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Modeling Dynamics of Human Gut Microbiota Derived from Gluten Metabolism: Obtention, Maintenance and Characterization of Complex Microbial Communities

Western diets are rich in gluten-containing products, which are frequently poorly digested. The human large intestine harbors microorganisms able to metabolize undigested gluten fragments that have escaped digestion by human enzymatic activities. The aim of this work was obtaining and culturing complex human gut microbial communities derived from gluten metabolism to model the dynamics of healthy human large intestine microbiota associated with different gluten forms. For this purpose, stool samples from six healthy volunteers were inoculated in media containing predigested gluten or predigested gluten plus non-digested gluten. Passages were carried out every 24 h for 15 days in the same medium and community composition along time was studied via V3-V4 16S rDNA sequencing. Diverse microbial communities were successfully obtained. Moreover, communities were shown to be maintained in culture with stable composition for 14 days. Under non-digested gluten presence, communities were enriched in members of Bacillota, such as Lachnospiraceae, Clostridiaceae, Streptococcaceae, Peptoniphilaceae, Selenomonadaceae or Erysipelotrichaceae, and members of Actinomycetota, such as Bifidobacteriaceae and Eggerthellaceae. Contrarily, communities exposed to digested gluten were enriched in Pseudomonadota. Hence, this study shows a method for culture and stable maintenance of gut communities derived from gluten metabolism. This method enables the analysis of microbial metabolism of gluten in the gut from a community perspective.

Design and application of a novel culturing chip (cChip) for culturing the uncultured aquatic microorganisms

Culturing uncultured microorganisms is an important aspect of microbiology. Once cultured, these microorganisms can be a source of useful antibiotics, enzymes etc. In this study, we have designed a novel culturing chip (cChip) to facilitate the growth of uncultured aquatic bacterial community by concentrating the samples. cChip was optimized for microbial growth using known bacteria in the laboratory as a pre-experiment. Then microorganisms from a freshwater lake were concentrated and inoculated, before putting the inoculated cChip in a simulated lake environment and further sub-culturing on laboratory media. High-throughput sequencing and traditional culturing were also performed for comparison. These three methods were able to detect 265 genera of microorganisms in the sample, of which 78.87% were detected by high-throughput sequencing, 30.94% by cChip, while only 6.42% were obtained by traditional culture. Moreover, all microorganisms obtained by traditional culture were also cultured using the cChip. A total of 45 new strains were isolated from the cChip, and their 16S rRNA gene sequences were 91.35% to 98.7% similar to their closest relatives according to NCBI GenBank database. We conclude that the design and simple operation of cChip can improve the culture efficiency of traditional culture by almost 5 times. To the best of our knowledge, this is the first report comparing a novel culturing method with high-throughput sequencing data and traditional culturing of the same samples.

Sole microbiome progression in a hatchery life cycle, from egg to juvenile

Recirculating aquaculture systems (RAS) pose unique challenges in microbial community management since they rely on a stable community with key target groups, both in the RAS environment and in the host (in this case, Solea senegalensis). Our goal was to determine how much of the sole microbiome is inherited from the egg stage, and how much is acquired during the remainder of the sole life cycle in an aquaculture production batch, especially regarding potentially probiotic and pathogenic groups. Our work comprises sole tissue samples from 2 days before hatching and up to 146 days after hatching (-2 to 146 DAH), encompassing the egg, larval, weaning, and pre-ongrowing stages. Total DNA was isolated from the different sole tissues, as well as from live feed introduced in the first stages, and 16S rRNA gene was sequenced (V6-V8 region) using the Illumina MiSeq platform. The output was analysed with the DADA2 pipeline, and taxonomic attribution with SILVAngs version 138.1. Using the Bray-Curtis dissimilarity index, both age and life cycle stage appeared to be drivers of bacterial community dissimilarity. To try to distinguish the inherited (present since the egg stage) from the acquired community (detected at later stages), different tissues were analysed at 49, 119 and 146 DAH (gill, intestine, fin and mucus). Only a few genera were inherited, but those that were inherited accompany the sole microbiome throughout the life cycle. Two genera of potentially probiotic bacteria (Bacillus and Enterococcus) were already present in the eggs, while others were acquired later, in particularly, forty days after live feed was introduced. The potentially pathogenic genera Tenacibaculum and Vibrio were inherited from the eggs, while Photobacterium and Mycobacterium seemed to be acquired at 49 and 119 DAH, respectively. Significant co-occurrence was found between Tenacibaculum and both Photobacterium and Vibrio. On the other hand, significantly negative correlations were detected between Vibrio and Streptococcus, Bacillus, Limosilactobacillus and Gardnerella. Our work reinforces the importance of life cycle studies, which can contribute to improve production husbandry strategies. However, we still need more information on this topic as repetition of patterns in different settings is essential to confirm our findings.

