Search ADS PubMed WorldCat Pereira FC , Berry D. Microbial nutrient niches in the gut: Microbial nutrient niches in the gut . Environ Microbiol . 2017 ; 19 : 1366 – 78 . Google Scholar Crossref Search ADS PubMed WorldCat Peterson LW , Artis D. Intestinal epithelial cells: regulators of barrier function and immune homeostasis . Nat Rev Immunol . 2014 ; 14 : 141 – 53 . Google Scholar Crossref Search ADS PubMed WorldCat Pham TAN , Clare S, Goulding D et al. Epithelial IL-22RA1-Mediated Fucosylation Promotes Intestinal Colonization Resistance to an Opportunistic Pathogen . Cell Host & Microbe . 2014 ; 16 : 504 – 16 . Google Scholar Crossref Search ADS PubMed WorldCat Pham VT , Mohajeri MH. The application of in vitro human intestinal models on the screening and development of pre- and probiotics . Beneficial Microbes . 2018 ; 9 : 725 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Plovier H , Everard A, Druart C et al. A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice . Nat Med . 2017 ; 23 : 107 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Png CW , Lindén SK, Gilshenan KS et al. Mucolytic Bacteria With Increased Prevalence in IBD Mucosa Augment In Vitro Utilization of Mucin by Other Bacteria . Am J Gastroenterol . 2010 ; 105 : 2420 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Poeker SA , Geirnaert A, Berchtold L et al. Understanding the prebiotic potential of different dietary fibers using an in vitro continuous adult fermentation model (PolyFermS) . Sci Rep . 2018 ; 8 : 4318 . Google Scholar Crossref Search ADS PubMed WorldCat Porter NT , Martens EC. The Critical Roles of Polysaccharides in Gut Microbial Ecology and Physiology . Annu Rev Microbiol . 2017 ; 71 : 349 – 69 . Google Scholar Crossref Search ADS PubMed WorldCat Praharaj AB , Dehury B, Mahapatra N et al. Molecular dynamics insights into the structure, function, and substrate binding mechanism of mucin desulfating sulfatase of gut microbe Bacteroides fragilis . J Cell Biochem . 2018 ; 119 : 3618 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Prescott NJ , Fisher SA, Franke A et al. A Nonsynonymous SNP in ATG16L1 Predisposes to Ileal Crohn's Disease and Is Independent of CARD15 and IBD5 . Gastroenterology . 2007 ; 132 : 1665 – 71 . Google Scholar Crossref Search ADS PubMed WorldCat Pretzer G , Snel J, Molenaar D et al. Biodiversity-Based Identification and Functional Characterization of the Mannose-Specific Adhesin of Lactobacillus plantarum . JB . 2005 ; 187 : 6128 – 36 . Google Scholar Crossref Search ADS WorldCat Pudlo NA , Urs K, Kumar SS et al. Symbiotic Human Gut Bacteria with Variable Metabolic Priorities for Host Mucosal Glycans . mBio . 2015 ; 6 : e01282 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Pépin J , Saheb N, Coulombe M-A et al. Emergence of Fluoroquinolones as the Predominant Risk Factor for Clostridium difficile- Associated Diarrhea: A Cohort Study during an Epidemic in Quebec . Clin Infect Dis . 2005 ; 41 : 1254 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Qadri F , Saha A, Ahmed T et al. Disease Burden Due to Enterotoxigenic Escherichia coli in the First 2 Years of Life in an Urban Community in Bangladesh . IAI . 2007 ; 75 : 3961 – 8 . Google Scholar Crossref Search ADS WorldCat Qi L , Xu Z, Jiang X et al. Preparation and antibacterial activity of chitosan nanoparticles . Carbohydr Res . 2004 ; 339 : 2693 – 700 . Google Scholar Crossref Search ADS PubMed WorldCat Qin J , Li R, Raes J et al. A human gut microbial gene catalogue established by metagenomic sequencing . Nature . 2010 ; 464 : 59 – 65 . Google Scholar Crossref Search ADS PubMed WorldCat Quigley EMM. Microflora Modulation of Motility . J Neurogastroenterol Motil . 2011 ; 17 : 140 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Quintero-Villegas MI , Aam BB, Rupnow J et al. Adherence Inhibition of Enteropathogenic Escherichia coli by Chitooligosaccharides with Specific Degrees of Acetylation and Polymerization . J Agric Food Chem . 2013 ; 61 : 2748 – 54 . Google Scholar Crossref Search ADS PubMed WorldCat Raafat D , Sahl H-G. Chitosan and its antimicrobial potential - a critical literature survey . Microb Biotechnol . 2009 ; 2 : 186 – 201 . Google Scholar Crossref Search ADS PubMed WorldCat Rakotoarivonina H , Gaillard-Martinie B, Forano E et al. Adhesion to cellulose of the Gram-positive bacterium Ruminococcus albus involves type IV pili . Microbiology . 2002 ; 148 : 1871 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Rang CU , Licht TR, Midtvedt T et al. Estimation of Growth Rates of Escherichia coli BJ4 in Streptomycin-Treated and Previously Germfree Mice by In Situ rRNA Hybridization . Clin Diagn Lab Immunol . 1999 ; 6 : 434 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Rasmussen TS , Koefoed AK, Jakobsen RR et al. Bacteriophage-mediated manipulation of the gut microbiome - promises and presents limitations . FEMS Microbiol Rev . 2020 ; 44 : 507 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Rausch P , Rehman A, Kunzel S et al. Colonic mucosa-associated microbiota is influenced by an interaction of Crohn disease and FUT2 (Secretor) genotype . Proc Natl Acad Sci . 2011 ; 108 : 19030 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Reddy B , Engle A, Katsifis S et al. Biochemical Epidemiology of Colon Cancer: Effect of Types of Dietary Fiber on Fecal Mutagens, Acid, and Neutral Sterols in Healthy Subjects . Cancer Res . 1989 ; 49 : 4629 – 35 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Reimer R , Maathuis A, Venema K et al. Effect of the Novel Polysaccharide PolyGlycopleX® on Short-Chain Fatty Acid Production in a Computer-Controlled in Vitro Model of the Human Large Intestine . Nutrients . 2014 ; 6 : 1115 – 27 . Google Scholar Crossref Search ADS PubMed WorldCat Renkonen O. Enzymatic in vitro synthesis of I-branches of mammalian polylactosamines: generation of scaffolds for multiple selectin-binding saccharide determinants : CMLS, Cell Mol Life Sci . 2000 ; 57 : 1423 – 39 . Google Scholar Crossref Search ADS WorldCat Reunanen J , von Ossowski I, Hendrickx APA et al. Characterization of the SpaCBA Pilus Fibers in the Probiotic Lactobacillus rhamnosus GG . Appl Environ Microbiol . 2012 ; 78 : 2337 – 44 . Google Scholar Crossref Search ADS PubMed WorldCat Reynolds A , Mann J, Cummings J et al. Carbohydrate quality and human health: a series of systematic reviews and meta-analyses . Lancet North Am Ed . 2019 ; 393 : 434 – 45 . Google Scholar Crossref Search ADS WorldCat Rhoades J , Manderson K, Wells A et al. Oligosaccharide-Mediated Inhibition of the Adhesion of Pathogenic Escherichia coli Strains to Human Gut Epithelial Cells In Vitro . J Food Prot . 2008 ; 71 : 2272 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Rho J , Wright DP, Christie DL et al. A Novel Mechanism for Desulfation of Mucin: Identification and Cloning of a Mucin-Desulfating Glycosidase (Sulfoglycosidase) from Prevotella Strain RS2 . JB . 2005 ; 187 : 1543 – 51 . Google Scholar Crossref Search ADS WorldCat Richard ML , Liguori G, Lamas B et al. Mucosa-associated microbiota dysbiosis in colitis associated cancer . Gut Microbes . 2018 ; 9 : 131 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Rintala A , Pietilä S, Munukka E et al. Gut Microbiota Analysis Results Are Highly Dependent on the 16S rRNA Gene Target Region, Whereas the Impact of DNA Extraction Is Minor . J Biomol Tech . 2017 ; 28 : 19 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Riva A , Kuzyk O, Forsberg E et al. A fiber-deprived diet disturbs the fine-scale spatial architecture of the murine colon microbiome . Nat Commun . 2019 ; 10 : 4366 . Google Scholar Crossref Search ADS PubMed WorldCat Roberts CL , Keita AV, Duncan SH et al. Translocation of Crohn's disease Escherichia coli across M-cells: contrasting effects of soluble plant fibres and emulsifiers . Gut . 2010 ; 59 : 1331 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Roberts CL , Keita AV, Parsons BN et al. Soluble plantain fibre blocks adhesion and M-cell translocation of intestinal pathogens . J Nutr Biochem . 2013 ; 24 : 97 – 103 . Google Scholar Crossref Search ADS PubMed WorldCat Rogers TE , Pudlo NA, Koropatkin NM et al. Dynamic responses of Bacteroides thetaiotaomicron during growth on glycan mixtures: Bacteroides responses to glycan mixtures . Mol Microbiol . 2013 ; 88 : 876 – 90 . Google Scholar Crossref Search ADS PubMed WorldCat Rogowski A , Briggs JA, Mortimer JC et al. Glycan complexity dictates microbial resource allocation in the large intestine . Nat Commun . 2015 ; 6 : 7481 . Google Scholar Crossref Search ADS PubMed WorldCat Romaní-Pérez M , Agusti A, Sanz Y. Innovation in microbiome-based strategies for promoting metabolic health . Curr Opin Clin Nutr Metab Care . 2017 ; 20 : 484 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat Rossez Y , Gosset P, Boneca IG et al. The LacdiNAc-Specific Adhesin LabA Mediates Adhesion of Helicobacter pylori to Human Gastric Mucosa . J Infect Dis . 2014 ; 210 : 1286 – 95 . Google Scholar Crossref Search ADS PubMed WorldCat Roubos-van den Hil PJ , Nout MJR, Beumer RR et al. Fermented soya bean (tempe) extracts reduce adhesion of enterotoxigenic Escherichia coli to intestinal epithelial cells . J Appl Microbiol . 2009 ; 106 : 1013 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Roubos-van den Hil PJ , Schols HA, Nout MJR et al. First Characterization of Bioactive Components in Soybean Tempe That Protect Human and Animal Intestinal Cells against Enterotoxigenic Escherichia coli (ETEC) Infection . J Agric Food Chem . 2010 ; 58 : 7649 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Roussel C , Galia W, Leriche F et al. Comparison of conventional plating, PMA-qPCR, and flow cytometry for the determination of viable enterotoxigenic Escherichia coli along a gastrointestinal in vitro model . Appl Microbiol Biotechnol . 2018a ; 102 : 9793 – 802 . Google Scholar Crossref Search ADS WorldCat Roussel C , Sivignon A, de Vallée A et al. Anti-infectious properties of the probiotic Saccharomyces cerevisiae CNCM I-3856 on enterotoxigenic E. coli (ETEC) strain H10407 . Appl Microbiol Biotechnol . 2018b ; 102 : 6175 – 89 . Google Scholar Crossref Search ADS WorldCat Roychowdhury S , Cadnum J, Glueck B et al. Faecalibacterium prausnitzii and a Prebiotic Protect Intestinal Health in a Mouse Model of Antibiotic and Clostridium difficile Exposure . Journal of Parenteral and Enteral Nutrition . 2018 ; 42 : 1156 – 67 . Google Scholar Crossref Search ADS PubMed WorldCat Rubinstein MR , Wang X, Liu W et al. Fusobacterium nucleatum Promotes Colorectal Carcinogenesis by Modulating E-Cadherin/β-Catenin Signaling via its FadA Adhesin . Cell Host & Microbe . 2013 ; 14 : 195 – 206 . Google Scholar Crossref Search ADS PubMed WorldCat Ruiz-Palacios GM , Cervantes LE, Ramos P et al. Campylobacter jejuni Binds Intestinal H(O) Antigen (Fucα1, 2Galβ1, 4GlcNAc), and Fucosyloligosaccharides of Human Milk Inhibit Its Binding and Infection . J Biol Chem . 2003 ; 278 : 14112 – 20 . Google Scholar Crossref Search ADS PubMed WorldCat Ríos-Covián D , Ruas-Madiedo P, Margolles A et al. Intestinal Short Chain Fatty Acids and their Link with Diet and Human Health . Front Microbiol . 2016 ; 7 : 185 . Google Scholar Crossref Search ADS PubMed WorldCat Sagar NM , Cree IA, Covington JA et al. The Interplay of the Gut Microbiome, Bile Acids, and Volatile Organic Compounds . Gastroenterology Research and Practice . 2015 ; 2015 : 1 – 6 . Google Scholar Crossref Search ADS WorldCat Salcedo J , Barbera R, Matencio E et al. Gangliosides and sialic acid effects upon newborn pathogenic bacteria adhesion: An in vitro study . Food Chem . 2013 ; 136 : 726 – 34 . Google Scholar Crossref Search ADS PubMed WorldCat Salonen A , Lahti L, Salojärvi J et al. Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men . ISME J . 2014 ; 8 : 2218 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Salyers AA , Vercellotti JR, West SE et al. Fermentation of mucin and plant polysaccharides by strains of Bacteroides from the human colon . Appl Environ Microbiol . 1977 ; 33 : 319 – 22 . Google Scholar Crossref Search ADS PubMed WorldCat Sanchez JI , Marzorati M, Grootaert C et al. Arabinoxylan-oligosaccharides (AXOS) affect the protein/carbohydrate fermentation balance and microbial population dynamics of the Simulator of Human Intestinal Microbial Ecosystem . Microb Biotechnol . 2009 ; 2 : 101 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Sarabia-Sainz HM , Armenta-Ruiz C, Sarabia-Sainz JA et al. Adhesion of enterotoxigenic Escherichia coli strains to neoglycans synthesised with prebiotic galactooligosaccharides . Food Chem . 2013 ; 141 : 2727 – 34 . Google Scholar Crossref Search ADS PubMed WorldCat Sausset R , Petit MA, Gaboriau-Routhiau V et al. New insights into intestinal phages . Mucosal Immunol . 2020 ; 13 : 205 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Schanler RJ. Randomized Trial of Donor Human Milk Versus Preterm Formula as Substitutes for Mothers’ Own Milk in the Feeding of Extremely Premature Infants . Pediatrics . 2005 ; 116 : 400 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Schembri MA , Kjaergaard K, Sokurenko EV et al. Molecular Characterization of the Escherichia coli FimH Adhesin . J Infect Dis . 2001 ; 183 : S28 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Scheppach W , German-Austrian Scfa Study Group . Treatment of distal ulcerative colitis with short-chain fatty acid enemas a placebo-controlled trial . Digest Dis Sci . 1996 ; 41 : 2254 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Schirmer M , Garner A, Vlamakis H et al. Microbial genes and pathways in inflammatory bowel disease . Nat Rev Microbiol . 2019 ; 17 : 497 – 511 . Google Scholar Crossref Search ADS PubMed WorldCat Schnorr SL , Candela M, Rampelli S et al. Gut microbiome of the Hadza hunter-gatherers . Nat Commun . 2014 ; 5 : 3654 . Google Scholar Crossref Search ADS PubMed WorldCat Schoster A , Kokotovic B, Permin A et al. In vitro inhibition of Clostridium difficile and Clostridium perfringens by commercial probiotic strains . Anaerobe . 2013 ; 20 : 36 – 41 . Google Scholar Crossref Search ADS PubMed WorldCat Schroeder BO , Birchenough GMH, Ståhlman M et al. Bifidobacteria or Fiber Protects against Diet-Induced Microbiota-Mediated Colonic Mucus Deterioration . Cell Host & Microbe . 2018 ; 23 : 27 – 40.e7 . Google Scholar Crossref Search ADS PubMed WorldCat Schultsz C , van den Berg FM, ten Kate FW et al. The intestinal mucus layer from patients with inflammatory bowel disease harbors high numbers of bacteria compared with controls . Gastroenterology . 1999 ; 117 : 1089 – 97 . Google Scholar Crossref Search ADS PubMed WorldCat Schwab C , Berry D, Rauch I et al. Longitudinal study of murine microbiota activity and interactions with the host during acute inflammation and recovery . ISME J . 2014 ; 8 : 1101 – 14 . Google Scholar Crossref Search ADS PubMed WorldCat Scott KP , Duncan SH, Flint HJ. Dietary fibre and the gut microbiota . Nutrition Bulletin . 2008 ; 33 : 201 – 11 . Google Scholar Crossref Search ADS WorldCat Sekirov I , Finlay BB. The role of the intestinal microbiota in enteric infection: Intestinal microbiota and enteric infections . J Physiol . 2009 ; 587 : 4159 – 67 . Google Scholar Crossref Search ADS PubMed WorldCat Seksik P. Alterations of the dominant faecal bacterial groups in patients with Crohn's disease of the colon . Gut . 2003 ; 52 : 237 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Sender R , Fuchs S, Milo R. Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host Cells in Humans . Cell . 2016 ; 164 : 337 – 40 . Google Scholar Crossref Search ADS PubMed WorldCat Seregin SS , Golovchenko N, Schaf B et al. NLRP6 Protects Il10 −/− Mice from Colitis by Limiting Colonization of Akkermansia muciniphila . Cell Rep . 2017 ; 19 : 733 – 45 . Google Scholar Crossref Search ADS PubMed WorldCat Sheridan P , Martin JC, Lawley TD et al. Polysaccharide utilization loci and nutritional specialization in a dominant group of butyrate-producing human colonic Firmicutes . Microb Genom . 2016 ; 2 : e000043 Google Scholar PubMed OpenURL Placeholder Text WorldCat Shin N-R , Lee J-C, Lee H-Y et al. An increase in the Akkermansia spp. population induced by metformin treatment improves glucose homeostasis in diet-induced obese mice . Gut . 2014 ; 63 : 727 – 35 . Google Scholar Crossref Search ADS PubMed WorldCat Shin W , Kim HJ. Intestinal barrier dysfunction orchestrates the onset of inflammatory host–microbiome cross-talk in a human gut inflammation-on-a-chip . Proc Natl Acad Sci USA . 2018 ; 115 : E10539 – 47 . Google Scholar Crossref Search ADS PubMed WorldCat Shin W , Wu A, Massidda MW et al. A Robust Longitudinal Co-culture of Obligate Anaerobic Gut Microbiome With Human Intestinal Epithelium in an Anoxic-Oxic Interface-on-a-Chip . Front Bioeng Biotechnol . 2019 ; 7 : 13 . Google Scholar Crossref Search ADS PubMed WorldCat Shoaf K , Mulvey GL, Armstrong GD et al. Prebiotic Galactooligosaccharides Reduce Adherence of Enteropathogenic Escherichia coli to Tissue Culture Cells . IAI . 2006 ; 74 : 6920 – 8 . Google Scholar Crossref Search ADS WorldCat Sicard J-F , Le Bihan G, Vogeleer P et al. Interactions of Intestinal Bacteria with Components of the Intestinal Mucus . Front Cell Infect Microbiol . 2017 ; 7 : 387 . Google Scholar Crossref Search ADS PubMed WorldCat Sikorska H , Smoragiewicz W. Role of probiotics in the prevention and treatment of meticillin-resistant Staphylococcus aureus infections . Int J Antimicrob Agents . 2013 ; 42 : 475 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Singh V , Yeoh BS, Chassaing B et al. Dysregulated Microbial Fermentation of Soluble Fiber Induces Cholestatic Liver Cancer . Cell . 2018 ; 175 : 679 – 694.e22 . Google Scholar Crossref Search ADS PubMed WorldCat Singh V , Yeoh BS, Walker RE et al. Microbiota fermentation-NLRP3 axis shapes the impact of dietary fibres on intestinal inflammation . Gut . 2019 ; 68 : 1801 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Sivignon A , de Vallée A, Barnich N et al. Saccharomyces cerevisiae CNCM I-3856 prevents colitis induced by AIEC bacteria in the transgenic mouse model mimicking Crohn's disease . Inflamm Bowel Dis . 2015 ; 21 : 276 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Smits SA , Leach J, Sonnenburg ED et al. Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania . Science . 2017 ; 357 : 802 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Snart J , Bibiloni R, Grayson T et al. Supplementation of the Diet with High-Viscosity Beta-Glucan Results in Enrichment for Lactobacilli in the Rat Cecum . AEM . 2006 ; 72 : 1925 – 31 . Google Scholar Crossref Search ADS WorldCat Sokurenko EV , Chesnokova V, Dykhuizen DE et al. Pathogenic adaptation of Escherichia coli by natural variation of the FimH adhesin . Proc Natl Acad Sci . 1998 ; 95 : 8922 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Sommer F , Adam N, Johansson MEV et al. Altered Mucus Glycosylation in Core 1 O-Glycan-Deficient Mice Affects Microbiota Composition and Intestinal Architecture . PLoS One . 2014 ; 9 : e85254 . Google Scholar Crossref Search ADS PubMed WorldCat Song M , Wu K, Meyerhardt JA et al. Fiber Intake and Survival After Colorectal Cancer Diagnosis . JAMA Oncol . 2018 ; 4 : 71 . Google Scholar Crossref Search ADS PubMed WorldCat Sonnenburg ED , Sonnenburg JL. Starving our Microbial Self: The Deleterious Consequences of a Diet Deficient in Microbiota-Accessible Carbohydrates . Cell Metab . 2014 ; 20 : 779 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Sonnenburg ED , Zheng H, Joglekar P et al. Specificity of Polysaccharide Use in Intestinal Bacteroides Species Determines Diet-Induced Microbiota Alterations . Cell . 2010 ; 141 : 1241 – 52 . Google Scholar Crossref Search ADS PubMed WorldCat Sonnenburg JL. Glycan Foraging in Vivo by an Intestine-Adapted Bacterial Symbiont . Science . 2005 ; 307 : 1955 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Sorbara MT , Pamer EG. Interbacterial mechanisms of colonization resistance and the strategies pathogens use to overcome them . Mucosal Immunol . 2019 ; 12 : 1 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Sossai P . Butyric acid: what is the future for this old substance? Swiss Med Wkly . 2012 ; 142 : w13596 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Sperandio B , Fischer N, Chevalier-Curt MJ et al. Virulent Shigella flexneri Affects Secretion, Expression, and Glycosylation of Gel-Forming Mucins in Mucus-Producing Cells . Infect Immun . 2013 ; 81 : 3632 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Spiga L , Winter MG, Furtado de Carvalho T et al. An Oxidative Central Metabolism Enables Salmonella to Utilize Microbiota-Derived Succinate . Cell Host Microbe . 2017 ; 22 : 291 – 301 ..e6. Google Scholar Crossref Search ADS PubMed WorldCat Stins MF , Prasadarao NV, Ibric L et al. Binding Characteristics of S Fimbriated Escherichia coli to Isolated Brain Microvascular Endothelial Cells . Am J Pathol . 1994 ; 145 : 1228 – 36 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Stone EL , Ismail MN, Lee SH et al. Glycosyltransferase Function in Core 2-Type Protein O Glycosylation . MCB . 2009 ; 29 : 3770 – 82 . Google Scholar Crossref Search ADS PubMed WorldCat Story JA , Kritchevsky D. Bile acid metabolism and fiber . Am J Clin Nutr . 1978 ; 31 : S199 – 202 . Google Scholar Crossref Search ADS PubMed WorldCat Strugala V , Dettmar PW, Pearson JP. Thickness and continuity of the adherent colonic mucus barrier in active and quiescent ulcerative colitis and Crohn's disease: Colonic mucus thickness in IBD . Int J Clin Pract . 2008 ; 62 : 762 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Stuyven E , Cox E, Vancaeneghem S et al. Effect of β-glucans on an ETEC infection in piglets . Vet Immunol Immunopathol . 2009 ; 128 : 60 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Swidsinski A , Ladhoff A, Pernthaler A et al. Mucosal flora in inflammatory bowel disease . Gastroenterology . 2002 ; 122 : 44 – 54 . Google Scholar Crossref Search ADS PubMed WorldCat Swidsinski A , Loening-Baucke V, Theissig F et al. Comparative study of the intestinal mucus barrier in normal and inflamed colon . Gut . 2007 ; 56 : 343 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Swidsinski A , Weber J, Loening-Baucke V et al. Spatial Organization and Composition of the Mucosal Flora in Patients with Inflammatory Bowel Disease . J Clin Microbiol . 2005 ; 43 : 3380 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Szabady RL , Yanta JH, Halladin DK et al. TagA is a secreted protease of Vibrio cholerae that specifically cleaves mucin glycoproteins . Microbiology . 2011 ; 157 : 516 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat Taghipoor M , Barles G, Georgelin C et al. Digestion modeling in the small intestine: Impact of dietary fiber . Math Biosci . 2014 ; 258 : 101 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Tailford LE , Crost EH, Kavanaugh D et al. Mucin glycan foraging in the human gut microbiome . Front Genet . 2015 ; 6 : 81 . Google Scholar Crossref Search ADS PubMed WorldCat Takao M , Yen H, Tobe T. LeuO enhances butyrate-induced virulence expression through a positive regulatory loop in enterohaemorrhagic E scherichia coli: Positive role of LeuO in EHEC virulence expression . Mol Microbiol . 2014 ; 93 : 1302 – 13 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Tapader R , Basu S, Pal A. Secreted proteases: A new insight in the pathogenesis of extraintestinal pathogenic Escherichia coli . Int J Med Microbiol . 2019 ; 309 : 159 – 68 . Google Scholar Crossref Search ADS PubMed WorldCat Taylor SL , McGuckin MA, Wesselingh S et al. Infection's Sweet Tooth: How Glycans Mediate Infection and Disease Susceptibility . Trends Microbiol . 2018 ; 26 : 92 – 101 . Google Scholar Crossref Search ADS PubMed WorldCat Tester RF , Karkalas J, Qi X. Starch—composition, fine structure and architecture . J Cereal Sci . 2004 ; 39 : 151 – 65 . Google Scholar Crossref Search ADS WorldCat Thibault R , Blachier F, Darcy-Vrillon B et al. Butyrate utilization by the colonic mucosa in inflammatory bowel diseases: A transport deficiency . Inflamm Bowel Dis . 2010 ; 16 : 684 – 95 . Google Scholar Crossref Search ADS PubMed WorldCat Tomas J , Mulet C, Saffarian A et al. High-fat diet modifies the PPAR-γ pathway leading to disruption of microbial and physiological ecosystem in murine small intestine . Proc Natl Acad Sci . 2016 ; 113 : 5934 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Tovaglieri A , Sontheimer-Phelps A, Geirnaert A et al. Species-specific enhancement of enterohemorrhagic E. coli pathogenesis mediated by microbiome metabolites . Microbiome . 2019 ; 7 : 43 . Google Scholar Crossref Search ADS PubMed WorldCat Tu QV , McGuckin MA, Mendz GL. Campylobacter jejuni response to human mucin MUC2: modulation of colonization and pathogenicity determinants . J Med Microbiol . 2008 ; 57 : 795 – 802 . Google Scholar Crossref Search ADS PubMed WorldCat Turnbaugh PJ , Bäckhed F, Fulton L et al. Diet-Induced Obesity Is Linked to Marked but Reversible Alterations in the Mouse Distal Gut Microbiome . Cell Host & Microbe . 2008 ; 3 : 213 – 23 . Google Scholar Crossref Search ADS PubMed WorldCat Turnbaugh PJ , Ley RE, Mahowald MA et al. An obesity-associated gut microbiome with increased capacity for energy harvest . Nature . 2006 ; 444 : 1027 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Turnbaugh PJ , Ridaura VK, Faith JJ et al. The Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice . Sci Transl Med . 2009 ; 1 : 6ra14 . Google Scholar Crossref Search ADS PubMed WorldCat Turner JR. Intestinal mucosal barrier function in health and disease . Nat Rev Immunol . 2009 ; 9 : 799 – 809 . Google Scholar Crossref Search ADS PubMed WorldCat Turroni F , Milani C, Duranti S et al. Glycan Utilization and Cross-Feeding Activities by Bifidobacteria . Trends Microbiol . 2018 ; 26 : 339 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Van den Abbeele P , Gérard P, Rabot S et al. Arabinoxylans and inulin differentially modulate the mucosal and luminal gut microbiota and mucin-degradation in humanized rats: Prebiotics modulate mucosal and luminal microbiota summary . Environ Microbiol . 2011 ; 13 : 2667 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Van den Abbeele P , Marzorati M, Derde M et al. Arabinoxylans, inulin and Lactobacillus reuteri 1063 repress the adherent-invasive Escherichia coli from mucus in a mucosa-comprising gut model . npj Biofilms Microbiomes . 2016 ; 2 : 16016 . Google Scholar Crossref Search ADS PubMed WorldCat Van de Wiele T , Van den Abbeele P, Ossieur W et al. The Simulator of the Human Intestinal Microbial Ecosystem (SHIME®) . In: Verhoeckx K, Cotter P, López-Expósito I et al. (eds). The Impact of Food Bioactives on Health . Cham : Springer International Publishing , 2015 , 305 – 17 . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Van Herreweghen F , De Paepe K, Roume H et al. Mucin degradation niche as a driver of microbiome composition and Akkermansia muciniphila abundance in a dynamic gut model is donor independent . FEMS Microbiol Ecol . 2018 ; 94 . Google Scholar OpenURL Placeholder Text WorldCat Van Nuenen M , Diederick Meyer P, Venema K. The Effect of Various Inulins and Clostridium difficile on the Metabolic Activity of the Human Colonic Microbiota in vitro . Microbial Ecology in Health and Disease . 2003 ; 15 : 137 – 44 . Google Scholar Crossref Search ADS WorldCat Vardaka VD , Yehia HM, Savvaidis IN. Effects of Citrox and chitosan on the survival of Escherichia coli O157:H7 and Salmonella enterica in vacuum-packaged turkey meat . Food Microbiol . 2016 ; 58 : 128 – 34 . Google Scholar Crossref Search ADS PubMed WorldCat Vernia P , Annese V, Bresci G et al. Topical butyrate improves efficacy of 5-ASA in refractory distal ulcerative colitis: results of a multicentre trial . Eur J Clin Invest . 2003 ; 33 : 244 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Vernia P , Marcheggiano A, Caprilli R et al. Short-chain fatty acid topical treatment in distal ulcerative colitis . Aliment Pharmacol Therap . 2007 ; 9 : 309 – 13 . Google Scholar Crossref Search ADS WorldCat Vimal DB , Khullar M, Gupta S et al. Intestinal mucins: the binding sites for Salmonella Typhimurium . Mol Cell Biochem . 2000 ; 204 : 107 – 17 . Google Scholar Crossref Search ADS PubMed WorldCat Vinolo MAR , Rodrigues HG, Nachbar RT et al. Regulation of Inflammation by Short Chain Fatty Acids . Nutrients . 2011 ; 3 : 858 – 76 . Google Scholar Crossref Search ADS PubMed WorldCat Vital M , Howe A, Bergeron N et al. Metagenomic Insights into the Degradation of Resistant Starch by Human Gut Microbiota . Appl Environ Microbiol . 2018 ; 84 : e01562 – 18 . Google Scholar Crossref Search ADS PubMed WorldCat Vodovnik M , Duncan SH, Reid MD et al. Expression of Cellulosome Components and Type IV Pili within the Extracellular Proteome of Ruminococcus flavefaciens 007 . PLoS One . 2013 ; 8 : e65333 . Google Scholar Crossref Search ADS PubMed WorldCat Vogt SL , Peña-Díaz J, Finlay BB. Chemical communication in the gut: Effects of microbiota-generated metabolites on gastrointestinal bacterial pathogens . Anaerobe . 2015 ; 34 : 106 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Vrieze A , Van Nood E, Holleman F et al. Transfer of Intestinal Microbiota From Lean Donors Increases Insulin Sensitivity in Individuals With Metabolic Syndrome . Gastroenterology . 2012 ; 143 : 913 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Vuik F , Dicksved J, Lam S et al. Composition of the mucosa-associated microbiota along the entire gastrointestinal tract of human individuals . United European Gastroenterol J . 2019 ; 7 : 897 – 907 . Google Scholar Crossref Search ADS PubMed WorldCat Wacklin P , Mäkivuokko H, Alakulppi N et al. Secretor Genotype (FUT2 gene) Is Strongly Associated with the Composition of Bifidobacteria in the Human Intestine . PLoS One . 2011 ; 6 : e20113 . Google Scholar Crossref Search ADS PubMed WorldCat Walker AW , Sanderson JD, Churcher C et al. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease . BMC Microbiol . 2011 ; 11 : 7 . Google Scholar Crossref Search ADS PubMed WorldCat Wang T , Cai G, Qiu Y et al. Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers . ISME J . 2012 ; 6 : 320 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Wang Y , Gänzle MG, Schwab C. Exopolysaccharide Synthesized by Lactobacillus reuteri Decreases the Ability of Enterotoxigenic Escherichia coli To Bind to Porcine Erythrocytes . AEM . 2010 ; 76 : 4863 – 6 . Google Scholar Crossref Search ADS WorldCat White BA , Lamed R, Bayer EA et al. Biomass Utilization by Gut Microbiomes . Annu Rev Microbiol . 2014 ; 68 : 279 – 96 . Google Scholar Crossref Search ADS PubMed WorldCat Wikoff WR , Anfora AT, Liu J et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites . Proc Natl Acad Sci . 2009 ; 106 : 3698 – 703 . Google Scholar Crossref Search ADS PubMed WorldCat Willats WGT , Knox JP, Mikkelsen JD. Pectin: new insights into an old polymer are starting to gel . Trends in Food Science & Technology . 2006 ; 17 : 97 – 104 . Google Scholar Crossref Search ADS WorldCat Willing BP , Vacharaksa A, Croxen M et al. Altering Host Resistance to Infections through Microbial Transplantation . PLoS One . 2011 ; 6 : e26988 . Google Scholar Crossref Search ADS PubMed WorldCat Wolf BW , Meulbroek JA, Jarvis KP et al. Dietary Supplementation with Fructooligosaccharides Increase Survival Time in a Hamster Model of Clostridium difficile-Colitis . Bioscience Microflora . 1997 ; 16 : 59 – 64 . Google Scholar Crossref Search ADS WorldCat Wong C , Harris PJ, Ferguson LR. Potential Benefits of Dietary Fibre Intervention in Inflammatory Bowel Disease . Int J Mol Sci . 2016 ; 17 : 919 . Google Scholar Crossref Search ADS WorldCat Wrzosek L , Miquel S, Noordine M-L et al. Bacteroides thetaiotaomicron and Faecalibacterium prausnitzii influence the production of mucus glycans and the development of goblet cells in the colonic epithelium of a gnotobiotic model rodent . BMC Biol . 2013 ; 11 : 61 . Google Scholar Crossref Search ADS PubMed WorldCat Wu GD , Chen J, Hoffmann C et al. Linking Long-Term Dietary Patterns with Gut Microbial Enterotypes . Science . 2011 ; 334 : 105 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Wu X , Wu Y, He L et al. Effects of the intestinal microbial metabolite butyrate on the development of colorectal cancer . J Cancer . 2018 ; 9 : 2510 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Xiao D , Wang Y, Liu G et al. Effects of Chitosan on Intestinal Inflammation in Weaned Pigs Challenged by Enterotoxigenic Escherichia coli . PLoS One . 2014 ; 9 : e104192 . Google Scholar Crossref Search ADS PubMed WorldCat Yatsunenko T , Rey FE, Manary MJ et al. Human gut microbiome viewed across age and geography . Nature . 2012 ; 486 : 222 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Younes I , Rinaudo M. Chitin and Chitosan Preparation from Marine Sources. Structure, Properties and Applications . Marine Drugs . 2015 ; 13 : 1133 – 74 . Google Scholar Crossref Search ADS PubMed WorldCat Yu L-C , Twu Y-C, Chang C-Y et al. Molecular basis of the adult i phenotype and the gene responsible for the expression of the human blood group I antigen . Blood . 2001 ; 98 : 3840 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Zackular JP , Baxter NT, Iverson KD et al. The Gut Microbiome Modulates Colon Tumorigenesis . mBio . 2013 ; 4 : e00692 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Zarepour M , Bhullar K, Montero M et al. The Mucin Muc2 Limits Pathogen Burdens and Epithelial Barrier Dysfunction during Salmonella enterica Serovar Typhimurium Colitis . Infect Immun . 2013 ; 81 : 3672 – 83 . Google Scholar Crossref Search ADS PubMed WorldCat Zeevi D , Korem T, Zmora N et al. Personalized Nutrition by Prediction of Glycemic Responses . Cell . 2015 ; 163 : 1079 – 94 . Google Scholar Crossref Search ADS PubMed WorldCat Ze X , Duncan SH, Louis P et al. Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon . ISME J . 2012 ; 6 : 1535 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Zhu L , Qin S, Zhai S et al. Inulin with different degrees of polymerization modulates composition of intestinal microbiota in mice . FEMS Microbiol Lett . 2017 ; 364 . Google Scholar OpenURL Placeholder Text WorldCat Zhu Y , González-Ortiz G, Jiménez-Díaz R et al. Exopolysaccharides from olive brines could reduce the adhesion of ETEC K88 to intestinal epithelial cells . Food Funct . 2018 ; 9 : 3884 – 94 . Google Scholar Crossref Search ADS PubMed WorldCat Zihler A , Gagnon M, Chassard C et al. Unexpected consequences of administering bacteriocinogenic probiotic strains for Salmonella populations, revealed by an in vitro colonic model of the child gut . Microbiology . 2010 ; 156 : 3342 – 53 . Google Scholar Crossref Search ADS PubMed WorldCat Zmora N , Suez J, Elinav E. You are what you eat: diet, health and the gut microbiota . Nat Rev Gastroenterol Hepatol . 2019 ; 16 : 35 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Zou J , Chassaing B, Singh V et al. Fiber-Mediated Nourishment of Gut Microbiota Protects against Diet-Induced Obesity by Restoring IL-22-Mediated Colonic Health . Cell Host & Microbe . 2018 ; 23 : 41 – 53.e4 . Google Scholar Crossref Search ADS PubMed WorldCat Zumbrun SD , Melton-Celsa AR, Smith MA et al. Dietary choice affects Shiga toxin-producing Escherichia coli (STEC) O157:H7 colonization and disease . Proc Natl Acad Sci USA . 2013 ; 110 : E2126 – 33 . Google Scholar Crossref Search ADS PubMed WorldCat © The Author(s) 2020. Published by Oxford University Press on behalf of FEMS. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png FEMS Microbiology Reviews Oxford University Press

