TY - JOUR AU1 - Che, Shun AU2 - Men, Yujie AB - Abstract Functional differentiation and metabolite exchange enable microbial consortia to perform complex metabolic tasks and efficiently cycle the nutrients. Inspired by the cooperative relationships in environmental microbial consortia, synthetic microbial consortia have great promise for studying the microbial interactions in nature and more importantly for various engineering applications. However, challenges coexist with promises, and the potential of consortium-based technologies is far from being fully harnessed. Thorough understanding of the underlying molecular mechanisms of microbial interactions is greatly needed for the rational design and optimization of defined consortia. These knowledge gaps could be potentially filled with the assistance of the ongoing revolution in systems biology and synthetic biology tools. As current fundamental and technical obstacles down the road being removed, we would expect new avenues with synthetic microbial consortia playing important roles in biological and environmental engineering processes such as bioproduction of desired chemicals and fuels, as well as biodegradation of persistent contaminants. Introduction Microorganisms ubiquitously exist in nature and lie at the heart of biogeochemical cycling [34], most of which stay together with others to survive and thrive in complex microbial communities. Ecological interactions among species shape the structure and functions of the community [66]. The diversity of functions and division of labor enable microbial communities to cycle the nutrients and to perform complicated functions more efficiently than individual populations. Moreover, growing in mixed cultures also exhibits stronger resistance and resilience for individual members to environmental changes [63]. Inspired by these distinct properties of environmental microbial communities, the consortium-based concept has become promising for resilient and cost-effective biotechnologies, in which synthetic microbial consortia containing 2 or more key species carry out desired functions cooperatively based on the microbial interaction principles in nature. We have dealt with undefined microbial consortia for centuries in different fields such as wastewater treatment, biogas production, as well as biodegradation and bioremediation. However, the enormous potential of microbial consortia is far from fully harnessed. In recent years, the understanding and application of microbial consortia have attracted broad interest in biosynthesis and bioprocessing [12, 17, 30, 117]. For example, biorefinery using biomass as feedstock is a sustainable solution for producing fuels and chemicals, mitigating climate change caused by traditional petroleum refineries [22]. Lignocellulose is a low-cost feedstock for biorefineries due to its abundance in nature. However, it is still challenging to genetically engineer complex pathways such as cellulolytic pathways in model strains for efficient and stable biosynthetic performance from cellulose-based feedstock [17]. Bioconversion of cellulosic biomass using synthetic microbial consortia is thus holding promise as an alternative approach for lignocellulosic biorefineries [64]. Some synthetic microbial consortia have already revealed superior capabilities in biosynthesis and biodegradation [122, 129, 145]. However, the lack of rational design of microbial consortia is the bottleneck of utilizing the vast potential of microbial consortia [60]. The current design of defined consortia mostly comes from the assembly of genetically engineerable model microorganisms such as Escherichia coli and yeast strains [61, 90, 145], which might genetically lack cooperative and communicative bases as they are not commonly found growing together in nature. Despite extensive research on microbial interactions, elucidating the underlying molecular mechanisms among co-existing microorganisms remains a major challenge to achieve a rational design of synthetic microbial consortia. The rapid development of omics technology and genome-editing tools in recent years opens opportunities and challenges in understanding and applying synthetic microbial consortia. Omics tools arm researchers with holistic views of metabolic fluxes, growth dynamics, and regulations in defined consortia [23, 85, 104], but pinpointing specific genes/pathways and connecting them between consortia members to achieve certain phenotypes of the consortium still needs to be further tackled. Moreover, the CRISPR/Cas-based toolkits enable rapid and efficient genome editing, transcriptional control, as well as high-throughput and trackable mutagenesis [28, 39, 132], but optimization of the machinery is needed particularly for non-model microorganisms. The integration of fundamental and technical gears will facilitate synthetic microbial consortia toward a stable and cost-effective approach for engineering applications such as biofuel/bioproducts synthesis and target biodegradation (Fig. 1). Fig. 1 Open in new tabDownload slide Design, characterization, and optimization of synthetic microbial consortia for biosynthesis/biodegradation In this review, we start from macro-scale microbial consortia identified and characterized from natural environments. Microbial interactions that may sustain a functional consortium are discussed with their potential applications in engineering fields and the implications for constructing synthetic microbial consortia. We then introduce the concept of synthetic microbial consortia and the synthetic and systems biology tools essential for the design and optimization of synthetic microbial consortia. The examples of using synthetic consortia for biosynthesis and biodegradation are given. In the end, we bring up current challenges that limit the application of synthetic microbial consortia together with some suggestions on future research directions to make the consortium-based biotechnologies more competitive in industrial and environmental applications. Environmental microbial consortia In nature, microorganisms typically occur in complex communities containing multiple populations that may metabolically interact with each other. In some cases, cells from a single population survive and thrive in complex communities where the interactions with cells from other populations determine the fitness of that population [133]. More importantly, functional differentiation and metabolite exchange during ecological interactions, particularly in cooperative relationships, enable co-existing species to cycle the nutrients efficiently and to gain strong resistance and resilience to environmental perturbations [63]. Microbe–microbe interactions Consortia are co-existing groups of two or more microbial species [127]. Microbial interactions determine the stability and functions of consortia. With combinations of positive, negative, and neutral effects between two species, there are six basic interaction modes: mutualism (e.g., syntrophy), commensalism, parasitism or predation, competition, amensalism, and neutralism [35]. Stable and robust growth is more likely achieved in consortia based on cooperative relationships, such as mutualism and commensalism. Mutualism refers to the cross-feeding between two species occurring via the exchange of metabolic products, which is beneficial to both partners [134]. In the case of commensalism, one community member benefits from the other (e.g., growing on the metabolites of the other), while the other community member is neither positively nor negatively affected [35]. Communicating by the exchange of metabolites or signals, members of a consortium coordinate their activities and benefit each other through the division of labor, which enables microbial consortia to have the capacity to perform complex functions and allows parallel or sequential processes for resource utilization. Diversity of biochemical reactions in consortia boosts the overall resource utilization efficiency and reduces the formation of byproducts [8]. Moreover, natural consortia may contain members that metabolize inhibitory and/or toxic byproducts of primary substrates, such as acetic acid, which if not being further consumed will waste the energy and carbon in it and inhibit the biomass production due to acidification and anion accumulation [15, 29, 107, 108]. Additionally, microbial consortia may have stronger resistance and resilience to fluctuations of environmental factors (e.g., pH, temperature, nutrient levels, and the presence of toxic compounds) [20]. The diversity of metabolic pathways possessed in different members can facilitate the survival of consortia in sub-optimal environments, which lack readily available substrates and/or have toxic compounds present [72]. The environmental resilience and metabolic diversity of microbial consortia are important to maintain the desired functions in bioremediation and bioproduction processes. Microbial interactions that sustain environmental microbial consortia One important microbial interaction in nature is cross-feeding (usually corresponds to mutualism, and sometimes commensalism, Fig. 2), which can lead to the more sustainable and robust growth of both partners than each in isolation [92]. One specific example of environmental consortia based on cross-feeding is syntrophy, an obligately mutualistic interaction. Syntrophy typically refers to a cooperative relationship in which the continuous utilization of one compound by organism A for growth is dependent on organism B that lives on the metabolic intermediate of A. More specifically, organism A carries out the degradation of specific compounds, which only becomes thermodynamically favorable to sustain the growth of A when the metabolites are kept at lower levels by organism B via exergonic consumption [84]. Fig. 2 Open in new tabDownload slide Six basic interaction modes between two species in microbial consortia Syntrophy is widely occurring in natural environments and to some extent, contributing to shaping the biogeochemical cycles of carbon, sulfur, and nitrogen. The most common example is the syntrophy between syntrophic bacteria and methanogens in various anaerobic environments, which is essential for anaerobic global carbon cycles converting organic matter to methane and carbon dioxide [112]. The anaerobic degradation of a wide range of carbon compounds, including the complex polymers like lipids, proteins, and polysaccharides by syntrophic consortia, usually takes several steps under anaerobic condition. The compounds are initially utilized by hydrolytic bacteria to form monomers, then by fermentative microorganisms to produce intermediates such as short-chain fatty acids (e.g., butyrate, propionate, acetate, and formate), CO2, and H2. Under standard conditions (i.e., 273 K, 1 atm, and 1 M of reactants), the fermentation of certain organic carbon intermediates is thermodynamically unfavorable (i.e., endergonic). The consumption of fermentation end products (e.g., H2, CO2, and acetate) by partners such as