Succession of the microbial communities and metabolic functions in composting or deep burial processing of dead chickens

1. This study examined the effects of composting and deep burial techniques on degradation efficiency of dead chickens. Different raw materials (crushed branches or rape straws) and disinfectants (quicklime or bleaching powder) were applied in composting and deep burial process, respectively. The whole process lasted for 90 d in both summer and winter.2. High throughput sequencing displayed that Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria and Deinococcus-Thermus were the most dominant bacterial phyla during the experiment. The relative abundance of Firmicutes dwindled gradually with prolonged composting duration, while Proteobacteria, Bacteroidetes and Deinococcus-Thermous increased gradually over time.3. The bacterial functions identified from the KEGG pathway showed that amino acid and carbohydrate metabolism were the major microbial metabolic pathways that determined final degradation efficiency. At the end of the trial, the decomposition status of chicken carcases and faecal coliforms were measured.4. The results demonstrated that the optimum decomposition effect was obtained in composting compared with other treatment groups. Low ambient temperature reduced degradation efficiency, due to restricted microbial activity. In addition, faecal coliforms were not completely removed by the deep burial process of dead chickens in winter.5. These findings provide a theoretical basis for the feasibility of composting chicken carcases instead of deep burial.

Determinants of synergistic cell-cell interactions in bacteria

Bacteria are ubiquitous and colonize virtually every conceivable habitat on earth. To achieve this, bacteria require different metabolites and biochemical capabilities. Rather than trying to produce all of the needed materials by themselves, bacteria have evolved a range of synergistic interactions, in which they exchange different commodities with other members of their local community. While it is widely acknowledged that synergistic interactions are key to the ecology of both individual bacteria and entire microbial communities, the factors determining their establishment remain poorly understood. Here we provide a comprehensive overview over our current knowledge on the determinants of positive cell-cell interactions among bacteria. Taking a holistic approach, we review the literature on the molecular mechanisms bacteria use to transfer commodities between bacterial cells and discuss to which extent these mechanisms favour or constrain the successful establishment of synergistic cell-cell interactions. In addition, we analyse how these different processes affect the specificity among interaction partners. By drawing together evidence from different disciplines that study the focal question on different levels of organisation, this work not only summarizes the state of the art in this exciting field of research, but also identifies new avenues for future research.

Impacts of biochar-based fertilization on soil arbuscular mycorrhizal fungal community structure in a karst mountainous area

The application of biochar-based fertilizer can improve soil properties in part by stimulating microbial activity and growth. Karst ecosystems, which make up large areas of Southwest China, are prone to degradation. Understanding the response of arbuscular mycorrhizal fungal (AMF) community structure to biochar-based fertilizer application is of great significance to karst soil restoration. A field experiment was conducted in a typical karst soil (calcareous sandy loam) in Southwest China. A high-throughput sequencing approach was used to investigate the effect of biochar-based fertilization on AMF community structure in the karst soil. With the control (CK), compost with NPK fertilizer (MF), biochar (B), a lower amount of biochar with compost and NPK fertilizer (B1MF), biochar with compost and NPK fertilizer (BMF), and a higher amount of biochar with compost and NPK fertilizer (B4MF), the field trials were set up for 24 months. Soil amendments increased soil nutrient content and AMF diversity. The composition and structure of the AMF community varied among the treatments. AMF community composition was significantly impacted by soil chemical properties such as TC (total carbon), TN (total nitrogen), TP (total phosphorus), and AP (available phosphorus). Furthermore, network analysis showed that biochar-based fertilization increased the scale and complexity of the microbial co-occurrence network. Biochar-based fertilization enabled more keystone species (such as order Diversisporales and Glomerales) in the soil AMF network to participate in soil carbon resource management and soil nutrient cycling, indicating that biochar-based fertilizer is beneficial for the restoration of degraded karst soils.

