Background: Glyphosate-based herbicides (GBHs) are broad-spectrum herbicides that act on the shikimate pathway in bacteria, fungi, and plants. The possible effects of GBHs on human health are the subject of an intense public debate for both its potential carcinogenic and non-carcinogenic effects, including its effects on microbiome. The present pilot study examines whether exposure to GBHs at doses of glyphosate considered to be “safe” (the US Acceptable Daily Intake - ADI - of 1.75 mg/kg bw/day), starting from in utero, may modify the composition of gut microbiome in Sprague Dawley (SD) rats. Methods: Glyphosate alone and Roundup, a commercial brand of GBHs, were administered in drinking water at doses comparable to the US glyphosate ADI (1.75 mg/kg bw/day) to F0 dams starting from the gestational day (GD) 6 up to postnatal day (PND) 125. Animal feces were collected at multiple time points from both F0 dams and F1 pups. The gut microbiota of 433 fecal samples were profiled at V3-V4 region of 16S ribosomal RNA gene and further taxonomically assigned and assessed for diversity analysis. We tested the effect of exposure on overall microbiome diversity using PERMANOVA and on individual taxa by LEfSe analysis. Results: Microbiome profiling revealed that low-dose exposure to Roundup and glyphosate resulted in significant and distinctive changes in overall bacterial composition in F1 pups only. Specifically, at PND31, corresponding to pre-pubertal age in humans, relative abundance for Bacteriodetes (Prevotella) was increased while the Firmicutes (Lactobacillus) was reduced in both Roundup and glyphosate exposed F1 pups compared to controls. Conclusions: This study provides initial evidence that exposures to commonly used GBHs, at doses considered safe, are capable of modifying the gut microbiota in early development, particularly before the onset of puberty. These findings warrant future studies on potential health effects of GBHs in early development such as childhood. Keywords: Roundup, Glyphosate, Gut microbiome, Early developmental stage * Correspondence: email@example.com; http://www.ramazzini.org Equal contributors Cesare Maltoni Cancer Research Center (CMCRC), Ramazzini Institute (RI), Via Saliceto, 3, 40010 Bentivoglio, Bologna, Italy Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Mao et al. Environmental Health (2018) 17:50 Page 2 of 12 Background its microbiome are starting to provide mechanistic in- Glyphosate (IUPAC chemical name N-(phosphono- sights into these interactions. The mechanisms in which methyl) glycine) is the active ingredient of the most the enteric microbiome modulates specific effects on the widely applied herbicide worldwide, glyphosate-based host is not completely clear, although several mediators herbicides (GBHs), including the best-known formula- have been suggested as potential vehicles for such influ- tion Roundup. The substance glyphosate was initially ence and might behave as effectors, enzyme cofactors and discovered in 1950 by a Swiss chemist, Henri Martin, at signal molecules. Such mediators include lipopolysaccha- the pharmaceutical company Cilag . Its herbicidal rides, peptidoglycans, short-chain fatty acids, neurotrans- properties were not discovered for another 20 years. mitters and gaseous molecules [14, 15]. Recent advances Since glyphosate was patented in 1974 by Monsanto as a in characterizing the composition and function of individ- herbicide, approximately 9.4 million tons of GBHs have ual microbial species and complex microbial communities been sprayed, nearly half a pound of glyphosate on every are revealing the importance of microbial metabolism for cultivated acre of land globally . Furthermore, after the host immune system . The gut microbiota pro- the introduction of genetically modified (GM) crops that duces an extremely diverse metabolite repertoire (such as are glyphosate-tolerant in 1996, usage of GBHs has sky- propionic acid, a short-chain fatty acids) from the anaer- rocketed; about two-thirds of the total GBHs usage took obic fermentation of exogenous undigested dietary com- place in recent decades. According to the National ponents (such as fibers) that reach the colon, as well as Academy of Sciences report , in 2014 alone, annual endogenous compounds that are generated by microor- glyphosate usage in agriculture industry exceeded 110 ganisms and the host . The single layer of epithelial million kilograms. Besides GM crops, farmers also apply cells that makes up the mucosal interface between the GBHs on non-GM crops in order to accelerate the har- host and microorganisms allows microbial metabolic vest. This practice, also known as desiccation, has led to products to gain access to and interact with host cells, and significant dietary exposure to the residues of glyphosate thus influence immune responses and disease risk, in and its primary metabolite AMPA (aminomethylpho- particular at high concentration . sphonic acid) [4, 5]. GBHs have been reported to alter microbiota in soil The primary herbicidal function of glyphosate is to in- , plants  and animals [21, 22]. A number of stud- hibit a key plant enzyme, namely 5-enolpyruvylshikimate- ies have suggested that GBHs could act as antibiotics in 3-phosphate synthase (EPSPS). This enzyme participates the mammalian gut microbiome. Recent studies have in the biosynthesis of aromatic amino acids (phenylalan- raised concerns about the health effects of glyphosate on ine, tyrosine and tryptophan) via the shikimate pathway in gut microbiota of farm animal when fed feed containing bacteria, fungi, and plants. The only enzyme known to residues of glyphosate. For example, farm animal studies catalyze a similar reaction in bacteria is the enzyme MurA linked epidemics of C. Botulinum-mediated diseases in (UDP-N-acetylglucosamine enolpyruvyl transferase, EC 2. dairy cows  to glyphosate exposure. It has been pro- 5.1.7), which catalyzes the first committed step in the syn- posed that glyphosate has a potential inhibiting effect on thesis of the peptidoglycan layer of the bacterial cell. growth of commensal bacteria, normally occupying the Growth and survival of bacteria relies on the functionality gut of farm animals. For example, a reduction of such of the enzyme MurA that is the target of the broad- beneficial bacteria could be a predisposing factor for spectrum antibiotic fosfomycin. Glyphosate appears to oc- Campylobacteriosis (campylobacter infection) described cupy a binding site of MurA, mimicking an intermediate as an emerging food-borne disease . Poultry is a state of the ternary enzyme-substrates complex . The major reservoir and source of transmission of campylo- similarity between the two enolpyruvyl transferases bacteriosis to humans . Furthermore, GBHs were EPSPSe and MurA appears to clarify the antibacterial ac- also found to be capable of inducing multiple-antibiotic tivity of Glyphosate. As the