methanogenic archaea and homoacetogens makes the fermentation reactions of the initial organic compounds thermodynamically favorable (exergonic) [119]. Such syntrophy between fermenters and methanogens is widely distributed in terrestrial and aquatic microbiomes, as well as in microbiomes in the gut of high-level organisms. Another example of syntrophy with metabolic cooperation is the co-existence of sulfate-reducing bacteria (SRB) and anaerobic methanotrophic (ANME) archaea as an obligate co-culture discovered recently from the ocean floor. The ANME archaea oxidize methane to CO2 by reverse methanogenic pathway. SRB take the electrons originally donated from methane and reduce sulfate to provide energy for growth of both partners [14, 31, 67]. The syntrophy between SRB and ANME uncovers an important route in the sulfur and carbon cycles coupling sulfate reduction to methane oxidation. Recent studies show that the interspecies electron transfer couples the two species by passing electrons from methane oxidation by ANME archaeon to SRB rather than using traditional diffusible syntrophic substrates such as hydrogen, formate, and acetate mentioned above [110, 120]. However, the detailed electron transfer mechanism remains to be further explored. Syntrophy also occurs to another type of ANME archaea that links the nitrogen cycle to the carbon cycle, nitrate-dependent denitrifying anaerobic methane oxidation (DAMO) archaea. In anoxic environments where organic carbons are limiting, DAMO archaea and anaerobic ammonium oxidation (Anammox) bacteria may co-exist via syntrophic interactions [50, 78]. Nitrate-dependent DAMO archaea anaerobically oxidize methane coupled to the reduction of nitrate to nitrite [33]. Anammox bacteria then consume the produced nitrite to oxidize ammonium and produce dinitrogen gas. As anammox bacteria also utilize nitrite as their reducing power to fix CO2 for their autotrophic growth, forming nitrate [70]. The formed nitrate can, in turn, be used by DAMO archaea. Such interactions are not only important to the biogeochemical cycles of nitrogen and carbon, but also to the engineering applications for nutrient removal. Theoretically, DAMO–anammox can result in a complete reduction of nitrate. It has been demonstrated in a recent enrichment study, where the consortium containing anammox bacteria and nitrate-dependent DAMO archaea is capable of complete removal of nitrate and ammonium through their syntrophic interactions with provided methane gas [54]. Besides the metabolically syntrophic cross-feeding between organisms A and B, detoxification is another important benefit that allows microbial consortia to sustain cell growth and functions. In this relationship, organism B is fed on the metabolites of organism A, while the sustainable growth of A benefits from the removal of its toxic metabolites by the other organism. One example is sulfur utilizing consortia, facilitating the conversion of organic sulfur to inorganic forms and promotes the biogeological cycling. The growth of SRB in pure culture is significantly inhibited by the accumulation of metabolic sulfide produced from elemental sulfur [98, 105]. In the consortium of green sulfur bacteria and SRB, sulfide produced by SRB is oxidized to elemental sulfur by green sulfur bacteria. Elemental sulfur is then reduced by SRB resulting in regeneration of sulfide. The concentrations of sulfide and elemental sulfur are kept at non-inhibitory levels allowing both partners to thrive [10]. Such one-way cross-feeding plus detoxification relationships have also been found in aerobic environments. Methanotrophic bacteria oxidize methane to methanol and methanol to formaldehyde in methane oxidation [49]. Co-existing methylotrophic organisms in laboratory enrichment are capable of oxidizing methanol relieving its inhibition on the growth of methanotroph [91]. It is also reported that the highly toxic formaldehyde is removed in the consortium of methanotrophs and methylotrophs [111]. Another example is the co-existence of ammonia-oxidizing bacteria (AOB) or archaea (AOA) and nitrite-oxidizing bacteria (NOB) found in both natural and built environments [42, 65, 93, 137]. During the nitrification process, ammonia is oxidized by AOB or AOA leading to the production of toxic metabolites nitrite, which is then removed by NOB through oxidation of nitrite to nitrate [80, 100, 121]. Microbial consortia could benefit from syntrophy via the third approach: organism A provides B essential substrates, while organism B offers protective habitats such as biofilms. Pseudomonas species are one group of important biofilm-forming microorganisms found in environmental consortia [47]. Cyanolichen contains phototrophic cyanobacteria and heterotrophic fungi forming a symbiotic relationship, where the phototrophic bacteria provide organic carbons to the heterotrophic fungi, and the filaments of fungi create a protective habitat that also traps moisture and nutrients for the cyanobacteria [2]. Systems-level understanding of microbial interactions in consortia Thanks to the rapid development of high-throughput sequencing and analytical chemistry, omics approaches ((meta)transcriptomics, (meta)proteomics, and metabolomics) have been broadly employed to analyze monoculture, defined consortia, enrichment culture, as well as environmental microbial communities to fill the knowledge gap of the underlying molecular mechanisms of microbial interactions [6, 21, 79, 143, 146]. Omics tools enlighten the understanding of microbial interactions by providing valuable information on functional diversity, gene expression levels, regulatory networks, and metabolite profiles [7, 103, 106, 127]. Different types of meta-omics analyses can complement and support each other, leading to integrated omics, a more comprehensive approach to decipher microbial interactions in detail (Fig. 3). With known genomic information of each consortium member, the current technology can generate informative metatranscriptomics and metaproteomics data to compare the temporal gene expression (mRNA and protein) between monocultures and consortia. For example, the temporal proteomes complemented with the metabolomic analysis elucidated the possible interactions between Ketogulonicigenium vulgare and Bacillus megaterium, which are artificially assembled together to produce 2-keto-gulonic acid (2-KGA), the precursor of vitamin C. The profiling of proteins and metabolites revealed that B. megaterium helped K. vulgare to resist reactive oxygen stress, and after sporulation and lysis B. megaterium also provided necessary nutrients, such as purine, for K. vulgare to grow better and produce more 2-KGA [79]. Fig. 3 Open in new tabDownload slide Schematic workflow using omics tools for metabolic network elucidation and rational metabolic engineering design Comparative transcriptomics and proteomics have also been applied to study interspecies relationships in various syntrophic consortia, including interspecies hydrogen transfer in consortia containing a hydrogenic fermenter and a hydrogenotrophic microorganism (methanogenic archaea or dechlorinating bacteria) [85, 88], nutrient cross-feeding between corrinoid-auxotrophic and corrinoid-producing bacteria [86, 87], and stress-related in-contact interactions resulting in exclusive Mn oxidation in a co-culture [76]. Multiple comparative omics analyses also provided insights into interspecies interactions in the archaeal consortium of marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans: compared with monocultures, the metabolism (e.g., ribosome protein synthesis and amino acid metabolism) of I. hospitalis was redirected to alternative pathways to sustain the growth of N. equitans, resulting in the reduction of metabolic diversity in the consortium [104]. The integrative omics analysis would be even more powerful if complemented with metabolic flux analyses (MFA). However, even for 13C-labeling metabolic flux analysis (13C-MFA) in a consortium, it is difficult to distinguish labeling fingerprints of different species using the typical amino acid-based isotopic tracing experiments for monocultures, as amino acids produced by different populations cannot be easily distinguished [40]. To overcome this, a peptide-based 13C-MFA together with protein-based stable isotope probing (SIP) and transcriptomic analyses have been developed, in which the unique sequences of amino acids in peptide allow the assignment of peptides to specific species in consortia [41]. Experimental peptide labeling patterns can be obtained by mass spectrometry via procedures similar to proteomics and protein-based SIP [13, 16, 57], and metabolic fluxes to each consortium member can be inferred from the peptide labeling patterns [101]. The extensive data generated from meta-omics can then be used to carry out flux balance analysis and to establish predictive models for microbial consortia [48, 101]. In addition, the above-mentioned systems biology tools can be combined with single-cell technologies such as fluorescence-activated cell sorting (FACS), Raman-activated cell sorting, and NanoSIMS to interpret the metabolic roles played by individual members in microbial consortia [32, 51, 74]. Engineering applications of environmental microbial consortia The discovery of microorganisms growing syntrophically in nature has directed the design of engineering applications in pollution control and renewable energy production. One example of macroscopic microbial consortia used in environmental engineering is the production of biogas through anaerobic digestion of excess activated sludge from wastewater treatment and combined with food wastes. Anaerobic digestion is considered as an energy-efficient and environment-friendly approach for bioenergy production [77], where syntrophic interactions between fermentative microorganisms and methanogens play crucial roles in methane production. The loss of activity of one partner may severely affect the activity of the other, causing acid accumulation and a significant decrease in methane content in the biogas [45, 53, 126]. More recently, the concept of complete nitrogen removal by membrane biofilm reactor has been tested in the laboratory taking advantage of the syntrophic interactions between DAMO microorganisms and anammox bacteria [138]. Algae–prokaryote consortia have also been used in wastewater treatment for energy-efficient nitrogen removal, where oxygenic phototrophs provide O2 instead of aeration for nitrifying and heterotrophic prokaryotes while prokaryotes provide CO2 and ammonia detoxification to algae [130]. Similar syntrophic relationship based on interspecies hydrogen transfer has been utilized in bioremediation of tetra-/tri-chloroethene (PCE and TCE)-contaminated fields with the addition of fermentable organic substrates, where fermenting bacteria supply hydrogen the sole electron donor used by the dechlorinating bacteria (i.e., Dehalococcoides spp.) and, in turn, hydrogen level is lowered down for the fermentation of organics to proceed further [3, 36, 82]. In addition to hydrogen, cross-feeding on another essential nutrient corrinoids has also been observed between the corrinoid-auxotrophic, dechlorinating Dehalococcoides and corrinoid-producing fermentative bacteria [86, 141]. Taken together, environmental microbial consortia can form tight mutualistic relationships via cross-feeding, detoxification, and biostructure formation. The microbial interactions and metabolic networks possessed in environmental microbial consortia may provide guidance for the design and optimization of stable, robust and efficient synthetic microbial consortia for a variety of engineering applications, such as biosynthesis and biodegradation. Synthetic microbial consortia for engineering purposes Synthetic microbial consortia refer to designed simple microbial communities with a defined composition of 2 or more (typically 2–3) species/strains. They hold great promise in a variety of engineering applications, including biosynthesis and bioremediation (bioaugmentation). Traditional medical and industrial biosynthesis processes rely on using genetically modified monoculture to create an all-in-one engineered strain capable of a broad spectrum of heterologous processes completing the bioconversion all the way to the end product. The fitness cost due to metabolic resource allocation makes it extremely challenging to engineer a single microbe to effectively and sustainably produce desired high-value products that require complex biosynthetic pathways [61, 135]. The division of labor among consortium members benefits each in terms of substrate utilization, redox balance (e.g., NAD+/NADH cycling) and cell growth [17]. Although at its infant stage, synthetic microbial consortia have been emerging as a new paradigm as they possess the potential to overcome the limitations of using a single population. First, it can achieve higher biosynthesis efficiency with less refined substrates (e.g., pretreated beech wood) due to the capacity of microbial consortia to utilize a broader range of raw and low-cost substrates [9, 37, 115]. Second, the application of microbial consortia can also potentially simplify the multi-step process to reduce the operational cost. For example, the reorganized one-step vitamin C production by synthetic consortium eliminates the requirement of second sterilization process in conventional two-step fermentation, and notably reduces the production cost [129]. In addition, synthetic microbial consortia are advantageous to complex communities for bioremediation when the key players may compete with the other non-contributing members in the community for limited substrates. Such substrate competition would be eliminated by constructing microbial consortia containing only the contributing species. Here, we will discuss the design and optimization of synthetic microbial consortia, and consortium-based applications for biosynthesis and biodegradation. Design of synthetic microbial consortia Successful synthetic microbial consortia not only carry out the desired functions but also sustain cell growth in a stable and robust way. More stable relationships among consortium members are formed when they highly depend on each other. Microbial interactions that lead to the interdependence and stable relationships include cross-feeding, detoxification, and biofilm formation, which are important consortium design principles [56, 85, 86, 115]. There are typically two strategies to select consortium members: (1) top-down (from complex to simple): the consortium members are the identified keystone players from one specific complex microbial community [109, 147] (Fig. 4a), and (2) bottom-up (from simple to complex): the consortium members are selected from an inclusive pool of isolated and/or engineered microorganisms, which may possess the desired traits but not necessarily have common environmental origins [58, 68] (Fig. 4b). Although the bottom-up approach facilitated by a variety of synthetic biology tools is a simple and common method to construct synthetic microbial consortia, the top-down strategy offers naturally occurring microbial interdependence that might be missing from an artificial combination of engineered microorganisms using the bottom-up strategy. The most efficient and stable macroscopic microbial consortia for cellulose utilization exist in nature, such as rumen microbiome. However, it is typically non-model species that are involved in those environmental microbial communities. The unavailability of isolates of unconventional microorganisms as well as the lack of their genomic information, metabolic pathways, and suitable engineering tools are the major obstacles that prevent the top-down approach from being widely applied in synthetic consortia construction. It is challenging particularly for biosynthesis purposes as they require more accurate control on the metabolic fluxes and the output products. As single-cell technologies and systems biology tools for community studies are being advanced [83, 144], one may expect a better understanding of the environmental microbial consortia, which will benefit a more stable and robust design of synthetic consortia using environmental microorganisms. Fig. 4 Open in new tabDownload slide Top-down (a) and bottom-up (b) approaches for synthetic consortia construction Optimization of synthetic microbial consortia Although promising, synthetic microbial consortia need to be optimized for the desired performance. One trade-off of using synthetic consortia for biosynthesis is the introduction of redundant metabolic pathways, rendering diluted flux toward the desired product. In addition, for defined consortia used as a bioaugmentation seed in bioremediation/biodegradation, they may need to carry out the reactions at sub-optimal growth conditions (e.g., low temperatures and low/high pH values) and low substrate levels (e.g., treating groundwater contaminations). To make the synthetic consortia cost-effective, stable, and robust, we need to modify the consortia or consortia members individually. The optimization methods include directed evolution, genomic and metabolic engineering, and artificial cell-to-cell communications. Directed evolution Directed evolution is a process simulating Darwinian selection to identify mutants with desired traits through iterative cycles of mutagenesis and enrichment of selected mutants. Different from natural evolutionary adaptation [128], directed evolution uses accelerated mutagenesis induced by a chemical mutagen or realized by molecular regulation and genetic/genomic engineering [26]. Random or targeted mutagenesis libraries are constructed, and the mutants are selected by monitoring the emergence of desired traits. Such mutagenesis and selection cycles drive the consortium system toward the desired phenotypes circumventing a thorough understanding of the metabolic networks and the underlying regulation mechanisms [5, 27]. The feedback-regulated evolution of phenotype has also been achieved in an adaptive control system, where the mutagenesis rate is maximized when no desired product is present and decreased when the desired product is in high concentration [24]. It has been successfully applied to select mutants with higher production of tyrosine and isoprenoid in E. coli [24]. Although directed evolution is typically based on single cells or proteins, theoretically it can also be applied to microbial consortia by evolving all members as growing together or generating mutant strains of individual consortium members for new consortia construction. It is a tremendous amount of work to construct mutant libraries and conduct selection experiments. Thus, more targeted approaches are needed. Directed evolution can be combined with genetic/genomic engineering to obtain desired traits when the genes/pathways essential for acquiring/losing the desired trait are known [73]. Genome and metabolic engineering Advances in synthetic biology toolkits, particularly the rapid development of genome-editing techniques open up more possibilities of optimizing synthetic microbial consortia through metabolic engineering. Engineered nucleases coupled with sequence-specific DNA-binding domain enable the site-directed genome editing via the generation of double-strand break (DSB) followed by nonhomologous end joining (NHEJ) or homology-directed repair (HDR) in diverse cell types and organisms [46]. The site-specific DSB can be generated by (1) Zinc-finger nucleases (ZFNs) [124], (2) transcription activator-like effector nucleases (TALENs) [89], and (3) clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. CRISPR/Cas genome-editing systems emerge rapidly in recent years due to their advantages over the other two genome-editing approaches, including higher efficiency, easier procedure, and the availability for multiplex genomic modification [46, 96]. The type II CRISPR/Cas system (i.e., CRISPR/Cas9) originated from Streptococcus pyogenes is the most applied CRISPR/Cas-based genome-editing machinery. It includes a Cas-encoding gene (cas9), a single guide RNA (sgRNA), and an editing template, which are carried by a plasmid to be introduced to the target cells. The sgRNA is composed of crRNA, tracrRNA, and a ~ 20 bp target sequence (protospacer) in the to-be-edited genome plus a protospacer-adjacent motif (PAM, a three-nucleotide sequence of NGG) (Fig. 5). Besides numerous applications in plants and animals, high selectivity and efficiency of genome editing by CRISPR/Cas9 have also been demonstrated in microorganisms, particularly those model strains like yeast and E. coli involved in biosynthesis [1, 4, 28, 59, 75, 94, 140]. Recently, there is an emerging need for CRISPR/Cas-based toolkits tailored to non-model strains of specific interest for bioenergy and bioproduct synthesis [113]. One challenge to edit non-conventional microbial genomes is that some bacteria such as Clostridium species are lack of NHEJ and active HDR. The mutated Cas9, Cas9 nickase has been successfully applied to carry out DNA deletion and insertion via the single-nick-triggered homologous recombination (SNHR) strategy for the cellulolytic Clostridium cellulolyticum, resulting in editing efficiency as high as 95% [140]. Other challenges for CRISPR/Cas9 application to non-model strains include the selection of effective promoter and compatible carrying vectors, as well as the optimization of sgRNA. The editing efficiency by the CRISPR/Cas9 machinery can be enhanced by selecting promoters and vectors most compatible with the target cells [95, 102]. Furthermore, researchers have recently developed a high-throughput method screening high-efficiency sgRNAs in a non-conventional yeast strain, which can be potentially applied to other non-conventional microbial strains [113]. Efficient CRISPR/Cas-based genome editing can be applied for knocking out and/or knocking in genes that are essential in microbe–microbe interactions, thus enhancing the stability and performance of synthetic consortia. For example, the enhancement of cellulolytic