Tripartite relationship between gut microbiota, intestinal mucus and dietary fibers: towards preventive strategies against enteric infections

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References (491)

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Oxford University Press
Copyright
Copyright © 2021 Federation of European Microbiological Societies
ISSN
0168-6445
eISSN
1574-6976
DOI
10.1093/femsre/fuaa052
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Abstract

ABSTRACT The human gut is inhabited by a large variety of microorganims involved in many physiological processes and collectively referred as to gut microbiota. Disrupted microbiome has been associated with negative health outcomes and especially could promote the onset of enteric infections. To sustain their growth and persistence within the human digestive tract, gut microbes and enteric pathogens rely on two main polysaccharide compartments, namely dietary fibers and mucus carbohydrates. Several evidences suggest that the three-way relationship between gut microbiota, dietary fibers and mucus layer could unravel the capacity of enteric pathogens to colonise the human digestive tract and ultimately lead to infection. The review starts by shedding light on similarities and differences between dietary fibers and mucus carbohydrates structures and functions. Next, we provide an overview of the interactions of these two components with the third partner, namely, the gut microbiota, under health and disease situations. The review will then provide insights into the relevance of using dietary fibers interventions to prevent enteric infections with a focus on gut microbial imbalance and impaired-mucus integrity. Facing the numerous challenges in studying microbiota–pathogen–dietary fiber-mucus interactions, we lastly describe the characteristics and potentialities of currently available in vitro models of the human gut. dietary fibers, mucus, gut microbiota, enteric pathogens, in vitro gut models INTRODUCTION The human gastrointestinal tract (GIT) harbors a complex and diverse community of 10 trillion of microorganisms from almost all kingdoms of life consisting of bacteria, viruses, fungi, archaea and protozoa and collectively referred to as gut microbiota (Qin et al. 2010; Sender, Fuchs and Milo 2016). The healthy adult intestinal microbiota is composed of more than one hundred bacterial species per individual, mainly dominated by the Firmicutes and Bacteroidetes phyla followed by members from the Proteobacteria, Actinobacteria, Fusobacteria and Verrucomicrobia. This complex microbial ecosystem contributes to various essential functions for host physiology, including energy extraction from food through fermentation of dietary fibers (Morrison and Preston 2016), vitamin synthesis (Belzer et al. 2017) and development and maturation of the immune system (Kamada et al. 2013). Disruption in gut microbiota composition and activity (termed dysbiosis) can occur and have been associated with negative health outcomes, such as digestive or extra-intestinal diseases like for example inflammatory bowel disease (IBD) or metabolic syndrome (Lavelle and Sokol 2020). In particular, disrupted microbiome could promote the onset of enteric infections (Ghosh et al. 2011; Willing et al.2011) or at least increase their severity. Enteric disease has been and continues to be a major cause of morbidity and mortality worldwide, associated with high societal burden and economical losses (Buzby and Roberts 2009). Gram-negative bacteria, such as Escherichia coli, Salmonella enterica, and Campylobacter jejuni, are among the leading causes of human gastro-intestinal infections in the world (Kotloff 2017). Healthy intestinal microbiota contributes to host resistance to enteric infection through its involvement in the development of the host immune system and provision of colonization resistance. Mechanism of colonization resistance are not fully described yet but it is now acknowledged that commensal microorganisms can impede pathogen establishment by different means like secretion of antimicrobials, competition for carbon sources, micronutrients or intestinal niches, support of gut barrier integrity and induction of host immune responses (Chow, Tang and Mazmanian 2011; Kamada et al. 2013; McKenney and Pamer 2016). Interestingly, the process of infection itself results in disturbances of gut microbiota (Sekirov and Finlay 2009). Colonization resistance, microbiome community structure and niche occupation are crucial parameters during enteric infections that are modulated by two main drivers, namely mucus and diet (Sorbara and Pamer 2019). In order to colonize the intestinal epithelium, pathogens have to get through the mucus, a secreted gel layer produced by the specialized secretory goblet cells, providing a physical, chemical and biological line of defense for the host (Turner 2009; Peterson and Artis 2014). Furthermore, the mucus constitutes an endogenous source of energy substrates and acts as a biological niche for the mucus-associated microbiota, which greatly differs from the one found in the digestive lumen (Li et al. 2015). Due to its location at the interface between the intestinal lumen and the epithelium, an increasing number of studies have shown intestinal mucus act as a major modulator of human health (Martens, Neumann and Desai 2018). Diet also represents a key factor that directly shapes human gut microbiota (Makki et al. 2018). In particular, dietary fibers are defined as a source of carbohydrates resistant to digestion and absorption in the human small intestine that undergo partial or complete microbial breakdown and fermentation in the colon, thus providing a preferential dietary substrate for gut microbes (Kaoutari et al. 2013). Dietary interventions involving fibers have already shown their potential in humans in preventing/fighting disorders associated with gut microbial imbalance and/or impaired-mucus integrity such as inflammatory bowel diseases (IBD) (Wong, Harris and Ferguson 2016) and metabolic-associated disorders (Cotillard et al. 2013; Sonnenburg and Sonnenburg 2014). This review aims for the first time to give new insights into the potential use of dietary fibers as a mean to prevent enteric infections, by bringing together and critically discussing the new knowledge on inter-connections between three determinent factors of gut homeostasis, namely gut microbiota, dietary fibers and mucus layer. The first section of the review gives a general overview of dietary fibers and mucus polysaccharide structures and properties, highlighting their similarities and differences. The second section provides an overview of the interactions between dietary fibers, mucus and gut microbiota in health and disease situations. The following section sketches the current state of the art on the antagonistic properties of dietary fibers in human enteric infections. At last, the review discusses current challenges in this field of research and emphasizes the potential of in vitro human gut models to decipher the tripartite relationships between gut microbiota, mucus and dietary fibers. DIETARY FIBERS AND HUMAN MUCUS-ASSOCIATED POLYSACCHARIDES: CAN WE MAKE AN ANALOGY? Key differences and similarities between dietary fibers and mucus-polysaccharides are summarized in Table 1. Table 1. Similarities and differences between dietary fibers and mucus polysaccharides. . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability GH: Glycoside hydrolase; PUL: Polysaccharide utilization loci. Open in new tab Table 1. Similarities and differences between dietary fibers and mucus polysaccharides. . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability . Dietary fibers . Mucus polysaccharides . 1. General features Origin Exogenous Endogenous Qualitative presence in the gut Variable (dependent upon dietary intakes) Constant (continuously produced and secreted by goblet cells) Structure (polysaccharide composition) More than 20 possible residues Six possible residues, some in common with dietary fibers Non-microbial factors influencing composition Environmental factors (diet including food processing) Environmental factors (mainly diet) Region of the gastrointestinal tract Genetic Ageing Physiological functions/Health promotion properties Faecal bulking / Transit time reduction Trapping of bile salts Reduction of glucose absorption Immune system modulation Microbiota maintenance Lubrication of the epithelium Maintenance of the epithelial barrier Immune system modulation Microbiota maintenance 2. Feeding mechanisms Microbiota accessibility Soluble fibers are easily accessible Insoluble fibers can be considered as niche with reduced accessibility Mucus shed in the digestive lumen is easily accessible Inner colonic layer is a niche nearly devoid of bacteria Niche colonisation Insoluble fiber particles are colonised by microorganisms with corresponding degrading functions Mucus is colonised by microorganisms with more or less degrading functions, the presence of such microbes is dependent upon dietary fibers availability Binding Microorganisms are able to use carbohydrate-binding molecules, specific proteins from extracellular structure and lectins to bind to dietary fibers Microorganisms are able to use carbohydrate adhesins to bind to mucus Degradation Degradation involves several enzymes: glycoside hydrolases, polysaccharide lyases and carbohydrate esterases Degradation involves several enzymes: glycoside hydrolases and polysaccharide lyases. Some enzymes are common with dietary fibers consumption. Fermentation Mucus and dietary fibers polysaccharides are fermented by gut microbiota leading to the production of gut-derived metabolites, especially short chain fatty acids 3. Ecological characteristics Vertical/Cross-feeding relationships By releasing or exposing simple polysaccharides, primary degrading-species allow cross-feeding species to feed themselves Primary degraders are considered to harbor complex dietary fibers degrading apparatus (cellulosome, PULs, …) Primary degraders have to handle external residues and possess appropriate GHs (sialidases, fucosidases,…) Horizontal ecological relationships Degradation by dietary fibers degrading species and versatile species Degradation by mucins degrading specialists and versatile species Impact on gut microbiota composition Microbiota composition is highly dependent on the daily and long-term dietary fibers intakes and composition The impact of mucus polysaccharides composition on microbiota composition gains in importance when the diet is depleted in dietary fibers 4. Involvement in pathologies Digestive and extra-digestive disorders Low dietary fiber intakes are linked with various digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, allergies, autoimmune diseases) Defects in mucus integrity are linked with digestive diseases (inflammatory bowel diseases, colorectal cancer) and extra-digestive pathologies (metabolic disorders, cystic fibrosis) Potential mechanisms of action Low dietary fiber intakes lead to microbiota dysbiosis and a loss of microbial diversity, mucus consumption and increased epithelial permeability Defects in mucus composition could be associated with microbiota dysbiosis (whether dysbiosis is the cause or consequence still remains unknown) and increased epithelial permeability GH: Glycoside hydrolase; PUL: Polysaccharide utilization loci. Open in new tab Brief overview of dietary fibers and mucus polysaccharides structures and properties Dietary fibers Structure A variety of definitions for dietary fiber have been promulgated by scientific and regulatory agencies worldwide. According to the Codex Alimentarius, dietary fibers mean carbohydrate polymers with 10 or more monomeric units, which are not hydrolysed by the endogenous enzymes in the small intestine of humans (Codex Alimentarius 2010; Porter and Martens 2017). They include carbohydrate polymers naturally occurring in the food as consumed, as well as polymers obtained from food raw materials or chemically synthetized that have shown a physiological effect of benefit to health (Codex Alimentarius 2010; Jones 2014). The definition could be extented to oligosaccharides containing between 3–9 monomeric units, depending on national authorities’ recommendations (Codex Alimentarius 2010). Dietary fibers can be divided into subgroups according to their origin, structure and physicochemical properties (Porter and Martens 2017). Nevertheless, most dietary fibers consumed by humans are generally of plant origin and found in different proportions in fruits, vegetables, legumes, cereals, nuts and seeds. Some of them are also derived from animals, fungi or bacteria. This is the case for human-milk oligosaccharides (HMOs), mannans from yeasts, chitin from fungi and exopolysaccharides from bacteria, which are found in fermented foods such as bread, cheese or yogurt (Porter and Martens 2017). Dietary fibers can also be divided into either oligosaccharide (between 3 and 10 monomeric units) or polysaccharides. Among the latter, there are different types (I to V) of resistant starches. They are called this way because their constitutive α(1→4) linked D-glucose polymer cannot be hydrolyzed by human amylases in the time between ingestion and reaching the large intestine (Fuentes-Zaragova et al. 2010). Then, there are non-starch polysaccharides which comprise cellulose (polymer made of β(1→4) linked D-glucose units), hemicelluloses (set of branched polysaccharides based on xylose, mannose, arabinose, glucose), fructans like inulin (β(2→1) linked fructose units) and pectins (complex polysaccharides composed of mostly galacturonic acid, galactose, arabinose and rhamnose) (Deehan et al. 2017). Dietary fibers comprise also resistant oligosaccharides made of fructose (FOS), galactose (GOS), xylose (XOS), mixtures of arabinose and xylose (AXOS) or pectic sugars (POS) (Deehan et al. 2017). In consequence, there is a tremendous diversity of plant-derived dietary fibers that differ in their sugar composition, type of linkage between sugars, degree of polymerization or branching; these structural characteristics impact dietary fibers with various properties, notably crystallinity, viscosity or solubility. The latter is particularly relevant for efficient and rapid fermentation by microorganisms (Holscher 2017). Dietary fiber intake and health effects Dietary fibers intake varies substantially among countries. Westernised diets of industrialised countries are depleted in fibers in favor of animal protein, fat, sugar and starch, while non-industrialised rural communities have greater fibers intake through fibrous plant-rich diets (De Filippo et al. 2010; Schnorr et al. 2014). Investigations into dietary habits revealed that on average adults consume between 12–18 grams, 14 grams and 16–29 grams of fibers per day in the USA, United Kingdom and Europe, respectively (EFSA Panel on Dietetic Products 2010; King, Mainous and Lambourne 2012; Holscher 2017). These dietary amounts are below USDA's recommendation of 25 grams for women and 38 grams for men up to 50 years of age (Jones 2014; Holscher 2017). The beneficial effects of dietary fibers on health are now widely recognised. They have direct physiological benefits such as increasing the volume of faecal bulk, decreasing the intestinal transit time, lowering glycaemia and cholesterol levels as well as suppressing adiposity and the associated parameters of metabolic syndrome (Dhingra et al. 2012; Zou et al. 2018). Populations with higher dietary fibers intakes present a lower incidence of immune dysregulation, with a lower risk to develop asthma, allergies, IBD, diabetes and colorectal cancer (Burkitt et al. 1972; Sonnenburg and Sonnenburg 2014). Insufficient dietary intake in industrialised countries has been associated with a disrupted host-microbiota relationship leading to an increased incidence of inflammatory-related disorders (Makki et al. 2018; Zou et al. 2018). Intestinal mucus polysaccharides Structure Continuously produced and secreted mainly by goblet cells, intestinal mucus varies in terms of structure and composition according to the considered mammalian species (Hugenholtz & de Vos 2018; Etienne-Mesmin et al. 2019). In human, mucus is found throughout the entire GIT of human from the stomach to the large intestine, with its thickness and structure varying depending on the segment of the digestive tract considered, but also with cross-sectional differences. Especially, in the colon, the mucus layer shows a double-layer structure, with an inner layer firmly attached to the epithelium, and an outer layer, constantly shed into the lumen and showing an expended volume due to proteolytic activities provided by the host but also by commensal bacteria (Atuma et al. 2001; Ijssennagger, van der Meer and van Mil 2016). Mucus is a complex viscoelastic adherent secretion composed of water, electrolytes, lipids and proteins. The main structural components of mucus (around 5%) are large glycoproteins called mucins. The core of O-linked glycans is formed by a combination of three sugars, galactose, N-acetylgalactosamine and N-acetylglucosamine (Holmén Larsson et al. 2009; Juge 2012), to which different chains of glycans can be attached. The terminal monosaccharide is usually fucose or sialic acid (Holmén Larsson et al. 2009; Juge 2012). Oligosaccharide chains can also be sulfated, especially in colonic regions (Rho et al. 2005). The glycan moieties are conjugated to proteins, mostly by O-link to serine and threonine but also by N-link to asparagine (Porter and Martens 2017). To date, several MUC genes have been described in human and named based on their discovery's order. Some of them belong to the secreted gel-forming mucin family, while others are classified in the membrane-associated family. Host-secreted mucin 2 (MUC2) glycoprotein is a major constituent of human small intestinal and colonic mucus, while MUC1, MUC5AC, and MUC6 are predominant in the stomach (Sicard et al. 2017). Main functions The mucus barrier has several functions, a primary one being the lubrication of the epithelium helping the progress of food material along the GIT Mucin proteins are also glycosylated polymers that constitute a carbon and energy source for the growth of resident gut microbiota (Tailford et al. 2015). Accumulating evidences demonstrate a crucial role of the mucus layer in maintaining gut homeostasis (Martens, Neumann and Desai 2018). Notably, it contains a large variety of host antimicrobial molecules (e.g. α and β defensins, IgA and IgM) that are retained within the net-like polymer structure of mucin proteins. In close collaboration with the immune system and the gut microbiota, the mucus is the first line of defense against encroaching bacteria that can breach and persist on the epithelial surface (Johansson and Hansson 2016). In particular, bacteriophages, bacteria-killing viruses, are able to interact with mucus and studies in mice demonstrated that phage particles are 4-fold more concentrated in mucus layer compared to the lumen content (Barr et al. 2013). Recent studies showed that phages represent key players in limiting bacteria persistence close to the epithelium and may play an important role in gut microbiota homeostasis (Almeida et al. 2019; Rasmussen et al. 2020; Sausset et al. 2020). The mucus layer therefore has a dual role. On one hand, it lubricates the intestine and acts as a defensive barrier against harmful aggressors. On the other hand, it provides an ecological niche for bacteria by providing adhesion sites and nutrients, as described in section II (Interactions of dietary fibers and mucus-associated polysaccharides with human gut microbiota). Similarities and differences between dietary fibers and mucus carbohydrates Origin and metabolism The first major distinction between dietary fibers and mucus carbohydrates is their origin. While dietary fibers are provided only from the external environment through the diet, mucus polysaccharides originate from the host itself. Consequently, dietary fibers uptake is inconstant and varies in quantity and composition throughout daytime, life and individual, while mucus polysaccharides are chemically more homogeneous and always present as an energy source for the microbial ecosystem. Nonetheless, dietary fibers and mucus carbohydrates are both non-digestible by host enzymes but can be metabolized in the intestine by the resident members of the gut microbiota and further fermented to yield short chain fatty acids (SCFAs) (mainly acetate, butyrate and propionate) and gases (e.g. dihydrogen, carbon dioxide, methane and hydrogen sulfide) (Morrison and Preston 2016). As dietary fibers, mucus polysaccharides can also be fermented in the digestive lumen due to constant shedding of the mucus layer (Johansson 2012). Nevertheless, SCFAs, especially butyrate, resulting from mucin cross-feeding provide an energy source directly usable by nearby colonocytes (Ouwerkerk, de Vos and Belzer 2013). Structure As a result of different linkages and more than 20 possible numerous monomeric units, the structure of carbohydrates is amazingly diverse as illustrated by dietary fibers heterogeneity (Porter and Martens 2017). By comparison, mucus carbohydrates constitute a more restricted group of polysaccharides with only six possible monomeric sugar units (galactose, N-acetylgalactosamine, N-acetylglucosamine, mannose, fucose and sialic acid) (Etienne-Mesmin et al. 2019). However, the diversity of the mucus polysaccharide structures is huge and can offer structural similarities with dietary fibers (Porter and Martens 2017). While the sugar monomers and linkages are different, there is a structural similarity in term of polymerisation, high cross-linkage, with linkages solely and specifically broken down by certain bacteria. HMOs from human breast milk illustrate well the tight line between dietary fibers and mucus polysaccharide structure. They are composed of repeated and variably branched lactose or N–acetyl-lactosamine units often decorated with sialic acid and fucose monosaccharides (Kunz et al. 2000; Ninonuevo et al. 2006). These structures share common patterns with human blood group antigens, which can be recovered in the mucus (Etienne-Mesmin et al. 2019). Actually, most humans (e.g. 80% of North Americans and Europeans) called secretors, express the fut2 gene and consequently harbor blood groups antigens on mucin-O linked glycans (Kelly et al. 1995). During early infancy, HMOs can be considered as the sole source of dietary fibers (Koropatkin, Cameron and Martens 2012). Thus, at an early stage, HMOs intake initiate the use of mucus polysaccharides as a nutritive source by the infant gut microbiota (Koropaktin, Cameron and Martens 2012). Interactions of dietary fibers and mucus-associated polysaccharides with human gut microbiota Substrate accessibility and microbial niches Dietary fibers Substrate accessibility is the first determinant parameter in microbial colonisation of dietary fibers and subsequent degradation and fermentation of their constituting carbohydrates. Restricted to the intestinal transit time, dietary fibers fermentation in the gut can take place in-between 18 hours up to 60 hours (De Paepe et al. 2020). For effective dietary fibers fermentation, poly- or oligosaccharide accessibility is therefore crucial. Soluble fibers, such as oligosaccharides (e.g. FOS), are free and easily accessible to microbes in the lumen (Koropatkin, Cameron and Martens 2012). Thus, they can be easily metabolised in the proximal GIT (mainly ileum and proximal colon), especially in normal transit individuals (Koropatkin, Cameron and Martens 2012). Insoluble fibers consist of a complex tridimensional network of different polysaccharides (for example, plant cell wall particles made of cellulose, hemicellulose and pectins) that renders these carbohydrates less accessible to microorganisms. Hence, they are mainly hydrolysed and fermented later in the distal colon where the microbial bacteria richness is the highest (Koropatkin, Cameron and Martens 2012). By themselves, insoluble dietary fibers particles present in the intestine can be considered as microbial niches since they face an ecological succession of microbial colonisers able to degrade them gradually along their progression through the GIT (De Paepe et al. 2020). The colonising microbial actors are dietary fibers specific (Leitch et al. 2007) and in vitro study of these dynamic communities could be highly predictive of their fiber-degrading capacities (De Paepe et al. 2019). For instance, using anaerobic batch cultures of faecal microbiota, De Paepe and colleagues showed that colonization of wheat bran particles by Bacteroides ovatus/stercoris, Prevotella copri and Firmicutes was associated with an increase in fermentation activity (De Paepe et al. 2019). Similarly, Leitch and colleagues found that resistant starch particles were enriched in Ruminococcus bromii, a starch-colonizing and degrading bacterium (Leitch et al. 2007; Ze et al. 2012; Vital et al. 2018). Some coloniser species, such as Bacteroides thetaiotaomicron and Roseburia intestinalis could even form biofilms at the surface of dietary fibers particles in the luminal digestive content (Mirande et al. 2010; Li et al. 2015). Mucus polysaccharides The mucus layer is also considered a well-known microbial niche in the GIT where colonisation is necessary for resident microorganisms to maintain their presence (Ouwerkerk, de Vos and Belzer 2013). Bacterial mucinases, described both in commensal bacteria and in pathogenic strains, allow access to the mucus layer by proteolysis of the core of mucin proteins then enabling bacterial colonisation (Etienne-Mesmin et al. 2019). To counterbalance mucinase action and maintain its net-like structure that retains the microbiota, the mucus contains structural proteins including protease inhibitors that protect the mucus from extensive degradation (Bansil and Turner 2018). Numerous studies have demonstrated that microbiota communities from the digestive lumen differ in term of composition and abundance from the mucus-associated ones, supporting differences in term of nutrient availability including oxygen and carbohydrate substrates (Chassaing and Gewirtz 2019). Compared to the digestive lumen, the human colonic mucus layer displays a markedly higher level of Firmicutes, Actinobacteria and Proteobacteria and a lower level of Bacteroidetes (Donaldson, Lee and Mazmanian 2016; Richard et al. 2018; Chassaing and Gewirtz 2019; Vuik et al. 2019). Especially, mucosal communities are highly enriched in Bacteroides acidifaciens, Bacteroides fragilis, the mucin-degrader Akkermansia muciniphila and in species belonging to the Lachnospiraceae taxa (Donaldson, Lee and Mazmanian 2016; Pereira and Berry 2017). Niche accessibility also determines a gradient in microbial colonisation of the mucus layer from the digestive lumen to the intestinal epithelium. Densely colonised, the colonic outer layer has a rapid turnover rate, with a renewal in one hour in mouse colon (Johansson 2012; Johansson, Sjövall and Hansson 2013) and bacterial growth rate has to keep in pace for their mucosal prevalence (Rang et al. 1999). Firmly attached to the epithelial cells, the inner colonic layer has for long been believed to be devoid of bacteria in accordance with its more constraining physical properties (Johansson, Sjövall and Hansson 2013). However, single-cell imaging at tissue scale in mice recently revealed the presence of bacteria in close proximity of the epithelium (Earle et al. 2015). Among them, Segmented Filamentous Bacteria have been identified in many vertebrate intestines (humans, rodents and chickens) as commensal strains able to invade this mucus layer without invading the host (Chen et al. 2018; Hedblom et al. 2018; Ladinsky et al. 2019). Recognition and binding strategies Dietary fibers Among the fiber-degrading bacteria isolated from the human gut, the Bacteroides genus has been the most extensively studied. Several members of this genus (e.g. Bacteroides thetaiotaomicron, Bacteroides xylanisolvens, Bacteroides intestinalis, Bacteroides ovatus) are able to forage an important repertoire of glycans in the gut (Kaoutari et al. 2013). These bacteria produce cell-surface enzyme systems that allow them to convert dietary fibers into oligosaccharides that are then internalised into the cell and further hydrolysed into simple sugars. All of these enzyme systems have the same cellular organisation and operating mode as the Starch-Utilization System (Sus) of Bacteroides thetaiotaomicron in which substrate recognition is ensured by the cell-surface protein called SusD (Martens et al. 2009). Each enzyme system is dedicated to a specific polysaccharide and contains a SusD-like protein recognising fructans (Sonnenburg et al. 2010), xylans (Rogowski et al. 2015, Despres et al. 2016a), xyloglucans (Larsbrink et al. 2014), and pectins (Martens et al. 2011; Despres et al. 2016b). Among the Firmicutes, the fiber-degrading bacteria belonging to the Ruminococcus genus also rely on very complex enzyme complexes called cellulosomes (Ruminococcus champanellensis, Ruminococcus flavefaciens) or amylosomes (Ruminococcus bromii) for substrate recognition and binding (Ben David et al. 2015; Cann, Bernardi and Mackie 2016). Ruminococcus albus and Ruminococcus flavefaciens have also been shown to attach to cellulose via type IV pili (Rakotoarivonina et al. 2002; Vodovnik et al. 2013). Studies of complex polysaccharide degrading apparatus in Firmicutes species (other than Ruminococcus) are very limited. Recent studies have shown that Roseburia intestinalis and Monoglobus pectinilyticus belonging to the Firmicutes phylum display the appropriate gear to be mannan and pectin primary degraders, respectively (Kim et al. 2019; La Rosa et al. 2019). Sheridan and colleagues also reported that Roseburia spp. and Eubacterium rectale possess their own Gram-positive polysaccharide utilization loci allowing complex glycans degradation (Sheridan et al. 2016). Otherwise, Firmicutes species are known to rely on a diverse array of transporters (such as ABC transporters) to import smaller sugars for intracellular processing. In particular, ABC transporters own an extracellular substrate-binding site for sugar recognition (Chen 2013). Mucus polysaccharides Microorganisms have developed different binding strategies to mucin. As for dietary fibers, Bacteroides species recognise mucus polysaccharides via a SusD-like protein belonging to the enzyme system involved in mucin glycan degradation (Martens et al. 2009; Sonnenburg et al. 2010). Bacteria can also use specialised cell-surface adhesins or lectins. For instance, the well-known mucus-binding protein MUB, produced by Lactobacillus reuteri ATCC 53608, is able to interact with terminal sialic acid of mucus (Etzold et al. 2014). Another strategy is to employ appendages such as pili and flagella. Lactobacillus rhamnosus SpaC adhesins are localised along the complete length of the bacterial pili. This is supposed to reinforce mucin-binding strength (Reunanen et al. 2012). As their surface counterparts, these pili adhesins also recognise precise carbohydrate patterns (Troge et al. 2012). Interestingly, some adhesins have been shown to recognise patterns encountered in both mucins and dietary fibers, likely due to structural similarities (Cooling et al. 2015; Dotz and Wuhrer 2016; Taylor et al. 2018). Hence, in addition to binding to mucin, a Lactobacillus plantarum mannose-specific adhesin binds also to glycan structure on yeast cell wall and Bifidobacterium infantis adhesin recognises HMOs (Pretzer et al. 2005; Garrido et al. 2011). Carbohydrate metabolism by human gut microbiota Specialized carbohydrate-active enzymes Enzymes involved in carbohydrate metabolism are named CAZymes (for Carbohydrate-active enzymes) and represent 2.6% of the total enzymes encoded by the human gut microbiome (Turnbaugh et al. 2008). Of note, carbohydrate metabolism is almost exclusively supported by the gut microbiome, with around 10 000 CAZymes found in the genome of 177 reference gut bacteria, compared to only 8 to 17 CAZymes in the human genome (Kaoutari et al. 2013; Kaoutari et al. 2014). In the CAZyme super family, glycoside hydrolases (GHs) hydrolyse the glycosidic bond between two or more carbohydrates or between a carbohydrate and a non-carbohydrate moiety, whereas polysaccharide lyases (PLs) cleave uronic-acid containing polysaccharides via a β-elimination mechanism and carbohydrate esterases (CEs) catalyze the de-O or de-N-acylation of substituted saccharides (Kaoutari et al. 2013). Based on their sequences, GHs are classified into 167 families, PLs into 40 families and CEs in 17 families (http://www.cazy.org/). CAZymes are highly specific and often associated with the degradation of one type of linkage (Snart et al. 2006, Chassard et al. 2010; Hamaker and Tuncil 2014). In addition to catalytic modules, CAZymes often contain carbohydrate-binding modules (CBM) that keep them bound to the substrate (Bolam et al. 1998; Boraston et al. 2004). CBMs have been classified into 86 families according to their amino acid sequence and their substrate specificity (http://www.cazy.org/). Some families contain plant dietary fibers specialised CAZymes (e.g. GH5, GH6, GH9, GH10, GH11, GH12, GH28, GH44, GH45, GH74, GH88, GH105, PL1, PL2, PL3, PL4, PL9, PL10, PL11, PL15) while other contain mucus polysaccharide specialised ones (e.g. GH20, GH29, GH33, GH42, GH84, GH85, GH89, GH95, GH98, GH101, GH112, GH129) (Hamaker and Tuncil 2014). CAZymes