EPSPS-driven pathway does resistance phenotype in potential pathogens . There- not exist in vertebrate cells, many scientists and environ- fore, GBHs may have the potential to modify the animal mental regulating agencies believed that glyphosate would and human microbiota, which, in turn, could influence impose minimal risks to mammals, in particular, humans human health. However, up to date, no direct evidence [7–9]. For this reason, the shikimate pathway has been the has been reported to suggest any interplay between target for the development of new anti-microbial and GBHs exposure and the microbiome in humans, espe- anti-parasite agents. In fact, glyphosate formulation has cially during early development or in animal models ex- been patented as anti-parasite drug . However, several posed to GBH with low dosage relevant to humans. As emerging evidence suggested that glyphosate or GBHs denoted in the Developmental Origins of Health and (such as Roundup) can adversely affect mammalian biol- Disease (DOHaD) paradigm , early environmental ogy via multiple mechanisms [11–13]. Downstream ana- exposures are important to human health. In particular, lyses of the functional interactions between the host and the prenatal and neonatal period represent a narrow but Mao et al. Environmental Health (2018) 17:50 Page 3 of 12 critical window of susceptibility to myriad environmental bedding (supplier: Giuseppe Bordignon, Treviso, Italy). exposures and conditions with potentially lifelong im- Analysis of chemical characteristics (pH, ashes, dry pacts on health and disease. A number of human and weight, specific weight) and possible contamination animal studies [27–29] associate several diseases with (metals, aflatoxin, polychlorobiphenyls, organophos- early-life imbalances of the gut microbiota, but it was re- phorus and organochlorine pesticides) of the bedding cently pointed out the need for further evidence that was performed by CONSULAB Laboratories (Treviso, GBHs, in particular at environmentally relevant doses, Italy). The cages were placed on racks, inside a single can result in disturbances in the gut microbiome of hu- room prepared for the experiment at 22 °C ± 3 °C man and animal populations with negative health impli- temperature and 50 ± 20% relative humidity. Daily cations . Furthermore, exploring the effects of GBHs checks on temperature and humidity were performed. on the microbiota from early-life until adulthood in The light was artificial and a light/dark cycle of 12 h different windows of susceptibility, may give a more was maintained. Husbandry factors stress-related were accurate portrayal of the microbial conditions that are controlled: rats were kept together (same room, same involved in pathogenesis. Possible alterations of the rack, no more than 3 per cage) and we did not relocate mammalian gut microbiota and its metabolites by envir- cages. Noise and handling time were minimized . onmental concentrations of GBHs in early development, starting from in utero, have never been explored in a Experimental protocol controlled laboratory animal study. The present pilot Two groups of SD rat dams and relative pups were study examines whether exposure to GBHs at doses of treated with either glyphosate or Roundup diluted in glyphosate considered to be “safe”, the US ADI of 1. drinking water at the glyphosate concentration of 1. 75 mg/kg bw/day, defined as the chronic Reference Dose 75 mg/kg bw/day. There were in total 24 F0 dams, entire (cRfD) determined by the US EPA , affect the litter at postnatal day (PND) 7 and PND 14, 108 F1 off- composition and diversity of the gut microbiome at early spring at PND 31 and PND 57 and 60 F1 at PND 125 in developmental stages in Sprague-Dawley rats. this study. The F0 female breeders received the treat- ment through drinking water from gestation day (GD) 6 Methods to the end of lactation. During pregnancy and lactation, Experimental model embryos and offspring (F1) were all retained in the litter The entire animal experiment was performed following and might receive the test compounds mainly through the rules by the Italian law regulating the use and treat- their dams (F0). After weaning on PND 28 offspring ment of animals for scientific purposes (Legislative were randomly distributed in two cohorts: animals be- Decree No. 26, 2014. Implementation of the directive n. longing to the 6-week cohort were sacrificed at PND 73 2010/63/EU on the protection of animals used for sci- ± 2, i.e. 6 weeks after weaning, animals belonging to the entific purposes. - G.U. General Series, n. 61 of March 13-week cohort were sacrificed at PND 125 ± 2, i.e. 14th 2014). All animal study procedures were per- 13 weeks after weaning. The F1 offspring might receive formed at the Cesare Maltoni Cancer Research Centre/ the treatment from their dams starting from in utero Ramazzini Institute (CMCRC/RI) (Bentivoglio, Italy). and mainly through milk during lactation. After wean- The study protocol was approved by the Ethical Com- ing, the offspring (F1) were treated through drinking mittee of Ramazzini Institute. The protocol of the ex- water until sacrifice. periment was also approved and formally authorized by The timeline of the experimental animal treatment the ad hoc commission of the Italian Ministry of Health and fecal sample collection is shown in Fig. 1. As illus- (ministerial approval n. 710/2015-PR). The CMCRC/RI trated, rat fecal samples were individually collected from animal breeding facility was the supplier for the all animals of the F0 generation (8 dams) from each Sprague-Dawley (SD) rats. Female breeders SD rats group before mating, at GD 5 (before the starting of the were placed individually in Polycarbonate cage treatment), GD 13, lactation day (LD) 7 and LD 14. (42x26x18cm; Tecniplast Buguggiate, Varese, Italy) with Fecal samples were also collected from 108 F1 pups, 18 a single unrelated male until evidence of copulation males and 18 females from each group during lactation was observed. After mating, matched females were at PND 7 and PND 14 (corresponding to LD 7 and 14 housed separately during gestation and delivery. New- for dams), before the achievement of puberty at PND 31, borns were housed with their mothers until weaning. after puberty at PND 57 and in adulthood at PND 125. Weaned offspring were co-housed, by sex and treat- Due to technical difficulty to identify fecal samples from ment group, not more than 3 per each cage. Cages were individual pups during lactation, only pooled samples at identified by a card indicating: study protocol code, ex- PND 7 and PND 14 were collected for each cage from perimental and pedigree numbers, dosage group. A the whole litter, not distinguished by gender. After wean- shallow layer of white fir wood shavings served as ing, fecal samples from each pup were individually Mao et al. Environmental Health (2018) 17:50 Page 4 of 12 Fig. 1 Timeline