activity of C. cellulolyticum converting cellulose into fermentable intermediates will open the possibility of constructing highly efficient cellulose-based synthetic consortia with specific fermenting bacteria converting the intermediates into biofuels and/or bioproducts. Fig. 5 Open in new tabDownload slide CRISPR–Cas9 system Besides genomic manipulation, transcriptional control can also be achieved by CRISPR-assisted systems, CRISPR interference (CRISPRi) with deactivated or “dead” Cas9 (dCas9) for transcriptional repression and CRISPR activation (CRISPRa) with a transcriptional activator protein fused with dCas9 for upregulation of gene expression [11, 19, 139]. The CRISPR-enabled transcriptional control has been applied to a twin-clostridial consortium. The consortium was able to produce 22.1 g/L acetone–butanol–ethanol (ABE) from alkali-extracted, deshelled corn cobs, which matches the titer of ABE produced from starchy feedstock and is evident to be a promising platform for ABE production from lignocellulose. The desired metabolic pathway is divided into four modules and shared between Clostridium cellulovorans and Clostridium beijerinckii via metabolic engineering. CRISPRi system was designed to decrease the transcription level of the target hydrogenase gene in C. cellulovorans. The production of ethanol was increased by tenfold, indicating that the NADH generated was redirected to the synthesis of ethanol rather than hydrogen gas [132]. Moreover, a recently developed CRISPR-enabled trackable genome engineering (CREATE) technique enables (1) the high-throughput construction of site-specific mutagenesis libraries (including site saturation mutagenesis of a given protein), which can link genotypes to phenotypes, and (2) the reconstruction of adaptive evolution libraries containing mutants with all evolved genotypes, which can pinpoint which mutation leads to the evolved phenotype [38]. The CRISPR/Cas system can also be applied to selectively remove undesired bacterial species/strains and quantitatively control the composition of consortia, which are critical to industrial synthetic consortia. Illustrated in E. coli, type I-E CRISPR/Cas system was found to be capable of distinguishing and removing highly similar strains in consortia, and the control of consortium composition can be achieved by varying the collection of delivered CRISPR RNAs [43]. CRISPR/Cas-based techniques are powerful tools to genetically and/or metabolically engineer each member of microbial consortia. Ideally, an optimized synthetic consortium should have (1) enhanced interdependency and stability, (2) alleviated substrate competition among members, and (3) increased flux toward the desired products. However, different from monocultures, it is even more challenging to optimize synthetic consortia. To achieve a rational metabolic engineering design and promotes the stability and efficiency of the consortium, it is critical to have a thorough understanding of metabolic networks among consortium members. Systems biology tools discussed in Sect. 2.3 can be employed to disentangle complex microbial interactions in undefined and defined consortia. Due to the complexity of microbial networks, although with a tremendous amount of information obtained by systems biology, it is still challenging to disentangle the key components that directly contribute to the cooperative interactions. High-throughput experimental screening tools and model simulation or machine learning are needed to complement with the traditional systems biology, for further identification and validation. Artificial cell-to-cell communication Another possible way to manipulate synthetic microbial consortia is introducing artificial cell-to-cell communication circuits. Cell-to-cell communication plays a crucial role in the organization and regulation of multicellular traits such as division of labor, inter- and intracellular communications, and coordination of cellular activities. Design and incorporation of cell-to-cell communications enable researchers to engineer population-level behaviors and functions [25]. Quorum sensing (QS) is one of the most common mechanisms of intra- and interspecies communication. The large diversity and availability in synthetic biology make QS an attractive approach for coordinating complex behavior in synthetic consortia [109, 118]. The population-level behavior is coordinated by bacteria which produce and respond to specific signaling molecules (acyl-homoserine lactones, AHLs) in a density-dependent way. The gene transcription is controlled by certain QS regulating proteins (either activators or repressors), which AHLs can bind to. There are a number of QS systems found in environmental microorganisms, including lux, esa, las, tra, rpa, rhl, and cin [71, 118]. To develop QS-based genetic circuits for regulating system behaviors in synthetic consortia, variants of the QS regulator EsaR were obtained from directed evolution, with more than 70-fold higher signal sensitivity than the wild-type EsaR. Thus, the variants can be used at low signal molecule concentrations ranging from 5 to 10,000 nM [118]. By engineering esaR promoters with a second EasR binding site, researchers were able to modulate QS-dependent gene expression, opening possibilities of using a single QS signal to tune the regulation of multiple genes, which can be used to control microbial behaviors in synthetic consortia [116]. For consortia constructed based on multiple QS systems, system pairs that exhibit orthogonality are more useful as they do not form interactions (i.e., signal crosstalk, promoter crosstalk, or both) that may interfere different regulation systems in the consortium. Two engineered QS systems, rpa and tra, were examined to be completely orthogonal. The orthogonality of QS systems can also be predicted by a software tool [71]. Three in silico identified orthogonal QS communication channels were simultaneously applied to a consortium of three E. coli populations, and they successfully controlled each population level in response to the specific AHL signal as predicted [71]. Thus, the QS-based cell–cell communication systems provide potential modules for versatile control of synthetic consortia [114]. Synthetic microbial consortia for biosynthesis Lignocellulosic biomass, the most abundant renewable carbon source, is an ideal feedstock for the production of biofuel and chemicals [44]. Biosynthesis of fuels and value-added chemicals from lignocellulosic biomass has been regarded as a sustainable alternative of current petroleum feedstock platforms. However, challenges remain in improving the bioconversion efficiency and lowering processing costs [97]. Consolidate bioprocessing (CBP) is thought to be a promising scheme for biorefinery due to its low cost and simple operation. However, monoculture typically has limited productivity, yield, and titer. Harnessing consortia is an attractive alternative for CBP, although there are challenges such as maintaining stability and boosting the productivity of consortia [136]. Biofuels A synthetic consortium of three epiphytic strains of Enterococcus was reported to produce 79.5 mL H2 per gram of added wheat straw xylose which is many folds more than the monoculture of those species. Another consortium consisting C. beijerinckii with C. cellulovorans was designed to enhance the production of acetone–butanol–ethanol from previous leftover wheat straw; however, the interactions among the above species remain elusive [125]. Cross-kingdom interactions also guide the design of synthetic consortium for biofuel production: a consortium containing a cellulolytic fungus Trichoderma reesei producing soluble saccharides and an engineered E. coli strain metabolizing the saccharides to isobutanol, achieved up to 1.88 g/L production of isobutanol from cellulosic biomass. This study also demonstrates that the cooperator–cheater interaction could be applied to the design of stable consortia with tuning capacity [90]. Moreover, physical compartmentation enables the growth of consortium consisting of both aerobic and anaerobic microorganisms, broadening the spectrum of potential applications of microbial consortia. A recent study demonstrates this concept with bioproduction of ethanol from wheat straw in single biofilm membrane reactor featuring both aerobic conditions for the cellulase-producing fungal strain T. reesei Rut C30 and anaerobic conditions for an ethanol-producing yeast strain Saccharomyces cerevisiae. The oxygen permeable membrane at the bottom of the reactor enables the formation of fungi biofilm, in which oxygen is depleted, and cellulolytic enzymes are synthesized and released. Sugars from cellulose hydrolysis are then fermented to ethanol in the upper anaerobic yeast biofilm [18]. Bioproducts Up to 19.8 g/L lactic acid was produced by a fungal–bacterial consortium of the aerobic fungus T. reesei and facultative anaerobic lactic acid bacterium Lactobacillus pentosus from non-detoxified steam-pretreated beech wood in a spatially structured biofilm, similar as described above. On dense oxygen permeable membrane, the oxygen is depleted in the biofilm of T. reesei, producing cellulases that hydrolyze cellulose to sugars including cellobiose, which may inhibit the fungal growth at high concentrations. In the anaerobic bulk liquid, L. pentosus fed with released sugars consumes cellobiose, which alleviates the inhibitory effect of cellobiose on T. reesei. The self-inhibitory by-product acetic acid produced by L. pentosus can, in turn, be consumed by T. reesei via cross-feeding, thus promoting a stable mutualistic relationship between the two species [115]. The conventional industrial bioproduction of 2-keto-l-gulonic acid (2-KGA), the precursor of vitamin C, is limited by a long incubation period and the additional sterilization process. Synthetic microbial consortia have been successfully applied for one-step vitamin C production, in which the yield of 2-KGA is comparable to the original two-step fermentation process. Consortia optimization via metabolic engineering was carried out to produce 2-KGA from d-sorbitol. The consortium of Gluconobacter oxydans and Ketogulonicigenium vulgare was reorganized with alleviated competition for substrate and enhancement of symbiotic relationship by deleting genes involved in sorbose metabolism of G. oxydans [129]. Traditional engineered strains typically hold long reconstituted metabolic pathways to produce high-value metabolites; however, parts of the pathway may require specialized environments for optimal performance, and the host may be metabolically overburdened. A consortium of engineered E. coli and S. cerevisiae is reported to successfully produce 33 mg/L oxygenated taxanes, precursors of the anti-cancer drug paclitaxel, through the distribution of a heterologous pathway into two engineered bacteria. In this division of labor, S. cerevisiae utilizes metabolic intermediates produced by E. coli. The fast growth of E. coli and the complete protein expression system of S. cerevisiae