relative to dietary fibers utilization are well characterised (White et al. 2014, Grondin et al. 2017). CAZymes involved in mucin metabolism have also been functionally characterised in resident members of the gut microbiota able to feed on mucins, including Akkermansia muciniphila, Bacteroides thetaiotaomicron, Bacteroides fragilis, Bifidobacterium bifidum and Ruminococcus gnavus, as recently reviewed (Tailford et al. 2015, Ndeh and Gilbert 2018). Of note, β-galactosidases from the GH2 family has been associated with the degradation of both mucus polysaccharides and dietary fibers (Turnbaugh et al. 2009). If most CBMs are involved in enzyme binding to dietary fibers polysaccharides, CBM in families 32, 40, 47 and 51 also recognise mucin carbohydrates (as reviewed in Ficko-Blean and Boraston 2012). Vertical ecological relationships in carbohydrate degradation Dietary fibers According to the degree of dietary fibers complexity, several CAZymes are needed for their complete hydrolysis (Martens et al. 2011) and the required time for their degradation in the human gut will vary (Sanchez et al. 2009). Such degradation process can be sequential and involves several different microorganisms. For example, Bifidobacterium spp. commonly need primary degradation of starch and xylan by species like Ruminoccocus bromii and Bacteroides ovatus to use the resulting malto- and xylo- oligosaccharides, respectively (Turroni et al. 2018). The relationship by which one microorganism allows another to feed is called cross-feeding (Falony et al. 2006). This mechanism is possible since GHs, PLs and CEs are typically secreted or cell surface-associated enzymes whose activity results in the availability of the released mono- or oligosaccharides for uptake by the hydrolase-producing organism itself but also by nearby bacteria. In the cross-feeding chain, microorganisms required to initiate the degradation are called primary degraders and are defined as ‘bacteria that are able to detect and degrade a complex carbohydrate owing to enzymatic equipment that is missing in other species’ (Kaoutari et al. 2013). If a primary degrader outcompetes the other organisms by being the most efficient in degrading a particular polysaccharide, hence being essential for further degradation by the resident microbiota, it is called bacteria with keystone functions or keystone species (Ze et al. 2012). For example, Ruminoccocus bromii has been regularly described as a resistant starch keystone species, and its absence within the ecosystem is associated with resistant starch indigestibility by the host (Ze et al. 2012; Vital et al. 2018). Mucus polysaccharides Mucus polysaccharides are also concerned by this cross feeding strategy (Png et al. 2010; Marcobal et al. 2013; Egan et al. 2014), since a combination of enzymatic activities from several mucolytic bacteria is required to complete mucin degradation (Derrien et al. 2010; Marcobal et al. 2013). As the O-glycans are covalently attached to the mucin peptides, the peripheral residues are the first targets for GH enzymes. Removal of sialic acid, fucose and glycosulfate is necessary before degradation of O-glycan chains (Corfield 2018). Bacteroides thetaiotaomicron, Bacteroides ovatus, Prevotella spp. strain RS2, Bifidobacterium breve UCC2003, or Bacteroides fragilis all possess mucin-desulfating sulfatases or glycosulfatases and are thus potential primary degraders (Salyers et al. 1977, Berteau et al. 2006, Benjdia et al. 2011; Egan et al. 2016, Praharaj et al. 2018). Facing the huge amount of constantly renewed substrate, there should exist some redundancies in mucus degrading capabilities between species. This is proven by the high numbers of primary degraders. Akkermansia muciniphila could be considered as a species that fulfills a keystone function in mucin degradation. Once the peripheral residues have been removed, the remainders of the O-glycan chains can be hydrolysed. The released saccharides, such as N-acetylglucosamine, N-acetylgalactosamine, galactose, fucose and N-acetylneuraminic acid (sialic acid) can be used by the bacterial degrader itself or by other resident bacteria (Bjursell, Martens and Gordon 2006; Martens, Chiang and Gordon 2008; Sonnenburg et al. 2010). Commensal Escherichia coli and Enterococcus are examples of cross-feeders unable to feed on mucin without microbial pre-digestion (Sicard et al. 2017). Horizontal ecological relationships in carbohydrate degradation Inside the ecological niche, microorganisms can also be classified as generalists or specialists based on their CAZyme equipment. Generalists can use a large number of different carbohydrate structures. When comparing the two main phyla inhabiting the human gut, Bacteroidetes are usually considered more generalists than Firmicutes (Kaoutari et al. 2013). With 308 CAZyme genes, Bacteroidetes thetaiotaomicron is a good example of a generalist species (Martens et al. 2008). On the opposite, other bacteria using relatively few polysaccharides, such as Ruminoccocus bromii (starch degrader only) and Roseburia inulinivorans (inulin degrader), are termed as ‘specialists’ (Koropatkin, Cameron and Martens 2012). Thanks to their CAZyme arsenal, generalist microorganisms can shift their metabolism depending on the diet, and are thought to be highly adaptable to different conditions depending on dietary fibers availability (Koropatkin, Cameron and Martens 2012). When several carbon sources are available, generalists exhibit hierarchical polysaccharide preferences (Rogers et al. 2013). For instance, Bacteroides thetaiotaomicron prioritises dietary fiber over mucus polysaccharide consumption (Kashyap et al. 2013), but this sense of priority is not shared by all microorganisms. Inversely, Bacteroides massiliensis and Bacteroides fragilis are more oriented towards mucosa-associated glycans (Pudlo et al. 2015). Then, large differences can be observed between species of a same genus. As an example, Bacteroides thetaiotaomicron and Bacteroides ovatus, which have 96.5% identity in their 16S rRNA gene sequences have less than one-third of their sus-like systems genes in common (Martens et al. 2011). Some generalists can even switch between dietary fibers and mucus polysaccharides (Sonnenburg 2005). This substrate versatility has been primarily described for Bacteroides species because of their large repertoire of CAZymes. In particular, a fiber-deprived diet forces the versatile species to use the pool of indigenous host glycans present in the mucus (Earle et al. 2015; Desai et al. 2016). This implies that, driven by the increase in selection pressure, strains can rapidly adapt to the mucus niche by switching their transcriptional repertoire to mucus polysaccharides consumption and/or acquiring new mucus polysaccharide degrading functions (Li et al. 2015). Low-fiber diets increase the expression of microbiota O-glycan CAZymes (Sonnenburg 2005), as well as mucinases (Desai et al. 2016). This results in increased inner mucus layer permeability as illustrated in murine models (Schroeder et al. 2018). Studies have shown that dietary fibers supplementation can reverse this loss of mucus integrity (Schroeder et al. 2018). Lastly, ‘versatile’ species can be opposed to ‘mucus specialists’ which rely on mucus polysaccharides as sole carbon source (Cockburn and Koropatkin 2016). Akkermansia muciniphila is a good example of a mucus specialist (Derrien, Belzer and de Vos 2017). Tailford and colleagues have reviewed bacteria with known mucus-degrading capabilities (Tailford et al. 2015). Effect of carbohydrates on gut microbiota composition and sources of variability Well-known effect of dietary fibers on the gut microbiota Large observational studies taught us that dietary fibers consumption affects human gut microbiota composition by evolutionary means (Yatsunenko et al. 2012; Clemente et al. 2015; Smits et al. 2017). The effect of short-term intervention studies appears much more modest, less permanent and with higher inter-subject variability, suggesting a day-to-day adaptation of the gut microbiota to the diet and dietary fibers in particular (Turnbaugh et al. 2009; Wu et al. 2011; Cotillard et al. 2013). Interestingly, most of these studies have focused on the effect of a specific fiber rather than using a rich/low fiber diet. The reported effects vary widely depending on the type of fiber investigated (Martínez et al. 2010), its crystalline form (Tester, Karkalas and Qi 2004; Lesmes et al. 2008), the degree of polymerisation (Hughes et al. 2008; Sanchez et al. 2009; Van den Abbeele et al. 2011; Zhu et al. 2017) and the dose (Bouhnik et al. 1999; Davis et al. 2011). Nevertheless, it is very tempting to associate specific microbiota variations to enrichment of microbial groups with the corresponding dietary fibers degradation capabilities. For instance, resistant starch supplementation has been found to increase Ruminoccocus bromii population, a well-known resistant starch degrader, in human faeces (Salonen et al. 2014; Vital et al. 2018). However, fiber consumption can influence microbiota composition by other indirect physiological effects. For instance, dietary fibers fermentation generates SCFAs leading to a lower colonic pH. Thus, selecting microbial groups resistant to low pH (Scott, Duncan and Flint 2008; Duncan et al. 2009). Dietary fibers are also able to trap bile salts (Story and Kritchevsky 1978), slow glucose absorption and modulate the immune system (Hooper, Littman and Macpherson 2012), mechanisms by which the microbiota composition is in turn affected. There is a huge discrepancy between individuals in terms of fiber-degrading capacities and effects of dietary fibers on their microbiota and this mainly relies on dietary habits (Ze et al. 2012). Multiple independent studies in humans have demonstrated stark differences in terms of microbiota composition and activity between urbanised populations consuming low fiber diets and rural populations, westernisation being characterized by a lower bacterial diversity, a lower Prevotella/Bacteroides ratio and a loss of CAZymes genes (Yatsunenko et al. 2012; Clemente et al. 2015; Martínez et al. 2015; Smits et al. 2017; Makki et al. 2018). Studies have shown that even rarely ingested dietary fibers (Kitahara et al. 2005; Hehemann et al. 2010; Hehemann et al. 2012) or long-considered unfermentable ones (De Filippo et al. 2010) can be catabolised by the gut microbiota of accustomed populations. Japanese consuming diets enriched in uncooked seaweed possess in their microbiota very rare genes (acquired from the environmental bacterium Bacteroides plebeius) encoding porphyranase and agarase enzymes enabling their digestion (Kitahara et al. 2005; Hehemann et al. 2010; Hehemann et al. 2012). Likewise, long-term over-generational consumption of (previously) indigestible dietary fibers can select for new specific degrading capabilities of the microbiota in a specific population (Hehemann et al. 2012). First evidences of a link between mucus polysaccharides and gut microbiota composition? Few pieces of evidences point out the influence of mucus polysaccharides on gut microbiota composition. Mice deficient in core 1-derived O-glycans exhibit a dysbiotic faecal microbiota (Sommer et al. 2014) and mice deficient in core 1- and core 2-derived O-glycans develop microbiota-dependent colitis (Bergstrom et al. 2016). However, since modifications of mucin glycosylation patterns affect mucus barrier function, it appears challenging to decipher whether this dysbiotic microbiota results from direct modulation of microbial communities or from other induced phenomenon, such as inflammation. More interestingly, Wacklin and colleagues have shown that human ABO blood groups, expressed in mucus O-linked glycans, are also involved in intestinal microbiota composition differences (Wacklin et al. 2011). Specifically, faecal microbiota from individuals harboring the B antigen on their mucosal surface (secretor B and AB) differed from the non-B antigen groups (Mäkivuokko et al. 2012). A study performed in mice confirmed these observations with differences in microbiota composition according to the presence or not of blood groups antigens, but also gave additional information on the effect of dietary fibers. Differences in blood group antigen microbiota were noticed only when mice diet was depleted in dietary fibers, suggesting the impact of mucus glycosylation on microbiota composition gains importance when mucus polysaccharides are the sole carbohydrate type left (Kashyap et al. 2013). GUT MICROBIOTA, DIETARY FIBERS AND INTESTINAL MUCUS: FROM HEALTH TO DISEASES? A number of studies highlight the crucial role of gut microbiota in human health and disease. A persistent imbalance in gut microbial communities termed dysbiosis has been associated with many diseases, including infections, allergy, asthma, IBD, obesity, diabetes, liver disease and colorectal cancer (Gong and Yang 2012). For inflammatory-related disorders (such as metabolic disorders, IBD or colorectal cancer), it remains challenging to identify common features in the observed dysbiosis. Within a specified pathology, results in terms of microbiota composition varied between the studies since microbiota analysis is highly dependent on the sampling, e.g. type of population, gastrointestinal location or disease stage (Lucas, Barnich and Nguyen 2017; Cuevas-Sierra et al. 2019). Still, lower microbiota diversity and shift in microbial populations are recurrent factors. Disease susceptibility can be transferred in axenic rodent by microbiota transplantation, highlighting the importance of dysbiosis in the onset of certain pathologies (Bäckhed et al. 2007; Turnbaugh et al. 2008; Ferreira, Willing and Finlay 2011; Vrieze et al. 2012; Liou et al. 2013; Zackular et al. 2013). However, the mechanisms by which the intestinal microbiota participate in these pathologies are still debated; some hypotheses have been proposed including altered energy supplies for the colonocytes, stool bulking, intestinal transit, modulation of the immune system, human gene expression and cell differentiation (Brownawell et al. 2012). In addition, regarding the thin equilibrium between mucus as a protective barrier and its host, defects in mucus integrity have been associated with many of these pathologies including the aforementioned inflammatory-related diseases (Ouwerkerk, de Vos and Belzer 2013, Corfield 2018, Etienne-Mesmin et al. 2019). As detailed below, increased risks of metabolic disorders, IBD and colorectal cancer have been inversely correlated to dietary fibers intakes. Although only little mechanistic data explain how fibers can prevent these pathologies, it is a worthy strategy to explore. One means by which dietary fibers supplementation could improve these conditions is by supporting microbiota diversity (Brownawell et al. 2012). Another hypothesis is related to the positive link between dietary fibers intakes and mucus barrier integrity. First, insoluble dietary fibers mechanically stimulate the intestinal epithelium to secrete mucus (McRorie and McKeown 2017). Second, SCFAs produced during dietary fibers fermentation also play a role in maintaining a balanced mucus production (Wrzosek et al. 2013). Finally, by preventing the ‘versatile’ part of the gut microbiota from shifting towards the utilization of mucus polysaccharides, dietary fibers intakes also act to maintain the mucus layer integrity (Desai et al. 2016; Schroeder et al. 2018; Zou et al. 2018). Current evidences for the relationship between dietary fibers, mucus and intestinal-inflammatory-related disorders Considering the close relationship between dietary fibers and mucus polysaccharides in the gut homeostasis, this section gives a current state of the art on their role in the frame of three intestinal-inflammatory-related pathologies, namely, obesity and metabolic disorders, IBD and colorectal cancer. Obesity and metabolic-related disorders Dietary fibers Metabolic disorders and obesity have been associated with dietary fibers intakes in humans (Fuller et al. 2016; Makki et al. 2018) and supplementation with dietary fibers improves the symptoms (Fechner, Kiehntopf and Jahreis 2014; Myhrstad et al. 2020). Interestingly, individual response to dietary fibers intervention depends on gut microbiota diversity prior to intervention, low response being associated with low microbiota diversity (Cotillard et al. 2013; Zeevi et al. 2015). These pathologies have also been linked to altered representation of bacterial genes and metabolic pathways involved in the processing of carbohydrates, including CAZymes (Turnbaugh et al. 2008). Even if dietary fibers degrading bacteria are depleted in metabolic disorders (Makki et al. 2018), the gut microbiome of genetically-induced obese mice is still more efficient in extracting energy from food compared to the microbiota of wild-type mice fed the same diet (Turnbaugh et al. 2006). In obese humans, increase proportion in the food of more easily degradable/fermentable substrates (together with reduced fiber intakes) may give a benefit to certain microbes, in relation to the gut microbiota dysbiotic state (Zmora et al. 2019). The improvement in metabolic disorders and obesity induced by dietary fibers supplementation could thus result from multiple effects in relation to microbiota modulation, notably SCFAs generation. Administration of SCFAs inhibits diet-induced obesity and improves metabolic syndrome in mice (Kimura et al. 2013; Den Besten et al. 2015; De Vadder et al. 2016), However, the beneficial effect of SCFAs on metabolic disorders is still debated as SCFAs are notably suggested to participate in energy uptake regulation (Janssen and Kersten 2015; Dabke, Hendrick and Devkota 2019). Mucus polysaccharides High-fat/low fiber diets have been shown to increase plasma lipopolysaccharide levels in mice (Cani et al. 2007) and humans (Romaní-Pérez, Agusti and Sanz 2017) which could incriminate epithelial barrier dysfunction. Studies investigating more precisely mucus integrity during obesity and metabolic disorders revealed decreased thickness and increased mucus permeability and microbiota encroachment (Chassaing, Ley and Gewirtz 2014; Chassaing et al. 2015; Tomas et al. 2016; Chassaing et al. 2017a). Some additional evidences point towards microbiota involvement in these observed mucus defect, as illustrated by the high number of studies involving the mucin specialist Akkermansia municiphila. First, Akkermansia muciniphila is less abundant in the intestinal microbiota of both genetic and diet-induced obese and diabetic mice, as well as in obese patients when compared to the faecal microbiota of healthy individuals (Everard et al. 2013; Shin et al. 2014). In mouse models of obesity and metabolic disorders, Akkermansia muciniphila treatment or oral administration of the Amuc_1100 bacterial outer-membrane protein from Akkermansia muciniphila restored the epithelial barrier defects and improved weight control (Plovier et al. 2017). These positive effects of Akkermansia muciniphila supplementation have recently been confirmed in overweight/obese insulin-resistant human individuals (Depommier et al. 2019). A recent mechanistic study in mice revealed that pasteurized Akkermansia muciniphila was able to increase faecal energy contents in decreasing gene expression of glucose and fructose intestinal transporters (Depommier et al. 2020). Of great interest, administration of Akkermansia muciniphila also increased goblet cells numbers and mucus production in the gut of mice fed a high fat diet (Shin et al. 2014). This has been highlighted as a probable means for the bacteria to maintain their carbon energy source in the gut (Van den Abbeele et al. 2011). Taken together, these data imply that specific gut bacteria enrichment or depletion could be intimately linked to the mucus defect observed when consuming a low fiber diet, and suggest that a long term low fiber diet pushes microorganisms toward mucus consumption, leading to mucus erosion. Some evidence has been already obtained in mice where a low-fiber diet drove a dysbiosis responsible for mucus defects (Schroeder et al. 2018; Zou et al. 2018). These defects could be prevented by transplanting a non-dysbiotic microbiota from fiber-fed mice (Schroeder et al. 2018) or by inulin supplementation in a microbiota-dependent manner (Zou et al. 2018). Inhibiting mucus consumption by reverting to adequate dietary fibers intakes could be a proper strategy for obese or metabolic syndrome patients whose microbiota diversity is not yet beyond reach. Inflammatory bowel diseases Dietary fibers Low dietary fibers intakes exacerbate colitis in mice and dietary fibers supplementation has beneficial effects limiting colitis development (Macia et al. 2015). Accordingly, in humans, low dietary fibers intakes are relatively consistent with IBD prevalence (Kakodkar and Mutlu 2017). In a prospective study following 170 776 women, intake of the highest quintile of dietary fibers (median of 24.3 g/day) was associated with a 40% reduction of Crohn's disease risk compared to the lowest quintile (median of 12.7 g/day) (Ananthakrishnan et al. 2013). As for metabolic disorders, the microbiome of IBD patients encodes fewer pathways related to carbohydrate metabolism (Morgan et al. 2012), together with a decrease in SCFAs production and SCFA producing-bacteria (Thibault et al. 2010; Vinolo et al. 2011, Machiels et al. 2014; Ríos-Covián et al. 2016). The beneficial therapeutic effects of SCFAs have been already observed in ulcerative colitis patients (Breuer et al. 1997; Scheppach and German-Austrian Scfa Study Group 1996, Vernia et al. 2003; Vernia et al. 2007) and this effect could be mediated by regulation of the host immune system and metabolism (Galvez, Rodríguez-Cabezas and Zarzuelo 2005; Wikoff et al. 2009). The use of butyrate enemas especially has shown promising results on ulcerative colitis patients' symptoms, but further clinical investigations will be required to overcome variations in studies outcomes and to conclude on their clinical effectiveness in human therapy (Sossai 2012). Specific sulfate-reducing bacteria may be involved in the induction of IBD upon low fiber/high fat–high protein diets. Indeed, low fiber animal-based food enriches the mouse microbiota in bile-tolerant microorganism, such as Bilophila wadsworthia, a sulfate-reducing bacteria that is incriminated to trigger inflammatory responses in the intestine (Devkota et al. 2012; David et al. 2014). This result could be a first clue in favor of dietary fibers effect on colorectal cancer. Human studies have confirmed an increase in sulfate-reducing bacteria in IBD patients (Ijssennagger, van der Meer and van Mil 2016). The produced sulfide could take part in the disease etiology by reducing disulfide bonds thus promoting permeability of the mucus network. Mucus polysaccharides When compared to healthy volunteers, the mucus layer of IBD patients is often thinner and more discontinuous (Strugala, Dettmar and Pearson 2008). The intestinal pattern of MUC genes and the glycosylation mucus profiles are also altered (Corfield 2018). Interestingly, mutations in the fut2 gene, responsible for the secretion of blood group antigens in the mucus layer or in ATG16L1 or XBP1 genes associated to goblet cell function are well-known IBD susceptibility factors (Prescott et al. 2007, Kaser et al. 2008, Cadwell et al. 2010; Rausch et al. 2011; Mohanan et al. 2018). In line with the close interactions between mucus and microbiota, the mucus-associated microbiota has been proposed to participate in IBD aetiology and/or severity. In biopsies from IBD patients, mucosal bacteria are found in greater number, in closer proximity to the intestinal epithelium and in denser biofilms (Schultsz et al. 1999; Swidsinski et al. 2002; Swidsinski et al. 2005; Swidsinski et al. 2007). These mucosal bacteria could show pathogenic properties as Bacteroides fragilis accounts for most of the biofilm mass (Swidsinski et al. 2005). Concerning mucin degrading-bacteria, in faecal samples and colon mucus-associated microbiota, an increased prevalence of Ruminococcus gnavus and Ruminococcus torques was associated to IBD (Png et al. 2010; Hall et al. 2017; Schirmer et al. 2018), whereas Akkermansia muciniphila has been negatively correlated with these pathologies (Png et al. 2010). Of note, these bacteria both degrade and stimulate intestinal mucus production (Hata and Smith 2004; Cervera-Tison et al. 2012; Crost et al. 2013; Lee and Ko 2014; Shin et al. 2014; Graziani et al. 2016) and whether their role is beneficial or not in IBD remains unclear (Derrien, Belzer and de Vos 2017; Seregin et al. 2017; Bian et al. 2019). As fiber-free diet leads to mucus penetrability, microbiota encroachment and low-grade inflammation (Zou et al. 2018), it should be relevant to further investigate if dietary fibers could play a decisive role in IBD prevention. Colorectal cancer Dietary fibers The development of colorectal cancer could be stackable with the events occurring during IBD. Thus, it is not surprising to identify commonly shared predisposition factors or physiological features between these two pathologies, and IBD prevention should logically impacts colorectal cancer prevalence. As for IBD, lower dietary fibers intake and lower fiber-degrading microbiota abundance are associated with increased colorectal cancer incidence (Wang et al. 2012; Aune et al. 2016). Of note, a recent meta-analysis covering 185 prospective trials and 58 clinical studies provided convincing evidence for an inverse correlation between dietary fibers intake and colorectal cancer risk (Reynolds et al. 2019). More surprisingly, increasing fiber intakes after diagnosis is associated with a better survival (Song et al. 2018). Both in vitro and in vivo studies have shown that some types of fibers (e.g. inulin, pectin, cellulose or resistant starch) may play a major role in colorectal cancer prevention (Reddy et al. 1989; Hylla et al. 1998; Buddington, Donahoo and Buddington 2002; Willats, Knox and Mikkelsen 2006; Fuentes-Zaragoza et al. 2010). These effects could be mediated by regulation of intestinal epithelial cell proliferation, inhibition of secondary bile acid production and anti-oxidant effects. However, to date investigations about the role of gut microbiota in the latter observations are preliminary (Fuller et al. 2016; Ocvirk et al. 2019). Nevertheless, a recent prospective cohort study identified an interesting inverse correlation between high-fiber diet and colorectal cancer positive for Fusobacterium nucleatum, a colonic tumorigenesis associated bacterium (Mehta et al. 2017). Fusobacterium species invade colonic epithelial cells to drive inflammation and tumorigenesis (Kostic et al. 2013; Rubinstein et al. 2013) and this result could be a first clue in favor of dietary fibers effect on colorectal cancer through microbiota modulation. The role of SCFAs, in particular butyric acid, resulting from fiber metabolism remains unclear (Donohoe et al. 2012). Apart from its role as an energy substrate for normal colonocytes, butyrate could be a potent inducer of apoptosis in cancer cells (Wu et al. 2018). Mucus polysaccharides Other potential bacterial colorectal cancer drivers have been identified, such as Helicobacter pylori, Streptococcus bovis or Clostridium septicum that need access to the epithelium to infect (Grahn et al. 2005; Mirza, McCloud and Cheetham 2009; Wang et al. 2012; Krishnan and Eslick 2014). Thus, when bacterial access to the epithelium is involved in colorectal cancer aetiology, we can rightly suppose that mucus barrier defects could increase the risk for colorectal cancer development. Moreover, colorectal cancer is characterized by mucin expression modifications and abnormal glycosylation patterns that progress with the tumor stages (Corfield et al. 2018). These local defects in colonic mucus barrier allow a close contact of microbiota with mucosal epithelial cells and lead to inflammatory responses (Corfield et al. 2018). In addition, in a mouse model of chemically induced carcinogenesis, the number and severity of the lesions were inversely correlated to the number of goblet cells, clearly supporting a role of mucus integrity in colorectal cancer prevention (Novaes et al. 2016). Altogether, as for IBD, these results strongly highlight the need for additional mechanistic studies to investigate if mucus deterioration may be prevented by high dietary fibers intakes in a colorectal cancer context. HOW ENTERIC PATHOGENS CAN INTERACT WITH MUCUS AND DIETARY FIBERS IN A COMPLEX MICROBIAL BACKGROUND? Mucus-associated polysaccharides: from interactions with enteric pathogens to a cue for their virulence? Pathogens binding to mucus Binding structures Most of the enteric pathogens including Enterobacteriaceae have to reach the intestinal epithelium and invade the mucosal barrier to promote their colonisation or persistence. Binding to mucus is, therefore, the primary colonisation challenge for pathogens (Sicard et al. 2017) but it can also favor subsequent bacterial adhesion. In vitro adherence of Salmonellae enterica serovar Typhimurium and Enterohemorrhagic Escherichia coli (EHEC) is higher on high-mucus producing cells (e.g. Ht29-MTX or LS174T) than in non- or low-mucus producing cells (e.g. Caco-2 or HT29) (Gagnon et al. 2013; Hews et al. 2017). As for commensals, pathogens use surface-associated appendages (adhesins, fimbriae and flagella) to bind to mucus polysaccharides. For instance, the close relatives Helicobacter pylori and Campylobacter jejuni possess several characterised adhesins that notably bind to blood group antigens and to sialic acid (Mahdavi 2002; Avril et al. 2006; Heikema et al. 2010; Moran, Gupta and Joshi 2011, Kenny et al. 2012; Rossez et al. 2014) while GbpA from Vibrio cholerae binds to N-acetylglucosamine (Bhowmick et al. 2008; Wong et al. 2012). Flagellar subunits of Campylobacter jejuni (Sicard et al2017), enteropathogenic Escherichia coli (Erdem et al. 2007) and Clostridioides difficile are all able to bind mucus polysaccharides. Enterobacteriaceae can interact with mucus glycans via various appendanges like type 1 pili, which harbors an adhesin, FimH, at the tip of fimbriae responsible for mannose-specific adhesive interactions (Abraham et al. 1983; Sokurenko et al. 1998; Schembri et al. 2001; Aprikian et al. 2007). Std fimbriae from Salmonella enterica serovar Typhimurium interacts with terminal fucose (Chessa et al. 2009) and mannose residues (Vimal et al. 2000) Sources of variations As described above, pathogen-mucus interactions are built on the recognition of specific saccharide patterns. As mucus polysaccharide composition changes all along the human GIT, it could be a strategy for precise site targeting in the gut (Owen et al. 2017). The pathogens also have to deal with host-related parameters known to induce variations in mucus structure and composition, such as genetics, diet, degradation by host microbiota and diseases. Illustrating this pathogen pattern dependency, Helicobacter pylori infections were found most prevalent in individuals from O than A group, suggesting a preferred attachment of the bacteria to O- blood group antigen present in the mucus (Kościelak 2012). On the contrary, Enterotoxigenic Escherichia coli (ETEC) seem to have a predilection for individuals from A group (Qadri et al. 2007; Ahmed et al. 2009). Some pathogenic bacteria as Shigella flexneri, Helicobacter pylori and Citrobacter rodentium are even able to reshape mucin glycosylation patterns (Sperandio et al. 2013; Pham et al. 2014; Magalhães et al. 2015). These modifications may adjust the expression of bacterial receptors (Barnich et al. 2007; Corfield et al. 2018) or impact the gut microbiota colonisation barrier (Pham et al. 2014). For instance, Helicobacter pylori infection affects host expression resulting in increased sialylation patterns that favor Helicobacter pylori SabA-mediated adhesion (Magalhães et al. 2015). Mucus degradation by pathogens Bacterial mucinases To face the mucus net-like properties, pathogens possess proteases called mucinases. These mucinases are classified according to the functional group involved in catalysis (e.g. metallo, serine and aspartic proteases), their site of action (endo- or exo- proteases) and their evolutionary relationships related to their amino acid sequence (Carroll 2013). Even if some mucinases, as SslE, are known to exist in both secreted and surface-associated forms, most of the characterised mucinases are secreted in the external environment by pathogens, probably for a wider impact on the mucus structure (Etienne-Mesmin et al. 2019). Mucinases have been well characterised in Enterobacteriaceae, in particular in ETEC and EHEC. These Escherichia coli pathovars are well armed with a diverse arsenal of mucinases, such as SslE, StcE, Hbp, YghJ and EatA (Dutta et al. 2002; Lathem et al. 2002; Leyton et al. 2003; Grys et al. 2005; Kumar et al. 2014). In Adherent Invasive Escherichia coli (AIEC), mucinase Vat-AIEC is over-expressed in the presence of bile salts and mucin, and contribute to bacteria penetration in the mucus layer to establish gut colonisation (Gibold et al. 2016). Mucinases have also been evidenced in Vibrio cholerae (Szabady et al. 2011), Yersinia enterocolitica (Mantle and Rombough 1993) and Clostridioides difficile (Janoir et al. 2007), suggesting the involvement of mucus depolymerisation during infection processes. For instance, EatA and YghJ help the delivery of ETEC toxins to the cell surface by degrading the mucus layer (Kumar et al. 2014; Luo et al. 2014) while StcE by reducing the colonic inner mucus layer promotes EHEC adherence (Hews et al. 2017). It is noteworthy that some commensal bacteria also possess mucinases, highlighting the fine line between pathogenicity and commensalism in the GIT. As an example, SslE is found both in commensal Escherichia coli and in ETEC and EHEC pathogenic strains (Etienne-Mesmin et al. 2019; Tapader, Basu and Pal 2019). Nevertheless, differences between commensal and pathogen mucinases reside at least in their expression levels. For example, pathogenic Escherichia coli generate significant amounts of YghJ compared to their commensal counterparts, while there is no difference in the putative catabolic amino acid sequences (Luo et al. 2014). Lastly, as for CAZymes, mucinases seem to have substrate specificities. For example, StcE preferentially cleaves MUC2 compared to MUC5AC (Hews et al. 2017) and YghJ targets MUC2 and MUC3 (Luo et al. 2013). Glycosyl hydrolases By their degrading potential, CAZymes, and notably GHs, could be another way to cleave mucus but