of the experimental animal treatment and fecal sample collection collected. About 2–3 droppings, collected directly from possible environmental contamination during the sample the anus of each animal, were preserved in cryovials on procession. The split high-quality reads were further an ice bed then stored at − 20 °C until shipment on dry processed by QIIME 1.9.0 . We used the command ice to the Icahn School of Medicine at Mount Sinai. For- pick_open_reference_otus.py with the defaulted green_ ceps used for collecting droppings were washed and gene 97_otus reference sequences to cluster of > 97% cleaned using sterile water and 1% sodium bicarbonate similar sequencing reads as an OTU using uclust . between each sampling to avoid cross contamination. Representative sequences for each OTU were aligned using PyNAST and build the phylogenetic tree. Finally, Bacterial 16S PCR and sequencing the QIIME generated biom-formatted OTU table con- Rat fecal DNA was extracted using the QIAamp PowerFe- tains the taxonomic information and absolute counts for cal DNA Kit (Qiagen, Valencia, CA) following the manu- each identified taxon in each sample. facturer’s instructions. Total DNA concentration was The diversity within each microbial community, so- determined by Qubit 2.0 Fluorometer (Life technologies, called alpha-diversity, was calculated using the Shannon Norwalk, CT). The phylogenetically informative V3–V4 Index  as metric and represented the measure of the region of 16S rRNA gene was amplified using universal diversity at the family and genus level. The overall micro- primer 347F/803R [33, 34] with dual-barcoding approach biome dissimilarities among all samples were accessed previously described . The integrity of the 16S PCR using the weighted UniFrac distance matrices . Non- amplicons was verified by agarose gel electrophoresis. The metric multiple dimensional scaling (NMDS) were used to resulting ~ 460-bp sized amplicons were pooled and then visualize the dissimilarities. The permutational multivari- sequenced with the Illumina MiSeq 2 × 250 paired-end se- ate analysis of variance PERMANOVA test , with the quencing platform at OCS genome technology center of maximum number of permutations = 999, was performed New York University Langone Medical Center. to assess the significance of the overall microbiome differ- ences between groups by collection timepoints and treat- 16S data analysis ment. The PERMANOVA procedure using the [Adonis] The sequencing data were merged and filtered to function of the R package vegan 2.0–5 partitions the remove the merged reads with a length of < 400 bp or distance matrix among sources of variation, fits linear the quality score of < Q30 at more than 1% of bases. models to distance matrices and uses a permutation test Sequentially, all filtered high quality reads were split by with pseudo-F ratios to obtain the p values. Using the dual-barcode and trimmed of primer regions using a LEfSe method , we further selected the microbiome self-defined bash script to integrate several sequencing features significantly associated to time of collection and processing commands from fastx , QIIME [37, 38], treatments at various taxonomic ranks. and seqtk . Duplicated measurements of four sample were processed and sequenced using different barcodes Results to test the sequencing reproducibility. Five blank sam- No unexpected clinical signs or symptoms were ob- ples were also sequenced and referenced to filter the served in the experimental animals during the in vivo Mao et al. Environmental Health (2018) 17:50 Page 5 of 12 phase. In particular, no sign of changes in maternal be- of the differences at overall rat gut microbiome between havior during lactation (nesting and nursing) were ob- treatment and control. The test results (p-values shown served during the experiment. There was no clinical in Fig. 3b) showed that the overall microbiome was sig- evidence of alterations in activity or behavior in pups. nificantly altered by both Roundup and glyphosate treat- Body weight, water and feed consumption both in dams ment compared to controls. Similarly, we also found and pups were no different across the groups. Litter significant differences in microbiota between Roundup sizes were fully comparable among groups, with mean and glyphosate exposed F1 pups. We also observed that number of live pups: control group 13.6 (range 10–16); the overall microbiome was significantly different by sex glyphosate group 13.3 (range 11–17); Roundup group at PND 125 (p-value = 0.028, 0.007 and 0.013 by PER- 13.9 (range 11–16). MANOVA test for Glyphosate, Roundup and control We extract the total DNAs from 433 SD rat fecal sam- group, respectively). To adjust for the sex effect, we per- ples. Following the timeline illustrated in Figs. 1, 120 formed additional multivariable PERMANOVA test with fecal samples were collected from 24 F0 dams in three both treatment and sex as predictive variables. We found treatment groups and at five time points (before mating, that those test results were consistent (Fig. 3b). However, GD5, GD13, LD7 and LD14). From F1 pups, we col- none of the F0 dam groups showed significant differ- lected 313 fecal samples, in which 13 at PND 7, 24 at ences in overall microbiota diversity.. PND 14, 108 each at PND 31 and PND 57, and 60 at The linear discriminant analysis effect size (LEfSe)ana- PND 125. We observed that the fecal samples of pups at lysis was performed using 16S sequencing data from rat PND 7 and PND 14 showed significant low DNA yields fecal samples in order to select particular discriminative (Additional file 1: Figure S1A). We further performed features of the glyphosate exposure. Consistently with the microbiome survey on 433 SD rat fecal samples, and 5 overall microbiome changes by exposure at different age water blanks using bacterial 16S sequencing on Illumina groups (Fig. 3), we found several significant differential MiSeq 2 × 250 pair-end platform. After merging and taxa features associated with exposure. In particular, at filtering by read length > 400 bp and the quality score > PND 31, the results showed that the microbiota of both Q30 at more than 99% of bases, we obtained ~ 2 million glyphosate and Roundup exposed pups had significantly high quality reads (the average number of reads = 4576 higher prevalence of Prevotella genus (Bacteroidetes per sample with standard deviation = 6567). The number phylum) and Mucispirillum genus (Deferribacteres of reads were not significant different by exposure type phylum) and lower prevalence of Lactobacillus genus (Fir- (Additional file 1: Figure S1A). The taxa composition micutes phylum) and Aggregatibacter genus (Proteobac- was grouped by age and the exposure types and summa- teria phylum) (Fig. 4a 1–2). However, some of the selected rized in Additional file 1: Figure S1B. We also provided features were treatment specific. For instance, among