are integrated for the biosynthesis of taxanes. To avoid the competition between the two species, researchers engineered mutualistic relationships in the consortium, where S. cerevisiae grew solely on acetate, a self-inhibitory product of E. coli [145]. Engineered E. coli consortia containing two functionally different strains have been applied to synthesize high-value natural products. Flavonoid was produced by an E. coli co-culture. The malonyl-CoA dependent upstream E. coli strain converts phenylpropanoic acids to flavanones, and the NADPH-dependent downstream E. coli strain transforms flavanones to flavan-3-ols. These two E. coli strains were individually optimized by improving flux to essential substrates and co-factors, and the combined consortia were screened based on titer. With the aid of empirical modeling, the optimization of carbon source, strain compatibility, temperature, and inoculation ratio leads to a 970-fold improvement in titer over the published production by single populations [62]. A more complex consortium containing four E. coli strains has been recently designed to conduct complete biosynthesis of anthocyanins from sugar. The division of metabolic burden and genetic optimization of individual strain enabled cooperative overexpression of 15 exogenous or modified enzymes from various plants and microbes, achieving milligram-per-liter production titer, which is several orders of magnitude higher than previous studies using enzymes from eukaryotic organisms [61]. Synthetic microbial consortia for biodegradation/bioremediation Synthetic microbial consortia may play important roles in bioremediation, as the division of labor in consortia is important for the degradation of persistent pollutants, which usually requires multiple steps, and cultures must be robust to the complex environment [52]. The constructed and optimized synthetic consortia can serve as the seed culture for bioaugmentation of in situ bioremediation practice and for biodegradation in more confined reactors as ex situ remediation approaches. It is worth noting that the application of engineered microbial consortia currently is, to the most extent, restrained in well-controlled bioprocesses to avoid genetic contamination from environmental microorganisms. In a batch study, the inhibitory effect of acetylene, a product of tetra- and trichloroethene biodegradation on the dechlorinating bacterium Dehalococcoides sp., was eliminated by co-cultivating an acetylene-fermenting bacterium, Pelobacter. The acetylene fermentation products also sustained the growth of the dechlorinating bacteria as energy and carbon source [81]. In addition, a consortium consisting of Bacillus clausii T and Bacillus clausii O/C, both isolated from human probiotics, alleviated the toxicity of antibiotics and showed a higher removal efficiency of select antibiotics than pure cultures [69]. A defined consortium isolated from petrochemical landfarm site (containing Mycobacterium fortuitum, Bacillus cereus, Microbacterium sp., Gordonia polyisoprenivorans, Microbacteriaceae bacterium, the Naphthalene-utilizing bacterium, and a fungus Fusarium oxysporum) was tested to degrade polycyclic aromatic hydrocarbons (PAHs) including anthracene, phenanthrene, and pyrene in soil. On average, 78% of three PAHs with different concentrations were mineralized by the consortium in 70 days. And the consortium showed more effective anthracene degradation than any of the isolates [55]. Similarly, the aliphatic and aromatic hydrocarbons of crude oil were efficiently degraded by a defined microalgal–bacterial consortium containing four bacterial species Sphingomonas sp. GY2B, Burkholderia cepacia GS3C, Pseudomonas sp. GP3A, and Pandoraea pnomenusa GP3B and one oil-tolerant microalga Scenedesmus obliquus GH2. Almost all alkanes, alkylcycloalkanes, alkylbenzenes naphthalene, fluorene, and phenanthrene were removed by this consortium [122]. Challenges and future research directions Challenges remain to be overcome before fully harnessing the potential of synthetic microbial consortia [117, 147]. First, the available number of orthogonal cell–cell interaction channels is limited [123]. Second, the underlying mechanisms and regulations of microbial interactions and their functional flexibility are poorly understood [142]. Although ubiquitously occurring in nature, inter- and intra-kingdom communications have not been well studied, as well [131]. Third, long-term homostasis of consortia could be difficult to maintain, as the long-term behavior of engineered organisms is unpredictable [17]. Fourth, some useful functions such as cellulolysis are possessed by non-model microorganisms such as Caldicellulosiruptor saccharolyticus [99], for which efficient genome-editing tools are lacking due to the limited knowledge of organism-specific biochemical pathways and regulatory mechanisms. In addition, fine tuning the behavior of multiple populations in consortia is still challenging. Expanding directed evolution used for a single population to multiple populations under varying environments is also needed. Future research is needed to address the above challenges. Potential directions include (1) obtaining a systems-level understanding of microbial interactions and metabolic networks in synthetic consortia for rational metabolic engineering design; (2) developing the state-of-the-art high-efficiency genome-editing toolkits for non-model microorganisms; (3) developing high-throughput screening tools and inexpensive gene-chip assay for directed evolution in multiple populations. The success of synthetic microbial consortia is, to a large extent, dependent on the advancement of systems biology, synthetic biology, analytical, and modeling tools. Only when we decipher the codes of microorganisms given by the mother nature to form strong and stable relationships among each other and know how to re-code them, synthetic microbial consortia will fully show their power in biosynthesis and biodegradation, as well as many other engineering applications. References 1. Altenbuchner J Editing of the Bacillus subtilis genome by the CRISPR-Cas9 system Appl Environ Microbiol 2016 82 5421 5427 10.1128/AEM.01453-16 4988203 Google Scholar Crossref Search ADS PubMed WorldCat 2. Aschenbrenner IA , Cernava T, Berg G, Grube M Understanding microbial multi-species symbioses Front Microbiol 2016 10.3389/fmicb.2016.00180 4757690 Google Scholar OpenURL Placeholder Text WorldCat Crossref 3. Aulenta F , Gossett JM, Papini MP, Rossetti S, Majone M Comparative study of methanol, butyrate, and hydrogen as electron donors for long-term dechlorination of tetrachloroethene in mixed anerobic cultures Biotechnol Bioeng 2005 91 743 753 10.1002/bit.20569 Google Scholar Crossref Search ADS PubMed WorldCat 4. Bao Z , Xiao H, Liang J, Zhang L, Xiong X, Sun N, Si T, Zhao H Homology-integrated CRISPR-Cas (HI-CRISPR) system for one-step multigene disruption in Saccharomyces cerevisiae Acs Synth Biol 2015 4 585 594 10.1021/sb500255k Google Scholar Crossref Search ADS PubMed WorldCat 5. Bassalo MC , Liu RM, Gill RT Directed evolution and synthetic biology applications to microbial systems Curr Opin Biotechnol 2016 39 126 133 10.1016/j.copbio.2016.03.016 Google Scholar Crossref Search ADS PubMed WorldCat 6. Becker J , Reinefeld J, Stellmacher R, Schafer R, Lange A, Meyer H, Lalk M, Zelder O, von Abendroth G, Schroder H, Haefner S, Wittmann C Systems-wide analysis and engineering of metabolic pathway fluxes in bio-succinate producing Basfia succiniciproducens Biotechnol Bioeng 2013 110 3013 3023 10.1002/bit.24963 Google Scholar Crossref Search ADS PubMed WorldCat 7. Beliaev AS , Romine MF, Serres M, Bernstein HC, Linggi BE, Markillie LM, Isern NG, Chrisler WB, Kucek LA, Hill EA, Pinchuk GE, Bryant DA, Wiley HS, Fredrickson JK, Konopka A Inference of interactions in cyanobacterial-heterotrophic co-cultures via transcriptome sequencing ISME J 2014 8 2243 2255 10.1038/ismej.2014.69 4992078 Google Scholar Crossref Search ADS PubMed WorldCat 8. Bernstein HC , Carlson RP Microbial consortia engineering for cellular factories: in vitro to in silico systems Comput Struct Biotechnol J 2012 3 e201210017 10.5936/csbj.201210017 3962199 Google Scholar Crossref Search ADS PubMed WorldCat 9. Bernstein HC , Paulson SD, Carlson RP Synthetic Escherichia coli consortia engineered for syntrophy demonstrate enhanced biomass productivity J Biotechnol 2012 157 159 166 10.1016/j.jbiotec.2011.10.001 Google Scholar Crossref Search ADS PubMed WorldCat 10. Biebl H , Pfennig N Growth yields of green sulfur bacteria in mixed cultures with sulfur and sulfate reducing bacteria Arch Microbiol 1978 117 9 16 10.1007/Bf00689344 Google Scholar Crossref Search ADS WorldCat 11. Bikard D , Jiang W, Samai P, Hochschild A, Zhang F, Marraffini LA Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system Nucleic Acids Res 2013 41 7429 7437 10.1093/nar/gkt520 3753641 Google Scholar Crossref Search ADS PubMed WorldCat 12. Bittihn P , Din MO, Tsimring LS, Hasty J Rational engineering of synthetic microbial systems: from single cells to consortia Curr Opin Microbiol 2018 45 92 99 10.1016/j.mib.2018.02.009 6151159 Google Scholar Crossref Search ADS PubMed WorldCat 13. Boaro AA , Kim YM, Konopka AE, Callister SJ, Ahring BK Integrated ‘omics analysis for studying the microbial community response to a pH perturbation of a cellulose-degrading bioreactor culture FEMS Microbiol Ecol 2014 90 802 815 10.1111/1574-6941.12435 Google Scholar Crossref Search ADS PubMed WorldCat 14. Boetius A , Ravenschlag K, Schubert CJ, Rickert D, Widdel F, Gieseke A, Amann R, Jorgensen BB, Witte U, Pfannkuche O A marine microbial consortium apparently mediating anaerobic oxidation of methane Nature 2000 407 623 626 10.1038/35036572 Google Scholar Crossref Search ADS PubMed WorldCat 15. Booth IR Regulation of cytoplasmic pH in bacteria Microbiol Rev 1985 49 359 378 373043 Google Scholar Crossref Search ADS PubMed WorldCat 16. Bozinovski D , Taubert M, Kleinsteuber S, Richnow HH, von Bergen M, Vogt C, Seifert J Metaproteogenomic analysis of a sulfate-reducing enrichment culture reveals genomic organization of key enzymes in the m-xylene degradation pathway and metabolic activity of proteobacteria Syst Appl Microbiol 2014 37 488 501 10.1016/j.syapm.2014.07.005 Google Scholar Crossref Search ADS PubMed WorldCat 17. Brenner K , You L, Arnold FH Engineering microbial consortia: a new frontier in synthetic biology Trends Biotechnol 2008 26 483 489 10.1016/j.tibtech.2008.05.004 Google Scholar Crossref Search ADS PubMed WorldCat 18. Brethauer S , Studer MH Consolidated bioprocessing of lignocellulose by a microbial consortium Energy Environ Sci 2014 7 1446 1453 10.1039/c3ee41753k Google Scholar Crossref Search ADS WorldCat 19. Bruder MR , Pyne ME, Moo-Young M, Chung DA, Chou CP Extending CRISPR-Cas9 technology from genome editing to transcriptional engineering in the genus Clostridium Appl Environ Microbiol 2016 82 6109 6119 10.1128/AEM.02128-16 5068152 Google Scholar Crossref Search ADS PubMed WorldCat 