Biochar-based fertilizer amendments improve the soil microbial community structure in a karst mountainous area

Biochar-based fertilizer amendment can improve soil properties partly due to stimulated microbial activities and growths. The karst ecosystem is prone to degradation and accounts for a large proportion of southwest China. Understanding of the response of the microbial community structure to biochar-based fertilizer application is of great significance in karst soil restoration. A field experiment located in southwest China was conducted in typical karst soil, and a high-throughput sequencing approach was used to investigate the effect of biochar-based fertilizer application on microbial community structure in karst soil. Field trials were set up for 24 months using the following treatments: control (CK), compost plus NPK fertilizer (MF), biochar (B), less biochar (half the quantity of biochar in B) plus compost and NPK fertilizer (B1MF), biochar plus compost and NPK fertilizer (BMF), and more biochar (double the quantity of biochar in B) plus compost and NPK fertilizer (B4MF). The results elucidated that BMF and B4MF treatments had higher contents of soil carbon and soil nutrients N, P, and K than the other treatments. Soil microbial abundance and diversity were significantly increased by biochar-based fertilizer amendments (BMF and B4MF), compared to CK (P < 0.05). BMF and B4MF treatments significantly increased the relative abundance of dominant microorganisms, compared to CK (P < 0.05). The difference in the composition of indicator microbes between each treated group indicated that soil amendments altered the microbial community structure. There was a strong correlation between soil properties (soil C-, N-, and P-fractions) and microbial community structure. Furthermore, network analysis revealed that the addition of biochar-based fertilizer increased the scale and complexity of the microbial co-occurrence network. To summarize, the application of biochar-based fertilizer enabled more keystone species in the soil microbial network to participate in soil carbon resource management and soil nutrient cycling, indicating that biochar-based fertilizer is beneficial for the restoration of karst-degraded soils.

NetCom: A Network-Based Tool for Predicting Metabolic Activities of Microbial Communities Based on Interpretation of Metagenomics Data

The study of microbial activity can be viewed as a triangle with three sides: environment (dominant resources in a specific habitat), community (species dictating a repertoire of metabolic conversions) and function (production and/or utilization of resources and compounds). Advances in metagenomics enable a high-resolution description of complex microbial communities in their natural environments and support a systematic study of environment-community-function associations. NetCom is a web-tool for predicting metabolic activities of microbial communities based on network-based interpretation of assembled and annotated metagenomics data. The algorithm takes as an input, lists of differentially abundant enzymatic reactions and generates the following outputs: (i) pathway associations of differently abundant enzymes; (ii) prediction of environmental resources that are unique to each treatment, and their pathway associations; (iii) prediction of compounds that are produced by the microbial community, and pathway association of compounds that are treatment-specific; (iv) network visualization of enzymes, environmental resources and produced compounds, that are treatment specific (2 and 3D). The tool is demonstrated on metagenomic data from rhizosphere and bulk soil samples. By predicting root-specific activities, we illustrate the relevance of our framework for forecasting the impact of soil amendments on the corresponding microbial communities. NetCom is available online.

Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR- and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.

Extracellular Metabolism Sets the Table for Microbial Cross-Feeding

The transfer of nutrients between cells, or cross-feeding, is a ubiquitous feature of microbial communities with emergent properties that influence our health and orchestrate global biogeochemical cycles. Cross-feeding inevitably involves the externalization of molecules. Some of these molecules directly serve as cross-fed nutrients, while others can facilitate cross-feeding. Altogether, externalized molecules that promote cross-feeding are diverse in structure, ranging from small molecules to macromolecules. The functions of these molecules are equally diverse, encompassing waste products, enzymes, toxins, signaling molecules, biofilm components, and nutrients of high value to most microbes, including the producer cell. As diverse as the externalized and transferred molecules are the cross-feeding relationships that can be derived from them. Many cross-feeding relationships can be summarized as cooperative but are also subject to exploitation. Even those relationships that appear to be cooperative exhibit some level of competition between partners. In this review, we summarize the major types of actively secreted, passively excreted, and directly transferred molecules that either form the basis of cross-feeding relationships or facilitate them. Drawing on examples from both natural and synthetic communities, we explore how the interplay between microbial physiology, environmental parameters, and the diverse functional attributes of extracellular molecules can influence cross-feeding dynamics. Though microbial cross-feeding interactions represent a burgeoning field of interest, we may have only begun to scratch the surface.