the the complete taxonomic OTU tables in Additional file 2. most significant features with LDA score > 3.0 and p- The overall microbiome dissimilarity, defined by beta- value< 0.05, we found increased Blautia genus (Firmicutes diversity, was visualized by non-parametric multi- phylum) and decreased Streptococcus genus (Firmicutes dimensional scaling (NMDS) plot of all samples (Fig. 2a) phylum) and Rothia genus (Actinobacteria phylum) only , dams only (Fig. 2b) and pups only (Fig. 2c). We found in glyphosate exposed PND 31 pups, but not in Roundup that the early postnatal samples at PND 7 and PND 14 exposed samples. In contrast, increased Parabacteroides were far apart from the dams at LD 7 and LD 14 while genus (Bacteroidetes phylum) and Veillonella genus (Fir- the later postnatal samples at PND 31, PND 57 and micutes phylum) were only found in Roundup exposed PND 125 were clustering with the dams (Fig. 2a). The pups, but not in glyphosate exposed samples at PND 31. mean and variance of the within-community diversity Between two exposures (Fig. 4a 3), Roundup exposed pups (α diversity) measured by Shannon index showed that showed increased Clostridia class (Firmicutes phylum), in the samples from dams possessed higher, while early particular, Blautia genus and Actinobacteria class (Actino- postnatal samples from pups showed lower α diversity bacteria phylum), in particular, Rothia and Bifidobacter- (Fig. 2d). Student t-test showed significantly increased ium genera at PND 31. Furthermore, we found the α diversity from PND 14 to PND 31 (p-value< 0.05 for treatment associated taxa features were not consistent at all treatment groups) but no differences between sam- different postnatal time points. Many features selected at ples at same age but different treatment group. PND 31 did not appeared at PND 57 (Fig. 4a 4–6, We compared the overall microbiome changes by Additional file 3: Figure S2), suggesting the less stability of treatment at different age groups from pups and dams. early-life microbiota and continuous effect on gut micro- Nonmetric multidimensional scaling (NMDS) plots visu- biota by the exposure. When counting the total abun- alized the overall microbiome dissimilarities by treat- dance % of the significant differential taxa by treatments, ment at PND 31 and 57 (Fig. 3a). The PERMANOVA the pups showed much higher impact by exposure than test was used at each age group to test the significance the dams (Fig. 4b). Mao et al. Environmental Health (2018) 17:50 Page 6 of 12 ab cd Fig. 2 The overall microbiome diversity. a, b,and c are non-metric dimensional scaling (NMDS) plots visualize the overall microbiome dissimilarities (beta-diversity) between individual rat across time. a All samples from SD dams (pink) and pups (green) of three treatment groups; b All samples from SD dam rats only. Colors indicate sample collection timepoint. BM: before mating; GD 5: gestation day 5; GD 13: gestation day 13; LD 7: lactation day 7; and LD 14: lactation day 14. c All samples from SD pup rats only. Colors indicate sample collection timepoint. PND 7 to PND 125: postnatal day 7 to postnatal day 125. d Box plots show the mean and variance of the within-community diversity (alpha-diversity) measured by Shannon index in three treatment groups across all time of collections Discussion cardiovascular disorders  and central nervous system GBHs are the most applied herbicides worldwide; dysfunctions such as learning and memory impairment, humans are commonly exposed to these environmental anxiety, stress, depression  and autism . These chemicals at a wide range of doses depending upon the chronic pathologies (non-communicable diseases – job setting (farming vs. food consumption) and route of NCDs) may occur even at doses that are much lower exposure (ingestion vs. inhalation). Environmental con- than the ones considered during risk assessment, in par- tamination from GBHs is now ubiquitous and residues ticular during sensitive periods of life (such as fetal de- of glyphosate has been found in air , groundwater velopment) [7, 22]. , drinking-water , crops , food  and ani- Recent advances in human microbiome research sug- mal feed . The possible effects of GBHs on human gested that the gut microbiome is a key player in human health are the subject of an intense public debate, for metabolism [64–66]. It is thus reasonable to hypothesize both its potential carcinogenic and non-carcinogenic ef- that exposure to environmental chemicals may modify fects, including endocrine disruption [52, 53], neurotox- the gut microbiome and its metabolites and ultimately icity , developmental and reproductive toxicity , influence human health. Microbiota-generated metabo- autoimmunity , gastrointestinal disorders , obes- lites and their cellular and molecular components are in- ity, diabetes [58–60], and other metabolic and creasingly being recognized as an essential part of Mao et al. Environmental Health (2018) 17:50 Page 7 of 12 Fig. 3 The effect of glyphosate exposure on overall microbiome diversity. a NMDS plots visualize the overall microbiome dissimilarities (beta-diversity) between individual rat of three treatments at PND 31 and PND 57. b PERMANOVA test is performed to test the significance among all three treatments (displayed in NMDS plots) and between two treatments (values are listed in tables). The p-values in parenthesis were adjusted for genders. G: glyphosate; R:Roundup; C:controlwater human physiology, with profound effects on the homeo- modulate the composition of the gut microbiome. In this stasis of the host organism. Unfortunately, determining study, when compared to the adult rat dams, the gut the concentrations of these biologically active substances microbiome of pups at PND 7 and 14 showed lower in target cells presents serious difficulties related to the taxonomical richness but higher variance within sample extraction and processing of samples, especially faecal and higher sample-to-sample dissimilarity . One pit- material, and the limitations of currently available meas- fall of our study was that direct measurements of expos- urement techniques . Meta-omics and evolving com- ure to GBHs in milk was not performed . In our putational frameworks will hopefully lead to the pilot study we simply reproduced the human exposure, systematic prediction and discovery of more microbial which includes lactation as only source of nourishment metabolites and components involved in neuroendo- for pups from birth until around PND 21. The short- crine, immune, metabolic, and epigenetic pathways. comings concerning the analysis of glyphosate in breast Rats are proposed to be more representative of the hu- milk are mainly related to the difficulty and stressing man gut microbiota than mice because the gut bacterial technical procedure for collecting milk from dams and communities of humanized rats more closely reflect the to the