20. Burmolle M , Webb JS, Rao D, Hansen LH, Sorensen SJ, Kjelleberg S Enhanced biofilm formation and increased resistance to antimicrobial agents and bacterial invasion are caused by synergistic interactions in multispecies biofilms Appl Environ Microbiol 2006 72 3916 3923 10.1128/Aem.03022-05 1489630 Google Scholar Crossref Search ADS PubMed WorldCat 21. Chandra Mohana N , Yashavantha Rao HC, Rakshith D, Mithun PR, Nuthan BR, Satish S Omics based approach for biodiscovery of microbial natural products in antibiotic resistance era J Genet Eng Biotechnol 2018 16 1 8 10.1016/j.jgeb.2018.01.006 6296576 Google Scholar Crossref Search ADS PubMed WorldCat 22. Cherubini F The biorefinery concept: using biomass instead of oil for producing energy and chemicals Energ Convers Manag 2010 51 1412 1421 10.1016/j.enconman.2010.01.015 Google Scholar Crossref Search ADS WorldCat 23. Chignell JF , Park S, Lacerda CMR, De Long SK, Reardon KF Label-free proteomics of a defined, binary co-culture reveals diversity of competitive responses between members of a model soil microbial system Microbiol Ecol 2018 75 701 719 10.1007/s00248-017-1072-1 Google Scholar Crossref Search ADS WorldCat 24. Chou HH , Keasling JD Programming adaptive control to evolve increased metabolite production Nat Commun 2013 10.1038/ncomms3595 3586725 Google Scholar OpenURL Placeholder Text WorldCat Crossref 25. Chuang JS Engineering multicellular traits in synthetic microbial populations Curr Opin Chem Biol 2012 16 370 378 10.1016/j.cbpa.2012.04.002 22591687 Google Scholar Crossref Search ADS PubMed WorldCat 26. Cobb RE , Chao R, Zhao HM Directed evolution: past, present, and future AIChE J 2013 59 1432 1440 10.1002/aic.13995 4344831 Google Scholar Crossref Search ADS PubMed WorldCat 27. Cobb RE , Sun N, Zhao HM Directed evolution as a powerful synthetic biology tool Methods 2013 60 81 90 10.1016/j.ymeth.2012.03.009 Google Scholar Crossref Search ADS PubMed WorldCat 28. Cobb RE , Wang Y, Zhao H High-efficiency multiplex genome editing of Streptomyces species using an engineered CRISPR/Cas system Acs Synth Biol 2015 4 723 728 10.1021/sb500351f Google Scholar Crossref Search ADS PubMed WorldCat 29. De Mey M , De Maeseneire S, Soetaert W, Vandamme E Minimizing acetate formation in E. coli fermentations J Ind Microbiol Biot 2007 34 689 700 10.1007/s10295-007-0244-2 Google Scholar Crossref Search ADS WorldCat 30. De Roy K , Marzorati M, Van den Abbeele P, Van de Wiele T, Boon N Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities Environ Microbiol 2014 16 1472 1481 10.1111/1462-2920.12343 Google Scholar Crossref Search ADS PubMed WorldCat 31. Dekas AE , Chadwick GL, Bowles MW, Joye SB, Orphan VJ Spatial distribution of nitrogen fixation in methane seep sediment and the role of the ANME archaea Environ Microbiol 2014 16 3012 3029 10.1111/1462-2920.12247 Google Scholar Crossref Search ADS PubMed WorldCat 32. Dekas AE , Connon SA, Chadwick GL, Trembath-Reichert E, Orphan VJ Activity and interactions of methane seep microorganisms assessed by parallel transcription and FISH-NanoSIMS analyses ISME J 2016 10 678 692 10.1038/ismej.2015.145 Google Scholar Crossref Search ADS PubMed WorldCat 33. Ettwig KF , Butler MK, Le Paslier D, Pelletier E, Mangenot S, Kuypers MMM, Schreiber F, Dutilh BE, Zedelius J, de Beer D, Gloerich J, Wessels HJCT, van Alen T, Luesken F, Wu ML, van de Pas-Schoonen KT, den Camp HJMO, Janssen-Megens EM, Francoijs KJ, Stunnenberg H, Weissenbach J, Jetten MSM, Strous M Nitrite-driven anaerobic methane oxidation by oxygenic bacteria Nature 2010 464 543 548 10.1038/nature08883 Google Scholar Crossref Search ADS PubMed WorldCat 34. Falkowski PG , Fenchel T, Delong EF The microbial engines that drive Earth’s biogeochemical cycles Science 2008 320 1034 1039 10.1126/science.1153213 Google Scholar Crossref Search ADS PubMed WorldCat 35. Faust K , Raes J Microbial interactions: from networks to models Nat Rev Microbiol 2012 10 538 550 10.1038/nrmicro2832 Google Scholar Crossref Search ADS PubMed WorldCat 36. Freeborn RA , West KA, Bhupathiraju VK, Chauhan S, Rahm BG, Richardson RE, Alvarez-Cohen L Phylogenetic analysis of TCE-dechlorinating consortia enriched on a variety of electron donors Environ Sci Technol 2005 39 8358 8368 10.1021/es048003p Google Scholar Crossref Search ADS PubMed WorldCat 37. Fu N , Peiris P, Markham J, Bavor J A novel co-culture process with Zymomonas mobilis and Pichia stipitis for efficient ethanol production on glucose/xylose mixtures Enzyme Microb Tech 2009 45 210 217 10.1016/j.enzmictec.2009.04.006 Google Scholar Crossref Search ADS WorldCat 38. Garst A , Lynch M, Evans R, Gill RT Strategies for the multiplex mapping of genes to traits Microb Cell Fact 2013 12 99 10.1186/1475-2859-12-99 3842685 Google Scholar Crossref Search ADS PubMed WorldCat 39. Garst AD , Bassalo MC, Pines G, Lynch SA, Halweg-Edwards AL, Liu RM, Liang LY, Wang ZW, Zeitoun R, Alexander WG, Gill RT Genome-wide mapping of mutations at single-nucleotide resolution for protein, metabolic and genome engineering Nat Biotechnol 2017 35 48 55 10.1038/nbt.3718 Google Scholar Crossref Search ADS PubMed WorldCat 40. Gebreselassie NA , Antoniewicz MR 13C-metabolic flux analysis of co-cultures: a novel approach Metab Eng 2015 31 132 139 10.1016/j.ymben.2015.07.005 5897767 Google Scholar Crossref Search ADS PubMed WorldCat 41. Ghosh A , Nilmeier J, Weaver D, Adams PD, Keasling JD, Mukhopadhyay A, Petzold CJ, Martin HG A peptide-based method for 13C metabolic flux analysis in microbial communities PLoS Comput Biol 2014 10 e1003827 10.1371/journal.pcbi.1003827 4154649 Google Scholar Crossref Search ADS PubMed WorldCat 42. Gieseke A , Bjerrum L, Wagner M, Amann R Structure and activity of multiple nitrifying bacterial populations co-existing in a biofilm Environ Microbiol 2003 5 355 369 10.1046/j.1462-2920.2003.00423.x Google Scholar Crossref Search ADS PubMed WorldCat 43. Gomaa AA , Klumpe HE, Luo ML, Selle K, Barrangou R, Beisel CL Programmable removal of bacterial strains by use of genome-targeting CRISPR-Cas systems Mbio 2014 5 e00913 e00928 10.1128/mBio.00928-13 Google Scholar Crossref Search ADS WorldCat 44. Gouveia L , Oliveira AC Microalgae as a raw material for biofuels production J Ind Microbiol Biot 2009 36 269 274 10.1007/s10295-008-0495-6 Google Scholar Crossref Search ADS WorldCat 45. Gujer W , Zehnder AJB Conversion processes in anaerobic-digestion Water Sci Technol 1983 15 127 167 10.2166/wst.1983.0164 Google Scholar Crossref Search ADS WorldCat 46. Gupta RM , Musunuru K Expanding the genetic editing tool kit: ZFNs, TALENs, and CRISPR-Cas9 J Clin Invest 2014 124 4154 4161 10.1172/Jci72992 4191047 Google Scholar Crossref Search ADS PubMed WorldCat 47. Haagensen JA , Hansen SK, Christensen BB, Pamp SJ, Molin S Development of spatial distribution patterns by biofilm cells Appl Environ Microbiol 2015 81 6120 6128 10.1128/AEM.01614-15 4542232 Google Scholar Crossref Search ADS PubMed WorldCat 48. Hanemaaijer M , Roling WF, Olivier BG, Khandelwal RA, Teusink B, Bruggeman FJ Systems modeling approaches for microbial community studies: from metagenomics to inference of the community structure Front Microbiol 2015 6 213 10.3389/fmicb.2015.00213 4365725 Google Scholar Crossref Search ADS PubMed WorldCat 49. Hanson RS , Hanson TE Methanotrophic bacteria Microbiol Rev 1996 60 439 471 239451 Google Scholar Crossref Search ADS PubMed WorldCat 50. Haroon MF , Hu SH, Shi Y, Imelfort M, Keller J, Hugenholtz P, Yuan ZG, Tyson GW Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage Nature 2013 500 567 570 10.1038/nature12375 Google Scholar Crossref Search ADS PubMed WorldCat 51. Hatzenpichler R , Connon SA, Goudeau D, Malmstrom RR, Woyke T, Orphan VJ Visualizing in situ translational activity for identifying and sorting slow-growing archaeal-bacterial consortia Proc Natl Acad Sci USA 2016 10.1073/pnas.1603757113 Google Scholar OpenURL Placeholder Text WorldCat Crossref 52. Hays SG , Patrick WG, Ziesack M, Oxman N, Silver PA Better together: engineering and application of microbial symbioses Curr Opin Biotechnol 2015 36 40 49 10.1016/j.copbio.2015.08.008 Google Scholar Crossref Search ADS PubMed WorldCat 53. Hill DT , Bolte JP Digester stress as related to iso-butyric and iso-valeric acids Biol Waste 1989 28 33 37 10.1016/0269-7483(89)90047-5 Google Scholar Crossref Search ADS WorldCat 54. Hu SH , Zeng RJ, Haroon MF, Keller J, Lant PA, Tyson GW, Yuan ZG A laboratory investigation of interactions between denitrifying anaerobic methane oxidation (DAMO) and anammox processes in anoxic environments Sci Rep-UK 2015 10.1038/srep08706 Google Scholar OpenURL Placeholder Text WorldCat Crossref 55. Jacques RJS , Okeke BC, Bento FM, Teixeira AS, Peralba MCR, Camargo FAO Microbial consortium bioaugmentation of a polycyclic aromatic hydrocarbons contaminated soil Bioresour Technol 2008 99 2637 2643 10.1016/j.biortech.2007.04.047 Google Scholar Crossref Search ADS PubMed WorldCat 56. Jagmann N , Philipp B Reprint of Design of synthetic microbial communities for biotechnological production processes J Biotechnol 2014 192 293 301 10.1016/j.jbiotec.2014.11.005 Google Scholar Crossref Search ADS PubMed WorldCat 57. Jehmlich N , Schmidt F, von Bergen M, Richnow HH, Vogt C Protein-based stable isotope probing (Protein-SIP) reveals active species within anoxic mixed cultures ISME J 2008 2 1122 1133 10.1038/ismej.2008.64 Google Scholar Crossref Search ADS PubMed WorldCat 58. Jia X , Liu C, Song H, Ding M, Du J, Ma Q, Yuan Y Design, analysis and application of synthetic microbial consortia Synth Syst Biotechnol 2016 1 109 117 10.1016/j.synbio.2016.02.001 5640696 Google Scholar Crossref Search ADS PubMed WorldCat 59. Jiang W , Bikard D, Cox D, Zhang F, Marraffini LA RNA-guided editing of bacterial genomes using CRISPR-Cas systems Nat Biotechnol 2013 31 233 239 10.1038/nbt.2508 3748948 Google Scholar Crossref Search ADS PubMed WorldCat 60. Johns NI , Blazejewski T, Gomes ALC, Wang HH Principles for designing synthetic microbial communities Curr Opin Microbiol 2016 31 146 153 10.1016/j.mib.2016.03.010 4899134 Google Scholar Crossref Search ADS PubMed WorldCat 61. Jones JA , Vernacchio VR, Collins SM, Shirke AN, Xiu Y, Englaender JA, Cress BF, McCutcheon CC, Linhardt RJ, Gross RA, Koffas MAG Complete biosynthesis of anthocyanins using E. coli polycultures Mbio 2017 10.1128/mbio.00621-17 5698548 Google Scholar OpenURL Placeholder Text WorldCat Crossref 62. Jones JA , Vernacchio VR, Sinkoe AL, Collins SM, Ibrahim MHA, Lachance DM, Hahn J, Koffas MAG Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids Metab Eng 2016 35 55 63 10.1016/j.ymben.2016.01.006 Google Scholar Crossref Search ADS PubMed WorldCat 63. Kato S , Haruta S, Cui ZJ, Ishii M, Igarashi Y Network relationships of bacteria in a stable mixed culture Microb Ecol 2008 56 403 411 10.1007/s00248-007-9357-4 Google Scholar Crossref Search ADS PubMed WorldCat 64. Kawaguchi H , Hasunuma T, Ogino C, Kondo A Bioprocessing of bio-based chemicals produced from lignocellulosic feedstocks Curr Opin Biotechnol 2016 42 30 39 