Community analysis and co-occurrence patterns in airway microbial communities during health and disease

Ecological relationships between bacteria are important when considering variation in bacterial communities in humans, with such variation playing an important role in both health and disease.

Using high-throughput sequence data of the 16S rRNA marker-gene, we analysed the prevalence of taxa in the airways of a number of health- and disease-associated cohorts and determined the main drivers of community variance and bacterial co-occurrence.

A number of facultative and obligately anaerobic bacterial taxa are commonly associated with the upper airways, forming the main “core” microbiota, e.g. Streptococcus spp., Veillonella spp., Prevotella spp., Granulicatella spp. and Fusobacterium spp. Opportunistic pathogenic bacteria associated with chronic airways disease, such as Pseudomonas spp. (Pseudomonas aeruginosa), Burkholderia spp. (Burkholderia cepacia complex) and Haemophilus spp. (Haemophilus influenzae) demonstrated poor correlation with other members of their respective communities (ρ<0.5; p>0.005), indicating probable independent acquisition and colonisation. Furthermore, our findings suggest that intra-genus variation between health and disease may affect community assemblies.

Improved understanding of how bacteria assemble in time and space during health and disease will enable the future development of tailored treatment according to the patient's own signature microbiota, potentially providing benefit to patients suffering from airway diseases characterised by chronic infection.

Within the airways, “core” community structures are formed between microbial taxa in both health and disease, with a number of common opportunistic pathogens not being members of such core communitieshttp://bit.ly/2Kau3ni

Modeling trophic dependencies and exchanges among insects' bacterial symbionts in a host-simulated environment

BACKGROUND

Individual organisms are linked to their communities and ecosystems via metabolic activities. Metabolic exchanges and co-dependencies have long been suggested to have a pivotal role in determining community structure. In phloem-feeding insects such metabolic interactions with bacteria enable complementation of their deprived nutrition. The phloem-feeding whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) harbors an obligatory symbiotic bacterium, as well as varying combinations of facultative symbionts. This well-defined bacterial community in B. tabaci serves here as a case study for a comprehensive and systematic survey of metabolic interactions within the bacterial community and their associations with documented occurrences of bacterial combinations. We first reconstructed the metabolic networks of five common B. tabaci symbionts genera (Portiera, Rickettsia, Hamiltonella, Cardinium and Wolbachia), and then used network analysis approaches to predict: (1) species-specific metabolic capacities in a simulated bacteriocyte-like environment; (2) metabolic capacities of the corresponding species' combinations, and (3) dependencies of each species on different media components.

RESULTS

The predictions for metabolic capacities of the symbionts in the host environment were in general agreement with previously reported genome analyses, each focused on the single-species level. The analysis suggests several previously un-reported routes for complementary interactions and estimated the dependency of each symbiont in specific host metabolites. No clear association was detected between metabolic co-dependencies and co-occurrence patterns.

CONCLUSIONS

The analysis generated predictions for testable hypotheses of metabolic exchanges and co-dependencies in bacterial communities and by crossing them with co-occurrence profiles, contextualized interaction patterns into a wider ecological perspective.

Evolution on the bright side of life: microorganisms and the evolution of mutualism

Mutualistic interactions, where two interacting species have a net beneficial effect on each other's fitness, play a crucial role in the survival and evolution of many species. Despite substantial empirical and theoretical work in past decades, the impact of these interactions on natural selection is not fully understood. In addition, mutualisms between microorganisms have been largely ignored, even though they are ecologically important and can be used as tools to bridge the gap between theory and empirical work. Here, I describe two problems with our current understanding of natural selection in mutualism and highlight the properties of microbial mutualisms that could help solve them. One problem is that bias and methodological problems have limited our understanding of the variety of mechanisms by which species may adapt to mutualism. Another problem is that it is rare for experiments testing coevolution in mutualism to address whether each species has adapted to evolutionary changes in its partner. These problems can be addressed with genome resequencing and time-shift experiments, techniques that are easier to perform in microorganisms. In addition, microbial mutualisms may inspire novel insights and hypotheses about natural selection in mutualism.