this activity has been poorly described in pathogens. To date, pathogen GHs, as commensal ones, have been preferentially studied as feeding tools rather than mucus-degrading enzymes. As a nice example, Salmonella contains 47 GHs that may degrade glycans. During infection in mice, specific deletion of nanH and malS genes impedes bacterial invasion, suggesting that these GHs may be considered as new virulence factors (Arabyan et al. 2016). Bacteroides fragilis has also been shown to require special polysaccharide utilization loci (containing GH along other CAZymes) for crypt colonisation, and mutants strains deficient for these loci failed to occupy crypts (Lee et al. 2013). However, it is not possible to decipher if these GH knock-out defects in colonisation can be attributed to mucus-degrading defect or to loss of feeding capabilities on other carbohydrate sources. Mucus-based feeding of pathogens Primary degraders or cross-feeding strategies CAZymes are also used by some pathogens to release mucus-derived sugars for their own consumption (Mondal et al. 2014; Arabyan et al. 2016). Salmonella enterica serovar Typhimurium has the ability to release carbohydrates from mucus by using its sialidase (Hoyer et al. 1992). Interestingly, Vibrio cholerae uses its chitinase ChiA2 to feed on both chitin fibers found in the aquatic environment and mucins in the gut (Huq et al. 1983; Meibom et al. 2004; Hunt et al. 2008; Mondal et al. 2014), most probably because of their structural similarities (chain polymers of β-1,4 linked N-acetylglucosamine residues). In line with this observation, mutants for chitin utilisation pathway display less capacity to penetrate mucus and are hypovirulent in a mouse model (Chourashi et al. 2016). Besides these examples, pathogens usually behave as non-primary degraders. They have limited CAZymes arsenal and often count on other mucin degraders to cross-feed. Escherichia coli pathogens represent a good example of this strategy. Indeed, they colonise the mouse large intestine by growing in intestinal mucus, but as they do not secrete extracellular GHs, they cannot degrade mucin-derived oligo- and polysaccharides and depend on other microbes which feed them with small saccharides and promote their own growth (Conway and Cohen 2015). In a gnotobiotic mouse model, EHEC colonise the mucus layer within the cooperation of local bacterial communities including Bacteroides thetaiotaomicron that cleaves host glycan-derived sugars and produces fucose (Pacheco et al. 2012). Similarly, Bacteroides thetaiotaomicron is also able to release free sialic acid from colon mucus glycans that can be further used by Clostridioides difficile and Salmonella enterica serovar Typhimurium to promote their own colonisation and persistence in the gnotobiotic mice gut (Ng et al. 2013). To date, more investigations are required to decipher if these cross-feed relationships also exist in the human gut. Importance of microbial background When gut microbiota is not disturbed, pathogens have to compete with commensal non-primary feeders to use mucus carbohydrates. Conway and Cohen (2015) showed that when gnotobiotic mice are pre-colonised with only three commensal Escherichia coli strains, these strains use all the mucus monosaccharides uptake possibilities to outcompete the pathogenic EHEC strain, leading to pathogen elimination (Leatham et al. 2009). In response, EHEC can utilize a large panel of mucus-derived monosaccharides and thereby compete with commensal Escherichia coli (Fabich et al. 2008). The metabolic flexibility of some pathogenic strains to use both glycolytic and gluconeogenic nutrients from the host may also represent a competitive advantage (Bertin et al. 2013). To outcompete the native microbiota, pathogens can benefit from gut disturbance that will leave free ecological niches. For instance, in human, antibiotic use is one of the leading risk factors for enteric diseases associated with Salmonella and Clostridioides difficile infections (Pavia et al. 1990; Kelly et al. 1994; Pépin et al. 2005; Doorduyn et al. 2006; Dethlefsen et al. 2008). Of interest, antibiotic treatment is also one of the drivers modulating mucin carbohydrates availability. Studies in mice showed that antibiotic treatment induced a spike in mucus-derived monosaccharides such as sialic acid, and these high concentrations of free monosaccharides facilitated the expansion of Salmonella enterica serovar Typhimurium and Clostridioides difficile (Ng et al. 2013). As further evidence, colonisation of gnotobiotic mice with a sialidase-deficient mutant of Bacteroides thetaiotaomicron induces reduction of free sialic acid levels impairing expansion of Clostridioides difficile. These transient effects could be reversed by exogenous dietary administration of free sialic acid (Ng et al. 2013). Pathogens and inflammation in a mucus-altered context There is scarce but promising evidence that inflammation driven by mucus alterations may support pathogen infection. First, in mouse models, defects in mucus glycosylation are clearly associated with inflammation (An et al. 2007; Stone et al. 2009; Burger-van Paassen et al. 2011). This inflammation occurs only when gut microbiota is present, suggesting that the close proximity between microbes and the epithelial brush border drives the response (Bergstrom et al. 2016). Besides, mice with genetically impaired mucus layer are more susceptible to pathogens such as Salmonella enterica (Bergstrom et al. 2010; Zarepour et al. 2013; Hecht et al. 2017). Altogether, mucus defects appear to be involved both in inflammation and pathogen susceptibility. As mucus over-degradation triggers an inflammatory state, we may hypothesise that mucus-degrading microorganisms or microorganisms benefiting from mucus degradation would be more adapted to an inflammatory environment. In this sense, colitis-induced with dextran sodium sulfate seemed to favor microorganisms expressing genes involved in mucus polysaccharide utilisation (Schwab et al. 2014). In the same way, recent studies suggest that pathogens could also benefit from this pro-inflammatory state. In both human and mice, inflamed microbiota is characterised by a reduced abundance of obligate anaerobic bacteria and expansion of facultative anaerobic bacteria from Proteobacteria phylum, mostly members of the Enterobacteriaceae family (Seksik 2003; Gophna et al. 2006; Baumgart et al. 2007; Lupp et al. 2007; Walker et al. 2011; Gevers et al. 2014, Chiodini et al. 2015). Interestingly, Enterobacteriaceae may also support this inflammatory state, thus promoting their own persistence in the gut (Garrett et al. 2010). Lastly, pathogens such as Salmonella have adapted their own metabolism and triggers inflammation-induced mucus fucosylation, allowing the pathogen to feed on fucose (Ansong et al. 2012; Bäumler and Sperandio 2016) in an inflammatory state. Salmonella enterica serovar Typhimiurium also benefits from inflammation-derived electron acceptors that facilitates utilization of microbiota-derived succinate as a carbon source (Spiga et al. 2017). Modulation of virulence genes by mucus-degradation products In addition to acting as binding sites or carbon sources for pathogens, mucin glycoproteins can influence the expression of different pathogen virulence genes, as shown by many in vitro studies (Vogt, Peña-Díaz and Finlay 2015). Many virulence genes of Campylobacter jejuni are upregulated in vitro in the presence of MUC2 glycoprotein (Tu, McGuckin and Mendz 2008) and fucose especially influences chemotaxis and biofilm formation that are important during gut infection (Dwivedi et al. 2016). In response to mucins, Vibrio cholerae also downregulates polysaccharide synthesis pathways involved in biofilm formation, thus promoting its motility within the mucus (Liu et al. 2015). Released monosaccharides from mucin O-glycan degradation can also act as a chemical cue to help pathogens to sense their environment and adapt accordingly. As illustrated with EHEC, fucose represses EHEC LEE expression involved in the formation of attachment and effacement lesions (Pacheco et al. 2012; Cameron and Sperandio 2015). The study postulates that gene repression through fucose-sensing may prevent energy expense in EHEC during LEE production before reaching the epithelial surface, where free fucose is not present (Pacheco et al. 2012, Cameron and Sperandio 2015). N-acetylglucosamine and sialic acid have also a negative effect on LEE expression under aerobic conditions (Le Bihan et al. 2017) but stimulate the production of a LEE effector (EspB) under micro-aerobic conditions, which are those found at a close proximity of the intestinal epithelium (Carlson-Banning and Sperandio 2016). Therefore, the availability of free monosaccharides is not the sole determinant factor in pathogen virulence regulation, but other parameters associated to bacterial localisation, such as oxygen conditions, must be considered. How can dietary fiber modulate enteric pathogen virulence? An overview of in vitro and in vivo studies investigating the potential of dietary fibers against human enteric pathogens is provided in Table 2. Table 2. In vitro and in vivo studies investigating the potential of dietary fibers against human enteric pathogens Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) AIEC: Adherent Invasive Escherichia coli, CCL: chemokine (C-C motif) ligand, CXLCL : chemokine (C-X-C motif) ligand, EHEC: enterohemorrhagic Escherichia coli, ELISA: Enzyme-Linked Immuno Sorbent Assay, EPEC: enteropathogenic Escherichia coli, ETEC: enterotoxigenic Escherichia coli, Gb 3: globotriosylceramide, GM : monosialotetrahexosylganglioside, IL: Interleukin, GM-CSF: Granulocyte Macrophage Colony Stimulating Factor, LT: heat-labile toxin, M-SHIME®: Mucosal Simulator of the Human Intestinal Microbial Ecosystem, Stx: Shiga toxin, ST:heat-stable toxin, TNF-α: Tumor Necrosis Factor Alpha, TLR: Toll like receptor. Open in new tab Table 2. In vitro and in vivo studies investigating the potential of dietary fibers against human enteric pathogens Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Cell adhesion assays . References . Tested fiber(s) . Doses . Pathogens . Cell or adhesion test model . Observed effect . Cravioto et al. 1991 Human milk oligosaccharides 3 g.L−1 EPEC (strains O1163, O1736, 851/71, E2348) Hep-2 cells (Human, carcinoma) Up to 92.8% adhesion inhibition with the pentasaccharides fraction against EPEC strain O1163 Stins et al. 1994 NeuAc alpha 2,3-sialyl lactose 50 µM S fimbriated Escherichia coli (strain GB101/13) Bovine brain endothelial cells 80% adhesion inhibition Idota and Kawakami 1995 Human milk oligosaccharides (GM1 and GM3) 1 g.L−1 ETEC (strain Pb-176) Caco-2 cells (Human, colorectal adenocarcinoma) 70 and 80% adhesion inhibition for GM3 and GM1 respectively Martín et al. 2002 Bovine milk oligosaccharides 0.33 g.L-1 ETEC strains from calves (K99–12, F41–15, K99–4, CCB1, CCB22, CCB33, CCB37) Hemagglutination of erythrocytes Hemagglutination inhibition depending on the saccharides and tested ETEC strains Ruiz-palacios et al. 2003 Alpha1,2-fucosyllactose 0.2 g.L−1 Campylobacter jejuni (invasive strain 287i) Hep-2 cells (Human, carcinoma) 54.8% adhesion inhibition Martin et al. 2004 Soluble plantain fibers 5 g.L−1 AIEC (strains HM427 and HM545) HM427 cells (isolated from Crohn's disease patients) and HM545 cells (from the tumor tissue of a colon cancer patient) 83 to 95% adhesion inhibition for the AIEC strains HM545 and HM427, respectively Coppa et al. 2006 Human milk oligosaccharides 10 g.L−1 EPEC O119, Vibrio cholerae (strain ATCC 14034), and Salmonella fyris (unspecified strain) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 42.2% adhesion inhibition against EPEC strain O119 Shoaf et al. 2006 Galacto-oligosaccharides 16 g.L−1 EPEC (strain E2348/69) HEp-2 cells (Human, carcinoma) and Caco-2 cells (Human, colorectal adenocarcinoma) 65 to 70% adhesion inhibition on Hep-2 and Caco-2 cells, respectively Rhoades et al. 2008 Pectin derived oligosaccharides 2.5 g.L−1 EPEC (strains O11:H27, O19H4, O128:H12), EHEC (strains 123900, 13127, 13128), Desulfovibrio desulfuricans (strain 12833) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90%, 85%, and 99% adhesion inhibition for EPEC, EHEC and Desulfovibrio desulfuricans strains respectively Kim et al. 2009 Lactobacillus acidophilus exopolysaccharides 1 g.L−1 EHEC O157:H7, Salmonella enteritidis, Salmonella typhimurium(strain KCCM 11806), Yersinia enterocolitica, Pseudomonas aeruginosa KCCM 11321, Listeria monocytogenes ScottA, and Bacillus cereus (unspecified strain) Biofilm test formation Up to 95% biofilm formation inhibition with Listeria monocytogenes ScottA Roubos-van den Hil et al. 2009 Soluble fermented soya beans extract 2.5 g.L−1 ETEC K88 (strain ID1000) Caco-2 cells (Human, colorectal adenocarcinoma) 40% adhesion inhibition Roberts et al. 2010 Plantain and broccoli soluble fibers 5 g.L−1 AIEC (strains LF82, HM580, HM605, HM615) Caco2-cl1 cells (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 45.3 to 82.6% inhibition of translocation of AIEC strains across M-cells for broccoli and plantain soluble fibers, respectively Roubos-van den Hil et al. 2010 Soluble fermented soya beans extract 10 g.L−1 ETEC K88 (strain ID1000) Ex vivo adhesion test to pig intestinal brush borders 99% adhesion inhibition Wang, Gänzle and Schwab 2010 Reuteran and levan 5 and 10 g.L−1 ETEC K88 (strains ECL13086, ECL13795, ECL13998 and ECL14048) Haemagglutination of erythrocytes Inhibition of haemagglutination Badia et al. 2012 Beta-galactomannan 0.5 to 20 mg.L−1 Salmonella enterica serovar Typhimurium IPI-2I cells (porcine, small intestine epithelium) Up to 70% adhesion inhibition Decrease of inflammation marker expression and cytokines production (IL-6, CXCL8) Salcedo et al. 2013 Human milk oligosaccharides motifs 0.004 to 0.8 mg.L−1 ETEC (strain CECT 685), EPEC (strain CECT 729), Listeria monocytogenes (strain CECT 935) Caco-2 cells (Human, colorectal adenocarcinoma) Up to 28% adhesion inhibition on EPEC with GM1 at 0.004 mg.L−1 González-Ortiz et al. 2013 Locust bean, wheat bran soluble extract, exopolysaccharides 1 and 10 g.L-1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 80% adhesion inhibition depending on the strains with 10 g.L−1 locust bean extract Quintero-Villegas et al. 2013 Chito-oligosaccharide 0.5 to 16 g.L−1 EPEC (strain E2348/69, O127:H6) HEp-2 cells (Human, carcinoma) Up to 95% adhesion inhibition at the dose 16 g.L−1 Roberts et al. 2013 Soluble plantain fibers 5 g.L−1 Salmonella enterica serovar Typhimurium (strain LT2), Shigella sonnei (strain unspecified), ETEC (C410) and Clostridioides difficile (strain 080042) Co-culture of Caco-2 (Human, colorectal adenocarcinoma) and Raji B cells (Human, burkitt's lymphoma) = M cell model 46.6 to 85% inhibition of adhesion and 46.4 to 80.2% decrease of translocation depending on the strains Sarabia-sainz et al. 2013 Neoglycans composed of conjugated porcine albumin and galacto-oligosaccharides 1 g.L−1 ETEC K88 (strain unspecified) Porcin gastric mucin Adhesion inhibition as measured by decreased optical density Chen et al. 2014 Reuteran and levan 10 g.L−1 ETEC K88 (strains ECL13795 and ECL13998) Haemagglutination of erythrocytes Inhibition of haemagglutination González-Ortiz et al. 2014 Locust bean, wheat bran soluble extract 10g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) Microtitration-based adhesion tests on ileal mucus from piglets Up to 95% adhesion inhibition with wheat bran extract Cilieborg et al. 2017 Lactose and alpha1,2-fucosyllactose 1 and 5 g.L−1 ETEC F18 (strain 9910297–2STM) PSIc1 cells (porcine, jejunal epithelium) Up to 70% adhesion inhibition with α-1,2-fucosyllactose at 5 g.L−1 Van den Abbeele et al. 2016 Inulin and galacto-oligosaccharides 3 g per day added to a continuously renewed compartment AIEC (strain LF82) M-SHIME® experiment with a mucus compartment comprising mucin-agar-covered microcosms More than 1 log decrease of AIEC counts in the mucus (could result from microbiota modulation—notably increase of mucosal lactobacilli and bifidobacteria counts) Di et al. 2017 Pectin derived oligosaccharides 0.001 to 5 g.L−1 EHEC (strain ATCC 43895) HT-29 cells (Human, colorectal adenocarcinoma) Up to 90% bacterial adhesion inhibition at the dose 0.005 g.L−1 Kuda et al. 2017 Alginate 1 g.L−1 Salmonella enterica serovar Typhimurium (strain NBRC 13245T) HT-29 Luc cells (Human, colorectal adenocarcinoma) 70 to 80% adhesion/invasion inhibition depending on alginate molecular weight Liu et al. 2017 Lactobacillus plantarum WLPL04 exopolysaccharides 0.01 to 1 g.L−1 EHEC O157:H7 (strain unspecified) HT-29 cells (Human, colorectal adenocarcinoma) Up to 30% adhesion inhibition and 60% anti biofilm activity at the highest dose Zhu et al. 2018 Exopolysaccharides produced during industrial fermentation of olives 10 g.L−1 ETEC K88 (strains: O149:K91:H10 [K-88]/LT-I/STb and F4-, F6-, F18-, LT1- ST1-, ST2 + Stx2e-) IPEC-J2 cells (porcine, jejunal epithelium) Up to 50% adhesion inhibition depending on the exopolysaccharides Leong et al. 2019 Goat milk oligosaccharides and galacto-oligosaccharides 20g.L−1 for galacto-oligosaccharides and at concentration found in infant formula for goat milk oligosaccharides EPEC (strain NCTC 10418) and Salmonella enterica serovar Typhimurium (strain unspecified) Caco-2 cells (Human, colorectal adenocarcinoma) 30% adhesion inhibition for EPEC and Salmonella enterica serovar Typhimurium Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Growth inhibition tests . References . Tested fiber(s) . Doses . Pathogens . Growth media . Observed effect . Liu et al. 2000 Chitosan 1 g.L−1 Agrobacterium tumefaciens, Bacillus cereus, Corinebacterium michiganence, Erwinia sp., Erwinia carotovora subsp, Escherichia coli, Klebsiella pneumoniae, Micrococcus luteus, Pseudomonas fluorescens, Staphylococcus aureus, Xanthomonas campestris (strains unspecified) Acetic acid (2M) Bacteria growth inhibition Qi et al. 2004 Chitonsan nanoparticules Nanoparticles at 0.0125 mg.L-1 and raw chitosan at 64 mg.L−1 Escherichia coli (strains K88 and ATCC 25922), Salmonella choleraesuis (strain ATCC 50020), Salmonella typhimurium (strain ATCC 50013) and Staphylococcus aureus (strain ATCC 25923) Acetic acid (0.25%) in water at pH 5.0 100% bacteria lethality Chantarasataporn et al. 2014 Chitosan derived oligosaccharides Up to 0.2 g.L−1 EHEC O157:H7 (strain DMST 12743), Staphylococcus aureus (strain ATCC 6538), Listeria monocytogenes (strain ATCC 19115), Bacillus cereus (strain C113) and Salmonella enteritidis (strain DMST 1706) Trypticase Soy broth Bactericidal activity Jeon et al. 2014 Chitosan microparticules 2 g.L−1 EHEC O157:H7 EDL933 (strain ATCC 48935), intra-uterine pathogenic Escherichia coli (strain unspecified), Salmonella enterica strain CDC3041–1, Klebsiella pneumoniae(strain unspecified), Vibrio cholerae (strain 395 classical O1) and Streptococcus uberis (strain unspecified) Luria Bertani mediumBrain Heart Infusion broth (for Streptococcus uberis) 100% bacteria lethality Ma et al. 2016 Chitosan microparticules 40 mg.L−1 EHEC O157:H7, Streptococcus uberis, Salmonella enterica, Escherichia coli, Klebsiella pneumonia, Staphylococcus aureus, Enterococcus, Vibrio cholerae (O1 El Tor), Vibrio cholerae (non-O1), Vibrio cholerae (O395) Mueller Hinton brothSimulated gastrointestinal fluids 100% bacteria lethality Garrido-Maestu et al. 2018 Chitosan nanoparticules 2 g.L−1 EHEC O157:H7 (strain unspecified) Luria Bertani broth 100% bacteria lethality Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination Toxin binding inhibition tests . References . Tested fiber(s)/Microorganisms . Doses . Toxins . In vitro and in vivomodels . Observed effect . Otnaess et al. 1983 GM1 Unspecified Cholera toxin and LT toxin from ETEC Toxin binding ELISA assay and rabbit ileal loop assays Inhibition of toxin binding to receptor and fluid secretions in rabbits intestinal loops Newburg et al. 1990 Fucosylated fraction of human milk oligosaccharides Unspecified ST toxin Mice Higher mice survival rate Idota et al. 1995 Sialyllactose 75 and 100 mg.L-1 Cholera toxin Toxin binding assay and rabbits Inhibition of toxin binding to receptor and fluid secretions in rabbit intestinal loops Paton et al. 2000 Gb3 expressing E. coli Unspecified Shiga toxins Toxin binding assay and mice Inhibition of toxin binding and full protection against EHEC (strains B2F1 and 97MW1) in mice Paton et al. 2005 GM2 and other oligosaccharides expressing E. coli Unspecified LT toxin from Escherichia coli C600:pEWD299 (cloned LT operon) Toxin binding assay and rabbits Inhibition of toxin binding and reduction of fluid secretion in rabbits Rhoades et al. 2008 Pectic oligosaccharides From 0.01 to 100 mg.L−1 Shiga toxins (Stx1 and Stx2) HT-29 cells viability test Decreased intestinal cell death whatever the dose tested Di et al. 2017 Pectic oligosaccharides From 1 to 100 mg.L−1 Shiga toxin (Stx2) HT-29 rRNA depurination test Up to 44% reduction of rRNA depurination In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) In vivo assays . References . Tested fibers . Doses . Pathogens . Animal models . Observed effect . Bovee-Oudenhoven et al. 1997 Lactulose 100 g.kg−1 lactulose Salmonella enteritidis (clinical isolate) Rat 2 log decrease of bacterial shedding at 2 days post-infection (calcium phosphate supplementation potentializes the effect) Kudva et al. 1997 High fiber (grass) vs Low fiber diet (corn and alfalfa) 100% grass vs 50% corn and 50% alfalfa EHEC (strain ATCC 43 894) Sheep Increased faecal shedding and detection time Wolf et al. 1997 Fructooligosaccharides 30 g.L−1 in drinking water, average equivalent of 240 mg/day Clostridioiedes difficile (strain VPI 10463) Hamster Increased hamster survival time Diez-Gonzalez et al. 1998 High non-starch polysaccharides diet vs high starch diet Hay and pasture diet vs grain based diets Naturally occuring Escherichia coli strains Cattle More than 1 log reduction of bacterial shedding Hayden et al. 1998 Psyllium 0.2 g.kg−1 ETEC K88 (strain M1823B) Piglets Improvement of diarrhoea (increase of lactobacillus/coliforms ratio and short chain fatty acids) Lema et al. 2002 High fiber containing diet 35% vs 5% dietary acid-detergent fiber containing diet Naturally occuring EHEC O157:H7 strains Sheep More than 1 log reduction of bacterial shedding Wellock et al. 2007 Inulin and cellulose 50 g.kg−1 (soluble or insoluble non starch polysaccahrides) vs 150 g.kg−1 (soluble or insoluble non starch polysaccharides) ETEC K88 Weaned pigs Improvement of diarrhoea and tendency in ETEC shedding reduction (better effect with inulin compared to fructooligosaccharides) Gilbert et al. 2008 High non starch polysaccharides diet vsh igh starch diet Roughage vs grain based diets Naturally occuring EHEC strains Cattle Reduced pathogen virulence gene expression Reduced Escherichia coli shedding and EHEC isolation Halas et al. 2009 Inulin 80 g.kg−1 ETEC K88 Weaning pigs Improvement of diarrhoea Stuyven et al. 2009 Microorganisms (Saccharomyces cerevisiaeand Sclerotium rolfsii) derived beta-glucans from 500 to 750 mg.kg−1 ETEC GIS 26 Piglets Improvement of diarrhoea, reduction of faecal shedding and immune reaction (IgM, IgA, IgG) Zumbrun et al. 2013 Guar gum vs cellulose fed mice 100 g.kg−1 guar gum diet vs 80 g.kg−1 cellulose and 20 g.kg−1 guar gum diet EHEC O157:H7 (strain 86–24) Mice Full guar gum diet (compared to mix diet) Increased bacterial shedding (more than 2-fold after 3 days post-infection), pathology severity and lethality Chen et al. 2014 Reuteran and levan, dextran and inulin 65 mL of a 10 g.L−1 solution injected by small intestinal segment ETEC K88 (strains ECL13795 et ECL13998) Piglets 40% to 65% reduction of fluid secretionDecreased adherence for reuteran Guerra-Ordaz et al. 2014 Lactulose 10 g.kg−1 ETEC K88 Piglets Increased average body weight gain (increased colonic lactobacilli counts and butyrate concentration) Xiao et al. 2014 Chitosan 0.3 g.kg−1 ETEC (strain unspecified) Weaned pigs Improvement of diarrhoea, decreased calprotectin and TLR4 levels and IL-1β and IL-6 expression in jejunal mucosa Andres-Barranco et al. 2015 Beta-galactomannan 2 and 3 g.kg−1 Salmonella enterica serovar Typhimurium Fatteni`ng pigs More than 90% reduction in Salmonella faecal shedding and mesenteric colonisation (lymph nodes), reduction in seroprevalence, whatever the tested dose Liu et al. 2016 Chitosan 0.3 g.kg−1 ETEC (SEC470 strain from human) Mice Nearly 1 log decrease in ETEC faecal shedding and jejunum colonisation at day 7 post-infection. Jejunal Intestinal inflammation markers decreased (expression of IL-1β, IL-6, IL-17, IL-18, TNF-α and TLR4 abundance) Jeong et al. 2011 Chitosan micro particules 18 g.kg−1 EHEC (strain EDL 933) Cattle Reduced shedding and more than twice reduction in detection time Kuda et al. 2017 Alginate 1 g.L−1 in drinking water Salmonella entericaserovar Typhimurium (strain NBRC 13245T) Mice 0.6 to 1 log reduction of bacterial liver invasion Jazi et al. 2019 Xylooligosaccharides 2 g.kg−1 Salmonellaentericaserovar Typhimurium (strain ATCC 14028) Broiler Less than one log reduction in intestinal colonisation, reduction of Salmonella impact on epithelial morphology (potential prebiotic effect of lactic acid bacteria) AIEC: Adherent Invasive Escherichia coli, CCL: chemokine (C-C motif) ligand, CXLCL : chemokine (C-X-C motif) ligand, EHEC: enterohemorrhagic Escherichia coli, ELISA: Enzyme-Linked Immuno Sorbent Assay, EPEC: enteropathogenic Escherichia coli, ETEC: enterotoxigenic Escherichia coli, Gb 3: globotriosylceramide, GM : monosialotetrahexosylganglioside, IL: Interleukin, GM-CSF: Granulocyte Macrophage Colony Stimulating Factor, LT: heat-labile toxin, M-SHIME®: Mucosal Simulator of the Human Intestinal Microbial Ecosystem, Stx: Shiga toxin, ST:heat-stable toxin, TNF-α: Tumor Necrosis Factor Alpha, TLR: Toll like receptor. Open in new tab Direct antagonistic effect of dietary fibers on pathogens Bacteriostatic effect Some dietary fibers such as chitosan (derived from chitin) have shown a direct bacteriostatic effect by inhibiting the growth of various pathogens, and especially EHEC (Chantarasataporn et al. 2014; Ma et al. 2016; Vardaka, Yehia and Savvaidis 2016; Garrido-Maestu et al. 2018). Chitosan antimicrobial activity probably results from the intracellular leakage via binding positively charged chitosan to negatively charged bacterial surface, leading membrane permeability alteration causing cell death (Jeon et al. 2014). Of interest, the broad in vitro effect of chitosan is also conserved in vivo for ETEC, EHEC and others animal pathogens, by decreasing pathogen colonisation (Jeong et al. 2011; Xiao et al. 2014; Jeon et al. 2016; Liu et al. 2016). Inhibition of cell adhesion Dietary fibers from different sources have proven efficiency in reducing pathogenic Escherichia coli adhesion to intestinal epithelial cells. Many of these fibers have a plant origin (Rhoades et al. 2008; Roubos-van den Hil et al. 2009; Roubos-van den Hil et al. 2010; González-Ortiz et al. 2013; Di et al. 2017). For example, soluble fiber extract from plantain bananas reduce adhesion of AIEC, ETEC and Shigella strains to intestinal epithelial cells (Martin et al. 2004; Roberts et al. 2010). Dietary fibers can be also produced by microorganisms. β-galactomannan from yeasts are able to decrease ETEC adhesion on Caco-2 cells (Jeon et al. 2012). Yeasts also harbor numerous oligomannosides on cell wall able to interact with FimH adhesin of type 1 pili and represent an interesting anti-adherence strategy in reducing pathogenic E. coli adhesion (Roussel et al. 2018b; Sivignon et al. 2015; Ganner and schatzmayr 2012). Bacterial exopolysaccharides from Lactobacillus spp. also inhibited EHEC adhesion on HT29 cells as well as biofilm formation (Kim, oh and Kim 2009, Liu et al. 2017). These exopolysaccharides do not necessarily contain mannose supporting other possible inhibitory effects (Liu et al. 2017). Lastly, dietary fibers can derive from milk. Adhesion of ETEC strains to intestinal Caco-2 cells was reduced by addition of human HMOs (Idota and Kawakami 1995; Salcedo et al. 2013) and goat milk oligosaccharides were also proven to decrease adhesion of human enteric pathogen as Escherichia coli and Salmonella enterica serovar Typhimurium in a Caco-2 cells model (Leong et al. 2019). Reduction of bacteria adhesion could be explained by shared patterns between mucin polysaccharides and dietary fibers, resulting in dietary fibers acting as a decoy for bacteria which escape from the mucus compartment. Inhibition of toxin binding and activity Interestingly, dietary fibers from human milk have also a direct inhibitory effect on pathogen toxins. Sialyl lactose contained in milk was able to inhibit cholera toxin binding to its receptor the monosialoganglioside 1 GM1 (Idota et al. 1995). GM1 is also the receptor of the heat-labile toxin (LT) from ETEC and, in rabbit small intestine loops, the ganglioside fraction of human milk was reported to inhibit LT toxin activity, probably by sharing similarities with GM1 (Otnaess, Laegreid and Ertresvåg 1983). Another human milk component, certainly a fucosylated oligosaccharide, is able to inhibit the ability of ETEC heat-stable toxin (ST) to induce diarrhea in mice and the binding of the extracellular domain of guanylate cyclase, the ST receptor, to fucosylated oligosaccharides was the mechanism involved (Newburg et al. 1990; Crane et al. 1994). In line with this, it seems that milk oligosaccharide richness is associated with infant resistance to many pathogens, notably ETEC (Newburg, Ruiz-Palacios and Morrow 2005). Using the direct inhibitory potential of enterotoxin by saccharides, genetically modified probiotics expressing surface oligosaccharides that effectively bind and inhibit LT from ETEC and Shiga toxins from EHEC have been designed (Paton, Morona and Paton 2000; Paton et al. 2005). One of these probiotics was capable of adsorbing LT toxin (approximately 5% of its own weight) that results in significant protection from LT–induced fluid secretion in rabbit ligated ileal loop assays (Paton et al. 2005). Indirect effect of dietary fibers through gut microbiota modulation Modulation of microbiota composition The resident microbiota is now widely recognised as a significant barrier to pathogen colonisation. This protective role is supported by many studies showing that commensal strains from gut microbiota promote inhibition mechanisms towards pathogens. Direct inhibitory effects are mediated by acid production, secretion of inhibitory molecules like bacteriocin or production of (mostly) unknown compounds able to repress virulence genes (Corr, Gahan and Hill 2007; Schoster et al. 2013; Sikorska and Smoragiewicz 2013). Therefore, microbiota modulation with dietary fibers may be a relevant means to prevent enteric infections (Conway and Cohen 2015). However, demonstrating a positive effect mediated by microbiota modulation is not easy. Even if a dietary fibers supplementation does modify the microbiota and has anti-infectious properties, how to prove that the beneficial effect results from the increase or decrease of specific microbial groups? Some clues can emerge from the simultaneous administration of probiotic strains and dietary fibers to specifically support the probiotic growth (resulting in a prebiotic effect for dietary fibers). In 2001, Asahara and colleagues showed that pre-colonisation of mice with probiotic Bifidobacterium breve inhibited Salmonella enterica serovar Typhimurium growth and translocation in others organs (Asahara et al. 2001). This effect was strengthened by co-administration of Bifidobacterium breve with prebiotic GOS, while GOS alone did not show any anti-infectious properties. However, the authors did not prove any change in Bifidobacterium breve proportion or activity by GOS administration (Asahara et al. 2001). More recently, the continuous oral administration of the probiotic Bifodobacterium breve strain Yakult inhibited mice infection by multidrug-resistant strain of Acinetobacter baumannii and GOS markedly potentiated the probiotic effect without providing any protection alone (Asahara et al. 2016). Another mouse study showed that the second generation probiotic Faecalibacterium prausnitzii plus potato starch reduced Clostridioides difficile colonisation, the combined effect being slightly better than the individual one (Roychowdhury et al. 2018). In a continuous anaerobic fermentation system inoculated with human faeces, combination of Lactobacillus plantarum 0407 and Bifidobacterium bifidum Bb12 together with oligofructose and XOS reduced Campylobacter jejuni growth whatever the mode of administration (prophylaxis treatment or co-administration with the pathogen). The dietary fibers alone failed to reproduce the combined effect of dietary fibers and probiotics but the dietary fibers did increase bifidobacteria counts, supporting a prebiotic effect (Fooks and Gibson 2003). Taken together, these studies in rodent models support that prevention of enteric infections by dietary fibers supplementation may be achievable. Nevertheless, the beneficial effect firstly depends on the previous identification of a specific probiotic group that can act in synergy with dietary fibers, without obvious associated prebiotic effect. Some evidences of dietary fibers efficiency against enteric infections are also available in humans, with the well-known prebiotics FOS and GOS. A study on 281 healthy infants reported that supplementation with GOS and/or FOS resulted in fewer episodes of acute diarrhea. Another study on 342 infants reported a lower incidence of gastroenteritis in the supplemented group with GOS and FOS compared to controls and reduced antibiotic courses per year (Bruzzese et al. 2009). Nevertheless, interpretation of these results are impeded by the lack of pathogen identification and in depth gut microbiota characterisation. Modulation of gut microbiota activity Microbial metabolites resulting from dietary fibers fermentation, such as SCFAs can also modulate pathogen virulence. Acetate at the concentration found in the human ileum stimulates the expression of Type III secretion System (T3SS) from Salmonella enterica serovar Typhimurium, while propionate added at the typical concentration of the human colon, represses T3SS expression (Lawhon et al. 2002). Contradictory results have been obtained for butyrate (at concentrations found in the human colon) with repression or over-expression of T3SS depending on the studies (Lawhon et al. 2002; Takao, Yen and Tobe 2014). Mice fed a diet rich in highly fermentable guar gum exhibited a 10- to 100-fold increase in EHEC