10.1016/j.copbio.2016.02.031 Google Scholar Crossref Search ADS PubMed WorldCat 65. Ke XB , Angel R, Lu YH, Conrad R Niche differentiation of ammonia oxidizers and nitrite oxidizers in rice paddy soil Environ Microbiol 2013 15 2275 2292 10.1111/1462-2920.12098 Google Scholar Crossref Search ADS PubMed WorldCat 66. Klitgord N , Segre D Ecosystems biology of microbial metabolism Curr Opin Biotechnol 2011 22 541 546 10.1016/j.copbio.2011.04.018 Google Scholar Crossref Search ADS PubMed WorldCat 67. Knittel K , Boetius A Anaerobic oxidation of methane: progress with an unknown process Annu Rev Microbiol 2009 63 311 334 10.1146/annurev.micro.61.080706.093130 Google Scholar Crossref Search ADS PubMed WorldCat 68. Kong W , Meldgin DR, Collins JJ, Lu T Designing microbial consortia with defined social interactions Nat Chem Biol 2018 14 821 829 10.1038/s41589-018-0091-7 Google Scholar Crossref Search ADS PubMed WorldCat 69. Kong XX , Jiang JL, Qiao B, Liu H, Cheng JS, Yuan YJ The biodegradation of cefuroxime, cefotaxime and cefpirome by the synthetic consortium with probiotic Bacillus clausii and investigation of their potential biodegradation pathways Sci Total Environ 2019 651 271 280 10.1016/j.scitotenv.2018.09.187 Google Scholar Crossref Search ADS PubMed WorldCat 70. Kuenen JG Anammox bacteria: from discovery to application Nat Rev Microbiol 2008 6 320 326 10.1038/nrmicro1857 Google Scholar Crossref Search ADS PubMed WorldCat 71. Kylilis N , Tuza ZA, Stan GB, Polizzi KM Tools for engineering coordinated system behaviour in synthetic microbial consortia Nat Commun 2018 9 2677 10.1038/s41467-018-05046-2 6041260 Google Scholar Crossref Search ADS PubMed WorldCat 72. LaPara TM , Zakharova T, Nakatsu CH, Konopka A Functional and structural adaptations of bacterial communities growing on particulate substrates under stringent nutrient limitation Microb Ecol 2002 44 317 326 10.1007/s00248-002-1046-8 Google Scholar Crossref Search ADS PubMed WorldCat 73. Lee J , Saddler JN, Um Y, Woo HM Adaptive evolution and metabolic engineering of a cellobiose- and xylose- negative Corynebacterium glutamicum that co-utilizes cellobiose and xylose Microb Cell Fact 2016 15 20 10.1186/s12934-016-0420-z 4722713 Google Scholar Crossref Search ADS PubMed WorldCat 74. Lee PK , Men Y, Wang S, He J, Alvarez-Cohen L Development of a fluorescence-activated cell sorting method coupled with whole genome amplification to analyze minority and trace Dehalococcoides genomes in microbial communities Environ Sci Technol 2015 49 1585 1593 10.1021/es503888y Google Scholar Crossref Search ADS PubMed WorldCat 75. Lian J , Bao Z, Hu S, Zhao H Engineered CRISPR/Cas9 system for multiplex genome engineering of polyploid industrial yeast strains Biotechnol Bioeng 2018 10.1002/bit.26569 Google Scholar OpenURL Placeholder Text WorldCat Crossref 76. Liang J , Bai Y, Men Y, Qu J Microbe-microbe interactions trigger Mn(II)-oxidizing gene expression ISME J 2017 11 67 77 10.1038/ismej.2016.106 Google Scholar Crossref Search ADS PubMed WorldCat 77. Lozanovski A , Lindner JP, Bos U Environmental evaluation and comparison of selected industrial scale biomethane production facilities across Europe Int J Life Cycle Ass 2014 19 1823 1832 10.1007/s11367-014-0791-5 Google Scholar Crossref Search ADS WorldCat 78. Luesken FA , Sanchez J, van Alen TA, Sanabria J, Op den Camp HJM, Jetten MSM, Kartal B Simultaneous nitrite-dependent anaerobic methane and ammonium oxidation processes Appl Environ Microbiol 2011 77 6802 6807 10.1128/Aem.05539-11 3187098 Google Scholar Crossref Search ADS PubMed WorldCat 79. Ma Q , Zhou J, Zhang W, Meng X, Sun J, Yuan YJ Integrated proteomic and metabolomic analysis of an artificial microbial community for two-step production of vitamin C PLoS One 2011 6 e26108 10.1371/journal.pone.0026108 3189245 Google Scholar Crossref Search ADS PubMed WorldCat 80. Maixner F , Noguera DR, Anneser B, Stoecker K, Wegl G, Wagner M, Daims H Nitrite concentration influences the population structure of Nitrospira-like bacteria Environ Microbiol 2006 8 1487 1495 10.1111/j.1462-2920.2006.01033.x Google Scholar Crossref Search ADS PubMed WorldCat 81. Mao X , Oremland RS, Liu T, Gushgari S, Landers AA, Baesman SM, Alvarez-Cohen L Acetylene fuels TCE reductive dechlorination by defined Dehalococcoides/Pelobacter consortia Environ Sci Technol 2017 51 2366 2372 10.1021/acs.est.6b05770 6436540 Google Scholar Crossref Search ADS PubMed WorldCat 82. Mao XW , Stenuit B, Polasko A, Alvarez-Cohen L Efficient metabolic exchange and electron transfer within a syntrophic trichloroethene-degrading coculture of Dehalococcoides mccartyi 195 and Syntrophomonas wolfei Appl Environ Microbiol 2015 81 2015 2024 10.1128/Aem.03464-14 4345365 Google Scholar Crossref Search ADS PubMed WorldCat 83. McGlynn SE , Chadwick GL, Kempes CP, Orphan VJ Single cell activity reveals direct electron transfer in methanotrophic consortia Nature 2015 526 531-U146 10.1038/nature15512 Google Scholar Crossref Search ADS WorldCat 84. McInerney MJ , Sieber JR, Gunsalus RP Syntrophy in anaerobic global carbon cycles Curr Opin Biotechnol 2009 20 623 632 10.1016/j.copbio.2009.10.001 2790021 Google Scholar Crossref Search ADS PubMed WorldCat 85. Men Y , Feil H, Verberkmoes NC, Shah MB, Johnson DR, Lee PK, West KA, Zinder SH, Andersen GL, Alvarez-Cohen L Sustainable syntrophic growth of Dehalococcoides ethenogenes strain 195 with Desulfovibrio vulgaris Hildenborough and Methanobacterium congolense: global transcriptomic and proteomic analyses ISME J 2012 6 410 421 10.1038/ismej.2011.111 Google Scholar Crossref Search ADS PubMed WorldCat 86. Men Y , Seth EC, Yi S, Allen RH, Taga ME, Alvarez-Cohen L Sustainable growth of Dehalococcoides mccartyi 195 by corrinoid salvaging and remodeling in defined lactate-fermenting consortia Appl Environ Microbiol 2014 80 2133 2141 10.1128/AEM.03477-13 3993147 Google Scholar Crossref Search ADS PubMed WorldCat 87. Men Y , Yu K, Baelum J, Gao Y, Tremblay J, Prestat E, Stenuit B, Tringe SG, Jansson J, Zhang T, Alvarez-Cohen L Metagenomic and metatranscriptomic analyses reveal structure and dynamics of a dechlorinating community containing Dehalococcoides mccartyi and corrinoid-providing microorganisms under cobalamin-limited condition Appl Environ Microbiol 2017 10.1128/aem.03508-16 5377501 Google Scholar OpenURL Placeholder Text WorldCat Crossref 88. Meyer B , Kuehl JV, Price MN, Ray J, Deutschbauer AM, Arkin AP, Stahl DA The energy-conserving electron transfer system used by Desulfovibrio alaskensis strain G20 during pyruvate fermentation involves reduction of endogenously formed fumarate and cytoplasmic and membrane-bound complexes, Hdr-Flox and Rnf Environ Microbiol 2014 16 3463 3486 10.1111/1462-2920.12405 Google Scholar Crossref Search ADS PubMed WorldCat 89. Miller JC , Tan S, Qiao G, Barlow KA, Wang J, Xia DF, Meng X, Paschon DE, Leung E, Hinkley SJ, Dulay GP, Hua KL, Ankoudinova I, Cost GJ, Urnov FD, Zhang HS, Holmes MC, Zhang L, Gregory PD, Rebar EJ A TALE nuclease architecture for efficient genome editing Nat Biotechnol 2011 29 143 148 10.1038/nbt.1755 Google Scholar Crossref Search ADS PubMed WorldCat 90. Minty JJ , Singer ME, Scholz SA, Bae CH, Ahn JH, Foster CE, Liao JC, Lin XN Design and characterization of synthetic fungal–bacterial consortia for direct production of isobutanol from cellulosic biomass Proc Natl Acad Sci USA 2013 110 14592 14597 10.1073/pnas.1218447110 Google Scholar Crossref Search ADS PubMed WorldCat 91. Moore RL The biology of hyphomicrobium and other prosthecate, budding bacteria Annu Rev Microbiol 1981 35 567 594 10.1146/annurev.mi.35.100181.003031 Google Scholar Crossref Search ADS PubMed WorldCat 92. Morris BE , Henneberger R, Huber H, Moissl-Eichinger C Microbial syntrophy: interaction for the common good FEMS Microbiol Rev 2013 37 384 406 10.1111/1574-6976.12019 Google Scholar Crossref Search ADS PubMed WorldCat 93. Mukherjee M , Ray A, Post AF, McKay RM, Bullerjahn GS Identification, enumeration and diversity of nitrifying planktonic archaea and bacteria in trophic end members of the Laurentian Great Lakes J Great Lakes Res 2016 42 39 49 10.1016/j.jglr.2015.11.007 Google Scholar Crossref Search ADS WorldCat 94. Nagaraju S , Davies NK, Walker DJ, Kopke M, Simpson SD Genome editing of Clostridium autoethanogenum using CRISPR/Cas9 Biotechnol Biofuels 2016 9 219 10.1186/s13068-016-0638-3 5069954 Google Scholar Crossref Search ADS PubMed WorldCat 95. Nagasaki A , Kato Y, Meguro K, Yamagishi A, Nakamura C, Uyeda TQP A genome editing vector that enables easy selection and identification of knockout cells Plasmid 2018 98 37 44 10.1016/j.plasmid.2018.08.005 Google Scholar Crossref Search ADS PubMed WorldCat 96. Nemudryi AA , Valetdinova KR, Medvedev SP, Zakian SM TALEN and CRISPR/Cas genome editing systems: tools of discovery Acta Nat 2014 6 19 40 10.32607/20758251-2014-6-3-19-40 Google Scholar Crossref Search ADS WorldCat 97. Olson DG , McBride JE, Shaw AJ, Lynd LR Recent progress in consolidated bioprocessing Curr Opin Biotechnol 2012 23 396 405 10.1016/j.copbio.2011.11.026 Google Scholar Crossref Search ADS PubMed WorldCat 98. Parkin GF , Lynch NA, Kuo WC, Vankeuren EL, Bhattacharya SK Interaction between sulfate reducers and methanogens fed acetate and propionate Res J Water Pollut Control Fed 1990 62 780 788 Google Scholar OpenURL Placeholder Text WorldCat 99. Pawar S Caldicellulosiruptor saccharolyticus: an ideal hydrogen producer? 