Analysis of Microbial Functions in the Rhizosphere Using a Metabolic-Network Based Framework for Metagenomics Interpretation

Advances in metagenomics enable high resolution description of complex bacterial communities in their natural environments. Consequently, conceptual approaches for community level functional analysis are in high need. Here, we introduce a framework for a metagenomics-based analysis of community functions. Environment-specific gene catalogs, derived from metagenomes, are processed into metabolic-network representation. By applying established ecological conventions, network-edges (metabolic functions) are assigned with taxonomic annotations according to the dominance level of specific groups. Once a function-taxonomy link is established, prediction of the impact of dominant taxa on the overall community performances is assessed by simulating removal or addition of edges (taxa associated functions). This approach is demonstrated on metagenomic data describing the microbial communities from the root environment of two crop plants – wheat and cucumber. Predictions for environment-dependent effects revealed differences between treatments (root vs. soil), corresponding to documented observations. Metabolism of specific plant exudates (e.g., organic acids, flavonoids) was linked with distinct taxonomic groups in simulated root, but not soil, environments. These dependencies point to the impact of these metabolite families as determinants of community structure. Simulations of the activity of pairwise combinations of taxonomic groups (order level) predicted the possible production of complementary metabolites. Complementation profiles allow formulating a possible metabolic role for observed co-occurrence patterns. For example, production of tryptophan-associated metabolites through complementary interactions is unique to the tryptophan-deficient cucumber root environment. Our approach enables formulation of testable predictions for species contribution to community activity and exploration of the functional outcome of structural shifts in complex bacterial communities. Understanding community-level metabolism is an essential step toward the manipulation and optimization of microbial function. Here, we introduce an analysis framework addressing three key challenges of such data: producing quantified links between taxonomy and function; contextualizing discrete functions into communal networks; and simulating environmental impact on community performances. New technologies will soon provide a high-coverage description of biotic and a-biotic aspects of complex microbial communities such as these found in gut and soil. This framework was designed to allow the integration of high-throughput metabolomic and metagenomic data toward tackling the intricate associations between community structure, community function, and metabolic inputs.

A stable genetic polymorphism underpinning microbial syntrophy

Syntrophies are metabolic cooperations, whereby two organisms co-metabolize a substrate in an interdependent manner. Many of the observed natural syntrophic interactions are mandatory in the absence of strong electron acceptors, such that one species in the syntrophy has to assume the role of electron sink for the other. While this presents an ecological setting for syntrophy to be beneficial, the potential genetic drivers of syntrophy remain unknown to date. Here, we show that the syntrophic sulfate-reducing species Desulfovibrio vulgaris displays a stable genetic polymorphism, where only a specific genotype is able to engage in syntrophy with the hydrogenotrophic methanogen Methanococcus maripaludis. This 'syntrophic' genotype is characterized by two genetic alterations, one of which is an in-frame deletion in the gene encoding for the ion-translocating subunit cooK of the membrane-bound COO hydrogenase. We show that this genotype presents a specific physiology, in which reshaping of energy conservation in the lactate oxidation pathway enables it to produce sufficient intermediate hydrogen for sustained M. maripaludis growth and thus, syntrophy. To our knowledge, these findings provide for the first time a genetic basis for syntrophy in nature and bring us closer to the rational engineering of syntrophy in synthetic microbial communities.