complex nature of the breast milk matrix. Indeed, gut microbiota of human donors [67, 68]. We have previ- milk is an aqueous mixture of carbohydrates, proteins ously used our animal model, SD rats, to study the effect and fat. Analytical methods developed for watery matri- of postnatal low-dose exposure to environmental chemi- ces cannot be directly transferred to breast milk. In April cals on windows of susceptibility and on the gut micro- 2014, a non-peer-reviewed report was published, in biome. The study  showed the low-level phthalate, which glyphosate in breast milk of American mothers paraben and triclosan exposure altered the gut micro- was detected in 3 out of 10 samples ranging from 76 to biome of adolescent rats. These results are consistent with 166 ng/mL. In this study, the concentration of glypho- other studies, indicating our animal model as a suitable sate in milk samples was determined by enzyme-linked model for studying microbiome [70, 71]. immunosorbent assay (ELISA) . The limit of quanti- Since glyphosate has shown enzyme inhibition activity fication (LOQ) of the assay was given as 75 μg/L in milk. in plants and microorganisms, we therefore postulate Other studies, based on liquid chromatography–tandem that low-dose exposure to glyphosate or GBHs may also mass spectrometry (LC-MS/MS) and a gas Mao et al. Environmental Health (2018) 17:50 Page 8 of 12 Fig. 4 Differential microbial features selected via LEfSe between treatment. a Clad plots visualize the significant differential taxa features from phylum (inner circle) to genus (outer circle) at PND 31 and PND 57. Color indicates the more abundant taxa under each condition. b The table lists the overall abundance of the significant differential taxa between treatment across time chromatography–tandem mass spectrometry (GC-MS/ adult dams. Previous evidence has shown that the gut MS) methods, have found no evidence of transfer of gly- microbiota at postnatal age is less stable than at adult phosate into milk. Both methods have been fully vali- age and it changes over the first several years of life . dated and reported as suitable for the determination of The maturation of the gut microbiota has been proven glyphosate with an LOQ of 1 ng/mL [72, 74]. Neverthe- to be affected by multiple factors, for instance, diet, less, future independent research is needed, considering medications, host genetics, etc. . Disruption of the different educational and ethnic backgrounds, location microbiota during its maturation by low doses of various of residence (e.g., urban compared with rural), occupa- environmental chemicals has been showed to alter host tional and dietary glyphosate exposure and adequate phenotypes, such as weight, metabolism and other dis- sample size of the cohort. ease risk . Our data suggests that the prepubertal Our results revealed that both glyphosate and glypho- age microbiota is more sensitive to GBH exposure com- sate formulated Roundup, at doses admitted in humans, pared to the adult microbiota, therefore the postnatal including children and pregnant women, significantly al- age is likely a “window of susceptibility” for GBHs to tered the microbiota diversity and resulted in prominent modulate the gut microbiome. changes at multiple taxon in exposed pups. However, Furthermore, our results showed that the overall those effects on microbiota were not significant in the microbiome diversity and composition were significantly Mao et al. Environmental Health (2018) 17:50 Page 9 of 12 different between Roundup and glyphosate, suggesting perturbations may impact subsequent health outcomes. possible synergistic effects of the mixed formulation on Nevertheless, these data strongly indicate that GBHs ex- gut microbiota. As most of GBHs contains multiple sur- posure can exerts biological effects early in development factants and adjuvants might act differently than glypho- which may have long-lasting health effects later in life. sate alone, it is not only important to understand the individual effects of glyphosate, but also the synergistic Conclusion impact of mixed formulations. In fact adjuvants might Our pilot study provides initial evidence that maternal ex- act alone or in a synergistic manner and increase the posure to commonly used GBHs, at doses currently con- toxic effects of glyphosate [78–81]. sidered as acceptable in humans, is capable of modifying In addition, both clinical and experimental studies the gut microbiota in rat pups, in particular before puberty showed impact of gut microbiota on the gut-brain axis (PND 31). Further long-term investigations are necessary (which mainly includes the immune, neuroendocrine, to elucidate if the shift in the microbiota induced by GBHs and neural pathways) [82–84] in an age-dependent man- exposure is contributing to the downstream other health ner . Gut bacteria communicating with the host effects. Nevertheless, understanding the microbiota through the microbiota-gut-brain axis could influence changes during this critical window of susceptibility could brain and behavior . In particular, the changes at be of great importance for disease prevention. The poten- postnatal microbiota may affect the neurvous system, tial health effects of GBHs during development, such as reflecting by changes in levels of pituitary hormones in- childhood, warrant further investigation. cluding ACTH [83, 87], cortisol, BNDF  and etc. Sprague-Dawley rats represent an excellent animal model to explore these early-life effects as their micro- Additional files biome is more similar to that of humans than the micro- Additional file 1: Figure S1. 16S microbiome profiling. A. Dot plot biota profile of mice . shows the distribution of the number of reads in three treatment groups. This study has some limitations. First, the actual levels The Wilcoxon test significance between two groups was listed in table of GBHs that reached the fetus during gestation or on the right and the diagonal of the table shows the average reads of each group. B. Box plot shows the mean and variation of total DNA through milk consumption postnatally by the offspring concentrations from rat fecal samples. C. Bar plot showed the mean cannot be accurately estimated. Second, we only col- abundance of microbial composition at phylum level for each treatment lected maternal feces so that we cannot fully evaluate and time of collection. (PDF 174 kb) the role of maternal microbiota in the fetal development Additional file 2: 16S OTU table in biom format. (BIOM 6871 kb) without the maternal sample/data collection from oral, Additional file 3: Figure S2. The changes of lactobacillus and Prevotella during the time of sampling. Line plots show the mean and standard error vaginal and other body sites. Indeed, in recent years it is of relative abundance% of Lactobacillus (upper figure) and Prevotella (lower becoming apparent that, besides breast milk, other