2014 Lund Lund University Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 100. Peng YZ , Zhu GB Biological nitrogen removal with nitrification and denitrification via nitrite pathway Appl Microbiol Biotechnol 2006 73 15 26 10.1007/s00253-006-0534-z Google Scholar Crossref Search ADS PubMed WorldCat 101. Perez-Garcia O , Lear G, Singhal N Metabolic metwork modeling of microbial interactions in natural and engineered environmental systems Front Microbiol 2016 7 673 10.3389/fmicb.2016.00673 4870247 Google Scholar PubMed OpenURL Placeholder Text WorldCat 102. Port F , Chen HM, Lee T, Bullock SL Optimized CRISPR/Cas tools for efficient germline and somatic genome engineering in Drosophila Proc Natl Acad Sci USA 2014 111 E2967 E2976 10.1073/pnas.1405500111 Google Scholar Crossref Search ADS PubMed WorldCat 103. Raes J , Bork P Molecular eco-systems biology: towards an understanding of community function Nat Rev Microbiol 2008 6 693 699 10.1038/nrmicro1935 Google Scholar Crossref Search ADS PubMed WorldCat 104. Rawle RA , Hamerly T, Tripet BP, Giannone RJ, Wurch L, Hettich RL, Podar M, Copie V, Bothner B Multi-omics analysis provides insight to the Ignicoccus hospitalis-Nanoarchaeum equitans association Biochim Biophys Acta Gen Subj 2017 1861 2218 2227 10.1016/j.bbagen.2017.06.001 Google Scholar Crossref Search ADS PubMed WorldCat 105. Reis MAM , Almeida JS, Lemos PC, Carrondo MJT Effect of hydrogen-sulfide on growth of sulfate reducing bacteria Biotechnol Bioeng 1992 40 593 600 10.1002/bit.260400506 Google Scholar Crossref Search ADS PubMed WorldCat 106. Rochfort S Metabolomics reviewed: a new “Omics” platform technology for systems biology and implications for natural products research J Nat Prod 2005 68 1813 1820 10.1021/np050255w Google Scholar Crossref Search ADS PubMed WorldCat 107. Roe AJ , O’Byrne C, McLaggan D, Booth IR Inhibition of Escherichia coli growth by acetic acid: a problem with methionine biosynthesis and homocysteine toxicity Microbiology 2002 148 2215 2222 10.1099/00221287-148-7-2215 Google Scholar Crossref Search ADS PubMed WorldCat 108. Russell JB , DiezGonzalez F The effects of fermentation acids on bacterial growth Adv Microb Physiol 1998 39 205 234 10.1016/S0065-2911(08)60017-X Google Scholar Crossref Search ADS PubMed WorldCat 109. Sabra W , Dietz D, Tjahjasari D, Zeng AP Biosystems analysis and engineering of microbial consortia for industrial biotechnology Eng Life Sci 2010 10 407 421 10.1002/elsc.201000111 Google Scholar Crossref Search ADS WorldCat 110. Scheller S , Yu H, Chadwick GL, McGlynn SE, Orphan VJ Artificial electron acceptors decouple archaeal methane oxidation from sulfate reduction Science 2016 351 703 707 10.1126/science.aad7154 Google Scholar Crossref Search ADS PubMed WorldCat 111. Schink B Synergistic interactions in the microbial world Antonie Van Leeuwenhoek 2002 81 257 261 10.1023/A:1020579004534 Google Scholar Crossref Search ADS PubMed WorldCat 112. Schink B , Stams AJM Syntrophism among prokaryotes Prokaryotes 2006 2 3 309 335 10.1007/0-387-30742-7_11 Google Scholar OpenURL Placeholder Text WorldCat Crossref 113. Schwartz C , Cheng J-F, Evans R, Schwartz CA, Wagner JM, Anglin S, Beitz A, Pan W, Lonardi S, Blenner M, Alper HS, Yoshikuni Y, Wheeldon I Validating genome-wide CRISPR-Cas9 function in the non-conventional yeast Yarrowia lipolytica BioRxiv 2018 10.1101/358630 Google Scholar OpenURL Placeholder Text WorldCat Crossref 114. Scott SR , Hasty J Quorum sensing communication modules for microbial consortia Acs Synth Biol 2016 5 969 977 10.1021/acssynbio.5b00286 5603278 Google Scholar Crossref Search ADS PubMed WorldCat 115. Shahab RL , Luterbacher JS, Brethauer S, Studer MH Consolidated bioprocessing of lignocellulosic biomass to lactic acid by a synthetic fungal–bacterial consortium Biotechnol Bioeng 2018 115 1207 1215 10.1002/bit.26541 Google Scholar Crossref Search ADS PubMed WorldCat 116. Shong J , Collins CH Engineering the esaR promoter for tunable quorum sensing- dependent gene expression Acs Synth Biol 2013 2 568 575 10.1021/sb4000433 Google Scholar Crossref Search ADS PubMed WorldCat 117. Shong J , Diaz MRJ, Collins CH Towards synthetic microbial consortia for bioprocessing Curr Opin Biotechnol 2012 23 798 802 10.1016/j.copbio.2012.02.001 Google Scholar Crossref Search ADS PubMed WorldCat 118. Shong J , Huang YM, Bystroff C, Collins CH Directed evolution of the quorum-sensing regulator EsaR for increased signal sensitivity ACS Chem Biol 2013 8 789 795 10.1021/cb3006402 4478592 Google Scholar Crossref Search ADS PubMed WorldCat 119. Sieber JR , McInerney MJ, Gunsalus RP Genomic insights into syntrophy: the paradigm for anaerobic metabolic cooperation Annu Rev Microbiol 2012 66 429 452 10.1146/annurev-micro-090110-102844 Google Scholar Crossref Search ADS PubMed WorldCat 120. Skennerton CT , Chourey K, Iyer R, Hettich RL, Tyson GW, Orphan VJ Methane-fueled syntrophy through extracellular electron transfer: uncovering the genomic traits conserved within diverse bacterial partners of anaerobic methanotrophic archaea Mbio 2017 10.1128/mbio.01561-17 5626972 Google Scholar OpenURL Placeholder Text WorldCat Crossref 121. Stahl DA , de la Torre JR Physiology and diversity of ammonia-oxidizing archaea Annu Rev Microbiol 2012 66 83 101 10.1146/annurev-micro-092611-150128 Google Scholar Crossref Search ADS PubMed WorldCat 122. Tang X , He LY, Tao XQ, Dang Z, Guo CL, Lu GN, Yi XY Construction of an artificial microalgal-bacterial consortium that efficiently degrades crude oil J Hazard Mater 2010 181 1158 1162 10.1016/j.jhazmat.2010.05.033 Google Scholar Crossref Search ADS PubMed WorldCat 123. Teague BP , Weiss R Synthetic communities, the sum of parts Science 2015 349 924 925 10.1126/science.aad0876 Google Scholar Crossref Search ADS PubMed WorldCat 124. Urnov FD , Rebar EJ, Holmes MC, Zhang HS, Gregory PD Genome editing with engineered zinc finger nucleases Nat Rev Genet 2010 11 636 646 10.1038/nrg2842 Google Scholar Crossref Search ADS PubMed WorldCat 125. Valdez-Vazquez I , Perez-Rangel M, Tapia A, Buitron G, Molina C, Hernandez G, Amaya-Delgado L Hydrogen and butanol production from native wheat straw by synthetic microbial consortia integrated by species of Enterococcus and Clostridium Fuel 2015 159 214 222 10.1016/j.fuel.2015.06.052 Google Scholar Crossref Search ADS WorldCat 126. Vandenberg L , Lentz CP Anaerobic digestion of pear waste - laboratory equipment design and preliminary results Can Inst F Sci Tec J 1971 4 159 165 10.1016/S0008-3860(71)74222-6 Google Scholar Crossref Search ADS WorldCat 127. VerBerkmoes NC , Denef VJ, Hettich RL, Banfield JF Functional analysis of natural microbial consortia using community proteomics Nat Rev Microbiol 2009 7 196 205 10.1038/nrmicro2080 Google Scholar Crossref Search ADS PubMed WorldCat 128. Waite AJ , Shou W Adaptation to a new environment allows cooperators to purge cheaters stochastically Proc Natl Acad Sci USA 2012 109 19079 19086 10.1073/pnas.1210190109 Google Scholar Crossref Search ADS PubMed WorldCat 129. Wang EX , Ding MZ, Ma Q, Dong XT, Yuan YJ Reorganization of a synthetic microbial consortium for one-step vitamin C fermentation Microb Cell Fact 2016 15 21 10.1186/s12934-016-0418-6 4727326 Google Scholar Crossref Search ADS PubMed WorldCat 130. Wang M , Keeley R, Zalivina N, Halfhide T, Scott K, Zhang Q, van der Steen P, Ergas SJ Advances in algal-prokaryotic wastewater treatment: a review of nitrogen transformations, reactor configurations and molecular tools J Environ Manag 2018 217 845 857 10.1016/j.jenvman.2018.04.021 Google Scholar Crossref Search ADS WorldCat 131. Weber W , Baba M, Fussenegger M Synthetic ecosystems based on airborne inter- and intrakingdom communication Proc Natl Acad Sci USA 2007 104 10435 10440 10.1073/pnas.0701382104 Google Scholar Crossref Search ADS PubMed WorldCat 132. Wen ZQ , Minton NP, Zhang Y, Li Q, Liu JL, Jiang Y, Yang S Enhanced solvent production by metabolic engineering of a twin-clostridial consortium Metab Eng 2017 39 38 48 10.1016/j.ymben.2016.10.013 Google Scholar Crossref Search ADS PubMed WorldCat 133. West SA , Griffin AS, Gardner A, Diggle SP Social evolution theory for microorganisms Nat Rev Microbiol 2006 4 597 607 10.1038/nrmicro1461 Google Scholar Crossref Search ADS PubMed WorldCat 134. Woyke T , Teeling H, Ivanova NN, Huntemann M, Richter M, Gloeckner FO, Boffelli D, Anderson IJ, Barry KW, Shapiro HJ, Szeto E, Kyrpides NC, Mussmann M, Amann R, Bergin C, Ruehland C, Rubin EM, Dubilier N Symbiosis insights through metagenomic analysis of a microbial consortium Nature 2006 443 950 955 10.1038/nature05192 Google Scholar Crossref Search ADS PubMed WorldCat 135. Wu G , Yan Q, Jones JA, Tang YJ, Fong SS, Koffas MAG Metabolic burden: cornerstones in synthetic biology and metabolic engineering applications Trends Biotechnol 2016 34 652 664 10.1016/j.tibtech.2016.02.010 Google Scholar Crossref Search ADS PubMed WorldCat 136. Wyman CE What is (and is not) vital to advancing cellulosic ethanol Trends Biotechnol 2007 25 153 157 10.1016/j.tibtech.2007.02.009 Google Scholar Crossref Search ADS PubMed WorldCat 137. Xia WW , Zhang CX, Zeng XW, Feng YZ, Weng JH, Lin XG, Zhu JG, Xiong ZQ, Xu J, Cai ZC, Jia ZJ Autotrophic growth of nitrifying community in an agricultural soil ISME J 2011 5 1226 1236 10.1038/ismej.2011.5 3146291 Google Scholar Crossref Search ADS PubMed WorldCat 138. Xie GJ , Cai C, Hu SH, Yuan ZG Complete nirogen removal from synthetic anaerobic sludge digestion liquor through integrating anammox and denitrifying anaerobic methane oxidation in a membrane biofilm reactor Environ Sci Technol 2017 51 819 827 10.1021/acs.est.6b04500 Google Scholar Crossref Search ADS PubMed WorldCat 139. Xu T , Li Y, Van Nostrand JD, He Z, Zhou J Cas9-based tools for targeted genome editing and transcriptional control Appl Environ Microbiol 2014 80 1544 1552 10.1128/AEM.03786-13 3957621 Google Scholar Crossref Search ADS PubMed WorldCat 140. Xu T , Li YC, Shi Z, Hemme CL, Li Y, Zhu YH, Van Nostrand JD, He ZL, Zhou JZ Efficient genome editing in Clostridium cellulolyticum via CRISPR-Cas9 nickase Appl Environ Microbiol 2015 81 4423 4431 10.1128/Aem.00873-15 4475897 Google Scholar Crossref Search ADS PubMed WorldCat 141. Yan J , Ritalahti KM, Wagner DD, Loffler FE Unexpected specificity of interspecies cobamide transfer from Geobacter spp. to organohalide-respiring Dehalococcoides mccartyi strains Appl Environ Microbiol 2012 78 6630 6636 10.1128/AEM.01535-12 3426716 Google Scholar Crossref Search ADS PubMed WorldCat 142. Youk H , Lim WA Secreting and sensing the same molecule allows cells to achieve versatile social behaviors Science 2014 343 1242782 10.1126/science.1242782 4145839 Google Scholar Crossref Search ADS PubMed WorldCat 143. Yu K , Yi S, Li B, Guo F, Peng XX, Wang ZP, Wu Y, Alvarez-Cohen L, Zhang T An integrated meta-omics approach reveals substrates involved in synergistic interactions in a bisphenol A (BPA)-degrading microbial community Microbiome 2019 10.1186/s40168-019-0634-5 6599330 Google Scholar OpenURL Placeholder Text WorldCat Crossref 144. Zampieri M , Sekar K, Zamboni N, Sauer U Frontiers of high-throughput metabolomics Curr Opin Chem Biol 2017 36 15 23 10.1016/j.cbpa.2016.12.006 Google Scholar Crossref Search ADS PubMed WorldCat 145. Zhou K , Qiao KJ, Edgar S, Stephanopoulos G Distributing a metabolic pathway among a microbial consortium enhances production of natural products Nat Biotechnol 2015 33 377-U157 10.1038/nbt.3095 Google Scholar OpenURL Placeholder Text WorldCat Crossref 146. Zhou YZ , Pope PB, Li SC, Wen B, Tan FJ, Cheng S, Chen J, Yang JL, Liu F, Lei XJ, Su QQ, Zhou C, Zhao J, Dong XZ, Jin T, Zhou X, Yang S, Zhang GY, Yang HM, Wang J, Yang RF, Eijsink VGH, Wang J Omics-based interpretation of synergism in a soil-derived cellulose-degrading microbial community Sci Rep UK 2014 10.1038/srep05288 Google Scholar OpenURL Placeholder Text WorldCat Crossref 147. Zuroff TR , Curtis WR Developing symbiotic consortia for lignocellulosic biofuel production Appl Microbiol Biotechnol 2012 93 1423 1435 10.1007/s00253-011-3762-9 Google Scholar Crossref Search ADS PubMed WorldCat Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. © Society for Industrial Microbiology 2019 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) © Society for Industrial Microbiology 2019 TI - Synthetic microbial consortia for biosynthesis and biodegradation: promises and challenges JF - Journal of Industrial Microbiology and Biotechnology DO - 10.1007/s10295-019-02211-4 DA - 2019-10-01 UR - https://www.deepdyve.com/lp/oxford-university-press/synthetic-microbial-consortia-for-biosynthesis-and-biodegradation-qYdcXqYHyr SP - 1343 EP - 1358 VL - 46 IS - 9-10 DP - DeepDyve ER -