Syntrophic Interactions Within a Butane-Oxidizing Bacterial Consortium Isolated from Puguang Gas Field in China

Butane oxidation by the hydrocarbon degradation bacteria has long been described, but little is known about the microbial interaction in this process. To investigate this interaction, the efficiency of butane oxidation was estimated in monocultures and co-cultures of six strains of butane-oxidizing bacteria (BOB) and a butanol-oxidizing strain. Results showed that the butane degradation velocity was at least 26 times higher in the co-culture of the seven strains (228.50 nmol h(-1)) than in the six individual monocultures (8.71 nmol h(-1)). Gas chromatographic analysis of metabolites in the cultures revealed the accumulation of butanol in the monocultures of BOB strains but not in the co-culture with the butanol-oxidizing strain. These results evidenced a novel syntrophic association between BOB and butanol-oxidizing bacteria in the butane oxidation. The BOB strains oxidized butane into butanol, but this activity was inhibited by the accumulated butanol in monocultures, whereas the removal of butanol by the butanol-oxidizing strain in co-culture could eliminate the suppression and improve the butane degradation efficiency. In the co-culture, both BOB and butanol-oxidizing bacteria could grow and the time needed for butane complete removal was shortened from more than 192 h to less than 4 h. The unsuppressed effect of the co-culture was also consistent with the results of reverse transcription quantitative real-time PCR (RT-qPCR) of bmoX gene because increased expression of this gene was detected during the syntrophic growth compared with that in monoculture, pointing to the upregulation of bmoX in the syntrophic interaction.

Metabolic cross-feeding via intercellular nanotubes among bacteria

Bacteria frequently exchange metabolites by diffusion through the extracellular environment, yet it remains generally unclear whether bacteria can also use cell-cell connections to directly exchange nutrients. Here we address this question by engineering cross-feeding interactions within and between Acinetobacter baylyi and Escherichia coli, in which two distant bacterial species reciprocally exchange essential amino acids. We establish that in a well-mixed environment E. coli, but likely not A. baylyi, can connect to other bacterial cells via membrane-derived nanotubes and use these to exchange cytoplasmic constituents. Intercellular connections are induced by auxotrophy-causing mutations and cease to establish when amino acids are externally supplied. Electron and fluorescence microscopy reveal a network of nanotubular structures that connects bacterial cells and enables an intercellular transfer of cytoplasmic materials. Together, our results demonstrate that bacteria can use nanotubes to exchange nutrients among connected cells and thus help to distribute metabolic functions within microbial communities.

Determining microbial products and identifying molecular targets in the human microbiome

Human-associated microbes are the source of many bioactive microbial products (proteins and metabolites) that play key functions both in human host pathways and in microbe-microbe interactions. Culture-independent studies now provide an accelerated means of exploring novel bioactives in the human microbiome; however, intriguingly, a substantial fraction of the microbial metagenome cannot be mapped to annotated genes or isolate genomes and is thus of unknown function. Meta'omic approaches, including metagenomic sequencing, metatranscriptomics, metabolomics, and integration of multiple assay types, represent an opportunity to efficiently explore this large pool of potential therapeutics. In combination with appropriate follow-up validation, high-throughput culture-independent assays can be combined with computational approaches to identify and characterize novel and biologically interesting microbial products. Here we briefly review the state of microbial product identification and characterization and discuss possible next steps to catalog and leverage the large uncharted fraction of the microbial metagenome.

Combining engineering and evolution to create novel metabolic mutualisms between species

Synthetic communities can be used as model systems for the molecular examination of species interactions. Manipulating synthetic communities to create novel beneficial interactions provides insight into the mechanisms of cooperation as well as the potential to improve the productivity of industrially relevant systems. Here, we present a general scheme for evolving a mutualism from a bacterial consortium in which one species consumes the by-products of another.

The genotypic view of social interactions in microbial communities

Dense and diverse microbial communities are found in many environments. Disentangling the social interactions between strains and species is central to understanding microbes and how they respond to perturbations. However, the study of social evolution in microbes tends to focus on single species. Here, we broaden this perspective and review evolutionary and ecological theory relevant to microbial interactions across all phylogenetic scales. Despite increased complexity, we reduce the theory to a simple null model that we call the genotypic view. This states that cooperation will occur when cells are surrounded by identical genotypes at the loci that drive interactions, with genetic identity coming from recent clonal growth or horizontal gene transfer (HGT). In contrast, because cooperation is only expected to evolve between different genotypes under restrictive ecological conditions, different genotypes will typically compete. Competition between two genotypes includes mutual harm but, importantly, also many interactions that are beneficial to one of the two genotypes, such as predation. The literature offers support for the genotypic view with relatively few examples of cooperation between genotypes. However, the study of microbial interactions is still at an early stage. We outline the logic and methods that help to better evaluate our perspective and move us toward rationally engineering microbial communities to our own advantage.