figure) during the time of sampling from PND 7 to PND 125. (PDF 543 kb) sources could allow maternal-offspring microbial trans- fer. Rodents “inherit” their microbiomes in a similar Abbreviations fashion to all placental mammals, including humans: ACTH: Adrenocorticotropic hormone; AMPA: Aminomethylphosphonic acid; through vaginal delivery and close maternal association BDNF: brain-derived neurotrophic factor; CMCRC: Cesare Maltoni Cancer throughout the neonatal period (vertical transmission). Research Center; DOHaD: Developmental origins of health and disease; ELISA: Enzyme-linked immunosorbent assay; EPSPS: 5-Enolpyruvylshikimate-3- Maternal vaginal, skin, mammary fecal and oral micro- phosphate synthase; EU: European Union; GBH: Glyphosate-based herbicides; biomes, microbial spreading in bedding are efficiently GC-MS/MS: gas chromatography–tandem mass spectrometry; transmitted to offspring and represent other possible GD: Gestational day; GM: Genetically modified; LC-MS/MS: Chromatography– tandem mass spectrometry; LD: Lactating day; LDA: Linear discriminant mechanisms of maternal influences on pups intestinal analysis; LEfSe: Linear discriminant analysis effect size; LOQ: Limit of colonization . Finally, the microbiome survey used a quantification; NCDs: Non-communicable diseases; NMDS: Non-metric cost-effective 16S amplicon targeted sequencing ap- multiple dimensional scaling; OUT: operational taxonomic unit; PND: Post natal day; PyNAST: Python nearest alignment space termination; proach. This technique allows us to identify differential QIIME: Quantitative insights into microbial ecology; RI: Ramazzini Institute; taxa compositions by exposure only to genus level. Add- SD: Sprague-Dawley; US ADI: United States Acceptable Daily Intake itional meta-genomics and meta-transcriptomic analysis may need to visualize the functional and metabolic alter- Acknowledgements nations and identify bacterial features at species/strain We thank the over 30.000 associates and volunteers of the Ramazzini Institute that made this pilot study possible through their commitment and level. In addition, given the differences in taxonomic generosity. We thank the Municipality of Bologna, the Emilia-Romagna composition of the microbiomes of rats and humans, Region, and the International Society of Doctors for Environment for the extent to which the results of this analysis can be organizing several events to promote this pilot study; “Coop Reno” and “Coopfond Fondo Mutualistico Legacoop” for supporting our research relevant to humans is not clear. Future work should in- activity. We thank the OCS genome technology center of New York vestigate how the route and concentration of exposure University Langone Medical Center for the library preparation and impact the rat microbiome, and quantify how these sequencing service. Mao et al. Environmental Health (2018) 17:50 Page 10 of 12 Funding 11. Tarazona JV, Court-Marques D, Tiramani M, Reich H, Pfeil R, Istace F, et al. This work was funded by Institution fund of Ramazzini Institute, Bologna, Glyphosate toxicity and carcinogenicity: a review of the scientific basis of Italy; Fondazione del Monte di Bologna e Ravenna (Bank Foundation), the European Union assessment and its differences with IARC. Arch Bologna, Italy; MSSM seed fund (JH) and CL and JC were supported by the Toxicol. 2017;91:2723–43. NIH/NIEHS P30ES023515. 12. Samsel A, Seneff S. Glyphosate, pathways to modern diseases III: manganese, neurological diseases, and associated pathologies. Surg Neurol Int. 2015;6:45. Availability of data and materials 13. IARC. Some organophosphate insecticides and herbicides. 2015. 16S rRNA gene sequencing information has been deposited into EMBL 14. Frye RE, Nankova B, Bhattacharyya S, Rose S, Bennuri SC, MacFabe DF. Nucleotide Sequence Database (ENA) with Project ID PRJEB24653 (ERP106496). Modulation of immunological pathways in autistic and neurotypical lymphoblastoid cell lines by the enteric microbiome metabolite propionic Authors’ contributions acid. Front Immunol. 2017;8:1670. QXM performed the fecal sample processing, PCR and library preparation, 15. Oleskin AV, Shenderov BA. Neuromodulatory effects and targets of the performed microbial sequencing analysis and bioinformatics, and drafted the SCFAs and gasotransmitters produced by the human symbiotic microbiota. manuscript. FM, SP, DM participated in the design of the study, performed Microb Ecol Heal Dis. 2016;27:30971. the animal experiments and sample collection, and drafted the manuscript. 16. MacFabe DF. Enteric short-chain fatty acids: microbial messengers of IM, AV, LB and LF performed the animal experiments and collected the metabolism, mitochondria, and mind: implications in autism spectrum samples. CL helped to draft the manuscript. FB and JC supervised the study, disorders. Microb Ecol Heal Dis. 2015;26:28177. participated in the design of the study and helped to draft the manuscript. 17. den Besten G, van Eunen K, Groen AK, Venema K, Reijngoud D-J, Bakker BM. JH conceived of the overall study, supervised the overall experiment, The role of short-chain fatty acids in the interplay between diet, gut implemented the bioinformatics, and coordination and draft the manuscript. microbiota, and host energy metabolism. J Lipid Res. 2013;54:2325–40. All authors read and approved the final manuscript. 18. Rooks MG, Garrett WS. Gut microbiota, metabolites and host immunity. Nat Rev Immunol. 2016;16:341–52. Ethics approval and consent to participate 19. Newman MM, Hoilett N, Lorenz N, Dick RP, Liles MR, Ramsier C, et al. Not applicable. Glyphosate effects on soil rhizosphere-associated bacterial communities. Sci Total Environ. 2016;543:155–60. Competing interests 20. Duke SO, Lydon J, Koskinen WC, Moorman TB, Chaney RL, Hammerschmidt The authors declare that they have no competing interests. R. Glyphosate effects on plant mineral nutrition, crop rhizosphere microbiota, and plant disease in glyphosate-resistant crops. J Agric Food Publisher’sNote Chem. 2012;60:10375–97. Springer Nature remains neutral with regard to jurisdictional claims in 21. Krüger M, Shehata AA, Schrödl W, Rodloff A. Glyphosate suppresses the published maps and institutional affiliations. antagonistic effect of enterococcus spp. on Clostridium botulinum. Anaerobe. 2013;20:74–8. Author details 22. Shehata AA, Schrödl W, Aldin AA, Hafez HM, Krüger M. The effect of Department of Genetics and Genomic Sciences, Icahn School of Medicine at glyphosate on potential pathogens and beneficial members of poultry Mount Sinai, 1428 Madison, New York, NY 10029, USA. Department of microbiota in vitro. Curr Microbiol. 2013;66:350–8. Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational 23. Ackermann W, Coenen M, Schrödl W, Shehata AA, Krüger M. The Cancer Research, Cancer Institute of Jiangsu Province, Nanjing Medical influence of glyphosate on the microbiota and production of botulinum University Affiliated Cancer Hospital, Nanjing, China. Cesare Maltoni Cancer neurotoxin during ruminal fermentation. Curr Microbiol. 