colonisation and developed illness compared to the control group fed with cellulose, which is considered as non-fermentable fiber (Zumbrun et al. 2013). This increased pathogenicity was associated to a rise in globotriaosylceramide expression (Shiga-toxin receptor), upregulated due to increase in butyrate concentrations (Zumbrun et al. 2013). Acetate produced by bifidobacteria seemed to protect mice from EHEC toxic effect by increasing intestinal epithelium barrier function (Fukuda et al. 2011). Lastly, an elegant gnotobiotic mouse study showed that a dietary fiber-rich diet could promote Clostridioides difficile colonisation in presence of succinate produced by Bacteroides thetaiotaomicron (Ferreyra et al. 2014). Of note, such a study must be interpreted cautiously since the experiments have been conducted in gnotobiotic mice lacking a competitive microbiota that would normally occupy the succinate-feeding niche. These examples illustrate the complexity in dietary fibers-microbiota-pathogens interactions and the need to investigate in depth pathogen specificities before assuming any dietary recommendation. Inhibition of pathogen interactions with mucus: a new mode of dietary fibers action? Figure 1 summarizes the potential role of dietary fibers in enteric infections, with an emphasis on mucus layer interactions. Figure 1. Open in new tabDownload slide Overview of the potential role of dietary fibers in preventing enteric infectionsReliable and converging data from scientific litterature are represented with numbers in circles, while data more hypothetical needing further investigations are represented with numbers in square. (1) Some dietary fibers exhibit direct bacteriostatic effects against pathogens. (2) Dietary fibers degradation lead to short-chain fatty acids (SCFAs) production that can modulate pathogens' virulence. (3) By presenting structure similarities with receptors, some dietary fibers can prevent pathogen adhesin binding to their receptors. (4) By the same competition mechanism, dietary fibers can also prevent toxin binding to their receptors. (5) Dietary fibers are able to promote gut microbiota diversity. (6) Dietary fibers may promote the growth of specific strains with probiotic properties and therefore exhibit anti-infectious properties. (7) Suitable dietary fibers intake prevents microbiota's switch to mucus consumption, limiting subsequent commensal microbiota encroachement and associated-intestinal inflammation. (8) Dietary fibers may prevent pathogen cross-feeding on mucus by limiting mucus degradation and/or by preserving the diversity of competing bacterial species. (9) By preventing mucus over-degradation by switchers microbes, dietary fibers can hamper pathogen progression close to the epithelial brush border and further restrict subsequent inflammation. Figure 1. Open in new tabDownload slide Overview of the potential role of dietary fibers in preventing enteric infectionsReliable and converging data from scientific litterature are represented with numbers in circles, while data more hypothetical needing further investigations are represented with numbers in square. (1) Some dietary fibers exhibit direct bacteriostatic effects against pathogens. (2) Dietary fibers degradation lead to short-chain fatty acids (SCFAs) production that can modulate pathogens' virulence. (3) By presenting structure similarities with receptors, some dietary fibers can prevent pathogen adhesin binding to their receptors. (4) By the same competition mechanism, dietary fibers can also prevent toxin binding to their receptors. (5) Dietary fibers are able to promote gut microbiota diversity. (6) Dietary fibers may promote the growth of specific strains with probiotic properties and therefore exhibit anti-infectious properties. (7) Suitable dietary fibers intake prevents microbiota's switch to mucus consumption, limiting subsequent commensal microbiota encroachement and associated-intestinal inflammation. (8) Dietary fibers may prevent pathogen cross-feeding on mucus by limiting mucus degradation and/or by preserving the diversity of competing bacterial species. (9) By preventing mucus over-degradation by switchers microbes, dietary fibers can hamper pathogen progression close to the epithelial brush border and further restrict subsequent inflammation. Binding to mucus: dietary fibers acting as a decoy Mucus polysaccharide patterns represent potential binding sites for intestinal pathogens and this observation can be extended to all mucosa surface-associated carbohydrates. Interestingly, saccharide-binding patterns are also found in dietary fibers and the hypothesis here is that dietary fibers can lure pathogens from mucus polysaccharides-associated patterns by presenting similar binding sites. The chitin-binding protein GbpA of Vibrio cholerae has been described as a common adherence factor for both chitin and intestinal surface, including mucus polysaccharides (Kirn, Jude and Taylor 2005; Wong et al. 2012; Younes and Rinaudo 2015). F17 fimbriae produced by ETEC strains recognizes N-acetylglucosamine-presenting receptors on the mucosa and this binding is inhibited by N-acetylglucosamine as well as N-acetylglucosamine oligomers (Buts et al. 2004). Blood group antigens on soluble glycans such as mucins or HMOs may serve as decoy receptors in pathogen defense (Pendu et al. 1983; Renkonen 2000; Yu et al. 2001). Owing to the commonly shared pattern between HMO and human blood groups epitope on mucus polysaccharides, it was shown that HMOs have the potential to inhibit many pathogens binding to mucus. These results are relevant for both pathogens with a tropism to ileum and colon since over 90% of ingested HMOs survive transit throughout the gut (Chaturvedi et al. 2001). HMO supplementation inhibited Campylobacter colonization of mice in vivo and human intestinal mucosa ex vivo (Ruiz-Palacios et al. 2003). Specifically, Campylobacter jejuni binds to fucosylated carbohydrates containing the H(O) blood group epitope and this binding is inhibited by HMOs. First evidences of HMO relevance in human enteric infection prevention come from breastfed infants who are at a 6-fold to 10-fold lower risk of developing necrotising enterocolitis than formula-fed ones (Lucas and Cole 1990; Schanler 2005; Meinzen-Derr et al. 2009). The infant protection would depend on HMO composition of the milk (Autran et al. 2018). Inhibition of mucus degradation by dietary fibers The gut microbiota ability to switch to mucus polysaccharides consumption when fiber intake is low is a relatively new discovery (Sonnenburg 2005). Desai and colleagues were pioneers in extending this notion to enteric pathogen (Desai et al. 2016). In a gnotobiotic mice model colonised by a synthetic human microbiota of 14 species, they showed that a low-fiber diet led the microbiota to switch to mucus polysaccharides consumption, and to enrichment in mucus degrading bacteria and mucus erosion. This greater penetrability induced a lethal susceptibility to the murine pathogen Citrobacter rodentium (Desai et al. 2016). Avoidance of mucus polysaccharides over degradation with adequate dietary fibers intake should allow a safe mucus-consuming microbiota to maintain, prevention of inflammatory reactions and therefore increased barrier to pathogen colonisation (Leatham et al. 2009). Furthermore, to maintain in the intestinal mucus layer, pathogens generally rely on cross-feeding (Pacheco et al. 2012; Ng et al. 2013). Distracting the versatile part of the microbiota from mucus degradation could prevent their adaptation to mucus consumption (Desai et al. 2016), thus avoiding them to feed pathogens in the mucus niche. On the contrary, other studies have reported that dietary fibers rich diet could promote pathogen colonisation by cross-feeding on fiber-derived metabolites from the lumen (Ferreyra et al. 2014). However, these studies have been conducted in antibiotic-treated mice, and we can argue that in a more complex physiological situation, other commensal microorganisms could have outcompeted with pathogens for fiber metabolites (Ferreyra et al. 2014). Altogether, these results indicate that other investigations are needed to address the question of whether enteric infections may benefit from dietary fibers intake or not. This would necessarily depend on fiber characteristics (fermentable or not), but also on the studied microbiota (e.g. selected strains or complex microbiota, antibiotic treatment, inflammation or not…) and type of models used. In any way, it should be interesting to evaluate dietary fibers anti-infectious properties under dysbiotic conditions (e.g. following antibiotic treatment, inflammation, metabolic disorders) to anticipate the effects due to the lack of competition by a diverse long-term resident microbiota. HUMAN IN VITRO GUT MODELS TO DECIPHER THE ROLE OF DIETARY FIBERS AND MUCUS IN ENTERIC INFECTIONS: INTEREST AND LIMITATIONS? Main scientific challenges to be addressed Recent studies have shown that fiber-deprived diets lead to defects of the intestinal mucus layer and correlates with increased pathogen susceptibility and negative outcomes such as inflammatory-related disorders. Nevertheless, a number of challenges need to be addressed before any fiber intake recommendation to prevent enteric infections can be made. First, beneficial effects appear to be fiber-dependent. The wide variety of fiber sources, chemical structure, physico-chemical properties (especially solubility), but also processing and preparation (Hernot et al. 2008), make studies challenging to interpret. As an example, Zumbrun and colleagues showing that guar gum strengthens the EHEC physiopathology in mice, which demonstrate that any deleterious effect observed for one specific type of fiber cannot be extrapolated to all others (Zumbrun et al. 2013). In addition, recent studies caution that processed foods enriched in refined fermentable dietary fibers could have side effects by increasing the risk of liver-related diseases and worsening colitis (Singh et al. 2018; Singh et al. 2019). Caution should be paid when choosing dietary fibers.Fibers with targeted properties should be favored in order to limit potential side effects (e.g. chitosan has shown a broad-spectrum antimicrobial activity) (Raafat and Sahl 2009). Second, utilising fibers for their antagonistic properties against enteric pathogens implies to get a better knowledge of the pathogen itself and to decipher meticulously molecular mechanisms involved in virulence. To establish effective anti-adhesion strategies, pathogen adhesins, their recognised motifs, as well as their distribution throughout human microbiota must be extensively characterized. In the same way, mucinase genes present in enteric pathogens should be characterised in depth. Their importance in pathogen virulence, as well as their mechanisms of action (e.g. recognition patterns), should be addressed. Of note, it would also be interesting to increase our knowledge on the few characterised GH from pathogens and their role during the infection process, especially their ability to degrade mucus. Data about pathogen feeding strategies are missing, especially in a complex microbial background, which would allow a better prediction of pathogen response to DF supplementation. Lastly, at the host level, throughout the GIT, enteric pathogens have to face a succession of different environmental conditions (e.g. pH, bile salts, oxygen and nutrient availability, mucus, and interactions with other resident microbes) that widely vary among individuals (Guerra et al. 2012). In particular, large-scale microbiome studies have confirmed a high degree of variability in microbiota composition among individuals, and dietary interventions in human studies clearly emphasised the inter-individual response of gut microbiota (Cotillard et al. 2013; Salonen et al. 2014; Hughes et al. 2019). In a human metabolic disorder context, individual responses to dietary fiber interventions seem to depend on gut microbiota diversity prior to intervention (baseline), with low responses being associated with low microbiota diversity (Cotillard et al. 2013; Zeevi et al. 2015), making it difficult to extrapolate the results from one individual to the general population. Differences in intervention studies outcomes are exacerbated by the absence of standardised protocols that results in important variations and outweigh biological differences (Lozupone et al. 2012). In particular, studies have shown that composition of the faecal bacterial community can be affected by experimental design and procedures, including sampling, storage or DNA extraction method, but also depends on 16S rRNA gene region targeted and sequencing platforms (Rintala et al. 2017; Panek et al. 2018; Chen et al. 2019). However, modulation of the gut microbiota through dietary fibers interventions still represent an attractive approach for promoting health through enteric disease prevention. In particular, using dietary fibers to sustain the growth of certain bacteria while limiting the expansion of pathogens or maintaining mucosal barrier integrity remain an achievable goal. Nevertheless, to date, only few studies have characterised the underlying mechanisms involved in the inter-relationship between gut microbiota community (including commensals and pathogens) and dietary fibers, considering the wide range of host shaping factors. Research in this field is clearly required to identify gut microbiota keystone species utilising or responding to specific fiber sources and to evaluate in-depth the metabolic cross-feeding mechanisms between microbial species. Several questions remain unresolved such as why certain microbes elicit mucosal barrier strengthening, while some other exhibit mucus-degrading activities. Of note, all these questions should be investigated in healthy individuals but also in patients. A pathogen response to dietary fibers intervention could greatly vary according to the host individual but also to its health status, closely related to its microbiota structure and functionalities (dysbiotic or non-dysbiotic microbiota). In particular, the possible exploitation of host inflammation by pathogens and the mechanisms involved should be investigated more thoroughly. Such studies could help to develop personalised dietary fibers interventions and maximise their beneficial effects. In vitro human gut models as a relevant alternative to in vivo studies In vivo approaches in humans obviously represent the gold standard to investigate the interactions between dietary fibers, gut microbiota and enteric pathogens. However, the biological interpretation is complicated due to a myriad of factors among which inter-individual variability is one of the main challenges. In human clinical trials, there is a huge discrepancy between the studies due to dietary habits, genetic background, lifestyle and geographical origin of participants, as well as the quality and quantity of dietary fibers tested. Strict compliance of participants to the tested diet in interventional studies is also a factor difficult to monitor. Thus, any specific effect related to dietary fibers interventions is difficult to measure in healthy people. Moreover, for evident ethical reasons, access to the different segments of the GIT (from the stomach to the distal colon) is very limited and collection of mucus layer from human biopsies remains difficult (Hansson 2012). To minimise invasive procedures, human gut microbiota studies are usually performed using faecal samples and measured as endpoints, thus making it difficult to decipher where in the GIT the effects of a specific treatment occur (Riva et al. 2019). Lastly, human clinical intervention studies are limited in scope or are even impossible, depending on the pathogenic microorganisms involved. A widespread alternative to clinical studies is the use of in vivo animal models. Animal models are undoubtedly very useful to study physiological or pathological conditions at the level of the entire organism. For decades, their use has been essential for a better understanding of various infectious diseases. To investigate the involvement of gut microbiota on host functions, the use of gnotobiotic animals is particularly relevant, even if these experiments remain expensive and time-consuming (Kirk 2012). Nevertheless, more and more attention should be paid to reduce dependence on animal studies considering the societal demand to limit experiments on animals and the increasing ethical constraints. Also, important caution should be applied when translating data obtained in animal models to humans. Importantly, in vivo approaches involving laboratory animals can be hampered by differences between animal and human digestive physiology including resident microbiota and susceptibility to infection by pathogens (Hugenholtz and de Vos 2018). Concerning dietary fibers, rats have a lower capacity to digest polysaccharides from fibers than human (Knudsen et al. 1994). Another alternative is the use of in vitro models simulating the human digestive environment. Such models can provide a timely and cost-efficient alternative to in vivo assays to perform mechanistic studies on the impact of dietary fibers on human microbiome under controlled conditions of health and disease. Indeed, in vitro approaches enable a high level of control excluding confounding environmental or dietary habits that typically impede the interpretation of in vivo studies and particularly enable to investigate the direct interactions of dietary fibers with gut microbiota, independently from the host. Compared to in vivo approaches, those models offer technical flexibility, accuracy, reproducibility, and are not limited by ethical constraints nor safety concerns, making them doubtlessusefull when working with pathogens to investigate human infectious. Nevertheless, these in vitro models are obviously limited by the lack of nervous or endocrinal systems, but also host immune responses meaning it impossible to monitor host-microbe based colonisation resistance determinants (Payne et al. 2012; Etienne-Mesmin et al. 2019). Importantly, diversity measures are always lower in in vitro gut models than in human faecal samples, suggesting that they are not yet capable of supporting the full range of species that are living in the human gut (Van de Wiele et al. 2015; Pham and Mohajeri 2018). Similarly, SCFAs that play a major role in gut homeostasis are not absorbed in most of in vitro models, or only by passive mechanisms, which may have an impact on gut microbiota or tested pathogenic microorganisms (Pham and Mohajeri 2018). Actually, a broad range of in vitro gut systems is available to reproduce the human GIT, from static mono-compartmental to dynamic multi-compartmental models (Guerra et al. 2012; Payne et al. 2012; Pham and Mohajeri 2018). The last ones are particularly relevant because they enable studying the complex and successive multistage processes of human digestion. They integrate key physicochemical and microbial parameters of the human gut, such as temperature, pH, transit time, digestive enzymes and bile salts, complex, metabolically active and regionalised resident gut microbiota from human origin, and anaerobiosis mainly in the colon compartments. Their spatial compartmentalisation allows sample collection over time and in the desired segment of the digestive tract. In this sense, they can be especially useful to answer research questions related to enteric pathogens with different sites of colonisation (e.g. stomach for Helicobacter pylori, distal small intestine for ETEC and EHEC or large intestine for EHEC). Among dynamic multi-compartmental models, the well-known and validated systems are the TNO gastro-Intestinal Model, namely TIM-1 for the gastric and small intestinal model and TIM-2 for the colon system (Minekus 2015), the continuous three-stage colon systems developed by Gibson, Cummings and MacFarlane (Gibson, Cummings and Macfarlane 1988) or the PolyFermS (Payne et al. 2012), and the Simulator of the Human Intestinal Microbial Ecosystem SHIME® that includes all the compartments from the stomach to the colon (Molly, Vande Woestyne and Verstraete 1993; Van de Wiele et al. 2015). Interestingly, these devices have been recently extended to mimicking specific conditions encountered within the GIT of young children or elderly people, that can be the at-risk population for enteric infections (Cinquin et al. 2006; Denis et al. 2016; Roussel et al. 2018a). In vitro gut models to decipher the key role of digestive secretions, mucus and gut microbiota Despite the obvious limitations of in vitro tools, i.e. no input from nervous, endocrine or immune systems, multi-scale human gut models represent a powerful platform to investigate pathogen survival, regulation of virulence factors (including toxins and adhesins), and interactions with gut microbiota, and decipher how dietary fibers can modulate these parameters to prevent enteric infections. In vitro models of the upper gut, mainly the TIM-1 model, have already shown their value to study the behavior of E. coli pathotypes, such as EHEC or ETEC, in the stomach and the three compartments of the small intestine, and the impact of both serotypes and food components (Etienne-Mesmin et al. 2011; Miszczycha et al. 2014; Roussel et al. 2018b). Despite the absence of metabolisation of dietary fibers in the stomach and small intestine, their viscosity and water holding capacity have to be considered (Taghipoor et al. 2014). Therefore, evaluating the detrimental or beneficial influence of dietary fibers on pathogen survival and/or virulence in the stomach and small intestine would be a future challenge. In the same way, by adding mucus secretion in the upper gut models, the effect of mucins on pathogen survival and virulence is relevant to assess. Besides, it has been shown that dietary fibers bind to bile salts which can subsequently escape re-absorption in the small intestine, increasing their concentration in the digestive lumen (Capuano 2017). Since bile salts have a well-known bactericidal effect, this observation opens the road for many investigations. At least, this hypothesis can easily be tested using in vitro models of the upper gut reproducing passive absorption phenomenon (like in TIM-1 displaying dialysis through hollow fibers). In vitro models of the lower gut are suitable tools to investigate the effect of enteric pathogens, with or without dietary fibers, as sole modulators of gut microbiota composition and metabolic activities. These colon models are inoculated with human faecal samples, and range from batch to continuous fermentation systems. The rapidity and high throughput of batch models render them very useful for large screening studies of dietary fibers (Pham and Mohajeri 2018), but this approach is limited by short-time fermentation (24 to 48h), but also accumulation of metabolites and pH decrease that could impede microbial activities (Payne et al. 2012). In continuous fermentation models, reproducing one or several parts of the human colon, faecal microbiota rapidly shift to adapt to the experimental conditions of the designated colon segment (Aguirre and Venema 2017). These models allow long-term dietary fibers supplementation studies, in accordance with data from clinical trials showing that changes in response to fiber intake could take up to several months to stabilise (Reimer et al. 2014). Several lines of evidence have already demonstrated the ability of dietary fibers to limit pathogen expansion in continuous fermentation models (Pham and Mohajeri 2018). For instance, the SHIME model has been used to demonstrate the antagonistic effects of long-chain arabinoxylans or inulin towards colonisation by opportunistic AIEC pathobiont (Van den Abbeele et al. 2016). Conversely, in the PolyFermS system, a detrimental effect of dietary fibers was demonstrated, since addition of inulin stimulated the growth of Salmonella in the distal colon (Zihler et al. 2010). In vitro colon models could be also advantageously used to assess the effect of dietary fibers on pathogen virulence factors in a complex microbial background. Of particular interest, specific configurations of in vitro colon models have been recently developed to obtain a more realistic view on processes that drive the gastrointestinal microbiome. Some in vitro gut models, such as the Mucosal-SHIME (M-SHIME®), now integrate the mucosal environment which represent a colonisation niche for some bacterial species, including pathogens (Van den Abbeele et al. 2016; Van Herreweghen et al. 2018). The Dietary Particle-Mucosal SHIME (DP-M-SHIME®) allows the incorporation of insoluble food particles, colonized by a specific subset of bacteria, then reproducing the fine-scale spatial organisation of the human gut (De Paepe et al. 2018; De Paepe et al. 2019; De Paepe et al. 2020). These models provide a platform to study gut microbiota functionality and niche differentiation, during treatments with dietary fibers and/or pathogens. However, one of the limitations is the nature and origin of mucins (gastric porcine mucins) used to assess the interactions with gut bacteria doubled by the inability to reproduce a colonic mucus gel recapitulating the in vivo situation. Mucin glycosylation that also plays a critical role in the interaction between gut bacteria and mucus cannot be reproduced in vitro. In vitro colon fermentation models allow the operation of several bioreactors in parallel inoculated with either (i) a same faecal sample to test different dietary fibers/pathogen conditions on the same microbiota or (ii) different faecal samples collected from various donors to evaluate inter-individual variations upon one treatment. Considering inter-individual variations is of high importance as gut microbiota response to any dietary intervention varies widely and depends on starting levels of bacterial species present within the established gut microbiota (Cotillard et al. 2013, Zeevi et al. 2015, Makki et al. 2018). As illustrated with the PolyFermS in vitro system, Lacroix and colleagues investigated the metabolic cross-feeding mechanism and showed that soluble dietary fibers supplementation (β-glucan, XOS, α-GOS and inulin) induced different metabolic and microbial responses depending on an individual's specific microbiota (Poeker et al. 2018). Similar inter-individual differences were observed in the SHIME model supplemented with wheat bran particles (De Paepe et al. 2019). Since cross-feeding relationships are complex and take time to establish and stabilise in vivo, the use of in vitro controlled laboratory settings is suitable to better understand the role played by keystone bacterial species. In particular, these in vitro tools will further help to better manipulate the gut microbiota with personalised dietary interventions. Indeed, the effect of dietary fibers on gut microbiota composition and metabolic activity can be easily monitored when considering inter-individual variability (testing different donor stools), especially with low or high microbial diversity associated with different dietary intakes or even pathological situations (with stool from patients). Additional evidences also suggest that gut-derived metabolites are important modulators of host pathophysiology, among them SCFAs are derived from microbial fermentation of dietary fibers. One main advantage of in vitro continuous models is the possibility to follow SCFA production over time in each colon compartment, and how it can be modulated by dietary fibers and/or pathogen infection (Poeker et al. 2018; De Paepe et al. 2020). In the TIM-2 model, Van Nuenen and colleagues demonstrated the potential of inulin to shift the metabolic activity of the human colonic microbiota (mainly branched-chain fatty acids) infected by Clostridioides difficile (van Nuenen, Diederick Meyer and Venema 2003). Non-targeted approaches can also be used to investigate the impact of dietary fibers or pathogens on gut microbiota activity, such as NMR-based metabolomics technique (Lamichhane et al. 2014) or volatolomics (Giannoukos et al. 2019). Of interest, recent studies have revealed that analysis of the microbial volatolome is a promising approach to detect an imbalance of microbial activity (Sagar et al. 2015, Cruz et al. 2020) and to diagnose metabolism changes in response to physiological stresses (Berkhout et al. 2018). Toward an integration of host responses In order to get closer to the in vivo situation by integrating host-microbiota interactions, current technological challenges aim to couple in vitro colon models to intestinal epithelial cells (Bahrami et al. 2011; Marzorati et al. 2014; Tovaglieri et al. 2019) or Toll-Like Receptor reporter cells (Chassaing et al. 2017b). This would allow a better understanding of how dietary fibers can modulate pathogen-induced inflammatory pathways in the presence of the complex colonic microbiota. In vitro gut models can also be coupled to more complex units, such as the HMI module (Marzorati et al. 2014) or the HuMiX gut-on-a-chip model (Greenhalgh et al. 2019). The HMI module has been specifically designed to be connected to continuous fermentation models such as the SHIME model and incorporates (micro)environmental from the mucosa such as microaerophilic conditions and shear forces. These conditions are extremely important for opportunistic pathogen colonisation and virulence as demonstrated for Salmonella, Shigella and E. coli (De Weirdt and Van de Wiele 2015). Challenge of HMI module with colonic microbiota originating from the SHIME model treated with dried-fermentable yeast induced a decrease of pro-inflammatory IL-8 production (Marzorati et al. 2014). Efforts should be pursued on better simulating the mechanical deformations resulting from peristalsis that could play an important role in holding pathogens exclusion as shown in vivo (Quigley 2011). Interestingly, to further investigate the mechanistic host–microbiome crosstalk in intestinal inflammation, gut-on-a-chip devices have been developed to model intestinal inflammation (Shin and Kim 2018). This is of particular interest since the role of inflammation in enteric infections needs to be unraveled. Recent upgrades in those chips have integrated the oxygen gradient microenvironment (Jalili-Firoozinezhad et al. 2019; Shin et al. 2019). Advanced Organ-on-a-Chip devices have also been engineered to investigate communications between gut microbiota and other organs, as illustrated for liver (Boeri et al. 2019). To study the bi-directional host-microbiota interactions in depth, colonic samples collected from in vitro gut fermentation models could be transferred to germ-free mice (Chassaing et al. 2017b) to see if dietary fibers-induced modifications of gut microbiota have the potential to influence the host and if those modifications can persist. From health to disease conditions The ultimate goal of most biomedical research is to gain greater insight into mechanisms of human diseases in order to develop new preventive strategies, including dietary strategies based on dietary fibers intakes. A major scientific and technical challenge would be then to optimise in vitro colon models to reproduce disease conditions, especially associated with inflammation-related disorders such as obesity, IBD or colorectal cancer. These models will be inoculated with faeces collected from patients, and the main objective would be to maintain for a long period in the bioreactor gut microbiota dysbiosis considered as a characteristic feature of the pathology (Leocádio et al. 2020). Dysbiosis patterns have been associated with an increase in the proportion of several potentially pathogenic bacteria in colorectal cancer patients and autists and have been widely postulated in obesity-related disorders and IBD (DeGruttola et al. 2016). Up to now, a unique study described the adaptation of the TIM-2 colon model to obese conditions (Aguirre, Bussolo de Souza and Venema 2016). Aguirre and colleagues showed by using the TIM-2 model inoculated with faecal samples from lean or obese patients that fermentable carbohydrates (arabinogalactan and inulin) are differently used by the microbiota from the two populations, with higher amount of energy extracted after fermentation by obese microbiota (Aguirre, Bussolo de Souza and Venema 2016). However, this study is hampered by the lack of adaptation of physicochemical parameters (e.g. pH, transit time) to specific digestive conditions found in obese patients. Therefore, more research is warranted in this field to fully determine specific digestive conditions of at-risk populations that can be implemented in the diseased in vitro colon models. This will help scientists to understand better how physicochemical parameters of the digestive tract could by themselves shape the resident microbiota. Conflicts of Interest None declared. REFERENCES Abraham SN , Hasty DL, Simpson WA et al. Antiadhesive properties of a quaternary structure-specific hybridoma antibody against type 1 fimbriae of Escherichia coli . J Exp Med . 1983 ; 158 : 1114 – 28 . Google Scholar Crossref Search ADS PubMed WorldCat Aguirre M , Bussolo de Souza C, Venema K. The Gut Microbiota from Lean and Obese Subjects Contribute Differently to the Fermentation of Arabinogalactan and Inulin . PLoS One . 2016 ; 11 : e0159236 . Google Scholar Crossref Search ADS PubMed WorldCat Aguirre M , Venema K. Challenges in simulating the human gut for understanding the role of the microbiota in obesity . Beneficial Microbes . 2017 ; 8 : 31 – 53 . Google Scholar Crossref Search ADS PubMed WorldCat Ahmed T , Lundgren A, Arifuzzaman M et al. Children with the Le(a+b−) Blood Group Have Increased Susceptibility to Diarrhea Caused by Enterotoxigenic Escherichia coli Expressing Colonization Factor I Group Fimbriae . IAI . 2009 ; 77 : 2059 – 64 . Google Scholar Crossref Search ADS WorldCat Almeida GMF , Laanto E, Ashrafi R et al. Bacteriophage Adherence to Mucus Mediates Preventive Protection against Pathogenic Bacteria . mBio . 2019 ; 10 : e01984 – 19 . Google Scholar Crossref Search ADS PubMed WorldCat Ananthakrishnan AN , Khalili H, Konijeti GG et al. A Prospective Study of Long-term Intake of Dietary Fiber and Risk of Crohn's Disease and Ulcerative Colitis . Gastroenterology . 2013 ; 145 : 970 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Andrés-Barranco S , Vico JP, Grilló MJ et al. Reduction of subclinical Salmonella infection in fattening pigs after dietary supplementation with a ß-galactomannan oligosaccharide . J Appl Microbiol . 2015 ; 118 : 284 – 94 . Google Scholar Crossref Search ADS PubMed WorldCat An G , Wei B, Xia B et al. Increased susceptibility to colitis and colorectal tumors in mice lacking core 3–derived O-glycans . J Exp Med . 2007 ; 204 : 1417 – 29 . Google Scholar Crossref Search ADS PubMed WorldCat Ansong C , Deatherage BL, Hyduke D et al. Studying Salmonellae and Yersiniae Host–Pathogen Interactions Using Integrated ‘Omics and Modeling . Systems Biology . 2012 ; 21 – 41 . Google Scholar OpenURL Placeholder Text WorldCat Aprikian P , Tchesnokova V, Kidd B et al. Interdomain Interaction in the FimH Adhesin of Escherichia coli Regulates the Affinity to Mannose . J Biol Chem . 2007 ; 282 : 23437 – 46 . Google Scholar Crossref Search ADS PubMed WorldCat Arabyan N , Park D, Foutouhi S et al. Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling . Sci Rep . 2016 ; 6 : 29525 . Google Scholar Crossref Search ADS PubMed WorldCat Asahara T , Nomoto K, Shimizu K et al. Increased resistance of mice to Salmonella enterica serovar Typhimurium infection by synbiotic administration of Bifidobacteria and transgalactosylated oligosaccharides . J Appl Microbiol . 2001 ; 91 : 985 – 96 . Google Scholar Crossref Search ADS PubMed WorldCat Asahara T , Takahashi A, Yuki N et al. Protective Effect of a Synbiotic against Multidrug-Resistant Acinetobacter baumannii in a Murine Infection Model . Antimicrob Agents Chemother . 2016 ; 60 : 3041 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Atuma C , Strugala V, Allen A et al. The adherent gastrointestinal mucus gel layer: thickness and physical state in vivo . Am J Physiol-Gastro Liver Physiol . 2001 ; 280 : G922 – 9 . Google Scholar Crossref Search ADS WorldCat Aune D , Keum N, Giovannucci E et al. Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies . BMJ . 2016 : i2716 . Google Scholar OpenURL Placeholder Text WorldCat Autran CA , Kellman BP, Kim JH et al. Human milk oligosaccharide composition predicts risk of necrotising enterocolitis in preterm infants . Gut . 2018 ; 67 : 1064 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Avril T , Wagner ER, Willison HJ et al. Sialic Acid-Binding Immunoglobulin-Like Lectin 7 Mediates Selective Recognition of Sialylated Glycans Expressed on Campylobacter jejuni Lipooligosaccharides . IAI . 2006 ; 74 : 4133 – 41 . Google Scholar Crossref Search ADS WorldCat Badia R , Zanello G, Chevaleyre C et al. Effect of Saccharomyces cerevisiae var. Boulardii and beta-galactomannan oligosaccharide on porcine intestinal epithelial and dendritic cells challenged in vitro with Escherichia coli F4 (K88) . Vet Res . 2012 ; 43 : 4 . Google Scholar Crossref Search ADS PubMed WorldCat Bahrami B , Child MW, Macfarlane S et al. Adherence and Cytokine Induction in Caco-2 Cells by Bacterial Populations from a Three-Stage Continuous-Culture Model of the Large Intestine . Appl Environ Microbiol . 2011 ; 77 : 2934 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Bansil R , Turner BS. The biology of mucus: Composition, synthesis and organization . Adv Drug Deliv Rev . 2018 ; 124 : 3 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Barnich N , Carvalho FA, Glasser A-L et al. CEACAM6 acts as a receptor for adherent-invasive E. coli, supporting ileal mucosa colonization in Crohn disease . J Clin Invest . 2007 ; 117 : 1566 – 74 . Google Scholar Crossref Search ADS PubMed WorldCat Barr JJ , Auro R, Furlan M et al. Bacteriophage adhering to mucus provide a non-host-derived immunity . Proc Natl Acad Sci USA . 2013 ; 110 : 10771 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Baumgart M , Dogan B, Rishniw M et al. Culture independent analysis of ileal mucosa reveals a selective increase in invasive Escherichia coli of novel phylogeny relative to depletion of Clostridiales in Crohn's disease involving the ileum . ISME J . 2007 ; 1 : 403 – 18 . Google Scholar Crossref Search ADS PubMed WorldCat Belzer C , Chia LW, Aalvink S et al. Microbial Metabolic Networks at the Mucus Layer Lead to Diet-Independent Butyrate and Vitamin B12 Production by Intestinal Symbionts . mBio . 2017 ; 8 : mBio.00770-17 , e00770 – 17 . Google Scholar Crossref Search ADS PubMed WorldCat Ben David Y , Dassa B, Borovok I et al. Ruminococcal cellulosome systems from rumen to human: Human ruminococcal cellulosome . Environ Microbiol . 2015 ; 17 : 3407 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Benjdia A , Martens EC, Gordon JI et al. Sulfatases and a Radical S -Adenosyl-l-methionine (AdoMet) Enzyme Are Key for Mucosal Foraging and Fitness of the Prominent Human Gut Symbiont , Bacteroides thetaiotaomicron J Biol Chem . 2011 ; 286 : 25973 – 82 . Google Scholar Crossref Search ADS PubMed WorldCat Bergstrom K , Kissoon-Singh V, Gibson DL et al. Muc2 Protects against Lethal Infectious Colitis by Disassociating Pathogenic and Commensal Bacteria from the Colonic Mucosa . PLoS Pathog . 2010 ; 6 : e1000902 . Google Scholar Crossref Search ADS PubMed WorldCat Bergstrom K , Liu X, Zhao Y et al. Defective Intestinal Mucin-Type O-Glycosylation Causes Spontaneous Colitis-Associated Cancer in Mice . Gastroenterology . 2016 ; 151 : 152 – 164.e11 . Google Scholar Crossref Search ADS PubMed WorldCat Berkhout DJC , Niemarkt HJ, de Boer NKH et al. The potential of gut microbiota and fecal volatile organic compounds analysis as early diagnostic biomarker for necrotizing enterocolitis and sepsis in preterm infants . Expert Review of Gastroenterology & Hepatology . 2018 ; 12 : 457 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Berteau O , Guillot A, Benjdia A et al. A New Type of Bacterial Sulfatase Reveals a Novel Maturation Pathway in Prokaryotes . J Biol Chem . 2006 ; 281 : 22464 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Bertin Y , Chaucheyras-Durand F, Robbe-Masselot C et al. Carbohydrate utilization by enterohaemorrhagic Escherichia coli O157:H7 in bovine intestinal content: Carbon nutrition of EHEC O157:H7 in the bovine intestine . Environ Microbiol . 2013 ; 15 : 610 – 22 . Google Scholar Crossref Search ADS PubMed WorldCat Bhowmick R , Ghosal A, Das B et al. Intestinal Adherence of Vibrio cholerae Involves a Coordinated Interaction between Colonization Factor GbpA and Mucin . IAI . 2008 ; 76 : 4968 – 77 . Google Scholar Crossref Search ADS WorldCat Bian X , Wu W, Yang L et al. Administration of Akkermansia muciniphila Ameliorates Dextran Sulfate Sodium-Induced Ulcerative Colitis in Mice . Front Microbiol . 2019 ; 10 : 2259 . Google Scholar Crossref Search ADS PubMed WorldCat Bjursell MK , Martens EC, Gordon JI. Functional Genomic and Metabolic Studies of the Adaptations of a Prominent Adult Human Gut Symbiont, Bacteroides thetaiotaomicron, to the Suckling Period . J Biol Chem . 2006 ; 281 : 36269 – 79 . Google Scholar Crossref Search ADS PubMed WorldCat Boeri L , Izzo L, Sardelli L et al. Advanced Organ-on-a-Chip Devices to Investigate Liver Multi-Organ Communication: Focus on Gut, Microbiota and Brain . Bioengineering . 2019 ; 6 : 91 . Google Scholar Crossref Search ADS WorldCat Bolam DN , Ciruela A, McQUEEN-MASON S et al. Pseudomonas cellulose-binding domains mediate their effects by increasing enzyme substrate proximity . Biochem J . 1998 ; 331 : 775 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Boraston AB , Bolam DN, Gilbert HJ et al. Carbohydrate-binding modules: fine-tuning polysaccharide recognition . Biochem J . 2004 ; 382 : 769 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Bouhnik Y , Vahedi K, Achour L et al. Short-Chain Fructo-Oligosaccharide Administration Dose-Dependently Increases Fecal Bifidobacteria in Healthy Humans . J Nutr . 1999 ; 129 : 113 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Bovee-Oudenhoven IM , Termont DS, Heidt PJ et al. Increasing the intestinal resistance of rats to the invasive pathogen Salmonella enteritidis: additive effects of dietary lactulose and calcium . Gut . 1997 ; 40 : 497 – 504 . Google Scholar Crossref Search ADS PubMed WorldCat Breuer RI , Soergel KH, Lashner BA et al. Short chain fatty acid rectal irrigation for left-sided ulcerative colitis: a randomised, placebo controlled trial . Gut . 1997 ; 40 : 485 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat Brownawell AM , Caers W, Gibson GR et al. Prebiotics and the Health Benefits of Fiber: Current Regulatory Status, Future Research, and Goals . J Nutr . 2012 ; 142 : 962 – 74 . Google Scholar Crossref Search ADS PubMed WorldCat Bruzzese E , Volpicelli M, Squeglia V et al. A formula containing galacto- and fructo-oligosaccharides prevents intestinal and extra-intestinal infections: An observational study . Clin Nutr . 2009 ; 28 : 156 – 61 . Google Scholar Crossref Search ADS PubMed WorldCat Buddington KK , Donahoo JB, Buddington RK. Dietary Oligofructose and Inulin Protect Mice from Enteric and Systemic Pathogens and Tumor Inducers . J Nutr . 2002 ; 132 : 472 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Burger-van Paassen N , van der Sluis M, Bouma J et al. Colitis development during the suckling-weaning transition in mucin Muc2-deficient mice . Am J Physiol-Gastro Liver Physiol . 2011 ; 301 : G667 – 78 . Google Scholar Crossref Search ADS WorldCat Burkitt DP , Walker ARP, Painter NS. Effect of dietary fiber on stools and transit-times, and its role in the causation of disease . Lancet North Am Ed . 1972 ; 300 : 1408 – 11 . Google Scholar Crossref Search ADS WorldCat Buts L , Bouckaert J, De Genst E et al. The fimbrial adhesin F17-G of enterotoxigenic Escherichia coli has an immunoglobulin-like lectin domain that binds N-acetylglucosamine: F-17G lectin domain structure . Mol Microbiol . 2004 ; 49 : 705 – 15 . Google Scholar Crossref Search ADS WorldCat Buzby JC , Roberts T. The Economics of Enteric Infections: Human Foodborne Disease Costs . Gastroenterology . 2009 ; 136 : 1851 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Bäckhed F , Manchester JK, Semenkovich CF et al. Mechanisms underlying the resistance to diet-induced obesity in germ-free mice . Proc Natl Acad Sci . 2007 ; 104 : 979 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Bäumler AJ , Sperandio V. Interactions between the microbiota and pathogenic bacteria in the gut . Nature . 2016 ; 535 : 85 – 93 . Google Scholar Crossref Search ADS PubMed WorldCat Cadwell K , Patel KK, Maloney NS et al. Virus-Plus-Susceptibility Gene Interaction Determines Crohn's Disease Gene Atg16L1 Phenotypes in Intestine . Cell . 2010 ; 141 : 1135 – 45 . Google Scholar Crossref Search ADS PubMed WorldCat Cameron EA , Sperandio V. Frenemies: Signaling and Nutritional Integration in Pathogen-Microbiota-Host Interactions . Cell Host & Microbe . 2015 ; 18 : 275 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Cani PD , Amar J, Iglesias MA et al. Metabolic Endotoxemia Initiates Obesity and Insulin Resistance . Diabetes . 2007 ; 56 : 1761 – 72 . Google Scholar Crossref Search ADS PubMed WorldCat Cann I , Bernardi RC, Mackie RI. Cellulose degradation in the human gut: Ruminococcus champanellensis expands the cellulosome paradigm: Ruminococcus champanellensis celulosome . Environ Microbiol . 2016 ; 18 : 307 – 10 . Google Scholar Crossref Search ADS PubMed WorldCat Capuano E. The behavior of dietary fiber in the gastrointestinal tract determines its physiological effect . Crit Rev Food Sci Nutr . 2017 ; 57 : 3543 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Carlson-Banning KM , Sperandio V. Catabolite and Oxygen Regulation of Enterohemorrhagic Escherichia coli Virulence . mBio . 2016 ; 7 : e01852 – 16 . Google Scholar Crossref Search ADS PubMed WorldCat Carroll IM. Enteric bacterial proteases in inflammatory bowel disease- pathophysiology and clinical implications . WJG . 2013 ; 19 : 7531 . Google Scholar Crossref Search ADS PubMed WorldCat Cervera-Tison M , Tailford LE, Fuell C et al. Functional Analysis of Family GH36 α-Galactosidases from Ruminococcus gnavus E1: Insights into the Metabolism of a Plant Oligosaccharide by a Human Gut Symbiont . Appl Environ Microbiol . 2012 ; 78 : 7720 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat Chantarasataporn P , Tepkasikul P, Kingcha Y et al. Water-based oligochitosan and nanowhisker chitosan as potential food preservatives for shelf-life extension of minced pork . Food Chem . 2014 ; 159 : 463 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Gewirtz AT. Identification of Inner Mucus-Associated Bacteria by Laser Capture Microdissection . Cell Mol Gastroenterol Hepatol . 2019 ; 7 : 157 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Koren O, Goodrich JK et al. Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome . Nature . 2015 ; 519 : 92 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Ley RE, Gewirtz AT. Intestinal Epithelial Cell Toll-like Receptor 5 Regulates the Intestinal Microbiota to Prevent Low-Grade Inflammation and Metabolic Syndrome in Mice . Gastroenterology . 2014 ; 147 : 1363 – 77 ..e17. Google Scholar Crossref Search ADS PubMed WorldCat Chassaing B , Raja SM, Lewis JD et al. Colonic Microbiota Encroachment Correlates With Dysglycemia in Humans . Cell Mol Gastroenterol Hepatol . 2017a ; 4 : 205 – 21 . Google Scholar Crossref Search ADS WorldCat Chassaing B , Van de Wiele T, De Bodt J et al. Dietary emulsifiers directly alter human microbiota composition and gene expression ex vivo potentiating intestinal inflammation . Gut . 2017b ; 66 : 1414 – 27 . Google Scholar Crossref Search ADS WorldCat Chassard C , Delmas E, Robert C et al. The cellulose-degrading microbial community of the human gut varies according to the presence or absence of methanogens: Cellulolytic microbiota and CH4 production in the human gut . FEMS Microbiol Ecol . 2010 ; 74 : 205 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Chaturvedi P , Warren CD, Buescher CR et al. Survival of Human Milk Oligosaccharides in the Intestine of Infants . Bioactive Components of Human Milk . 2001 ; 34 : 315 – 23 . Google Scholar Crossref Search ADS WorldCat Chen B , Chen H, Shu X et al. Presence of Segmented Filamentous Bacteria in Human Children and Its Potential Role in the Modulation of Human Gut Immunity . Front Microbiol . 2018 ; 9 : 1403 . Google Scholar Crossref Search ADS PubMed WorldCat Chen J. Molecular mechanism of the Escherichia coli maltose transporter . Curr Opin Struct Biol . 2013 ; 23 : 492 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Chen XY , Woodward A, Zijlstra RT et al. Exopolysaccharides Synthesized by Lactobacillus reuteri Protect against Enterotoxigenic Escherichia coli in Piglets . Appl Environ Microbiol . 2014 ; 80 : 5752 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Chen Z , Hui PC, Hui M et al. Impact of Preservation Method and 16S rRNA Hypervariable Region on Gut Microbiota Profiling . mSystems . 2019 ; 4 . Google Scholar OpenURL Placeholder Text WorldCat Chessa D , Winter MG, Jakomin M et al. Salmonella enterica serotype Typhimurium Std fimbriae bind terminal α(1,2)fucose residues in the cecal mucosa . Mol Microbiol . 2009 ; 71 : 864 – 75 . Google Scholar Crossref Search ADS PubMed WorldCat Chiodini RJ , Dowd SE, Chamberlin WM et al. Microbial Population Differentials between Mucosal and Submucosal Intestinal Tissues in Advanced Crohn's Disease of the Ileum . PLoS One . 2015 ; 10 : e0134382 . Google Scholar Crossref Search ADS PubMed WorldCat Chourashi R , Mondal M, Sinha R et al. Role of a sensor histidine kinase ChiS of Vibrio cholerae in pathogenesis . Int J Med Microbiol . 2016 ; 306 : 657 – 65 . Google Scholar Crossref Search ADS PubMed WorldCat Chow J , Tang H, Mazmanian SK. Pathobionts of the gastrointestinal microbiota and inflammatory disease . Curr Opin Immunol . 2011 ; 23 : 473 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Cilieborg MS , Sangild PT, Jensen ML et al. α1,2-Fucosyllactose Does Not Improve Intestinal Function or Prevent Escherichia coli F18 Diarrhea in Newborn Pigs . J Pediatr Gastroenterol Nutr . 2017 ; 64 : 310 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Cinquin C , Le Blay G, Fliss I et al. New three-stage in vitro model for infant colonic fermentation with immobilized fecal microbiota: Model for infant colon fermentation . FEMS Microbiol Ecol . 2006 ; 57 : 324 – 36 . Google Scholar Crossref Search ADS PubMed WorldCat Clemente JC , Pehrsson EC, Blaser MJ et al. The microbiome of uncontacted Amerindians . Sci Adv . 2015 ; 1 : e1500183 . Google Scholar Crossref Search ADS PubMed WorldCat Cockburn DW , Koropatkin NM. Polysaccharide Degradation by the Intestinal Microbiota and Its Influence on Human Health and Disease . J Mol Biol . 2016 ; 428 : 3230 – 52 . Google Scholar Crossref Search ADS PubMed WorldCat CODEX Alimentarius Commission . CODEX Alimentarius (CODEX) Guidelines on Nutrition Labeling CAC/GL 2–1985 as Last Amended 2010 . Rome : FAO ; 2010 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Conway T , Cohen PS. Commensal and Pathogenic Escherichia coli Metabolism in the Gut . Microbiology Spectrum . 2015 ; 3 . Google Scholar OpenURL Placeholder Text WorldCat Coppa GV , Zampini L, Galeazzi T et al. Human Milk Oligosaccharides Inhibit the Adhesion to Caco-2 Cells of Diarrheal Pathogens: Escherichia c oli, Vibrio cholerae, and Salmonella fyris . Pediatr Res . 2006 ; 59 : 377 – 82 . Google Scholar Crossref Search ADS PubMed WorldCat Corfield AP. The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human . Microorganisms . 2018 ; 6 : 78 . Google Scholar Crossref Search ADS WorldCat Corfield AP . The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human . Microorganisms . 2018 ; 6 : 78 . Google Scholar Crossref Search ADS WorldCat Corr SC , Gahan CGM, Hill C. Impact of selected Lactobacillus and Bifidobacterium species on Listeria monocytogenes infection and the mucosal immune response . FEMS Immunol Med Microbiol . 2007 ; 50 : 380 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Cotillard A , Kennedy SP, Kong LC et al. Dietary intervention impact on gut microbial gene richness . Nature . 2013 ; 500 : 585 – 88 . Google Scholar Crossref Search ADS PubMed WorldCat Crane JK , Azar SS, Stam A et al. Oligosaccharides from Human Milk Block Binding and Activity of the Escherichia coli Heat-Stable Enterotoxin (STa) in T84 Intestinal Cells . J Nutr . 1994 ; 124 : 2358 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Cravioto A , Tello A, Villafan H et al. Inhibition of Localized Adhesion of Enteropathogenic Escherichia coli to HEp-2 Cells by Immunoglobulin and Oligosaccharide Fractions of Human Colostrum and Breast Milk . J Infect Dis . 1991 ; 163 : 1247 – 55 . Google Scholar Crossref Search ADS PubMed WorldCat Crost EH , Tailford LE, Le Gall G et al. Utilisation of Mucin Glycans by the Human Gut Symbiont Ruminococcus gnavus Is Strain-Dependent . PLoS One . 2013 ; 8 : e76341 . Google Scholar Crossref Search ADS PubMed WorldCat Cruz R , Palmeira JD, Martins ZE et al. Multidisciplinary approach to determine the effect of polybrominated diphenyl ethers on gut microbiota . Environ Pollut . 2020 ; 260 : 113920 . Google Scholar Crossref Search ADS PubMed WorldCat Cuevas-Sierra A , Ramos-Lopez O, Riezu-Boj JI et al. Diet, Gut Microbiota, and Obesity: Links with Host Genetics and Epigenetics and Potential Applications . Adv Nutr . 2019 ; 10 : S17 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Dabke K , Hendrick G, Devkota S. The gut microbiome and metabolic syndrome . J Clin Invest . 2019 ; 129 : 4050 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat David LA , Maurice CF, Carmody RN et al. Diet rapidly and reproducibly alters the human gut microbiome . Nature . 2014 ; 505 : 559 – 63 . Google Scholar Crossref Search ADS PubMed WorldCat Davis LMG , Martínez I, Walter J et al. Barcoded Pyrosequencing Reveals That Consumption of Galactooligosaccharides Results in a Highly Specific Bifidogenic Response in Humans . PLoS One . 2011 ; 6 : e25200 . Google Scholar Crossref Search ADS PubMed WorldCat Deehan EC , Duar RM, Armet AM et al. Modulation of the Gastrointestinal Microbiome with Nondigestible Fermentable Carbohydrates To Improve Human Health . Microbiol Spectrum . 2017 ; 5 : BAD – 0019 . Google Scholar OpenURL Placeholder Text WorldCat De Filippo C , Cavalieri D, Di Paola M et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa . Proc Natl Acad Sci . 2010 ; 107 : 14691 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat DeGruttola AK , Low D, Mizoguchi A et al. Current Understanding of Dysbiosis in Disease in Human and Animal Models . Inflamm Bowel Dis . 2016 ; 22 : 1137 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Den Besten G , Bleeker A, Gerding A et al. Short-Chain Fatty Acids Protect Against High-Fat Diet–Induced Obesity via a PPARγ-Dependent Switch From Lipogenesis to Fat Oxidation . Diabetes . 2015 ; 64 : 2398 – 408 . Google Scholar Crossref Search ADS PubMed WorldCat Denis S , Sayd T, Georges A et al. Digestion of cooked meat proteins is slightly affected by age as assessed using the dynamic gastrointestinal TIM model and mass spectrometry . Food Funct . 2016 ; 7 : 2682 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat De Paepe K , Verspreet J, Courtin CM et al. Microbial succession during wheat bran fermentation and colonisation by human faecal microbiota as a result of niche diversification . ISME J . 2020 ; 14 : 584 – 96 . Google Scholar Crossref Search ADS PubMed WorldCat De Paepe K , Verspreet J, Rezaei MN et al. Isolation of wheat bran-colonizing and metabolizing species from the human fecal microbiota . PeerJ . 2019 ; 7 : e6293 . Google Scholar Crossref Search ADS PubMed WorldCat De Paepe K , Verspreet J, Verbeke K et al. Introducing insoluble wheat bran as a gut microbiota niche in an in vitro dynamic gut model stimulates propionate and butyrate production and induces colon region specific shifts in the luminal and mucosal microbial community: Long-term wheat bran intervention in the SHIME . Environ Microbiol . 2018 ; 20 : 3406 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Depommier C , Everard A, Druart C et al. Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: a proof-of-concept exploratory study . Nat Med . 2019 ; 25 : 1096 – 103 . Google Scholar Crossref Search ADS PubMed WorldCat Depommier C , Van Hul M, Everard A et al. Pasteurized Akkermansia muciniphila increases whole-body energy expenditure and fecal energy excretion in diet-induced obese mice . Gut Microbes . 2020 : 1 – 15 . Google Scholar OpenURL Placeholder Text WorldCat Derrien M , Belzer C, de Vos WM. Akkermansia muciniphila and its role in regulating host functions . Microb Pathog . 2017 ; 106 : 171 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Derrien M , van Passel MWJ, van de Bovenkamp JHB et al. Mucin-bacterial interactions in the human oral cavity and digestive tract . Gut Microbes . 2010 ; 1 : 254 – 68 . Google Scholar Crossref Search ADS PubMed WorldCat Desai MS , Seekatz AM, Koropatkin NM et al. A Dietary Fiber-Deprived Gut Microbiota Degrades the Colonic Mucus Barrier and Enhances Pathogen Susceptibility . Cell . 2016 ; 167 : 1339 – 1353.e21 . Google Scholar Crossref Search ADS PubMed WorldCat Despres J , Forano E, Lepercq P et al. Unraveling the pectinolytic function of Bacteroides xylanisolvens using a RNA-seq approach and mutagenesis . BMC Genomics . 2016a ; 17 : 147 . Google Scholar Crossref Search ADS WorldCat Despres J , Forano E, Lepercq P et al. Xylan degradation by the human gut Bacteroides xylanisolvens XB1AT involves two distinct gene clusters that are linked at the transcriptional level . BMC Genomics . 2016b ; 17 : 326 . Google Scholar Crossref Search ADS WorldCat Dethlefsen L , Huse S, Sogin ML et al. The Pervasive Effects of an Antibiotic on the Human Gut Microbiota, as Revealed by Deep 16S rRNA Sequencing . PLoS Biol . 2008 ; 6 : e280 . Google Scholar Crossref Search ADS PubMed WorldCat De Vadder F , Kovatcheva-Datchary P, Zitoun C et al. Microbiota-Produced Succinate Improves Glucose Homeostasis via Intestinal Gluconeogenesis . Cell Metab . 2016 ; 24 : 151 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Devkota S , Wang Y, Musch MW et al. Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10−/− mice . Nature . 2012 ; 487 : 104 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat De Weirdt R , Van de Wiele T. Micromanagement in the gut: microenvironmental factors govern colon mucosal biofilm structure and functionality . npj Biofilms Microbiomes . 2015 ; 1 : 15026 . Google Scholar Crossref Search ADS PubMed WorldCat Dhingra D , Michael M, Rajput H et al. Dietary fibre in foods: a review . J Food Sci Technol . 2012 ; 49 : 255 – 66 . Google Scholar Crossref Search ADS PubMed WorldCat Diez-Gonzalez F , Callaway TR, Kizoulis MG et al. Grain feeding and the dissemination of acid-resistant Escherichia coli from cattle . Science . 1998 ; 281 : 1666 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Di R , Vakkalanka MS, Onumpai C et al. Pectic oligosaccharide structure-function relationships: Prebiotics, inhibitors of Escherichia coli O157:H7 adhesion and reduction of Shiga toxin cytotoxicity in HT29 cells . Food Chem . 2017 ; 227 : 245 – 54 . Google Scholar Crossref Search ADS PubMed WorldCat Donaldson GP , Lee SM, Mazmanian SK. Gut biogeography of the bacterial microbiota . Nat Rev Microbiol . 2016 ; 14 : 20 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat Donohoe DR , Collins LB, Wali A et al. The Warburg Effect Dictates the Mechanism of Butyrate-Mediated Histone Acetylation and Cell Proliferation . Mol Cell . 2012 ; 48 : 612 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Doorduyn Y , Van Den Brandhof WE, Van Duynhoven Y et al. Risk factors for Salmonella Enteritidis and Typhimurium (DT104 and non-DT104) infections in The Netherlands: predominant roles for raw eggs in Enteritidis and sandboxes in Typhimurium infections . Epidemiol Infect . 2006 ; 134 : 617 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat Dotz V , Wuhrer M. Histo-blood group glycans in the context of personalized medicine . Biochimica et Biophysica Acta (BBA) - General Subjects . 2016 ; 1860 : 1596 – 607 . Google Scholar Crossref Search ADS WorldCat Duncan SH , Louis P, Thomson JM et al. The role of pH in determining the species composition of the human colonic microbiota . Environ Microbiol . 2009 ; 11 : 2112 – 22 . Google Scholar Crossref Search ADS PubMed WorldCat Dutta PR , Cappello R, Navarro-García F et al. Functional Comparison of Serine Protease Autotransporters of Enterobacteriaceae . IAI . 2002 ; 70 : 7105 – 13 . Google Scholar Crossref Search ADS WorldCat Dwivedi R , Nothaft H, Garber J et al. L-fucose influences chemotaxis and biofilm formation in Campylobacter jejuni: L-fucose influence on C. jejuni . Mol Microbiol . 2016 ; 101 : 575 – 89 . Google Scholar Crossref Search ADS PubMed WorldCat Earle KA , Billings G, Sigal M et al. Quantitative Imaging of Gut Microbiota Spatial Organization . Cell Host & Microbe . 2015 ; 18 : 478 – 88 . Google Scholar Crossref Search ADS PubMed WorldCat EFSA Panel on Dietetic Products . Scientific Opinion on the substantiation of health claims related to dietary fibre (ID 744, 745, 746, 748, 749, 753, 803, 810, 855, 1415, 1416, 4308, 4330) pursuant to Article 13(1) of Regulation (EC) No 1924/2006 . EFSA Journal : 23 . OpenURL Placeholder Text WorldCat Egan M , Jiang H, O'Connell Motherway M et al. Glycosulfatase-Encoding Gene Cluster in Bifidobacterium breve UCC2003 . Appl Environ Microbiol . 2016 ; 82 : 6611 – 23 . Google Scholar Crossref Search ADS PubMed WorldCat Egan M , O'Connell Motherway M, Kilcoyne M et al. Cross-feeding by Bifidobacterium breve UCC2003 during co-cultivation with Bifidobacterium bifidum PRL2010 in a mucin-based medium . BMC Microbiol . 2014 ; 14 : 282 . Google Scholar Crossref Search ADS PubMed WorldCat Erdem AL , Avelino F, Xicohtencatl-Cortes J et al. Host Protein Binding and Adhesive Properties of H6 and H7 Flagella of Attaching and Effacing Escherichia coli . JB . 2007 ; 189 : 7426 – 35 . Google Scholar Crossref Search ADS WorldCat Etienne-Mesmin L , Chassaing B, Desvaux M et al. Experimental models to study intestinal microbes–mucus interactions in health and disease . FEMS Microbiol Rev . 2019 ; 43 : 457 – 89 . Google Scholar Crossref Search ADS PubMed WorldCat Etienne-Mesmin L , Livrelli V, Privat M et al. Effect of a New Probiotic Saccharomyces cerevisiae Strain on Survival of Escherichia coli O157:H7 in a Dynamic Gastrointestinal Model . Appl Environ Microbiol . 2011 ; 77 : 1127 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Etzold S , MacKenzie DA, Jeffers F et al. Structural and molecular insights into novel surface-exposed mucus adhesins from Lactobacillus reuteri human strains: A novel mucus adhesin from Lactobacillus reuteri . Mol Microbiol . 2014 ; 92 : 543 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Everard A , Belzer C, Geurts L et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity . Proc Natl Acad Sci . 2013 ; 110 : 9066 – 71 . Google Scholar Crossref Search ADS PubMed WorldCat Fabich AJ , Jones SA, Chowdhury FZ et al. Comparison of Carbon Nutrition for Pathogenic and Commensal Escherichia coli Strains in the Mouse Intestine . IAI . 2008 ; 76 : 1143 – 52 . Google Scholar Crossref Search ADS WorldCat Falony G , Vlachou A, Verbrugghe K et al. Cross-Feeding between Bifidobacterium longum BB536 and Acetate-Converting, Butyrate-Producing Colon Bacteria during Growth on Oligofructose . AEM . 2006 ; 72 : 7835 – 41 . Google Scholar Crossref Search ADS WorldCat Fechner A , Kiehntopf M, Jahreis G. The Formation of Short-Chain Fatty Acids Is Positively Associated with the Blood Lipid–Lowering Effect of Lupin Kernel Fiber in Moderately Hypercholesterolemic Adults . J Nutr . 2014 ; 144 : 599 – 607 . Google Scholar Crossref Search ADS PubMed WorldCat Ferreira RBR , Willing BP, Finlay BB. Bringing Koch's Postulates to the Table in IBD . Cell Host & Microbe . 2011 ; 9 : 353 – 4 . Google Scholar Crossref Search ADS PubMed WorldCat Ferreyra JA , Wu KJ, Hryckowian AJ et al. Gut Microbiota-Produced Succinate Promotes C. difficile Infection after Antibiotic Treatment or Motility Disturbance . Cell Host & Microbe . 2014 ; 16 : 770 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Ficko-Blean E , Boraston AB. Insights into the recognition of the human glycome by microbial carbohydrate-binding modules . Curr Opin Struct Biol . 2012 ; 22 : 570 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Fooks LJ , Gibson GR. Mixed culture fermentation studies on the effects of synbiotics on the human intestinal pathogens Campylobacter jejuni and Escherichia coli . Anaerobe . 2003 ; 9 : 231 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Fuentes-Zaragoza E , Riquelme-Navarrete MJ, Sánchez-Zapata E et al. Resistant starch as functional ingredient: A review . Food Res Int . 2010 ; 43 : 931 – 42 . Google Scholar Crossref Search ADS WorldCat Fukuda S , Toh H, Hase K et al. Bifidobacteria can protect from enteropathogenic infection through production of acetate . Nature . 2011 ; 469 : 543 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Fuller S , Beck E, Salman H et al. New Horizons for the Study of Dietary Fiber and Health: A Review . Plant Foods Hum Nutr . 2016 ; 71 : 1 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Gagnon M , Zihler Berner A, Chervet N et al. Comparison of the Caco-2, HT-29 and the mucus-secreting HT29-MTX intestinal cell models to investigate Salmonella adhesion and invasion . J Microbiol Methods . 2013 ; 94 : 274 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Galvez J , Rodríguez-Cabezas ME, Zarzuelo A. Effects of dietary fiber on inflammatory bowel disease . Mol Nutr Food Res . 2005 ; 49 : 601 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Ganner A , Schatzmayr G. Capability of yeast derivatives to adhere enteropathogenic bacteria and to modulate cells of the innate immune system . Appl Microbiol Biotechnol . 2012 ; 95 : 289 – 97 . Google Scholar Crossref Search ADS PubMed WorldCat Garrett WS , Gallini CA, Yatsunenko T et al. Enterobacteriaceae Act in Concert with the Gut Microbiota to Induce Spontaneous and Maternally Transmitted Colitis . Cell Host & Microbe . 2010 ; 8 : 292 – 300 . Google Scholar Crossref Search ADS PubMed WorldCat Garrido-Maestu A , Ma Z, Paik S-Y-R et al. Engineering of chitosan-derived nanoparticles to enhance antimicrobial activity against foodborne pathogen Escherichia coli O157:H7 . Carbohydr Polym . 2018 ; 197 : 623 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Garrido D , Kim JH, German JB et al. Oligosaccharide Binding Proteins from Bifidobacterium longum subsp. infantis Reveal a Preference for Host Glycans . PLoS One . 2011 ; 6 : e17315 . Google Scholar Crossref Search ADS PubMed WorldCat Gevers D , Kugathasan S, Denson LA et al. The Treatment-Naive Microbiome in New-Onset Crohn’s Disease . Cell Host & Microbe . 2014 ; 15 : 382 – 92 . Google Scholar Crossref Search ADS PubMed WorldCat Ghosh S , Dai C, Brown K et al. Colonic microbiota alters host susceptibility to infectious colitis by modulating inflammation, redox status, and ion transporter gene expression . Am J Physiol-Gastro Liver Physiol . 2011 ; 301 : G39 – 49 . Google Scholar Crossref Search ADS WorldCat Giannoukos S , Agapiou A, Brkić B et al. Volatolomics: A broad area of experimentation . J Chromatogr B . 2019 ; 1105 : 136 – 47 . Google Scholar Crossref Search ADS WorldCat Gibold L , Garenaux E, Dalmasso G et al. The Vat-AIEC protease promotes crossing of the intestinal mucus layer by Crohn's disease-associated Escherichia coli: Vat-AIEC Favours Mucus Layer's Crossing by LF82 E. coli . Cell Microbiol . 2016 ; 18 : 617 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Gibson GR , Cummings JH, Macfarlane GT. Use of a three-stage continuous culture system to study the effect of mucin on dissimilatory sulfate reduction and methanogenesis by mixed populations of human gut bacteria . Appl Environ Microbiol . 1988 ; 54 : 2750 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Gilbert RA , Denman SE, Padmanabha J et al. Effect of diet on the concentration of complex Shiga toxin-producing Escherichia coli and EHEC virulence genes in bovine faeces, hide and carcass . Int J Food Microbiol . 2008 ; 121 : 208 – 16 . Google Scholar Crossref Search ADS PubMed WorldCat Gong J , Yang C. Advances in the methods for studying gut microbiota and their relevance to the research of dietary fiber functions . Food Res Int . 2012 ; 48 : 916 – 29 . Google Scholar Crossref Search ADS WorldCat González-Ortiz G , Hermes RG, Jiménez-Díaz R et al. Screening of extracts from natural feed ingredients for their ability to reduce enterotoxigenic Escherichia coli (ETEC) K88 adhesion to porcine intestinal epithelial cell-line IPEC-J2 . Vet Microbiol . 2013 ; 167 : 494 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat González-Ortiz G , Pérez JF, Hermes RG et al. Screening the ability of natural feed ingredients to interfere with the adherence of enterotoxigenic Escherichia coli (ETEC) K88 to the porcine intestinal mucus . Br J Nutr . 