From metabolism to ecology: cross-feeding interactions shape the balance between polymicrobial conflict and mutualism

Polymicrobial interactions are widespread in nature and play a major role in maintaining human health and ecosystems. Whenever one organism uses metabolites produced by another organism as energy or nutrient sources, it is called cross-feeding. The ecological outcomes of cross-feeding interactions are poorly understood and potentially diverse: mutualism, competition, exploitation, or commensalism. A major reason for this uncertainty is the lack of theoretical approaches linking microbial metabolism to microbial ecology. To address this issue, we explore the dynamics of a one-way interspecific cross-feeding interaction in which food can be traded for a service (detoxification). Our results show that diverse ecological interactions (competition, mutualism, exploitation) can emerge from this simple cross-feeding interaction and can be predicted by the metabolic, demographic, and environmental parameters that govern the balance of the costs and benefits of association. In particular, our model predicts stronger mutualism for intermediate by-product toxicity because the resource-service exchange is constrained to the service being neither too vital (high toxicity impairs resource provision) nor dispensable (low toxicity reduces need for service). These results support the idea that bridging microbial ecology and metabolism is a critical step toward a better understanding of the factors governing the emergence and dynamics of polymicrobial interactions.

Microbial co-occurrence relationships in the human microbiome

The healthy microbiota show remarkable variability within and among individuals. In addition to external exposures, ecological relationships (both oppositional and symbiotic) between microbial inhabitants are important contributors to this variation. It is thus of interest to assess what relationships might exist among microbes and determine their underlying reasons. The initial Human Microbiome Project (HMP) cohort, comprising 239 individuals and 18 different microbial habitats, provides an unprecedented resource to detect, catalog, and analyze such relationships. Here, we applied an ensemble method based on multiple similarity measures in combination with generalized boosted linear models (GBLMs) to taxonomic marker (16S rRNA gene) profiles of this cohort, resulting in a global network of 3,005 significant co-occurrence and co-exclusion relationships between 197 clades occurring throughout the human microbiome. This network revealed strong niche specialization, with most microbial associations occurring within body sites and a number of accompanying inter-body site relationships. Microbial communities within the oropharynx grouped into three distinct habitats, which themselves showed no direct influence on the composition of the gut microbiota. Conversely, niches such as the vagina demonstrated little to no decomposition into region-specific interactions. Diverse mechanisms underlay individual interactions, with some such as the co-exclusion of Porphyromonaceae family members and Streptococcus in the subgingival plaque supported by known biochemical dependencies. These differences varied among broad phylogenetic groups as well, with the Bacilli and Fusobacteria, for example, both enriched for exclusion of taxa from other clades. Comparing phylogenetic versus functional similarities among bacteria, we show that dominant commensal taxa (such as Prevotellaceae and Bacteroides in the gut) often compete, while potential pathogens (e.g. Treponema and Prevotella in the dental plaque) are more likely to co-occur in complementary niches. This approach thus serves to open new opportunities for future targeted mechanistic studies of the microbial ecology of the human microbiome.

The human body is a complex ecosystem where microbes compete, and cooperate. These interactions can support health or promote disease, e.g. in dental plaque formation. The Human Microbiome Project collected and sequenced ca. 5,000 samples from 18 different body sites, including the airways, gut, skin, oral cavity and vagina. These data allowed the first assessment of significant patterns of co-presence and exclusion among human-associated bacteria. We combined sparse regression with an ensemble of similarity measures to predict microbial relationships within and between body sites. This captured known relationships in the dental plaque, vagina, and gut, and also predicted novel interactions involving members of under-characterized phyla such as TM7. We detected relationships necessary for plaque formation and differences in community composition among dominant members of the gut and vaginal microbiomes. Most relationships were strongly niche-specific, with only a few hub microorganisms forming links across multiple body areas. We also found that phylogenetic distance had a strong impact on the interaction type: closely related microorganisms co-occurred within the same niche, whereas most exclusive relationships occurred between more distantly related microorganisms. This establishes both the specific organisms and general principles by which microbial communities associated with healthy humans are assembled and maintained.

How sulphate-reducing microorganisms cope with stress: lessons from systems biology

Sulphate-reducing microorganisms (SRMs) are a phylogenetically diverse group of anaerobes encompassing distinct physiologies with a broad ecological distribution. As SRMs have important roles in the biogeochemical cycling of carbon, nitrogen, sulphur and various metals, an understanding of how these organisms respond to environmental stresses is of fundamental and practical importance. In this Review, we highlight recent applications of systems biology tools in studying the stress responses of SRMs, particularly Desulfovibrio spp., at the cell, population, community and ecosystem levels. The syntrophic lifestyle of SRMs is also discussed, with a focus on system-level analyses of adaptive mechanisms. Such information is important for understanding the microbiology of the global sulphur cycle and for developing biotechnological applications of SRMs for environmental remediation, energy production, biocorrosion control, wastewater treatment and mineral recovery.

Direct exchange of electrons within aggregates of an evolved syntrophic coculture of anaerobic bacteria

Microbial consortia that cooperatively exchange electrons play a key role in the anaerobic processing of organic matter. Interspecies hydrogen transfer is a well-documented strategy for electron exchange in dispersed laboratory cultures, but cooperative partners in natural environments often form multispecies aggregates. We found that laboratory evolution of a coculture of Geobacter metallireducens and Geobacter sulfurreducens metabolizing ethanol favored the formation of aggregates that were electrically conductive. Sequencing aggregate DNA revealed selection for a mutation that enhances the production of a c-type cytochrome involved in extracellular electron transfer and accelerates the formation of aggregates. Aggregate formation was also much faster in mutants that were deficient in interspecies hydrogen transfer, further suggesting direct interspecies electron transfer.

Emergent cooperation in microbial metabolism

Mixed microbial communities exhibit emergent biochemical properties not found in clonal monocultures. We report a new type of synthetic genetic interaction, synthetic mutualism in trans (SMIT), in which certain pairs of auxotrophic Escherichia coli mutants complement one another's growth by cross-feeding essential metabolites. We find significant metabolic synergy in 17% of 1035 such pairs tested, with SMIT partners identified throughout the metabolic network. Cooperative phenotypes show more growth on average by aiding the proliferation of their conjugate partner, thereby expanding the source of their own essential metabolites. We construct a quantitative, predictive, framework for describing SMIT interactions as governed by stoichiometric models of the metabolic networks of the interacting strains.

Evolution of cooperative cross-feeding could be less challenging than originally thought

The act of cross-feeding whereby unrelated species exchange nutrients is a common feature of microbial interactions and could be considered a form of reciprocal altruism or reciprocal cooperation. Past theoretical work suggests that the evolution of cooperative cross-feeding in nature may be more challenging than for other types of cooperation. Here we re-evaluate a mathematical model used previously to study persistence of cross-feeding and conclude that the maintenance of cross-feeding interactions could be favoured for a larger parameter ranges than formerly observed. Strikingly, we also find that large populations of cross-feeders are not necessarily vulnerable to extinction from an initially small number of cheats who receive the benefit of cross-feeding but do not reciprocate in this cooperative interaction. This could explain the widespread cooperative cross-feeding observed in natural populations.

The large-scale organization of the bacterial network of ecological co-occurrence interactions

In their natural environments, microorganisms form complex systems of interactions. Understating the structure and organization of bacterial communities is likely to have broad medical and ecological consequences, yet a comprehensive description of the network of environmental interactions is currently lacking. Here, we mine co-occurrences in the scientific literature to construct such a network and demonstrate an expected pattern of association between the species' lifestyle and the recorded number of co-occurring partners. We further focus on the well-annotated gut community and show that most co-occurrence interactions of typical gut bacteria occur within this community. The network is then clustered into species-groups that significantly correspond with natural occurring communities. The relationships between resource competition, metabolic yield and growth rate within the clusters correspond with the r/K selection theory. Overall, these results support the constructed clusters as a first approximation of a bacterial ecosystem model. This comprehensive collection of predicted communities forms a new data resource for further systematic characterization of the ecological design principals shaping communities. Here, we demonstrate its utility for predicting cooperation and inhibition within communities.