2014;70:374–82. Research Center (CMCRC), Ramazzini Institute (RI), Via Saliceto, 3, 40010 4 24. Houf K, Stephan R. Isolation and characterization of the emerging foodborn Bentivoglio, Bologna, Italy. Department of Veterinary Medical Sciences, 5 pathogen Arcobacter from human stool. J Microbiol Methods. 2007;68:408–13. University of Bologna, Bologna, Italy. Department of Agricultural Sciences, 25. Kurenbach B, Marjoshi D, Amábile-Cuevas CF, Ferguson GC, Godsoe W, University of Bologna, Bologna, Italy. Department of Environmental Gibson P, et al. Sublethal exposure to commercial formulations of the Medicine and Public Health, Icahn School of Medicine at Mount Sinai, 1428 herbicides dicamba, 2,4-dichlorophenoxyacetic acid, and glyphosate cause Madison, New York, NY 10029, USA. changes in antibiotic susceptibility in Escherichia coli and Salmonella enterica serovar typhimurium. MBio. 2015;6(2):e00009-1. Received: 2 February 2018 Accepted: 10 May 2018 26. Heindel JJ, Vandenberg LN. Developmental origins of health and disease: a paradigm for understanding disease cause and prevention. Curr Opin Pediatr. 2015;27:248–53. References 1. Franz J, Mao M. Sikorski J. A Unique Global Herbicide: Glyphosate; 1997. 27. Wang Z, Klipfell E, Bennett BJ, Koeth R, Levison BS, Dugar B, et al. Gut flora 2. Benbrook CM. Trends in glyphosate herbicide use in the United States and metabolism of phosphatidylcholine promotes cardiovascular disease. globally. Environ Sci Eur. 2016;28:3. Nature. 2011;472:57–65. 3. Myers JP, Antoniou MN, Blumberg B, Carroll L, Colborn T, Everett LG, et al. 28. Adams JB, Johansen LJ, Powell LD, Quig D, Rubin RA. Gastrointestinal flora Concerns over use of glyphosate-based herbicides and risks associated with and gastrointestinal status in children with autism - comparisons to typical exposures: a consensus statement. Environ Health. 2016;15:19. children and correlation with autism severity. BMC Gastroenterol. 2011;11:22. 4. Bovey RW, Miller FR, Baur JR. Preharvest desiccation of grain Sorghum with 29. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An glyphosate. Agron J. 1975;67:618–21. obesity-associated gut microbiome with increased capacity for energy 5. Toledo MZ, Ishizuka MS, Cavariani C, De Barros F-NJ, Picoli LB. Pre-harvest harvest. Nature. 2006;444:1027–31. desiccation with glyphosate and quality of stored soybean seeds. Semin 30. Mesnage R, Antoniou MN. Facts and fallacies in the debate on glyphosate Agrar. 2014;35:765–73. toxicity. Front Public Heal. 2017;5:316. 6. Schönbrunn E, Eschenburg S, Shuttleworth WA, Schloss JV, Amrhein N, 31. EPA. Reregistration eligibility decision (RED) glyphosate. 1993. Evans JN, et al. Interaction of the herbicide glyphosate with its target 32. Laukens D, Brinkman BM, Raes J, De Vos M, Vandenabeele P. enzyme 5-enolpyruvylshikimate 3-phosphate synthase in atomic detail. Proc Heterogeneity of the gut microbiome in mice: guidelines for optimizing Natl Acad Sci U S A. 2001;98:1376–80. experimental design. FEMS Microbiol Rev. 2015;40:117–32. 7. On C, Peer P. Conclusion on the peer review of the pesticide risk 33. Franzén O, Hu J, Bao X, Itzkowitz SH, Peter I, Bashir A. Improved OTU- assessment of the active substance glyphosate. EFSA J. 2015;13:4302. icking using long-read 16S rRNA gene amplicon sequencing and generic 8. ECHA. Echa’s committee for risk assessment (rac). 2017. hierarchical clustering. Microbiome. 2015;3:43. 9. EPA. Draft human health and ecological risk assessments for glyphosate. 2017. 34. Nossa CW, Oberdorf WE, Yang L, Aas JA, Paster BJ, Desantis TZ, et al. Design 10. Abraham W. Glyphosate formulations and their use for the inhibition of 5- of 16S rRNA gene primers for 454 pyrosequencing of the human foregut enolpyruvylshikimate-3-phosphate synthase. 2010. US Patent n. microbiome. World J Gastroenterol. 2010;16:4135–44. US7771736B2. Mao et al. Environmental Health (2018) 17:50 Page 11 of 12 35. Torres J, Bao X, Goel A, Colombel JF, Pekow J, Jabri B, et al. The features of 60. Knip M, Siljander H. The role of the intestinal microbiota in type 1 diabetes mucosa-associated microbiota in primary sclerosing cholangitis. Aliment mellitus. Nat Rev Endocrinol. 2016;12:154–67. Pharmacol Ther. 2016;43:790–801. 61. Tang WHW, Hazen SL. The contributory role of gut microbiota in 36. Schmieder R, Edwards R. Quality control and preprocessing of cardiovascular disease. J Clin Invest. 2014;124:4204–11. metagenomic datasets. Bioinformatics. 2011;27:863–4. 62. Dinan TG, Cryan JF. Melancholic microbes: a link between gut microbiota 37. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello and depression? Neurogastroenterol Motil. 2013;25:713–9. EK, et al. QIIME allows analysis of high-throughput community sequencing 63. Vuong HE, Hsiao EY. Emerging roles for the gut microbiome in autism data. Nat Methods. 2010;7:335–6. Spectrum disorder. Biol Psychiatry. 2017;81(5):411-23. 38. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello 64. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. EK, et al. Correspondence QIIME allows analysis of high- throughput A core gut microbiome in obese and lean twins. Nature. 2009;457:480–4. community sequencing data intensity normalization improves color calling 65. Turnbaugh PJ, Gordon JI. The core gut microbiome, energy balance and in SOLiD sequencing. Nat Publ Gr. 2010;7:335–6. obesity. J Physiol. 2009;587(Pt 17):4153–8. 39. Shen W, Le S, Li Y, Hu F. SeqKit: a cross-platform and ultrafast toolkit for 66. Cho I, Blaser MJ. The human microbiome: at the interface of health and FASTA/Q file manipulation. PLoS One. 2016;11(10):e0163962. disease. Nat Rev Genet. 2012;13:260–70. 40. Edgar RC. Search and clustering orders of magnitude faster than BLAST. 67. Flemer B, Gaci N, Borrel G, Sanderson IR, Chaudhary PP, Tottey W, et al. Bioinformatics. 2010;26:2460–1. Fecal microbiota variation across the lifespan of the healthy laboratory rat. 41. Shannon CE. A mathematical theory of communication. Bell Syst Tech J. Gut Microbes. 2017;8:428–39. July 1928;1948(27):379–423. 68. Wos-Oxley ML, Bleich A, Oxley APA, Kahl S, Janus LM, Smoczek A, et al. 42. Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparing Comparative evaluation of establishing a human gut microbial community microbial communities. Appl Environ Microbiol. 2005;71:8228–35. within rodent models. Gut Microbes. 2012;3:234–49. 43. Anderson MJ. A new method for non parametric multivariate analysis of 69. Hu J, Raikhel V, Gopalakrishnan K, Fernandez-Hernandez H, Lambertini L, variance. Austral Ecol. 2001;26:32–46. Manservisi F, et al. Effect of postnatal low-dose exposure to environmental 44. Oksanen J. Multivariate analysis of ecological communities in R: vegan chemicals on the gut microbiome in a rodent model. Microbiome. 