2014 ; 111 : 633 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Gophna U , Sommerfeld K, Gophna S et al. Differences between Tissue-Associated Intestinal Microfloras of Patients with Crohn's Disease and Ulcerative Colitis . J Clin Microbiol . 2006 ; 44 : 4136 – 41 . Google Scholar Crossref Search ADS PubMed WorldCat Grahn N , Hmani-Aifa M, Fransén K et al. Molecular identification of Helicobacter DNA present in human colorectal adenocarcinomas by 16S rDNA PCR amplification and pyrosequencing analysis . J Med Microbiol . 2005 ; 54 : 1031 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Graziani F , Pujol A, Nicoletti C et al. Ruminococcus gnavus E1 modulates mucin expression and intestinal glycosylation . J Appl Microbiol . 2016 ; 120 : 1403 – 17 . Google Scholar Crossref Search ADS PubMed WorldCat Greenhalgh K , Ramiro-Garcia J, Heinken A et al. Integrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells . Cell Rep . 2019 ; 27 : 1621 – 32 ..e9. Google Scholar Crossref Search ADS PubMed WorldCat Grondin JM , Tamura K, Déjean G et al. Polysaccharide Utilization Loci: Fueling Microbial Communities . J Bacteriol . 2017 ; 199 : e00860 – 16 ., e00860-16 . Google Scholar Crossref Search ADS PubMed WorldCat Grys TE , Siegel MB, Lathem WW et al. The StcE Protease Contributes to Intimate Adherence of Enterohemorrhagic Escherichia coli O157:H7 to Host Cells . IAI . 2005 ; 73 : 1295 – 303 . Google Scholar Crossref Search ADS WorldCat Guerra-Ordaz AA , González-Ortiz G, La Ragione RM et al. Lactulose and Lactobacillus plantarum, a Potential Complementary Synbiotic To Control Postweaning Colibacillosis in Piglets . Appl Environ Microbiol . 2014 ; 80 : 4879 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Guerra A , Etienne-Mesmin L, Livrelli V et al. Relevance and challenges in modeling human gastric and small intestinal digestion . Trends Biotechnol . 2012 ; 30 : 591 – 600 . Google Scholar Crossref Search ADS PubMed WorldCat Halas D , Hansen CF, Hampson DJ et al. Effect of dietary supplementation with inulin and/or benzoic acid on the incidence and severity of post-weaning diarrhoea in weaner pigs after experimental challenge with enterotoxigenic Escherichia coli . Arch Anim Nutr . 2009 ; 63 : 267 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Hall AB , Yassour M, Sauk J et al. A novel Ruminococcus gnavus clade enriched in inflammatory bowel disease patients . Genome Med . 2017 ; 9 : 103 . Google Scholar Crossref Search ADS PubMed WorldCat Hamaker BR , Tuncil YE. A Perspective on the Complexity of Dietary Fiber Structures and Their Potential Effect on the Gut Microbiota . J Mol Biol . 2014 ; 426 : 3838 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Hansson GC. Role of mucus layers in gut infection and inflammation . Curr Opin Microbiol . 2012 ; 15 : 57 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Hata DJ , Smith DS. Blood Group B Degrading Activity of Ruminococcus gnavus α-Galactosidase . Artificial Cells, Blood Substitutes, and Biotechnology . 2004 ; 32 : 263 – 74 . Google Scholar Crossref Search ADS WorldCat Hayden UL , McGuirk SM, West SE et al. Psyllium improves fecal consistency and prevents enhanced secretory responses in jejunal tissues of piglets infected with ETEC . Dig Dis Sci . 1998 ; 43 : 2536 – 41 . Google Scholar Crossref Search ADS PubMed WorldCat Hecht AL , Casterline BW, Choi VM et al. A Two-Component System Regulates Bacteroides fragilis Toxin to Maintain Intestinal Homeostasis and Prevent Lethal Disease . Cell Host & Microbe . 2017 ; 22 : 443 – 8 ..e5. Google Scholar Crossref Search ADS PubMed WorldCat Hedblom GA , Reiland HA, Sylte MJ et al. Segmented Filamentous Bacteria – Metabolism Meets Immunity . Front Microbiol . 2018 ; 9 : 1991 . Google Scholar Crossref Search ADS PubMed WorldCat Hehemann J-H , Correc G, Barbeyron T et al. Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota . Nature . 2010 ; 464 : 908 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Hehemann J-H , Kelly AG, Pudlo NA et al. Bacteria of the human gut microbiome catabolize red seaweed glycans with carbohydrate-active enzyme updates from extrinsic microbes . Proc Natl Acad Sci . 2012 ; 109 : 19786 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat Heikema AP , Bergman MP, Richards H et al. Characterization of the Specific Interaction between Sialoadhesin and Sialylated Campylobacter jejuni Lipooligosaccharides . IAI . 2010 ; 78 : 3237 – 46 . Google Scholar Crossref Search ADS WorldCat Hernot DC , Boileau TW, Bauer LL et al. In Vitro Digestion Characteristics of Unprocessed and Processed Whole Grains and Their Components . J Agric Food Chem . 2008 ; 56 : 10721 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Hews CL , Tran S-L, Wegmann U et al. The StcE metalloprotease of enterohaemorrhagic Escherichia coli reduces the inner mucus layer and promotes adherence to human colonic epithelium ex vivo . Cell Microbiol . 2017 ; 19 : e12717 . Google Scholar Crossref Search ADS WorldCat Holmén Larsson JM , Karlsson H, Sjövall H et al. A complex, but uniform O-glycosylation of the human MUC2 mucin from colonic biopsies analyzed by nanoLC/MSn . Glycobiology . 2009 ; 19 : 756 – 66 . Google Scholar Crossref Search ADS PubMed WorldCat Holscher HD. Dietary fiber and prebiotics and the gastrointestinal microbiota . Gut Microbes . 2017 ; 8 : 172 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Hoyer LL , Hamilton AC, Steenbergen SM et al. Cloning, sequencing and distribution of the Salmonella typhimurium LT2 siaiidase gene, nanH, provides evidence for interspecies gene transfer . Mol Microbiol . 1992 ; 6 : 873 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Hugenholtz F , de Vos WM. Mouse models for human intestinal microbiota research: a critical evaluation . Cell Mol Life Sci . 2018 ; 75 : 149 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Hughes RL , Marco ML, Hughes JP et al. The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models-Part I: Overview of Current Methods . Adv Nutr . 2019 ; 10 : 953 – 78 . Google Scholar Crossref Search ADS PubMed WorldCat Hughes SA , Shewry PR, Gibson GR et al. In vitro fermentation of oat and barley derived β-glucans by human faecal microbiota . FEMS Microbiol Ecol . 2008 ; 64 ; 482 – 93 . Google Scholar Crossref Search ADS PubMed WorldCat Hunt DE , Gevers D, Vahora NM et al. Conservation of the Chitin Utilization Pathway in the Vibrionaceae . AEM . 2008 ; 74 : 44 – 51 . Google Scholar Crossref Search ADS WorldCat Huq A , Small EB, West PA et al. Ecological relationships between Vibrio cholerae and planktonic crustacean copepods . Appl Environ Microbiol . 1983 ; 45 : 275 – 83 . Google Scholar Crossref Search ADS PubMed WorldCat Hylla S , Gostner A, Dusel G et al. Effects of resistant starch on the colon in healthy volunteers: possible implications for cancer prevention . Am J Clin Nutr . 1998 ; 67 : 136 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Idota T , Kawakami H, Murakami Y et al. Inhibition of Cholera Toxin by Human Milk Fractions and Sialyllactose . Biosci Biotechnol Biochem . 1995 ; 59 : 417 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Idota T , Kawakami H. Inhibitory Effects of Milk Gangliosides on the Adhesion of Escherichia coli to Human Intestinal Carcinoma Cells . Biosci Biotechnol Biochem . 1995 ; 59 : 69 – 72 . Google Scholar Crossref Search ADS PubMed WorldCat Ijssennagger N , van der Meer R, van Mil SWC. Sulfide as a Mucus Barrier-Breaker in Inflammatory Bowel Disease? Trends Mol Med . 2016 ; 22 : 190 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Jalili-Firoozinezhad S , Gazzaniga FS, Calamari EL et al. A complex human gut microbiome cultured in an anaerobic intestine-on-a-chip . Nat Biomed Eng . 2019 ; 3 : 520 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Janoir C , Péchiné S, Grosdidier C et al. Cwp84, a Surface-Associated Protein of Clostridium difficile, Is a Cysteine Protease with Degrading Activity on Extracellular Matrix Proteins . JB . 2007 ; 189 : 7174 – 80 . Google Scholar Crossref Search ADS WorldCat Janssen AWF , Kersten S. The role of the gut microbiota in metabolic health . FASEB J . 2015 ; 29 : 3111 – 23 . Google Scholar Crossref Search ADS PubMed WorldCat Jazi V , Mohebodini H, Ashayerizadeh A et al. Fermented soybean meal ameliorates Salmonella Typhimurium infection in young broiler chickens . Poult Sci . 2019 ; 98 : 5648 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Jeong KC , Kang MY, Kang J et al. Reduction of Escherichia coli O157:H7 Shedding in Cattle by Addition of Chitosan Microparticles to Feed . Appl Environ Microbiol . 2011 ; 77 : 2611 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Jeon SJ , Ma Z, Kang M et al. Application of chitosan microparticles for treatment of metritis and in vivo evaluation of broad spectrum antimicrobial activity in cow uteri . Biomaterials . 2016 ; 110 : 71 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Jeon SJ , Oh M, Yeo W-S et al. Underlying Mechanism of Antimicrobial Activity of Chitosan Microparticles and Implications for the Treatment of Infectious Diseases . PLoS One . 2014 ; 9 : e92723 . Google Scholar Crossref Search ADS PubMed WorldCat Johansson MEV , Hansson GC. Immunological aspects of intestinal mucus and mucins . Nat Rev Immunol . 2016 ; 16 : 639 – 49 . Google Scholar Crossref Search ADS PubMed WorldCat Johansson MEV , Sjövall H, Hansson GC. The gastrointestinal mucus system in health and disease . Nat Rev Gastroenterol Hepatol . 2013 ; 10 : 352 – 61 . Google Scholar Crossref Search ADS PubMed WorldCat Johansson MEV. Fast Renewal of the Distal Colonic Mucus Layers by the Surface Goblet Cells as Measured by In Vivo Labeling of Mucin Glycoproteins . PLoS One . 2012 ; 7 : e41009 . Google Scholar Crossref Search ADS PubMed WorldCat Jones JM. CODEX-aligned dietary fiber definitions help to bridge the ‘fiber gap .’ Nutr J . 2014 ; 13 : 34 . Google Scholar Crossref Search ADS PubMed WorldCat Juge N . Microbial adhesins to gastrointestinal mucus . Trends Microbiol . 2012 ; 20 : 30 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Kakodkar S , Mutlu EA. Diet as a Therapeutic Option for Adult Inflammatory Bowel Disease . Gastroenterol Clin North Am . 2017 ; 46 : 745 – 67 . Google Scholar Crossref Search ADS PubMed WorldCat Kamada N , Chen GY, Inohara N et al. Control of pathogens and pathobionts by the gut microbiota . Nat Immunol . 2013 ; 14 : 685 – 90 . Google Scholar Crossref Search ADS PubMed WorldCat Kaoutari AE , Armougom F, Gordon JI et al. The abundance and variety of carbohydrate-active enzymes in the human gut microbiota . Nat Rev Microbiol . 2013 ; 11 : 497 – 504 . Google Scholar Crossref Search ADS PubMed WorldCat Kaoutari AE , Armougom F, Raoult D et al. Le microbiote intestinal et la digestion des polysaccharides . Med Sci (Paris) . 2014 ; 30 : 259 – 65 . Google Scholar Crossref Search ADS PubMed WorldCat Kaser A , Lee A-H, Franke A et al. XBP1 Links ER Stress to Intestinal Inflammation and Confers Genetic Risk for Human Inflammatory Bowel Disease . Cell . 2008 ; 134 : 743 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Kashyap PC , Marcobal A, Ursell LK et al. Genetically dictated change in host mucus carbohydrate landscape exerts a diet-dependent effect on the gut microbiota . Proc Natl Acad Sci . 2013 ; 110 : 17059 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Kelly CP , Pothoulakis C, LaMont JT. Clostridium difficile Colitis . N Engl J Med . 1994 ; 330 ; 257 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Kelly RJ , Rouquier S, Giorgi D et al. Sequence and Expression of a Candidate for the Human Secretor Blood Group α(1,2)Fucosyltransferase Gene (FUT2) . J Biol Chem . 1995 ; 270 : 4640 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Kenny DT , Skoog EC, Lindén SK et al. Presence of terminal N-acetylgalactosamineβ1-4N-acetylglucosamine residues on O-linked oligosaccharides from gastric MUC5AC: Involvement in Helicobacter pylori colonization? Glycobiology . 2012 ; 22 : 1077 – 85 . Google Scholar Crossref Search ADS PubMed WorldCat Kim CC , Healey GR, Kelly WJ et al. Genomic insights from Monoglobus pectinilyticus: a pectin-degrading specialist bacterium in the human colon . ISME J . 2019 ; 13 : 1437 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Kimura I , Ozawa K, Inoue D et al. The gut microbiota suppresses insulin-mediated fat accumulation via the short-chain fatty acid receptor GPR43 . Nat Commun . 2013 ; 4 : 1829 . Google Scholar Crossref Search ADS PubMed WorldCat Kim Y , oh S, Kim SH. Released exopolysaccharide (r-EPS) produced from probiotic bacteria reduce biofilm formation of enterohemorrhagic Escherichia coli O157:H7 . Biochem Biophys Res Commun . 2009 ; 379 : 324 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat King DE , Mainous AG, Lambourne CA. Trends in Dietary Fiber Intake in the United States, 1999–2008 . J Acad Nutrition Dietetics . 2012 ; 112 : 642 – 8 . Google Scholar Crossref Search ADS WorldCat Kirk RGW . “Life in a Germ-Free World”: Isolating Life from the Laboratory Animal to the Bubble Boy . Bull Hist Med . 2012 ; 86 : 237 – 75 . Google Scholar Crossref Search ADS PubMed WorldCat Kirn TJ , Jude BA, Taylor RK. A colonization factor links Vibrio cholerae environmental survival and human infection . Nature . 2005 ; 438 : 863 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Kitahara M , Sakamoto M, Ike M et al. Bacteroides plebeius sp. nov. and Bacteroides coprocola sp. nov., isolated from human faeces . Int J Syst Evol Microbiol . 2005 ; 55 : 2143 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Knudsen KEB , Wisker E, Daniel M et al. Digestibility of energy, protein, fat and non-starch polysaccharides in mixed diets: Comparative studies between man and the rat . Br J Nutr . 1994 ; 71 : 471 – 87 . Google Scholar Crossref Search ADS PubMed WorldCat Koropatkin NM , Cameron EA, Martens EC. How glycan metabolism shapes the human gut microbiota . Nat Rev Microbiol . 2012 ; 10 : 323 – 35 . Google Scholar Crossref Search ADS PubMed WorldCat Kostic AD , Chun E, Robertson L et al. Fusobacterium nucleatum Potentiates Intestinal Tumorigenesis and Modulates the Tumor-Immune Microenvironment . Cell Host & Microbe . 2013 ; 14 : 207 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Kotloff KL . The Burden and Etiology of Diarrheal Illness in Developing Countries . Pediatr Clin North Am . 2017 ; 64 : 799 – 814 . Google Scholar Crossref Search ADS PubMed WorldCat Kościelak J. The Hypothesis on Function of Glycosphingolipids and ABO Blood Groups Revisited . Neurochem Res . 2012 ; 37 : 1170 – 84 . Google Scholar Crossref Search ADS PubMed WorldCat Krishnan S , Eslick GD. Streptococcus bovis infection and colorectal neoplasia: a meta-analysis . Colorectal Dis . 2014 ; 16 : 672 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Kuda T , Hirano S, Yokota Y et al. Effect of depolymerized sodium alginate on Salmonella Typhimurium infection in human enterocyte-like HT-29-Luc cells and BALB/c mice . J Funct Foods . 2017 ; 28 : 122 – 6 . Google Scholar Crossref Search ADS WorldCat Kudva IT , Hunt CW, Williams CJ et al. Evaluation of dietary influences on Escherichia coli O157:H7 shedding by sheep . Appl Environ Microbiol . 1997 ; 63 : 3878 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Kumar P , Luo Q, Vickers TJ et al. EatA, an Immunogenic Protective Antigen of Enterotoxigenic Escherichia coli, Degrades Intestinal Mucin . Infect Immun . 2014 ; 82 : 500 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Kunz C , Rudloff S, Baier W et al. OLIGOSACCHARIDES IN HUMAN MILK : Structural, Functional, and Metabolic Aspects . Annu Rev Nutr . 2000 ; 20 : 699 – 722 . Google Scholar Crossref Search ADS PubMed WorldCat Ladinsky MS , Araujo LP, Zhang X et al. Endocytosis of commensal antigens by intestinal epithelial cells regulates mucosal T cell homeostasis . Science . 2019 ; 363 : eaat4042 . Google Scholar Crossref Search ADS PubMed WorldCat Lamichhane S , Yde CC, Forssten S et al. Impact of Dietary Polydextrose Fiber on the Human Gut Metabolome . J Agric Food Chem . 2014 ; 62 : 9944 – 51 . Google Scholar Crossref Search ADS PubMed WorldCat La Rosa SL , Leth ML, Michalak L et al. The human gut Firmicute Roseburia intestinalis is a primary degrader of dietary β-mannans . Nat Commun . 2019 ; 10 : 905 . Google Scholar Crossref Search ADS PubMed WorldCat Larsbrink J , Rogers TE, Hemsworth GR et al. A discrete genetic locus confers xyloglucan metabolism in select human gut Bacteroidetes . Nature . 2014 ; 506 : 498 – 502 . Google Scholar Crossref Search ADS PubMed WorldCat Lathem WW , Grys TE, Witowski SE et al. StcE, a metalloprotease secreted by Escherichia coli O157:H7, specifically cleaves C1 esterase inhibitor . Mol Microbiol . 2002 ; 45 : 277 – 88 . Google Scholar Crossref Search ADS PubMed WorldCat Lavelle A , Sokol H. Gut microbiota-derived metabolites as key actors in inflammatory bowel disease . Nat Rev Gastroenterol Hepatol . 2020 ; 17 : 223 – 37 . Google Scholar Crossref Search ADS PubMed WorldCat Lawhon SD , Maurer R, Suyemoto M et al. Intestinal short-chain fatty acids alter Salmonella typhimurium invasion gene expression and virulence through BarA/SirA: Short-chain fatty acids and Salmonella invasion . Mol Microbiol . 2002 ; 46 : 1451 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Leatham MP , Banerjee S, Autieri SM et al. Precolonized Human Commensal Escherichia coli Strains Serve as a Barrier to E. coli O157:H7 Growth in the Streptomycin-Treated Mouse Intestine . IAI . 2009 ; 77 : 2876 – 86 . Google Scholar Crossref Search ADS WorldCat Le Bihan G , Sicard J-F, Garneau P et al. The NAG Sensor NagC Regulates LEE Gene Expression and Contributes to Gut Colonization by Escherichia coli O157:H7 . Front Cell Infect Microbiol . 2017 ; 7 : 134 . Google Scholar Crossref Search ADS PubMed WorldCat Lee H , Ko G. Effect of Metformin on Metabolic Improvement and Gut Microbiota . Appl Environ Microbiol . 2014 ; 80 : 5935 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Lee SM , Donaldson GP, Mikulski Z et al. Bacterial colonization factors control specificity and stability of the gut microbiota . Nature . 2013 ; 501 : 426 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Leitch ECM , Walker AW, Duncan SH et al. Selective colonization of insoluble substrates by human faecal bacteria . Environ Microbiol . 2007 ; 9 : 667 – 79 . Google Scholar Crossref Search ADS PubMed WorldCat Lema M , Williams L, Walker L et al. Effect of dietary fiber on E. coli O157:H7 shedding in lambs . Small Ruminant Research . 2002 : 7 . Google Scholar OpenURL Placeholder Text WorldCat Leocádio PCL , Oriá RB, Crespo-Lopez ME et al. Obesity: More Than an Inflammatory, an Infectious Disease? Front Immunol . 2020 ; 10 : 3092 . Google Scholar Crossref Search ADS PubMed WorldCat Leong A , Liu Z, Almshawit H et al. Oligosaccharides in goats’ milk-based infant formula and their prebiotic and anti-infection properties . Br J Nutr . 2019 ; 122 : 441 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Lesmes U , Beards EJ, Gibson GR et al. Effects of Resistant Starch Type III Polymorphs on Human Colon Microbiota and Short Chain Fatty Acids in Human Gut Models . J Agric Food Chem . 2008 ; 56 : 5415 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Leyton DL , Sloan J, Hill RE et al. Transfer Region of pO113 from Enterohemorrhagic Escherichia coli: Similarity with R64 and Identification of a Novel Plasmid-Encoded Autotransporter, EpeA . IAI . 2003 ; 71 : 6307 – 19 . Google Scholar Crossref Search ADS WorldCat Li H , Limenitakis JP, Fuhrer T et al. The outer mucus layer hosts a distinct intestinal microbial niche . Nat Commun . 2015 ; 6 : 8292 . Google Scholar Crossref Search ADS PubMed WorldCat Liou AP , Paziuk M, Luevano J-M et al. Conserved Shifts in the Gut Microbiota Due to Gastric Bypass Reduce Host Weight and Adiposity . Sci Transl Med . 2013 ; 5 : 178ra41 . Google Scholar Crossref Search ADS PubMed WorldCat Liu G , Chen S, Guan G et al. Chitosan Modulates Inflammatory Responses in Rats Infected with Enterotoxigenic Escherichia coli . Mediators Inflamm . 2016 ; 2016 : 1 – 6 . Google Scholar OpenURL Placeholder Text WorldCat Liu XF , Guan YL, Yang DZ et al. Antibacterial action of chitosan and carboxymethylated chitosan . J Appl Polym Sci . 2000 ; 79 : 1324 – 35 . Google Scholar OpenURL Placeholder Text WorldCat Liu Z , Wang Y, Liu S et al. Vibrio cholerae Represses Polysaccharide Synthesis To Promote Motility in Mucosa . Infect Immun . 2015 ; 83 : 1114 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Liu Z , Zhang Z, Qiu L et al. Characterization and bioactivities of the exopolysaccharide from a probiotic strain of Lactobacillus plantarum WLPL04 . J Dairy Sci . 2017 ; 100 : 6895 – 905 . Google Scholar Crossref Search ADS PubMed WorldCat Lozupone CA , Stombaugh JI, Gordon JI et al. Diversity, stability and resilience of the human gut microbiota . Nature . 2012 ; 489 : 220 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Lucas A , Cole TJ. Breast milk and neonatal necrotising enterocolitis . Lancet North Am Ed . 1990 ; 336 : 1519 – 23 . Google Scholar Crossref Search ADS WorldCat Lucas C , Barnich N, Nguyen H. Microbiota, Inflammation and Colorectal Cancer . IJMS . 2017 ; 18 : 1310 . Google Scholar Crossref Search ADS WorldCat Luo Q , Kumar P, Vickers TJ et al. Enterotoxigenic Escherichia coli Secretes a Highly Conserved Mucin-Degrading Metalloprotease To Effectively Engage Intestinal Epithelial Cells . Infect Immun . 2014 ; 82 : 509 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Lupp C , Robertson ML, Wickham ME et al. Host-Mediated Inflammation Disrupts the Intestinal Microbiota and Promotes the Overgrowth of Enterobacteriaceae . Cell Host & Microbe . 2007 ; 2 : 119 – 29 . Google Scholar Crossref Search ADS PubMed WorldCat Machiels K , Joossens M, Sabino J et al. A decrease of the butyrate-producing species Roseburia hominis and Faecalibacterium prausnitzii defines dysbiosis in patients with ulcerative colitis . Gut . 2014 ; 63 : 1275 – 83 . Google Scholar Crossref Search ADS PubMed WorldCat Macia L , Tan J, Vieira AT et al. Metabolite-sensing receptors GPR43 and GPR109A facilitate dietary fibre-induced gut homeostasis through regulation of the inflammasome . Nat Commun . 2015 ; 6 : 6734 . Google Scholar Crossref Search ADS PubMed WorldCat Magalhães A , Marcos-Pinto R, Nairn AV et al. Helicobacter pylori chronic infection and mucosal inflammation switches the human gastric glycosylation pathways . Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease . 2015 ; 1852 : 1928 – 39 . Google Scholar Crossref Search ADS WorldCat Magalhães A , Marcos-Pinto R, Nairn AV et al. Helicobacter pylori chronic infection and mucosal inflammation switches the human gastric glycosylation pathways . Biochim Biophys Acta Mol Basis Dis . 2015 ; 1852 : 1928 – 39 . Google Scholar Crossref Search ADS WorldCat Mahdavi J. Helicobacter pylori SabA Adhesin in Persistent Infection and Chronic Inflammation . Science . 2002 ; 297 : 573 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Makki K , Deehan EC, Walter J et al. The Impact of Dietary Fiber on Gut Microbiota in Host Health and Disease . Cell Host & Microbe . 2018 ; 23 : 705 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Mantle M , Rombough C. Growth in and breakdown of purified rabbit small intestinal mucin by Yersinia enterocolitica . Infect Immun . 1993 ; 61 : 4131 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Marcobal A , Southwick AM, Earle KA et al. A refined palate: Bacterial consumption of host glycans in the gut . Glycobiology . 2013 ; 23 : 1038 – 46 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Chiang HC, Gordon JI. Mucosal Glycan Foraging Enhances Fitness and Transmission of a Saccharolytic Human Gut Bacterial Symbiont . Cell Host & Microbe . 2008 ; 4 : 447 – 57 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Koropatkin NM, Smith TJ et al. Complex Glycan Catabolism by the Human Gut Microbiota: The Bacteroidetes Sus-like Paradigm . J Biol Chem . 2009 ; 284 : 24673 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Lowe EC, Chiang H et al. Recognition and Degradation of Plant Cell Wall Polysaccharides by Two Human Gut Symbionts . PLoS Biol . 2011 ; 9 : e1001221 . Google Scholar Crossref Search ADS PubMed WorldCat Martens EC , Neumann M, Desai MS. Interactions of commensal and pathogenic microorganisms with the intestinal mucosal barrier . Nat Rev Microbiol . 2018 ; 16 : 457 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Martin HM , Campbell BJ, Hart CA et al. Enhanced Escherichia coli adherence and invasion in Crohn's disease and colon cancer . Gastroenterology . 2004 ; 127 : 80 – 93 . Google Scholar Crossref Search ADS PubMed WorldCat Martínez I , Kim J, Duffy PR et al. Resistant Starches Types 2 and 4 Have Differential Effects on the Composition of the Fecal Microbiota in Human Subjects . PLoS One . 2010 ; 5 : e15046 . Google Scholar Crossref Search ADS PubMed WorldCat Martínez I , Stegen JC, Maldonado-Gómez MX et al. The Gut Microbiota of Rural Papua New Guineans: Composition, Diversity Patterns, and Ecological Processes . Cell Rep . 2015 ; 11 : 527 – 38 . Google Scholar Crossref Search ADS PubMed WorldCat Marzorati M , Vanhoecke B, De Ryck T et al. The HMITM module: a new tool to study the Host-Microbiota Interaction in the human gastrointestinal tract in vitro . BMC Microbiol . 2014 ; 14 : 133 . Google Scholar Crossref Search ADS PubMed WorldCat Ma Z , Kim D, Adesogan AT et al. Chitosan Microparticles Exert Broad-Spectrum Antimicrobial Activity against Antibiotic-Resistant Micro-organisms without Increasing Resistance . ACS Appl Mater Interfaces . 2016 ; 8 : 10700 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat McKenney PT , Pamer EG. From Hype to Hope: The Gut Microbiota in Enteric Infectious Disease . Cell . 2015 ; 163 : 1326 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat McRorie JW , McKeown NM. Understanding the Physics of Functional Fibers in the Gastrointestinal Tract: An Evidence-Based Approach to Resolving Enduring Misconceptions about Insoluble and Soluble Fiber . J Acad Nutrition and Dietetics . 2017 ; 117 : 251 – 64 . Google Scholar Crossref Search ADS WorldCat Mehta RS , Nishihara R, Cao Y et al. Association of Dietary Patterns With Risk of Colorectal Cancer Subtypes Classified by Fusobacterium nucleatum in Tumor Tissue . JAMA Oncol . 2017 ; 3 : 921 . Google Scholar Crossref Search ADS PubMed WorldCat Meibom KL , Li XB, Nielsen AT et al. The Vibrio cholerae chitin utilization program . Proc Natl Acad Sci . 2004 ; 101 : 2524 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Meinzen-Derr J , Poindexter B, Wraje L et al. Role of human milk in extremely low birth weight infants’ risk of necrotizing enterocolitis or death . J Perinatol . 2009 ; 29 : 57 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat Minekus M . The TNO Gastro-Intestinal Model (TIM) . In: Verhoeckx K, Cotter P, López-Expósito I et al. (eds). The Impact of Food Bioactives on Health . Cham : Springer International Publishing , 2015 , 37 – 46 . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Mirande C , Kadlecikova E, Matulova M et al. Dietary fibre degradation and fermentation by two xylanolytic bacteria Bacteroides xylanisolvens XB1A T and Roseburia intestinalis XB6B4 from the human intestine . J Appl Microbiol . 2010 ; 109 : 451 – 60 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Mirza NN , McCloud JM, Cheetham MJ. Clostridium septicum sepsis and colorectal cancer - a reminder . World J Surg Onc . 2009 ; 7 : 73 . Google Scholar Crossref Search ADS WorldCat Miszczycha SD , Thévenot J, Denis S et al. Survival of Escherichia coli O26:H11 exceeds that of Escherichia coli O157:H7 as assessed by simulated human digestion of contaminated raw milk cheeses . Int J Food Microbiol . 2014 ; 172 : 40 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Mohanan V , Nakata T, Desch AN et al. C1orf106 is a colitis risk gene that regulates stability of epithelial adherens junctions . Science . 2018 ; 359 : 1161 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Molly K , Vande Woestyne M, Verstraete W. Development of a 5-step multi-chamber reactor as a simulation of the human intestinal microbial ecosystem . Appl Microbiol Biotechnol . 1993 ; 39 : 254 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Mondal M , Nag D, Koley H et al. The Vibrio cholerae Extracellular Chitinase ChiA2 Is Important for Survival and Pathogenesis in the Host Intestine . PLoS One . 2014 ; 9 : e103119 . Google Scholar Crossref Search ADS PubMed WorldCat Moran AP , Gupta A, Joshi L. Sweet-talk: role of host glycosylation in bacterial pathogenesis of the gastrointestinal tract . Gut . 2011 ; 60 : 1412 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat Morgan XC , Tickle TL, Sokol H et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment . Genome Biol . 2012 ; 13 : R79 . Google Scholar Crossref Search ADS PubMed WorldCat Morrison DJ , Preston T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism . Gut Microbes . 2016 ; 7 : 189 – 200 . Google Scholar Crossref Search ADS PubMed WorldCat Myhrstad MCW , Tunsjø H, Charnock C et al. Dietary Fiber, Gut Microbiota, and Metabolic Regulation—Current Status in Human Randomized Trials . Nutrients . 2020 ; 12 : 859 . Google Scholar Crossref Search ADS WorldCat Mäkivuokko H , Lahtinen SJ, Wacklin P et al. Association between the ABO blood group and the human intestinal microbiota composition . BMC Microbiol . 2012 ; 12 : 94 . Google Scholar Crossref Search ADS PubMed WorldCat Ndeh D , Gilbert HJ. Biochemistry of complex glycan depolymerisation by the human gut microbiota . FEMS Microbiol Rev . 2018 ; 42 : 146 – 64 . Google Scholar Crossref Search ADS PubMed WorldCat Newburg DS , Pickering LK, McCluer RH et al. Fucosylated Oligosaccharides of Human Milk Protect Suckling Mice from Heat-Stabile Enterotoxin of Escherichia coli . J Infect Dis . 1990 ; 162 : 1075 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Newburg DS , Ruiz-Palacios GM, Morrow AL. Human Milk Glycans Protect Infants Against Enteric Pathogens . Annu Rev Nutr . 2005 ; 25 : 37 – 58 . Google Scholar Crossref Search ADS PubMed WorldCat Ng KM , Ferreyra JA, Higginbottom SK et al. Microbiota-liberated host sugars facilitate post-antibiotic expansion of enteric pathogens . Nature . 2013 ; 502 : 96 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Ninonuevo MR , Park Y, Yin H et al. A Strategy for Annotating the Human Milk Glycome . J Agric Food Chem . 2006 ; 54 : 7471 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Novaes RD , Sequetto PL, Vilela Gonçalves R et al. Depletion of enteroendocrine and mucus-secreting cells is associated with colorectal carcinogenesis severity and impaired intestinal motility in rats: CELLS AND COLORECTAL CARCINOGENESIS . Microsc Res Tech . 2016 ; 79 : 3 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Ocvirk S , Wilson AS, Appolonia CN et al. Fiber, Fat, and Colorectal Cancer: New Insight into Modifiable Dietary Risk Factors . Curr Gastroenterol Rep . 2019 ; 21 : 62 . Google Scholar Crossref Search ADS PubMed WorldCat Otnaess AB , Laegreid A, Ertresvåg K. Inhibition of enterotoxin from Escherichia coli and Vibrio cholerae by gangliosides from human milk . Infect Immun . 1983 ; 40 : 563 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Ouwerkerk JP , de Vos WM, Belzer C. Glycobiome: Bacteria and mucus at the epithelial interface . Best Practice & Research Clinical Gastroenterology . 2013 ; 27 : 25 – 38 . Google Scholar Crossref Search ADS PubMed WorldCat Owen CD , Tailford LE, Monaco S et al. Unravelling the specificity and mechanism of sialic acid recognition by the gut symbiont Ruminococcus gnavus . Nat Commun . 2017 ; 8 : 2196 . Google Scholar Crossref Search ADS PubMed WorldCat Pacheco AR , Curtis MM, Ritchie JM et al. Fucose sensing regulates bacterial intestinal colonization . Nature . 2012 ; 492 : 113 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Panek M , Čipčić Paljetak H, Barešić A et al. Methodology challenges in studying human gut microbiota - effects of collection, storage, DNA extraction and next generation sequencing technologies . Sci Rep . 2018 ; 8 : 5143 . Google Scholar Crossref Search ADS PubMed WorldCat Paton AW , Jennings MP, Morona R et al. Recombinant Probiotics for Treatment and Prevention of Enterotoxigenic Escherichia coli Diarrhea . Gastroenterology . 2005 ; 128 : 1219 – 28 . Google Scholar Crossref Search ADS PubMed WorldCat Paton AW , Morona R, Paton JC. A new biological agent for treatment of Shiga toxigenic Escherichia coli infections and dysentery in humans . Nat Med . 2000 ; 6 : 265 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat Pavia AT , Shipman LD, Wells JG et al. Epidemiologic Evidence that Prior Antimicrobial Exposure Decreases Resistance to Infection by Antimicrobial-Sensitive Salmonella . J Infect Dis . 1990 ; 161 : 255 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Payne AN , Zihler A, Chassard C et al. Advances and perspectives in in vitro human gut fermentation modeling . Trends Biotechnol . 2012 ; 30 : 17 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat Pendu JL , Lemieux RU, Dalix AM et al. Competition between ABO and Le Gene Specified Enzymes . Vox Sang . 1983 ; 45 : 349 – 58 . Google Scholar Crossref Search ADS PubMed WorldCat Pereira FC , Berry D. Microbial nutrient niches in the gut: Microbial nutrient niches in the gut . Environ Microbiol . 2017 ; 19 : 1366 – 78 . Google Scholar Crossref Search ADS PubMed WorldCat Peterson LW , Artis D. Intestinal epithelial cells: regulators of barrier function and immune homeostasis . Nat Rev Immunol . 2014 ; 14 : 141 – 53 . Google Scholar Crossref Search ADS PubMed WorldCat Pham TAN , Clare S, Goulding D et al. Epithelial IL-22RA1-Mediated Fucosylation Promotes Intestinal Colonization Resistance to an Opportunistic Pathogen . Cell Host & Microbe . 2014 ; 16 : 504 – 16 . Google Scholar Crossref Search ADS PubMed WorldCat Pham VT , Mohajeri MH. The application of in vitro human intestinal models on the screening and development of pre- and probiotics . Beneficial Microbes . 2018 ; 9 : 725 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Plovier H , Everard A, Druart C et al. A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice . Nat Med . 2017 ; 23 : 107 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Png CW , Lindén SK, Gilshenan KS et al. Mucolytic Bacteria With Increased Prevalence in IBD Mucosa Augment In Vitro Utilization of Mucin by Other Bacteria . Am J Gastroenterol . 2010 ; 105 : 2420 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Poeker SA , Geirnaert A, Berchtold L et al. Understanding the prebiotic potential of different dietary fibers using an in vitro continuous adult fermentation model (PolyFermS) . Sci Rep . 2018 ; 8 : 4318 . Google Scholar Crossref Search ADS PubMed WorldCat Porter NT , Martens EC. The Critical Roles of Polysaccharides in Gut Microbial Ecology and Physiology . Annu Rev Microbiol . 2017 ; 71 : 349 – 69 . Google Scholar Crossref Search ADS PubMed WorldCat Praharaj AB , Dehury B, Mahapatra N et al. Molecular dynamics insights into the structure, function, and substrate binding mechanism of mucin desulfating sulfatase of gut microbe Bacteroides fragilis . J Cell Biochem . 2018 ; 119 : 3618 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Prescott NJ , Fisher SA, Franke A et al. A Nonsynonymous SNP in ATG16L1 Predisposes to Ileal Crohn's Disease and Is Independent of CARD15 and IBD5 . Gastroenterology . 2007 ; 132 : 1665 – 71 . Google Scholar Crossref Search ADS PubMed WorldCat Pretzer G , Snel J, Molenaar D et al. Biodiversity-Based Identification and Functional Characterization of the Mannose-Specific Adhesin of Lactobacillus plantarum . JB . 2005 ; 187 : 6128 – 36 . Google Scholar Crossref Search ADS WorldCat Pudlo NA , Urs K, Kumar SS et al. Symbiotic Human Gut Bacteria with Variable Metabolic Priorities for Host Mucosal Glycans . mBio . 2015 ; 6 : e01282 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Pépin J , Saheb N, Coulombe M-A et al. Emergence of Fluoroquinolones as the Predominant Risk Factor for Clostridium difficile- Associated Diarrhea: A Cohort Study during an Epidemic in Quebec . Clin Infect Dis . 2005 ; 41 : 1254 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Qadri F , Saha A, Ahmed T et al. Disease Burden Due to Enterotoxigenic Escherichia coli in the First 2 Years of Life in an Urban Community in Bangladesh . IAI . 2007 ; 75 : 3961 – 8 . Google Scholar Crossref Search ADS WorldCat Qi L , Xu Z, Jiang X et al. Preparation and antibacterial activity of chitosan nanoparticles . Carbohydr Res . 2004 ; 339 : 2693 – 700 . Google Scholar Crossref Search ADS PubMed WorldCat Qin J , Li R, Raes J et al. A human gut microbial gene catalogue established by metagenomic sequencing . Nature . 2010 ; 464 : 59 – 65 . Google Scholar Crossref Search ADS PubMed WorldCat Quigley EMM. Microflora Modulation of Motility . J Neurogastroenterol Motil . 2011 ; 17 : 140 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Quintero-Villegas MI , Aam BB, Rupnow J et al. Adherence Inhibition of Enteropathogenic Escherichia coli by Chitooligosaccharides with Specific Degrees of Acetylation and Polymerization . J Agric Food Chem . 2013 ; 61 : 2748 – 54 . Google Scholar Crossref Search ADS PubMed WorldCat Raafat D , Sahl H-G. Chitosan and its antimicrobial potential - a critical literature survey . Microb Biotechnol . 2009 ; 2 : 186 – 201 . Google Scholar Crossref Search ADS PubMed WorldCat Rakotoarivonina H , Gaillard-Martinie B, Forano E et al. Adhesion to cellulose of the Gram-positive bacterium Ruminococcus albus involves type IV pili . Microbiology . 2002 ; 148 : 1871 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Rang CU , Licht TR, Midtvedt T et al. Estimation of Growth Rates of Escherichia coli BJ4 in Streptomycin-Treated and Previously Germfree Mice by In Situ rRNA Hybridization . Clin Diagn Lab Immunol . 1999 ; 6 : 434 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Rasmussen TS , Koefoed AK, Jakobsen RR et al. Bacteriophage-mediated manipulation of the gut microbiome - promises and presents limitations . FEMS Microbiol Rev . 2020 ; 44 : 507 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Rausch P , Rehman A, Kunzel S et al. Colonic mucosa-associated microbiota is influenced by an interaction of Crohn disease and FUT2 (Secretor) genotype . Proc Natl Acad Sci . 2011 ; 108 : 19030 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Reddy B , Engle A, Katsifis S et al. Biochemical Epidemiology of Colon Cancer: Effect of Types of Dietary Fiber on Fecal Mutagens, Acid, and Neutral Sterols in Healthy Subjects . Cancer Res . 1989 ; 49 : 4629 – 35 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Reimer R , Maathuis A, Venema K et al. Effect of the Novel Polysaccharide PolyGlycopleX® on Short-Chain Fatty Acid Production in a Computer-Controlled in Vitro Model of the Human Large Intestine . Nutrients . 2014 ; 6 : 1115 – 27 . Google Scholar Crossref Search ADS PubMed WorldCat Renkonen O. Enzymatic in vitro synthesis of I-branches of mammalian polylactosamines: generation of scaffolds for multiple selectin-binding saccharide determinants : CMLS, Cell Mol Life Sci . 2000 ; 57 : 1423 – 39 . Google Scholar Crossref Search ADS WorldCat Reunanen J , von Ossowski I, Hendrickx APA et al. Characterization of the SpaCBA Pilus Fibers in the Probiotic Lactobacillus rhamnosus GG . Appl Environ Microbiol . 2012 ; 78 : 2337 – 44 . Google Scholar Crossref Search ADS PubMed WorldCat Reynolds A , Mann J, Cummings J et al. Carbohydrate quality and human health: a series of systematic reviews and meta-analyses . Lancet North Am Ed . 2019 ; 393 : 434 – 45 . Google Scholar Crossref Search ADS WorldCat Rhoades J , Manderson K, Wells A et al. Oligosaccharide-Mediated Inhibition of the Adhesion of Pathogenic Escherichia coli Strains to Human Gut Epithelial Cells In Vitro . J Food Prot . 2008 ; 71 : 2272 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Rho J , Wright DP, Christie DL et al. A Novel Mechanism for Desulfation of Mucin: Identification and Cloning of a Mucin-Desulfating Glycosidase (Sulfoglycosidase) from Prevotella Strain RS2 . JB . 2005 ; 187 : 1543 – 51 . Google Scholar Crossref Search ADS WorldCat Richard ML , Liguori G, Lamas B et al. Mucosa-associated microbiota dysbiosis in colitis associated cancer . Gut Microbes . 2018 ; 9 : 131 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Rintala A , Pietilä S, Munukka E et al. Gut Microbiota Analysis Results Are Highly Dependent on the 16S rRNA Gene Target Region, Whereas the Impact of DNA Extraction Is Minor . J Biomol Tech . 2017 ; 28 : 19 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Riva A , Kuzyk O, Forsberg E et al. A fiber-deprived diet disturbs the fine-scale spatial architecture of the murine colon microbiome . Nat Commun . 2019 ; 10 : 4366 . Google Scholar Crossref Search ADS PubMed WorldCat Roberts CL , Keita AV, Duncan SH et al. Translocation of Crohn's disease Escherichia coli across M-cells: contrasting effects of soluble plant fibres and emulsifiers . Gut . 2010 ; 59 : 1331 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Roberts CL , Keita AV, Parsons BN et al. Soluble plantain fibre blocks adhesion and M-cell translocation of intestinal pathogens . J Nutr Biochem . 2013 ; 24 : 97 – 103 . Google Scholar Crossref Search ADS PubMed WorldCat Rogers TE , Pudlo NA, Koropatkin NM et al. Dynamic responses of Bacteroides thetaiotaomicron during growth on glycan mixtures: Bacteroides responses to glycan mixtures . Mol Microbiol . 2013 ; 88 : 876 – 90 . Google Scholar Crossref Search ADS PubMed WorldCat Rogowski A , Briggs JA, Mortimer JC et al. Glycan complexity dictates microbial resource allocation in the large intestine . Nat Commun . 2015 ; 6 : 7481 . Google Scholar Crossref Search ADS PubMed WorldCat Romaní-Pérez M , Agusti A, Sanz Y. Innovation in microbiome-based strategies for promoting metabolic health . Curr Opin Clin Nutr Metab Care . 2017 ; 20 : 484 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat Rossez Y , Gosset P, Boneca IG et al. The LacdiNAc-Specific Adhesin LabA Mediates Adhesion of Helicobacter pylori to Human Gastric Mucosa . J Infect Dis . 2014 ; 210 : 1286 – 95 . Google Scholar Crossref Search ADS PubMed WorldCat Roubos-van den Hil PJ , Nout MJR, Beumer RR et al. Fermented soya bean (tempe) extracts reduce adhesion of enterotoxigenic Escherichia coli to intestinal epithelial cells . J Appl Microbiol . 2009 ; 106 : 1013 – 21 . Google Scholar Crossref Search ADS PubMed WorldCat Roubos-van den Hil PJ , Schols HA, Nout MJR et al. First Characterization of Bioactive Components in Soybean Tempe That Protect Human and Animal Intestinal Cells against Enterotoxigenic Escherichia coli (ETEC) Infection . J Agric Food Chem . 2010 ; 58 : 7649 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Roussel C , Galia W, Leriche F et al. Comparison of conventional plating, PMA-qPCR, and flow cytometry for the determination of viable enterotoxigenic Escherichia coli along a gastrointestinal in vitro model . Appl Microbiol Biotechnol . 2018a ; 102 : 9793 – 802 . Google Scholar Crossref Search ADS WorldCat Roussel C , Sivignon A, de Vallée A et al. Anti-infectious properties of the probiotic Saccharomyces cerevisiae CNCM I-3856 on enterotoxigenic E. coli (ETEC) strain H10407 . Appl Microbiol Biotechnol . 2018b ; 102 : 6175 – 89 . Google Scholar Crossref Search ADS WorldCat Roychowdhury S , Cadnum J, Glueck B et al. Faecalibacterium prausnitzii and a Prebiotic Protect Intestinal Health in a Mouse Model of Antibiotic and Clostridium difficile Exposure . Journal of Parenteral and Enteral Nutrition . 2018 ; 42 : 1156 – 67 . Google Scholar Crossref Search ADS PubMed WorldCat Rubinstein MR , Wang X, Liu W et al. Fusobacterium nucleatum Promotes Colorectal Carcinogenesis by Modulating E-Cadherin/β-Catenin Signaling via its FadA Adhesin . Cell Host & Microbe . 2013 ; 14 : 195 – 206 . Google Scholar Crossref Search ADS PubMed WorldCat Ruiz-Palacios GM , Cervantes LE, Ramos P et al. Campylobacter jejuni Binds Intestinal H(O) Antigen (Fucα1, 2Galβ1, 4GlcNAc), and Fucosyloligosaccharides of Human Milk Inhibit Its Binding and Infection . J Biol Chem . 2003 ; 278 : 14112 – 20 . Google Scholar Crossref Search ADS PubMed WorldCat Ríos-Covián D , Ruas-Madiedo P, Margolles A et al. Intestinal Short Chain Fatty Acids and their Link with Diet and Human Health . Front Microbiol . 2016 ; 7 : 185 . Google Scholar Crossref Search ADS PubMed WorldCat Sagar NM , Cree IA, Covington JA et al. The Interplay of the Gut Microbiome, Bile Acids, and Volatile Organic Compounds . Gastroenterology Research and Practice . 2015 ; 2015 : 1 – 6 . Google Scholar Crossref Search ADS WorldCat Salcedo J , Barbera R, Matencio E et al. Gangliosides and sialic acid effects upon newborn pathogenic bacteria adhesion: An in vitro study . Food Chem . 2013 ; 136 : 726 – 34 . Google Scholar Crossref Search ADS PubMed WorldCat Salonen A , Lahti L, Salojärvi J et al. Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men . ISME J . 2014 ; 8 : 2218 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Salyers AA , Vercellotti JR, West SE et al. Fermentation of mucin and plant polysaccharides by strains of Bacteroides from the human colon . Appl Environ Microbiol . 1977 ; 33 : 319 – 22 . Google Scholar Crossref Search ADS PubMed WorldCat Sanchez JI , Marzorati M, Grootaert C et al. Arabinoxylan-oligosaccharides (AXOS) affect the protein/carbohydrate fermentation balance and microbial population dynamics of the Simulator of Human Intestinal Microbial Ecosystem . Microb Biotechnol . 2009 ; 2 : 101 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Sarabia-Sainz HM , Armenta-Ruiz C, Sarabia-Sainz JA et al. Adhesion of enterotoxigenic Escherichia coli strains to neoglycans synthesised with prebiotic galactooligosaccharides . Food Chem . 2013 ; 141 : 2727 – 34 . Google Scholar Crossref Search ADS PubMed WorldCat Sausset R , Petit MA, Gaboriau-Routhiau V et al. New insights into intestinal phages . Mucosal Immunol . 2020 ; 13 : 205 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Schanler RJ. Randomized Trial of Donor Human Milk Versus Preterm Formula as Substitutes for Mothers’ Own Milk in the Feeding of Extremely Premature Infants . Pediatrics . 2005 ; 116 : 400 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Schembri MA , Kjaergaard K, Sokurenko EV et al. Molecular Characterization of the Escherichia coli FimH Adhesin . J Infect Dis . 2001 ; 183 : S28 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Scheppach W , German-Austrian Scfa Study Group . Treatment of distal ulcerative colitis with short-chain fatty acid enemas a placebo-controlled trial . Digest Dis Sci . 1996 ; 41 : 2254 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Schirmer M , Garner A, Vlamakis H et al. Microbial genes and pathways in inflammatory bowel disease . Nat Rev Microbiol . 2019 ; 17 : 497 – 511 . Google Scholar Crossref Search ADS PubMed WorldCat Schnorr SL , Candela M, Rampelli S et al. Gut microbiome of the Hadza hunter-gatherers . Nat Commun . 2014 ; 5 : 3654 . Google Scholar Crossref Search ADS PubMed WorldCat Schoster A , Kokotovic B, Permin A et al. In vitro inhibition of Clostridium difficile and Clostridium perfringens by commercial probiotic strains . Anaerobe . 2013 ; 20 : 36 – 41 . Google Scholar Crossref Search ADS PubMed WorldCat Schroeder BO , Birchenough GMH, Ståhlman M et al. Bifidobacteria or Fiber Protects against Diet-Induced Microbiota-Mediated Colonic Mucus Deterioration . Cell Host & Microbe . 2018 ; 23 : 27 – 40.e7 . Google Scholar Crossref Search ADS PubMed WorldCat Schultsz C , van den Berg FM, ten Kate FW et al. The intestinal mucus layer from patients with inflammatory bowel disease harbors high numbers of bacteria compared with controls . Gastroenterology . 1999 ; 117 : 1089 – 97 . Google Scholar Crossref Search ADS PubMed WorldCat Schwab C , Berry D, Rauch I et al. Longitudinal study of murine microbiota activity and interactions with the host during acute inflammation and recovery . ISME J . 2014 ; 8 : 1101 – 14 . Google Scholar Crossref Search ADS PubMed WorldCat Scott KP , Duncan SH, Flint HJ. Dietary fibre and the gut microbiota . Nutrition Bulletin . 2008 ; 33 : 201 – 11 . Google Scholar Crossref Search ADS WorldCat Sekirov I , Finlay BB. The role of the intestinal microbiota in enteric infection: Intestinal microbiota and enteric infections . J Physiol . 2009 ; 587 : 4159 – 67 . Google Scholar Crossref Search ADS PubMed WorldCat Seksik P. Alterations of the dominant faecal bacterial groups in patients with Crohn's disease of the colon . Gut . 2003 ; 52 : 237 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Sender R , Fuchs S, Milo R. Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host Cells in Humans . Cell . 2016 ; 164 : 337 – 40 . Google Scholar Crossref Search ADS PubMed WorldCat Seregin SS , Golovchenko N, Schaf B et al. NLRP6 Protects Il10 −/− Mice from Colitis by Limiting Colonization of Akkermansia muciniphila . Cell Rep . 2017 ; 19 : 733 – 45 . Google Scholar Crossref Search ADS PubMed WorldCat Sheridan P , Martin JC, Lawley TD et al. Polysaccharide utilization loci and nutritional specialization in a dominant group of butyrate-producing human colonic Firmicutes . Microb Genom . 2016 ; 2 : e000043 Google Scholar PubMed OpenURL Placeholder Text WorldCat Shin N-R , Lee J-C, Lee H-Y et al. An increase in the Akkermansia spp. population induced by metformin treatment improves glucose homeostasis in diet-induced obese mice . Gut . 2014 ; 63 : 727 – 35 . Google Scholar Crossref Search ADS PubMed WorldCat Shin W , Kim HJ. Intestinal barrier dysfunction orchestrates the onset of inflammatory host–microbiome cross-talk in a human gut inflammation-on-a-chip . Proc Natl Acad Sci USA . 2018 ; 115 : E10539 – 47 . Google Scholar Crossref Search ADS PubMed WorldCat Shin W , Wu A, Massidda MW et al. A Robust Longitudinal Co-culture of Obligate Anaerobic Gut Microbiome With Human Intestinal Epithelium in an Anoxic-Oxic Interface-on-a-Chip . Front Bioeng Biotechnol . 2019 ; 7 : 13 . Google Scholar Crossref Search ADS PubMed WorldCat Shoaf K , Mulvey GL, Armstrong GD et al. Prebiotic Galactooligosaccharides Reduce Adherence of Enteropathogenic Escherichia coli to Tissue Culture Cells . IAI . 2006 ; 74 : 6920 – 8 . Google Scholar Crossref Search ADS WorldCat Sicard J-F , Le Bihan G, Vogeleer P et al. Interactions of Intestinal Bacteria with Components of the Intestinal Mucus . Front Cell Infect Microbiol . 2017 ; 7 : 387 . Google Scholar Crossref Search ADS PubMed WorldCat Sikorska H , Smoragiewicz W. Role of probiotics in the prevention and treatment of meticillin-resistant Staphylococcus aureus infections . Int J Antimicrob Agents . 2013 ; 42 : 475 – 81 . Google Scholar Crossref Search ADS PubMed WorldCat Singh V , Yeoh BS, Chassaing B et al. Dysregulated Microbial Fermentation of Soluble Fiber Induces Cholestatic Liver Cancer . Cell . 2018 ; 175 : 679 – 694.e22 . Google Scholar Crossref Search ADS PubMed WorldCat Singh V , Yeoh BS, Walker RE et al. Microbiota fermentation-NLRP3 axis shapes the impact of dietary fibres on intestinal inflammation . Gut . 2019 ; 68 : 1801 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Sivignon A , de Vallée A, Barnich N et al. Saccharomyces cerevisiae CNCM I-3856 prevents colitis induced by AIEC bacteria in the transgenic mouse model mimicking Crohn's disease . Inflamm Bowel Dis . 2015 ; 21 : 276 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Smits SA , Leach J, Sonnenburg ED et al. Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania . Science . 2017 ; 357 : 802 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Snart J , Bibiloni R, Grayson T et al. Supplementation of the Diet with High-Viscosity Beta-Glucan Results in Enrichment for Lactobacilli in the Rat Cecum . AEM . 2006 ; 72 : 1925 – 31 . Google Scholar Crossref Search ADS WorldCat Sokurenko EV , Chesnokova V, Dykhuizen DE et al. Pathogenic adaptation of Escherichia coli by natural variation of the FimH adhesin . Proc Natl Acad Sci . 1998 ; 95 : 8922 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Sommer F , Adam N, Johansson MEV et al. Altered Mucus Glycosylation in Core 1 O-Glycan-Deficient Mice Affects Microbiota Composition and Intestinal Architecture . PLoS One . 2014 ; 9 : e85254 . Google Scholar Crossref Search ADS PubMed WorldCat Song M , Wu K, Meyerhardt JA et al. Fiber Intake and Survival After Colorectal Cancer Diagnosis . JAMA Oncol . 2018 ; 4 : 71 . Google Scholar Crossref Search ADS PubMed WorldCat Sonnenburg ED , Sonnenburg JL. Starving our Microbial Self: The Deleterious Consequences of a Diet Deficient in Microbiota-Accessible Carbohydrates . Cell Metab . 2014 ; 20 : 779 – 86 . Google Scholar Crossref Search ADS PubMed WorldCat Sonnenburg ED , Zheng H, Joglekar P et al. Specificity of Polysaccharide Use in Intestinal Bacteroides Species Determines Diet-Induced Microbiota Alterations . Cell . 2010 ; 141 : 1241 – 52 . Google Scholar Crossref Search ADS PubMed WorldCat Sonnenburg JL. Glycan Foraging in Vivo by an Intestine-Adapted Bacterial Symbiont . Science . 2005 ; 307 : 1955 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Sorbara MT , Pamer EG. Interbacterial mechanisms of colonization resistance and the strategies pathogens use to overcome them . Mucosal Immunol . 2019 ; 12 : 1 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Sossai P . Butyric acid: what is the future for this old substance? Swiss Med Wkly . 2012 ; 142 : w13596 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Sperandio B , Fischer N, Chevalier-Curt MJ et al. Virulent Shigella flexneri Affects Secretion, Expression, and Glycosylation of Gel-Forming Mucins in Mucus-Producing Cells . Infect Immun . 2013 ; 81 : 3632 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Spiga L , Winter MG, Furtado de Carvalho T et al. An Oxidative Central Metabolism Enables Salmonella to Utilize Microbiota-Derived Succinate . Cell Host Microbe . 2017 ; 22 : 291 – 301 ..e6. Google Scholar Crossref Search ADS PubMed WorldCat Stins MF , Prasadarao NV, Ibric L et al. Binding Characteristics of S Fimbriated Escherichia coli to Isolated Brain Microvascular Endothelial Cells . Am J Pathol . 1994 ; 145 : 1228 – 36 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Stone EL , Ismail MN, Lee SH et al. Glycosyltransferase Function in Core 2-Type Protein O Glycosylation . MCB . 2009 ; 29 : 3770 – 82 . Google Scholar Crossref Search ADS PubMed WorldCat Story JA , Kritchevsky D. Bile acid metabolism and fiber . Am J Clin Nutr . 1978 ; 31 : S199 – 202 . Google Scholar Crossref Search ADS PubMed WorldCat Strugala V , Dettmar PW, Pearson JP. Thickness and continuity of the adherent colonic mucus barrier in active and quiescent ulcerative colitis and Crohn's disease: Colonic mucus thickness in IBD . Int J Clin Pract . 2008 ; 62 : 762 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Stuyven E , Cox E, Vancaeneghem S et al. Effect of β-glucans on an ETEC infection in piglets . Vet Immunol Immunopathol . 2009 ; 128 : 60 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Swidsinski A , Ladhoff A, Pernthaler A et al. Mucosal flora in inflammatory bowel disease . Gastroenterology . 2002 ; 122 : 44 – 54 . Google Scholar Crossref Search ADS PubMed WorldCat Swidsinski A , Loening-Baucke V, Theissig F et al. Comparative study of the intestinal mucus barrier in normal and inflamed colon . Gut . 2007 ; 56 : 343 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Swidsinski A , Weber J, Loening-Baucke V et al. Spatial Organization and Composition of the Mucosal Flora in Patients with Inflammatory Bowel Disease . J Clin Microbiol . 2005 ; 43 : 3380 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Szabady RL , Yanta JH, Halladin DK et al. TagA is a secreted protease of Vibrio cholerae that specifically cleaves mucin glycoproteins . Microbiology . 2011 ; 157 : 516 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat Taghipoor M , Barles G, Georgelin C et al. Digestion modeling in the small intestine: Impact of dietary fiber . Math Biosci . 2014 ; 258 : 101 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Tailford LE , Crost EH, Kavanaugh D et al. Mucin glycan foraging in the human gut microbiome . Front Genet . 2015 ; 6 : 81 . Google Scholar Crossref Search ADS PubMed WorldCat Takao M , Yen H, Tobe T. LeuO enhances butyrate-induced virulence expression through a positive regulatory loop in enterohaemorrhagic E scherichia coli: Positive role of LeuO in EHEC virulence expression . Mol Microbiol . 2014 ; 93 : 1302 – 13 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Tapader R , Basu S, Pal A. Secreted proteases: A new insight in the pathogenesis of extraintestinal pathogenic Escherichia coli . Int J Med Microbiol . 2019 ; 309 : 159 – 68 . Google Scholar Crossref Search ADS PubMed WorldCat Taylor SL , McGuckin MA, Wesselingh S et al. Infection's Sweet Tooth: How Glycans Mediate Infection and Disease Susceptibility . Trends Microbiol . 2018 ; 26 : 92 – 101 . Google Scholar Crossref Search ADS PubMed WorldCat Tester RF , Karkalas J, Qi X. Starch—composition, fine structure and architecture . J Cereal Sci . 2004 ; 39 : 151 – 65 . Google Scholar Crossref Search ADS WorldCat Thibault R , Blachier F, Darcy-Vrillon B et al. Butyrate utilization by the colonic mucosa in inflammatory bowel diseases: A transport deficiency . Inflamm Bowel Dis . 2010 ; 16 : 684 – 95 . Google Scholar Crossref Search ADS PubMed WorldCat Tomas J , Mulet C, Saffarian A et al. High-fat diet modifies the PPAR-γ pathway leading to disruption of microbial and physiological ecosystem in murine small intestine . Proc Natl Acad Sci . 2016 ; 113 : 5934 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Tovaglieri A , Sontheimer-Phelps A, Geirnaert A et al. Species-specific enhancement of enterohemorrhagic E. coli pathogenesis mediated by microbiome metabolites . Microbiome . 2019 ; 7 : 43 . Google Scholar Crossref Search ADS PubMed WorldCat Tu QV , McGuckin MA, Mendz GL. Campylobacter jejuni response to human mucin MUC2: modulation of colonization and pathogenicity determinants . J Med Microbiol . 2008 ; 57 : 795 – 802 . Google Scholar Crossref Search ADS PubMed WorldCat Turnbaugh PJ , Bäckhed F, Fulton L et al. Diet-Induced Obesity Is Linked to Marked but Reversible Alterations in the Mouse Distal Gut Microbiome . Cell Host & Microbe . 2008 ; 3 : 213 – 23 . Google Scholar Crossref Search ADS PubMed WorldCat Turnbaugh PJ , Ley RE, Mahowald MA et al. An obesity-associated gut microbiome with increased capacity for energy harvest . Nature . 2006 ; 444 : 1027 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat Turnbaugh PJ , Ridaura VK, Faith JJ et al. The Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice . Sci Transl Med . 2009 ; 1 : 6ra14 . Google Scholar Crossref Search ADS PubMed WorldCat Turner JR. Intestinal mucosal barrier function in health and disease . Nat Rev Immunol . 2009 ; 9 : 799 – 809 . Google Scholar Crossref Search ADS PubMed WorldCat Turroni F , Milani C, Duranti S et al. Glycan Utilization and Cross-Feeding Activities by Bifidobacteria . Trends Microbiol . 2018 ; 26 : 339 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Van den Abbeele P , Gérard P, Rabot S et al. Arabinoxylans and inulin differentially modulate the mucosal and luminal gut microbiota and mucin-degradation in humanized rats: Prebiotics modulate mucosal and luminal microbiota summary . Environ Microbiol . 2011 ; 13 : 2667 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat Van den Abbeele P , Marzorati M, Derde M et al. Arabinoxylans, inulin and Lactobacillus reuteri 1063 repress the adherent-invasive Escherichia coli from mucus in a mucosa-comprising gut model . npj Biofilms Microbiomes . 2016 ; 2 : 16016 . Google Scholar Crossref Search ADS PubMed WorldCat Van de Wiele T , Van den Abbeele P, Ossieur W et al. The Simulator of the Human Intestinal Microbial Ecosystem (SHIME®) . In: Verhoeckx K, Cotter P, López-Expósito I et al. (eds). The Impact of Food Bioactives on Health . Cham : Springer International Publishing , 2015 , 305 – 17 . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Van Herreweghen F , De Paepe K, Roume H et al. Mucin degradation niche as a driver of microbiome composition and Akkermansia muciniphila abundance in a dynamic gut model is donor independent . FEMS Microbiol Ecol . 2018 ; 94 . Google Scholar OpenURL Placeholder Text WorldCat Van Nuenen M , Diederick Meyer P, Venema K. The Effect of Various Inulins and Clostridium difficile on the Metabolic Activity of the Human Colonic Microbiota in vitro . Microbial Ecology in Health and Disease . 2003 ; 15 : 137 – 44 . Google Scholar Crossref Search ADS WorldCat Vardaka VD , Yehia HM, Savvaidis IN. Effects of Citrox and chitosan on the survival of Escherichia coli O157:H7 and Salmonella enterica in vacuum-packaged turkey meat . Food Microbiol . 2016 ; 58 : 128 – 34 . Google Scholar Crossref Search ADS PubMed WorldCat Vernia P , Annese V, Bresci G et al. Topical butyrate improves efficacy of 5-ASA in refractory distal ulcerative colitis: results of a multicentre trial . Eur J Clin Invest . 2003 ; 33 : 244 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Vernia P , Marcheggiano A, Caprilli R et al. Short-chain fatty acid topical treatment in distal ulcerative colitis . Aliment Pharmacol Therap . 2007 ; 9 : 309 – 13 . Google Scholar Crossref Search ADS WorldCat Vimal DB , Khullar M, Gupta S et al. Intestinal mucins: the binding sites for Salmonella Typhimurium . Mol Cell Biochem . 2000 ; 204 : 107 – 17 . Google Scholar Crossref Search ADS PubMed WorldCat Vinolo MAR , Rodrigues HG, Nachbar RT et al. Regulation of Inflammation by Short Chain Fatty Acids . Nutrients . 2011 ; 3 : 858 – 76 . Google Scholar Crossref Search ADS PubMed WorldCat Vital M , Howe A, Bergeron N et al. Metagenomic Insights into the Degradation of Resistant Starch by Human Gut Microbiota . Appl Environ Microbiol . 2018 ; 84 : e01562 – 18 . Google Scholar Crossref Search ADS PubMed WorldCat Vodovnik M , Duncan SH, Reid MD et al. Expression of Cellulosome Components and Type IV Pili within the Extracellular Proteome of Ruminococcus flavefaciens 007 . PLoS One . 2013 ; 8 : e65333 . Google Scholar Crossref Search ADS PubMed WorldCat Vogt SL , Peña-Díaz J, Finlay BB. Chemical communication in the gut: Effects of microbiota-generated metabolites on gastrointestinal bacterial pathogens . Anaerobe . 2015 ; 34 : 106 – 15 . Google Scholar Crossref Search ADS PubMed WorldCat Vrieze A , Van Nood E, Holleman F et al. Transfer of Intestinal Microbiota From Lean Donors Increases Insulin Sensitivity in Individuals With Metabolic Syndrome . Gastroenterology . 2012 ; 143 : 913 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat Vuik F , Dicksved J, Lam S et al. Composition of the mucosa-associated microbiota along the entire gastrointestinal tract of human individuals . United European Gastroenterol J . 2019 ; 7 : 897 – 907 . Google Scholar Crossref Search ADS PubMed WorldCat Wacklin P , Mäkivuokko H, Alakulppi N et al. Secretor Genotype (FUT2 gene) Is Strongly Associated with the Composition of Bifidobacteria in the Human Intestine . PLoS One . 2011 ; 6 : e20113 . Google Scholar Crossref Search ADS PubMed WorldCat Walker AW , Sanderson JD, Churcher C et al. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease . BMC Microbiol . 2011 ; 11 : 7 . Google Scholar Crossref Search ADS PubMed WorldCat Wang T , Cai G, Qiu Y et al. Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers . ISME J . 2012 ; 6 : 320 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat Wang Y , Gänzle MG, Schwab C. Exopolysaccharide Synthesized by Lactobacillus reuteri Decreases the Ability of Enterotoxigenic Escherichia coli To Bind to Porcine Erythrocytes . AEM . 2010 ; 76 : 4863 – 6 . Google Scholar Crossref Search ADS WorldCat White BA , Lamed R, Bayer EA et al. Biomass Utilization by Gut Microbiomes . Annu Rev Microbiol . 2014 ; 68 : 279 – 96 . Google Scholar Crossref Search ADS PubMed WorldCat Wikoff WR , Anfora AT, Liu J et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites . Proc Natl Acad Sci . 2009 ; 106 : 3698 – 703 . Google Scholar Crossref Search ADS PubMed WorldCat Willats WGT , Knox JP, Mikkelsen JD. Pectin: new insights into an old polymer are starting to gel . Trends in Food Science & Technology . 2006 ; 17 : 97 – 104 . Google Scholar Crossref Search ADS WorldCat Willing BP , Vacharaksa A, Croxen M et al. Altering Host Resistance to Infections through Microbial Transplantation . PLoS One . 2011 ; 6 : e26988 . Google Scholar Crossref Search ADS PubMed WorldCat Wolf BW , Meulbroek JA, Jarvis KP et al. Dietary Supplementation with Fructooligosaccharides Increase Survival Time in a Hamster Model of Clostridium difficile-Colitis . Bioscience Microflora . 1997 ; 16 : 59 – 64 . Google Scholar Crossref Search ADS WorldCat Wong C , Harris PJ, Ferguson LR. Potential Benefits of Dietary Fibre Intervention in Inflammatory Bowel Disease . Int J Mol Sci . 2016 ; 17 : 919 . Google Scholar Crossref Search ADS WorldCat Wrzosek L , Miquel S, Noordine M-L et al. Bacteroides thetaiotaomicron and Faecalibacterium prausnitzii influence the production of mucus glycans and the development of goblet cells in the colonic epithelium of a gnotobiotic model rodent . BMC Biol . 2013 ; 11 : 61 . Google Scholar Crossref Search ADS PubMed WorldCat Wu GD , Chen J, Hoffmann C et al. Linking Long-Term Dietary Patterns with Gut Microbial Enterotypes . Science . 2011 ; 334 : 105 – 8 . Google Scholar Crossref Search ADS PubMed WorldCat Wu X , Wu Y, He L et al. Effects of the intestinal microbial metabolite butyrate on the development of colorectal cancer . J Cancer . 2018 ; 9 : 2510 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Xiao D , Wang Y, Liu G et al. Effects of Chitosan on Intestinal Inflammation in Weaned Pigs Challenged by Enterotoxigenic Escherichia coli . PLoS One . 2014 ; 9 : e104192 . Google Scholar Crossref Search ADS PubMed WorldCat Yatsunenko T , Rey FE, Manary MJ et al. Human gut microbiome viewed across age and geography . Nature . 2012 ; 486 : 222 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat Younes I , Rinaudo M. Chitin and Chitosan Preparation from Marine Sources. Structure, Properties and Applications . Marine Drugs . 2015 ; 13 : 1133 – 74 . Google Scholar Crossref Search ADS PubMed WorldCat Yu L-C , Twu Y-C, Chang C-Y et al. Molecular basis of the adult i phenotype and the gene responsible for the expression of the human blood group I antigen . Blood . 2001 ; 98 : 3840 – 5 . Google Scholar Crossref Search ADS PubMed WorldCat Zackular JP , Baxter NT, Iverson KD et al. The Gut Microbiome Modulates Colon Tumorigenesis . mBio . 2013 ; 4 : e00692 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Zarepour M , Bhullar K, Montero M et al. The Mucin Muc2 Limits Pathogen Burdens and Epithelial Barrier Dysfunction during Salmonella enterica Serovar Typhimurium Colitis . Infect Immun . 2013 ; 81 : 3672 – 83 . Google Scholar Crossref Search ADS PubMed WorldCat Zeevi D , Korem T, Zmora N et al. Personalized Nutrition by Prediction of Glycemic Responses . Cell . 2015 ; 163 : 1079 – 94 . Google Scholar Crossref Search ADS PubMed WorldCat Ze X , Duncan SH, Louis P et al. Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon . ISME J . 2012 ; 6 : 1535 – 43 . Google Scholar Crossref Search ADS PubMed WorldCat Zhu L , Qin S, Zhai S et al. Inulin with different degrees of polymerization modulates composition of intestinal microbiota in mice . FEMS Microbiol Lett . 2017 ; 364 . Google Scholar OpenURL Placeholder Text WorldCat Zhu Y , González-Ortiz G, Jiménez-Díaz R et al. Exopolysaccharides from olive brines could reduce the adhesion of ETEC K88 to intestinal epithelial cells . Food Funct . 2018 ; 9 : 3884 – 94 . Google Scholar Crossref Search ADS PubMed WorldCat Zihler A , Gagnon M, Chassard C et al. Unexpected consequences of administering bacteriocinogenic probiotic strains for Salmonella populations, revealed by an in vitro colonic model of the child gut . Microbiology . 2010 ; 156 : 3342 – 53 . Google Scholar Crossref Search ADS PubMed WorldCat Zmora N , Suez J, Elinav E. You are what you eat: diet, health and the gut microbiota . Nat Rev Gastroenterol Hepatol . 2019 ; 16 : 35 – 56 . Google Scholar Crossref Search ADS PubMed WorldCat Zou J , Chassaing B, Singh V et al. Fiber-Mediated Nourishment of Gut Microbiota Protects against Diet-Induced Obesity by Restoring IL-22-Mediated Colonic Health . Cell Host & Microbe . 2018 ; 23 : 41 – 53.e4 . Google Scholar Crossref Search ADS PubMed WorldCat Zumbrun SD , Melton-Celsa AR, Smith MA et al. Dietary choice affects Shiga toxin-producing Escherichia coli (STEC) O157:H7 colonization and disease . Proc Natl Acad Sci USA . 2013 ; 110 : E2126 – 33 . Google Scholar Crossref Search ADS PubMed WorldCat © The Author(s) 2020. Published by Oxford University Press on behalf of FEMS. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Journal

FEMS Microbiology ReviewsOxford University Press

Published: Oct 7, 2020

Keywords: dietary fiber; mucus; pathogenic organism; microbiome; polysaccharides; infections; carbohydrates

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