2016; tutorial. R Doc. June 10, 2015. http://www.cc.oulu.fi/~jarioksa/opetus/ 4(1):26. metodi/vegantutor.pdf. Accessed 14 May 2018. 70. Gao B, Tu P, Bian X, Chi L, Ru H, Lu K. Profound perturbation induced by 45. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. triclosan exposure in mouse gut microbiome: a less resilient microbial Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12:R60. community with elevated antibiotic and metal resistomes. BMC Pharmacol 46. Majewski MS, Coupe RH, Foreman WT, Capel PD. Pesticides in Mississippi air Toxicol. 2017;18(1):46. and rain: a comparison between 1995 and 2007. Environ Toxicol Chem. 71. Yee AL, Gilbert JA. Is triclosan harming your microbiome? Science. 2016;353: 2014;33:1283–93. 348–9. 47. Battaglin WA, Meyer MT, Kuivila KM, Dietze JE. Glyphosate and its 72. Mcguire MK, Mcguire MA, Price WJ, Shafii B, Carrothers JM, Lackey KA, et al. degradation product AMPA occur frequently and widely in U.S. soils, surface Glyphosate and aminomethylphosphonic acid are not detectable in human water, groundwater, and precipitation. J Am Water Resour Assoc. 2014;50: milk. Am J Clin Nutr. 2016;103:1285–90. 275–90. 73. Honeycutt Z, Rowlands H. Glyphosate Testing Full Report: Findings in 48. Rendón-Von Osten J, Dzul-Caamal R. Glyphosate residues in groundwater, American Mothers’ Breast Milk, Urine and Water. 2014. https://www. drinking water and urine of subsistence farmers from intensive agriculture momsacrossamerica.com/glyphosate_testing_results . Accessed 14 May localities: a survey in Hopelchén, Campeche, Mexico. Int J Environ Res 2018. Public Health. 2017;14(6):E595. 74. Steinborn A, Alder L, Michalski B, Zomer P, Bendig P, Martinez SA, et al. 49. Cuhra M. Review of GMO safety assessment studies: glyphosate residues in Determination of glyphosate levels in breast milk samples from Germany by roundup ready crops is an ignored issue. Environ Sci Eur. 2015;27:20. LC-MS/MS and GC-MS/MS. J Agric Food Chem. 2016;64:1414–21. 50. EFSA. The 2014 European Union report on pesticide residues in food. EFSA 75. Rodríguez JM, Murphy K, Stanton C, Ross RP, Kober OI, Juge N, et al. The J. 2016;14:4611. composition of the gut microbiota throughout life, with an emphasis on early life. Microb Ecol Heal Dis. 2015;26:26050. 51. Mesnage R, Defarge N, Rocque LM, De Vendômois JS, Séralini GE. Laboratory rodent diets contain toxic levels of environmental contaminants: 76. Jakobsson HE, Jernberg C, Andersson AF, Sjölund-Karlsson M, Jansson JK, implications for regulatory tests. PLoS One. 2015;10(7):e0128429. Engstrand L. Short-term antibiotic treatment has differing long-term 52. Gasnier C, Dumont C, Benachour N, Clair E, Chagnon MC, Séralini GE. impacts on the human throat and gut microbiome. PLoS One. 2010;5:e9836. Glyphosate-based herbicides are toxic and endocrine disruptors in human 77. Suez J, Korem T, Zeevi D, Zilberman-Schapira G, Thaiss CA, Maza O, et al. cell lines. Toxicology. 2009;262:184–91. Artificial sweeteners induce glucose intolerance by altering the gut 53. Romano MA, Wisniewski P, Viau P, Romano RM, Campos DA, Bernardi MM, microbiota. Nature. 2014;514:181–6. et al. Glyphosate impairs male offspring reproductive development by 78. Coalova I. Ríos de Molina M del C, Chaufan G. Influence of the spray disrupting gonadotropin expression. Arch Toxicol. 2012;86:663–73. adjuvant on the toxicity effects of a glyphosate formulation. Toxicol Vitr. 2014;28:1306–11. 54. Cattani D, de Liz Oliveira Cavalli VL, Heinz Rieg CE, Domingues JT, Dal-Cim T, Tasca CI, et al. Mechanisms underlying the neurotoxicity induced by 79. Mesnage R, Bernay B, Séralini GE. Ethoxylated adjuvants of glyphosate- glyphosate-based herbicide in immature rat hippocampus: involvement of based herbicides are active principles of human cell toxicity. Toxicology. glutamate excitotoxicity. Toxicology. 2014;320:34–45. 2013;314:122–8. 55. Williams AL, Watson RE, Desesso JM. Developmental and reproductive 80. Defarge N, Takács E, Lozano VL, Mesnage R, de Vendômois JS, Séralini GE, et outcomes in humans and animals after glyphosate exposure: a critical al. Co-formulants in glyphosate-based herbicides disrupt aromatase activity analysis. Journal of Toxicology and Environmental Health-Part B: Critical in human cells below toxic levels. Int J Environ Res Public Health. 2016; Reviews. 2012;15:39–96. 13(3):E264. 56. Chen J, Chia N, Kalari KR, Yao JZ, Novotna M, Soldan MMP, et al. Multiple 81. Williams GM, Kroes R, Munro IC. Safety evaluation and risk assessment of sclerosis patients have a distinct gut microbiota compared to healthy the herbicide roundup and its active ingredient, glyphosate, for humans. controls. Sci Rep. 2016;6:28484. Regul Toxicol Pharmacol. 2000;31(2 I):117–65. 57. Cenit MC, Olivares M, Codoñer-Franch P, Sanz Y. Intestinal microbiota and 82. Foster JA, McVey Neufeld KA. Gut-brain axis: how the microbiome celiac disease: Cause, consequence or co-evolution? Nutrients. 2015;7:6900–23. influences anxiety and depression. Trends Neurosci. 2013;36:305–12. 58. Cani PD, Geurts L, Matamoros S, Plovier H, Duparc T. Glucose metabolism: 83. Heijtz RD, Wang S, Anuar F, Qian Y, Bjorkholm B, Samuelsson A, et al. focus on gut microbiota, the endocannabinoid system and beyond. Normal gut microbiota modulates brain development and behavior. Proc Diabetes and Metabolism. 2014;40:246–57. Natl Acad Sci. 2011;108:3047–52. 59. De Goffau MC, Luopajärvi K, Knip M, Ilonen J, Ruohtula T, Härkönen T, et al. 84. Koloski NA, Jones M, Kalantar J, Weltman M, Zaguirre J, Talley NJ. The brain– Fecal microbiota composition differs between children with β-cell gut pathway in functional gastrointestinal disorders is bidirectional: a 12- autoimmunity and those without. Diabetes. 2013;62:1238–44. year prospective population-based study. Gut. 2012;61:1284–90. Mao et al. Environmental Health (2018) 17:50 Page 12 of 12 85. Carabotti M, Scirocco A, Maselli MA, Severi C. The gut-brain axis: interactions between enteric microbiota, central and enteric nervous systems. Ann Gastroenterol. 2015;28:203–9. 86. Liang S, Wang T, Hu X, Luo J, Li W, Wu X, et al. Administration of Lactobacillus helveticus NS8 improves behavioral, cognitive, and biochemical aberrations caused by chronic restraint stress. Neuroscience. 2015;310:561–77. 87. Sudo N, Chida Y, Aiba Y, Sonoda J, Oyama N, Yu XN, et al. Postnatal microbial colonization programs the hypothalamic-pituitary-adrenal system for stress response in mice. J Physiol. 2004;558:263–75. 88. Bercik P, Denou E, Collins J, Jackson W, Lu J, Jury J, et al. The intestinal microbiota affect central levels of brain-derived neurotropic factor and behavior in mice. Gastroenterology. 2011;141(2):599-609. 89. Nguyen TLA, Vieira-Silva S, Liston A, Raes J. How informative is the mouse for human gut microbiota research? Dis Model Mech. 2015;8:1–16.
Environmental Health – Springer Journals
Published: May 29, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera