The ecology of the microbiome: Networks, competition, and stability

Cell morphology drives spatial patterning in microbial communities

The clearest phenotypic characteristic of microbial cells is their shape, but we do not understand how cell shape affects the dense communities, known as biofilms, where many microbes live. Here, we use individual-based modeling to systematically vary cell shape and study its impact in simulated communities. We compete cells with different cell morphologies under a range of conditions and ask how shape affects the patterning and evolutionary fitness of cells within a community. Our models predict that cell shape will strongly influence the fate of a cell lineage: we describe a mechanism through which coccal (round) cells rise to the upper surface of a community, leading to a strong spatial structuring that can be critical for fitness. We test our predictions experimentally using strains of Escherichia coli that grow at a similar rate but differ in cell shape due to single amino acid changes in the actin homolog MreB. As predicted by our model, cell types strongly sort by shape, with round cells at the top of the colony and rod cells dominating the basal surface and edges. Our work suggests that cell morphology has a strong impact within microbial communities and may offer new ways to engineer the structure of synthetic communities.

Relationship between intestinal flora microenvironment and colorectal cancer

Intestinal flora is a hot research topic. Studies suggest that intestinal flora is associated with the development of metabolic diseases, autoimmune diseases, neurological disorders, cognitive and behavioral disorders, cancer and so on. In this paper, we retrieved and analyzed the literature published in the past ten years which studied the relationship between microbiota microenvironment and colorectal cancer. We discuss the definitions of intestinal flora, microbiota microenvironment and colorectal cancer, the composition of intestinal flora, imbalance of intestinal flora, correlation between microbiota microenvironment and colorectal cancer, and the pathophysiology of colorectal cancer associated with microbiota microenvironment, with an aim to reveal the role of intestinal flora microenvironment in the pathogenesis of colorectal cancer, and to provide ideas and clues for the development of new intestinal flora-targeted approaches for prevention and treatment of colorectal cancer.

Probiotic Diversity Enhances Rhizosphere Microbiome Function and Plant Disease Suppression

Bacterial communities associated with plant roots play an important role in the suppression of soil-borne pathogens, and multispecies probiotic consortia may enhance disease suppression efficacy. Here we introduced defined Pseudomonas species consortia into naturally complex microbial communities and measured the importance of Pseudomonas community diversity for their survival and the suppression of the bacterial plant pathogen Ralstonia solanacearum in the tomato rhizosphere microbiome. The survival of introduced Pseudomonas consortia increased with increasing diversity. Further, high Pseudomonas diversity reduced pathogen density in the rhizosphere and decreased the disease incidence due to both intensified resource competition and interference with the pathogen. These results provide novel mechanistic insights into elevated pathogen suppression by diverse probiotic consortia in naturally diverse plant rhizospheres. Ecologically based community assembly rules could thus play a key role in engineering functionally reliable microbiome applications.

The increasing demand for food supply requires more-efficient control of plant diseases. The use of probiotics, i.e., naturally occurring bacterial antagonists and competitors that suppress pathogens, has recently reemerged as a promising alternative to agrochemical use. It is, however, still unclear how many and which strains we should choose for constructing effective probiotic consortia. Here we present a general ecological framework for assembling effective probiotic communities based on in vitro characterization of community functioning. Specifically, we show that increasing the diversity of probiotic consortia enhances community survival in the naturally diverse rhizosphere microbiome, leading to increased pathogen suppression via intensified resource competition and interference with the pathogen. We propose that these ecological guidelines can be put to the test in microbiome engineering more widely in the future.

Making a microbiome: the many determinants of host-associated microbial community composition

The composition of many host-associated microbial communities is characterized by seemingly contradictory features: strong selection for specific taxa by the host, but substantial variability among hosts and over time within one host. Recent advances have revealed that both deterministic and stochastic processes operating across multiple spatial scales shape the composition of host-associated microbial communities. Although most research has focused on deterministic processes within individual hosts, the microbiota within each host is increasingly recognized to contribute to a wider metacommunity maintained by transmission between individual hosts and dispersal between host-associated and free-living microbial communities. By applying a community ecology perspective encompassing the microbial metacommunity, the many determinants of host-associated microbial community composition can be identified, guiding the directions of future research.

MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles

Background

The complexity and dynamics of microbial communities are major factors in the ecology of a system. With the NGS technique, metagenomics data provides a new way to explore microbial interactions. Lotka-Volterra models, which have been widely used to infer animal interactions in dynamic systems, have recently been applied to the analysis of metagenomic data.

Results

In this paper, we present the Lotka-Volterra model based tool, the Metagenomic Microbial Interacticon Simulator (MetaMIS), which is designed to analyze the time series data of microbial community profiles. MetaMIS first infers underlying microbial interactions from abundance tables for operational taxonomic units (OTUs) and then interprets interaction networks using the Lotka-Volterra model. We also embed a Bray-Curtis dissimilarity method in MetaMIS in order to evaluate the similarity to biological reality. MetaMIS is designed to tolerate a high level of missing data, and can estimate interaction information without the influence of rare microbes. For each interaction network, MetaMIS systematically examines interaction patterns (such as mutualism or competition) and refines the biotic role within microbes. As a case study, we collect a human male fecal microbiome and show that Micrococcaceae, a relatively low abundance OTU, is highly connected with 13 dominant OTUs and seems to play a critical role. MetaMIS is able to organize multiple interaction networks into a consensus network for comparative studies; thus we as a case study have also identified a consensus interaction network between female and male fecal microbiomes.

Conclusions

MetaMIS provides an efficient and user-friendly platform that may reveal new insights into metagenomics data. MetaMIS is freely available at: https://sourceforge.net/projects/metamis/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1359-0) contains supplementary material, which is available to authorized users.

Estimating the probability of coexistence in cross-feeding communities

The dynamics of many microbial ecosystems are driven by cross-feeding interactions, in which metabolites excreted by some species are metabolised further by others. The population dynamics of such ecosystems are governed by frequency-dependent selection, which allows for stable coexistence of two or more species. We have analysed a model of cross-feeding based on the replicator equation, with the aim of establishing criteria for coexistence in ecosystems containing three species, given the information of the three species' ability to coexist in their three separate pairs, i.e. the long term dynamics in the three two-species component systems. The triple-system is studied statistically and the probability of coexistence in the species triplet is computed for two models of species interactions. The interaction parameters are modelled either as stochastically independent or organised in a hierarchy where any derived metabolite carries less energy than previous nutrients in the metabolic chain. We differentiate between different modes of coexistence with respect to the pair-wise dynamics of the species, and find that the probability of coexistence is close to 12 for triplet systems with three pair-wise coexistent pairs and for the so-called intransitive systems. Systems with two and one pair-wise coexistent pairs are more likely to exist for random interaction parameters, but are on the other hand much less likely to exhibit triplet coexistence. Hence we conclude that certain species triplets are, from a statistical point of view, rare, but if allowed to interact are likely to coexist. This knowledge might be helpful when constructing synthetic microbial communities for industrial purposes.

The robustness of ecosystems to the species loss of community

To study the robustness of ecosystems is crucial to promote the sustainable development of human society. This paper aims to analyze the robustness of ecosystems from an interesting viewpoint of the species loss of community. Unlike the existing definitions, we first introduce the notion of a community as a population of species belonging to the same trophic level. We then put forward a novel multiobjective optimization model which can be utilized to discover community structures from arbitrary unipartite networks. Because an ecosystem is commonly represented as a multipartite network, we further introduce a mechanism of competition among species whereby a multipartite network is transformed into a unipartite signed network without loss of species interaction information. Finally, we examine three strategies to test the robustness of an ecosystem. Our experiments indicate that ecosystems are robust to random species loss of community but fragile to target ones. We also investigate the relationships between the robustness of an ecosystem and that of its community composed network both to species loss. Our experiments indicate that the robustness analysis of a large-scale ecosystem to species loss may be akin to that of its community composed network which is usually small in size.

Contextual organismality: Beyond pattern to process in the emergence of organisms

Biologists have taken the concept of organism largely for granted. However, advances in the study of chimerism, symbiosis, bacterial‐eukaryote associations, and microbial behavior have prompted a redefinition of organisms as biological entities exhibiting low conflict and high cooperation among their parts. This expanded view identifies organisms in evolutionary time. However, the ecological processes, mechanisms, and traits that drive the formation of organisms remain poorly understood. Recognizing that organismality can be context dependent, we advocate elucidating the ecological contexts under which entities do or do not act as organisms. Here we develop a “contextual organismality” framework and provide examples of entities, such as honey bee colonies, tumors, and bacterial swarms, that can act as organisms under specific life history, resource, or other ecological circumstances. We suggest that context dependence may be a stepping stone to the development of increased organismal unification, as the most integrated biological entities generally show little context dependence. Recognizing that organismality is contextual can identify common patterns and testable hypotheses across different entities. The contextual organismality framework can illuminate timeless as well as pressing issues in biology, including topics as disparate as cancer emergence, genomic conflict, evolution of symbiosis, and the role of the microbiota in impacting host phenotype.

Alteration of Fecal Microbiota Profiles in Juvenile Idiopathic Arthritis. Associations with HLA-B27 Allele and Disease Status

Alteration of gut microbiota is involved in several chronic inflammatory and autoimmune diseases, including rheumatoid arthritis, and gut microbial “pro-arthritogenic” profiles have been hypothesized. Intestinal inflammation may be involved in spondyloarthropathies and in a subset of patients affected by Juvenile Idiopathic Arthritis (JIA), the most common chronic rheumatic disease of childhood. We compared the fecal microbiota composition of JIA patients with healthy subjects (HS), evaluating differences in microbial profiles between sub-categories of JIA, such as enthesitis-related arthritis (JIA-ERA), in which inflammation of entheses occurs, and polyarticular JIA, non-enthesitis related arthritis (JIA-nERA). Through taxon-level analysis, we discovered alteration of fecal microbiota components that could be involved in subclinical gut inflammation, and promotion of joint inflammation. We observed abundance in Ruminococcaceae in both JIA categories, reduction in Clostridiaceae and Peptostreptococcaceae in JIA-ERA, and increase in Veillonellaceae in JIA-nERA, respectively, compared with HS. Among the more relevant genera, we found an increase in Clostridium cluster XIVb, involved in colitis and arthritis, in JIA-ERA patients compared with HS, and a trend of decrease in Faecalibacterium, known for anti-inflammatory properties, in JIA-nERA compared with JIA-ERA and HS. Differential abundant taxa identified JIA patients for the HLA-B27 allele, including Bilophila, Clostridium cluster XIVb, Oscillibacter, and Parvimonas. Prediction analysis of metabolic functions showed that JIA-ERA metagenome was differentially enriched in bacterial functions related to cell motility and chemotaxis, suggesting selection of potential virulence traits. We also discovered differential microbial profiles and intra-group variability among active disease and remission, suggesting instability of microbial ecosystem in autoimmune diseases with respect to healthy status. Similarly to other chronic autoimmune and inflammatory diseases, different microbial profiles, as observed among different JIA subgroups compared to HS, and potential functional acquisition related to migration, could promote inflammation and contribute to the disease pathogenesis.

Transitioning from Microbiome Composition to Microbial Community Interactions: The Potential of the Metaorganism Hydra as an Experimental Model

Animals are home to complex microbial communities, which are shaped through interactions within the community, interactions with the host, and through environmental factors. The advent of high-throughput sequencing methods has led to novel insights in changing patterns of community composition and structure. However, deciphering the different types of interactions among community members, with their hosts and their interplay with their environment is still a challenge of major proportion. The emerging fields of synthetic microbial ecology and community systems biology have the potential to decrypt these complex relationships. Studying host-associated microbiota across multiple spatial and temporal scales will bridge the gap between individual microorganism studies and large-scale whole community surveys. Here, we discuss the unique potential of Hydra as an emerging experimental model in microbiome research. Through in vivo, in vitro, and in silico approaches the interaction structure of host-associated microbial communities and the effects of the host on the microbiota and its interactions can be disentangled. Research in the model system Hydra can unify disciplines from molecular genetics to ecology, opening up the opportunity to discover fundamental rules that govern microbiome community stability.

Microbiome: Should we diversify from diversity?

Studies on microbiome diversity are flooding the current literature, yet lessons from ecology clearly demonstrate that diversity is just one factor to consider when analyzing an ecosystem, along with its stability, structure and function. Measures of diversity may be a useful tool for interpreting metagenomic data but the question remains as to how informative they are and what insight they may provide into the state of the microbiome. A study utilizing mathematical modeling to investigate the ecological dynamics of microbial communities has shown that diversity and stability may not always be concomitant. This finding is pertinent to the gut microbiome field, especially since diversity comparisons between healthy and pathological states frequently yield contradictory results. There is a need to broaden our approach to the analysis of microbiome data if we are to better understand this complex ecological community and its role in human health and disease.

Beyond 16S rRNA Community Profiling: Intra-Species Diversity in the Gut Microbiota

Interactions with microbes affect many aspects of animal biology, including immune system development, nutrition and health. In vertebrates, the gut microbiota is dominated by a small subset of phyla, but the species composition within these phyla is typically not conserved. Moreover, several recent studies have shown that bacterial species in the gut are composed of a multitude of strains, which frequently co-exist in their host, and may be host-specific. However, since the study of intra-species diversity is challenging, particularly in the setting of complex, host-associated microbial communities, our current understanding of the distribution, evolution and functional relevance of intra-species diversity in the gut is scarce. In order to unravel how genomic diversity translates into phenotypic diversity, community analyses going beyond 16S rRNA profiling, in combination with experimental approaches, are needed. Recently, the honeybee has emerged as a promising model for studying gut bacterial communities, particularly in terms of strain-level diversity. Unlike most other invertebrates, the honeybee gut is colonized by a remarkably consistent and specific core microbiota, which is dominated by only eight bacterial species. As for the vertebrate gut microbiota, these species are composed of highly diverse strains suggesting that similar evolutionary forces shape gut community structures in vertebrates and social insects. In this review, we outline current knowledge on the evolution and functional relevance of strain diversity within the gut microbiota, including recent insights gained from mammals and other animals such as the honeybee. We discuss methodological approaches and propose possible future avenues for studying strain diversity in complex bacterial communities.

Effects of captivity and artificial breeding on microbiota in feces of the red-crowned crane (Grus japonensis)

Reintroduction of the threatened red-crowned crane has been unsuccessful. Although gut microbiota correlates with host health, there is little information on gut microbiota of cranes under different conservation strategies. The study examined effects of captivity, artificial breeding and life stage on gut microbiota of red-crown cranes. The gut microbiotas of wild, captive adolescent, captive adult, artificially bred adolescent and artificially bred adult cranes were characterized by next-generation sequencing of 16S rRNA gene amplicons. The gut microbiotas were dominated by three phyla: Firmicutes (62.9%), Proteobacteria (29.9%) and Fusobacteria (9.6%). Bacilli dominated the 'core' community consisting of 198 operational taxonomic units (OTUs). Both captivity and artificial breeding influenced the structures and diversities microbiota of the gut. Especially, wild cranes had distinct compositions of gut microbiota from captive and artificially bred cranes. The greatest alpha diversity was found in captive cranes, while wild cranes had the least. According to the results of ordination analysis, influences of captivity and artificial breeding were greater than that of life stage. Overall, captivity and artificial breeding influenced the gut microbiota, potentially due to changes in diet, vaccination, antibiotics and living conditions. Metagenomics can serve as a supplementary non-invasive screening tool for disease control.

MMinte: an application for predicting metabolic interactions among the microbial species in a community

BACKGROUND

The explosive growth of microbiome research has yielded great quantities of data. These data provide us with many answers, but raise just as many questions. 16S rDNA-the backbone of microbiome analyses-allows us to assess α-diversity, β-diversity, and microbe-microbe associations, which characterize the overall properties of an ecosystem. However, we are still unable to use 16S rDNA data to directly assess the microbe-microbe and microbe-environment interactions that determine the broader ecology of that system. Thus, properties such as competition, cooperation, and nutrient conditions remain insufficiently analyzed. Here, we apply predictive community metabolic models of microbes identified with 16S rDNA data to probe the ecology of microbial communities.

RESULTS

We developed a methodology for the large-scale assessment of microbial metabolic interactions (MMinte) from 16S rDNA data. MMinte assesses the relative growth rates of interacting pairs of organisms within a community metabolic network and whether that interaction has a positive or negative effect. Moreover, MMinte's simulations take into account the nutritional environment, which plays a strong role in determining the metabolism of individual microbes. We present two case studies that demonstrate the utility of this software. In the first, we show how diet influences the nature of the microbe-microbe interactions. In the second, we use MMinte's modular feature set to better understand how the growth of Desulfovibrio piger is affected by, and affects the growth of, other members in a simplified gut community under metabolic conditions suggested to be determinant for their dynamics.

CONCLUSION

By applying metabolic models to commonly available sequence data, MMinte grants the user insight into the metabolic relationships between microbes, highlighting important features that may relate to ecological stability, susceptibility, and cross-feeding. These relationships are at the foundation of a wide range of ecological questions that impact our ability to understand problems such as microbially-derived toxicity in colon cancer.

Interspecific Bacterial Interactions are Reflected in Multispecies Biofilm Spatial Organization

Interspecies interactions are essential for the persistence and development of any kind of complex community, and microbial biofilms are no exception. Multispecies biofilms are structured and spatially defined communities that have received much attention due to their omnipresence in natural environments. Species residing in these complex bacterial communities usually interact both intra- and interspecifically. Such interactions are considered to not only be fundamental in shaping overall biomass and the spatial distribution of cells residing in multispecies biofilms, but also to result in coordinated regulation of gene expression in the different species present. These communal interactions often lead to emergent properties in biofilms, such as enhanced tolerance against antibiotics, host immune responses, and other stresses, which have been shown to provide benefits to all biofilm members not only the enabling sub-populations. However, the specific molecular mechanisms of cellular processes affecting spatial organization, and vice versa, are poorly understood and very complex to unravel. Therefore, detailed description of the spatial organization of individual bacterial cells in multispecies communities can be an alternative strategy to reveal the nature of interspecies interactions of constituent species. Closing the gap between visual observation and biological processes may become crucial for resolving biofilm related problems, which is of utmost importance to environmental, industrial, and clinical implications. This review briefly presents the state of the art of studying interspecies interactions and spatial organization of multispecies communities, aiming to support theoretical and practical arguments for further advancement of this field.

Resource Availability Modulates the Cooperative and Competitive Nature of a Microbial Cross-Feeding Mutualism

Mutualisms between species play an important role in ecosystem function and stability. However, in some environments, the competitive aspects of an interaction may dominate the mutualistic aspects. Although these transitions could have far-reaching implications, it has been difficult to study the causes and consequences of this mutualistic–competitive transition in experimentally tractable systems. Here, we study a microbial cross-feeding mutualism in which each yeast strain supplies an essential amino acid for its partner strain. We find that, depending upon the amount of freely available amino acid in the environment, this pair of strains can exhibit an obligatory mutualism, facultative mutualism, competition, parasitism, competitive exclusion, or failed mutualism leading to extinction of the population. A simple model capturing the essential features of this interaction explains how resource availability modulates the interaction and predicts that changes in the dynamics of the mutualism in deteriorating environments can provide advance warning that collapse of the mutualism is imminent. We confirm this prediction experimentally by showing that, in the high nutrient competitive regime, the strains rapidly reach a common carrying capacity before slowly reaching the equilibrium ratio between the strains. However, in the low nutrient regime, before collapse of the obligate mutualism, we find that the ratio rapidly reaches its equilibrium and it is the total abundance that is slow to reach equilibrium. Our results provide a general framework for how mutualisms may transition between qualitatively different regimes of interaction in response to changes in nutrient availability in the environment.

A combination of computational modeling and experiments reveals the striking effects of changing resource availability on the population dynamics observed between two cross-feeding yeast strains.

Species often engage in mutualistic interactions that are beneficial for both partners. However, there is also a cost associated with cooperation, for example, in the form of energy required to make nutrients for a partner. When environments change, the costs and benefits of cooperating can change as well, and this can cause the mutualistic interaction to break down into other interaction types, such as parasitism. In this study, we varied nutrient availability to examine how changing environments can affect the interaction between two cross-feeding yeast strains. Lower nutrient concentrations made each strain more dependent on the nutrients provided by its partner strain and thus favored cooperation. Using both experiments and mathematic models, we found that in different environments, these yeast strains can interact in at least seven different qualitatively different ways, including obligate mutualism, facultative mutualism, parasitism, and competition. We also found that the dynamics of how the two strains influence each other change drastically in different nutrient concentrations. Examining the population dynamics could therefore potentially be used to predict the stability or collapse of a community.

Bacteroidales Secreted Antimicrobial Proteins Target Surface Molecules Necessary for Gut Colonization and Mediate Competition In Vivo

We recently showed that human gut Bacteroidales species secrete antimicrobial proteins (BSAPs), and we characterized in vitro the first such BSAP produced by Bacteroides fragilis In this study, we identified a second potent BSAP produced by the ubiquitous and abundant human gut species Bacteroides uniformis The two BSAPs contain a membrane attack complex/perforin (MACPF) domain but share very little sequence similarity. We identified the target molecules of BSAP-sensitive cells and showed that each BSAP targets a different class of surface molecule: BSAP-1 targets an outer membrane protein of sensitive B. fragilis strains, and BSAP-2 targets the O-antigen glycan of lipopolysaccharide (LPS) of sensitive B. uniformis strains. Species-wide genomic and phenotypic analyses of B. fragilis and B. uniformis showed that BSAP-producing strains circumvent killing by synthesizing an orthologous nontargeted surface molecule. The BSAP genes are adjacent to the gene(s) encoding their target replacements, suggesting coacquisition. Using a gnotobiotic mouse competitive-colonization model, we found that the BSAP surface targets are important for colonization of the mammalian gut, thereby explaining why they are maintained in sensitive strains and why they were replaced rather than deleted in BSAP-producing strains. Using isogenic BSAP-producing, -sensitive, and -resistant strains, we show that a BSAP-producing strain outcompetes a sensitive strain but not a resistant strain in the mammalian gut. Human gut metagenomic datasets reveal that BSAP-1-sensitive strains do not cooccur with BSAP-1-producing strains in human gut microbiotas, further supporting the idea that BSAPs are important competitive factors with relevance to the strain-level composition of the human gut microbiota.

IMPORTANCE

We know relatively little about the ecology of the human intestinal microbiota and the combination of factors that dictate which strains and species occupy an individual's gut microbial community. Interference competition, mediated by bacterial factors that directly harm other members, is beginning to be appreciated as important in contributing to species- and strain-level dynamics of abundant gut bacteria. Here, we show that gut Bacteroidales secrete antimicrobial proteins (BSAPs) that antagonize strains of the same species. We show that BSAPs target molecules of sensitive cells that are important for gut colonization and therefore are maintained in sensitive cells. In an experimental animal model of gut colonization, a BSAP-1-producing strain antagonized and outcompeted an isogenic sensitive strain. Furthermore, metagenomic analyses showed that BSAP-1-producing and -sensitive strains are not found together in human gut microbiotas. These data suggest that BSAPs are strong ecological drivers shaping the strain-level composition of gut communities.

Signaling in Host-Associated Microbial Communities

Human-associated microbiota form and stabilize communities based on interspecies interactions. We review how these microbe-microbe and microbe-host interactions are communicated to shape communities over a human's lifespan, including periods of health and disease. Modeling and dissecting signaling in host-associated communities is crucial to understand their function and will open the door to therapies that prevent or correct microbial community dysfunction to promote health and treat disease.

Multifaceted Interfaces of Bacterial Competition

Microbial communities span many orders of magnitude, ranging in scale from hundreds of cells on a single particle of soil to billions of cells within the lumen of the gastrointestinal tract. Bacterial cells in all habitats are members of densely populated local environments that facilitate competition between neighboring cells. Accordingly, bacteria require dynamic systems to respond to the competitive challenges and the fluctuations in environmental circumstances that tax their fitness. The assemblage of bacteria into communities provides an environment where competitive mechanisms are developed into new strategies for survival. In this minireview, we highlight a number of mechanisms used by bacteria to compete between species. We focus on recent discoveries that illustrate the dynamic and multifaceted functions used in bacterial competition and discuss how specific mechanisms provide a foundation for understanding bacterial community development and function.

Host Gut Motility Promotes Competitive Exclusion within a Model Intestinal Microbiota

The gut microbiota is a complex consortium of microorganisms with the ability to influence important aspects of host health and development. Harnessing this “microbial organ” for biomedical applications requires clarifying the degree to which host and bacterial factors act alone or in combination to govern the stability of specific lineages. To address this issue, we combined bacteriological manipulation and light sheet fluorescence microscopy to monitor the dynamics of a defined two-species microbiota within a vertebrate gut. We observed that the interplay between each population and the gut environment produces distinct spatiotemporal patterns. As a consequence, one species dominates while the other experiences sudden drops in abundance that are well fit by a stochastic mathematical model. Modeling revealed that direct bacterial competition could only partially explain the observed phenomena, suggesting that a host factor is also important in shaping the community. We hypothesized the host determinant to be gut motility, and tested this mechanism by measuring colonization in hosts with enteric nervous system dysfunction due to a mutation in the ret locus, which in humans is associated with the intestinal motility disorder known as Hirschsprung disease. In mutant hosts we found reduced gut motility and, confirming our hypothesis, robust coexistence of both bacterial species. This study provides evidence that host-mediated spatial structuring and stochastic perturbation of communities can drive bacterial population dynamics within the gut, and it reveals a new facet of the intestinal host–microbe interface by demonstrating the capacity of the enteric nervous system to influence the microbiota. Ultimately, these findings suggest that therapeutic strategies targeting the intestinal ecosystem should consider the dynamic physical nature of the gut environment.

Live imaging of a model intestinal microbiota reveals that enteric neural function and peristalsis, combined with the spatial structure of microbial communities, can drive competition between bacterial species.

Hundreds of microbial species thrive within the gut of humans and other animals, where they can influence the health of their host in profound ways. The factors that shape the composition of the resident gut microbiota are not well understood, but identifying them represents an important step toward developing treatments for diseases associated with microbial imbalances. Current experimental approaches poorly capture spatial and temporal aspects of microbial interactions within the gut, and yet these features may hold clues to what determines the composition of the microbiota. To address this issue, we used state-of-the-art live imaging to track two bacterial species within the intestine of a model vertebrate host, the zebrafish. We observed strikingly different interplay between the spatial organization of each population and the intestine’s peristaltic activity. As a result, one species dominates while the other experiences sudden drops in abundance, the dynamics of which are predicted by a stochastic mathematical model. From this work, we conclude that the composition of indigenous microbial communities may, in part, be shaped by a combination of the physical intestinal environment and the spatial structure of bacterial populations.

Do Vertebrate Gut Metagenomes Confer Rapid Ecological Adaptation?

During times of rapid environmental change, survival of most vertebrate populations depends on their phenomic plasticity. Although differential gene-expression and post-transcriptional processes of the host genome receive focus as the main molecular mechanisms, growing evidence points to the gut microbiota as a key driver defining hosts' phenotypes. We propose that the plasticity of the gut microbiota might be an essential factor determining phenomic plasticity of vertebrates, and that it might play a pivotal role when vertebrates acclimate and adapt to fast environmental variation. We contemplate some key questions and suggest methodological approaches and experimental designs that can be used to evaluate whether gut microorganisms provide a boost of plasticity to vertebrates' phenomes, thereby increasing their acclimation and adaptation capacity.

The roles of amensalistic and commensalistic interactions in large ecological network stability

Ecological communities comprise diverse species and their interactions. Notably, ecological and evolutionary studies have revealed that reciprocal interactions such as predator–prey, competition, and mutualism, are key drivers of community dynamics. However, there is an argument that many species interactions are asymmetric, where one species unilaterally affects another species (amensalism or commensalism). This raises the unanswered question of what is the role of unilateral interactions in community dynamics. Here I use a theoretical approach to demonstrate that unilateral interactions greatly enhance community stability. The results suggested that amensalism and commensalism were more stabilizing than symmetrical interactions, such as competition and mutualism, but they were less stabilizing than an asymmetric antagonistic interaction. A mix of unilateral interactions increased stability. Furthermore, in communities with all interaction types, unilateral interactions tended to increase stability. This study suggests that unilateral interactions play a major role in maintaining communities, underlining the need to further investigate their roles in ecosystem dynamics.

A Commensal Bacterium Promotes Virulence of an Opportunistic Pathogen via Cross-Respiration

Bacteria rarely inhabit infection sites alone, instead residing in diverse, multispecies communities. Despite this fact, bacterial pathogenesis studies primarily focus on monoculture infections, overlooking how community interactions influence the course of disease. In this study, we used global mutant fitness profiling (transposon sequencing [Tn-seq]) to determine the genetic requirements for the pathogenic bacterium Aggregatibacter actinomycetemcomitans to cause disease when coinfecting with the commensal bacterium Streptococcus gordonii. Our results show that S. gordonii extensively alters A. actinomycetemcomitans requirements for virulence factors and biosynthetic pathways during infection. In addition, we discovered that the presence of S. gordonii enhances the bioavailability of oxygen during infection, allowing A. actinomycetemcomitans to shift from a primarily fermentative to a respiratory metabolism that enhances its growth yields and persistence. Mechanistically, respiratory metabolism enhances the fitness of A. actinomycetemcomitans in vivo by increasing ATP yields via central metabolism and creating a proton motive force. Our results reveal that, similar to cross-feeding, where one species provides another species with a nutrient, commensal bacteria can also provide electron acceptors that promote the respiratory growth and fitness of pathogens in vivo, an interaction that we term cross-respiration.

Commensal bacteria can enhance the virulence of pathogens in mixed-species infections. However, knowledge of the mechanisms underlying this clinically relevant phenomenon is lacking. To bridge this gap, we comprehensively determined the genes a pathogen needs to establish coinfection with a commensal. Our findings show that the metabolism of the pathogen is low-energy-yielding in monoinfection, but in coinfection, the commensal improves the fitness of the pathogen by increasing the bioavailability of oxygen, thereby shifting the pathogen toward a high-energy-yielding metabolism. Similar to cross-feeding, this interaction, which we term cross-respiration, illustrates that commensal bacteria can provide electron acceptors that enhance the virulence of pathogens during infection.

Resource limitation drives spatial organization in microbial groups

Dense microbial groups such as bacterial biofilms commonly contain a diversity of cell types that define their functioning. However, we have a limited understanding of what maintains, or purges, this diversity. Theory suggests that resource levels are key to understanding diversity and the spatial arrangement of genotypes in microbial groups, but we need empirical tests. Here we use theory and experiments to study the effects of nutrient level on spatio-genetic structuring and diversity in bacterial colonies. Well-fed colonies maintain larger well-mixed areas, but they also expand more rapidly compared with poorly-fed ones. Given enough space to expand, therefore, well-fed colonies lose diversity and separate in space over a similar timescale to poorly fed ones. In sum, as long as there is some degree of nutrient limitation, we observe the emergence of structured communities. We conclude that resource-driven structuring is central to understanding both pattern and process in diverse microbial communities.

Triclosan Exposure Is Associated with Rapid Restructuring of the Microbiome in Adult Zebrafish

Growing evidence indicates that disrupting the microbial community that comprises the intestinal tract, known as the gut microbiome, can contribute to the development or severity of disease. As a result, it is important to discern the agents responsible for microbiome disruption. While animals are frequently exposed to a diverse array of environmental chemicals, little is known about their effects on gut microbiome stability and structure. Here, we demonstrate how zebrafish can be used to glean insight into the effects of environmental chemical exposure on the structure and ecological dynamics of the gut microbiome. Specifically, we exposed forty-five adult zebrafish to triclosan-laden food for four or seven days or a control diet, and analyzed their microbial communities using 16S rRNA amplicon sequencing. Triclosan exposure was associated with rapid shifts in microbiome structure and diversity. We find evidence that several operational taxonomic units (OTUs) associated with the family Enterobacteriaceae appear to be susceptible to triclosan exposure, while OTUs associated with the genus Pseudomonas appeared to be more resilient and resistant to exposure. We also found that triclosan exposure is associated with topological alterations to microbial interaction networks and results in an overall increase in the number of negative interactions per microbe in these networks. Together these data indicate that triclosan exposure results in altered composition and ecological dynamics of microbial communities in the gut. Our work demonstrates that because zebrafish afford rapid and inexpensive interrogation of a large number of individuals, it is a useful experimental system for the discovery of the gut microbiome's interaction with environmental chemicals.

Inhibitory interactions promote frequent bistability among competing bacteria

It is largely unknown how the process of microbial community assembly is affected by the order of species arrival, initial species abundances and interactions between species. A minimal way of capturing competitive abilities in a frequency-dependent manner is with an invasibility network specifying whether a species at low abundance can increase in frequency in an environment dominated by another species. Here, using a panel of prolific small-molecule producers and a habitat with feast-and-famine cycles, we show that the most abundant strain can often exclude other strains—resulting in bistability between pairs of strains. Instead of a single winner, the empirically determined invasibility network is ruled by multiple strains that cannot invade each other, and does not contain loops of cyclic dominance. Antibiotic inhibition contributes to bistability by helping producers resist invasions while at high abundance and by reducing producers' ability to invade when at low abundance.

We know little about the effect of relationships between species on the assembly of microbial communities. Here the authors map pairwise invasion relations between bacteria and find that instead of one strain dominating, inhibitory interactions mean that often neither strain can invade the other.

Principles for designing synthetic microbial communities

Advances in synthetic biology to build microbes with defined and controllable properties are enabling new approaches to design and program multispecies communities. This emerging field of synthetic ecology will be important for many areas of biotechnology, bioenergy and bioremediation. This endeavor draws upon knowledge from synthetic biology, systems biology, microbial ecology and evolution. Fully realizing the potential of this discipline requires the development of new strategies to control the intercellular interactions, spatiotemporal coordination, robustness, stability and biocontainment of synthetic microbial communities. Here, we review recent experimental, analytical and computational advances to study and build multi-species microbial communities with defined functions and behavior for various applications. We also highlight outstanding challenges and future directions to advance this field.

Network-based metabolic analysis and microbial community modeling

Network inference is being applied to studies of microbial ecology to visualize and characterize microbial communities. Network representations can allow examination of the underlying organizational structure of a microbial community, and identification of key players or environmental conditions that influence community assembly and stability. Microbial co-association networks provide information on the dynamics of community structure as a function of time or other external variables. Community metabolic networks can provide a mechanistic link between species through identification of metabolite exchanges and species specific resource requirements. When used together, co-association networks and metabolic networks can provide a more in-depth view of the hidden rules that govern the stability and dynamics of microbial communities.

Holes in the Hologenome: Why Host-Microbe Symbioses Are Not Holobionts

The advent of relatively inexpensive tools for characterizing microbial communities has led to an explosion of research exploring the diversity, ecology, and evolution of microbe-host systems. Some now question whether existing conceptual frameworks are adequate to explain microbe-host systems. One popular paradigm is the "holobiont-hologenome," which argues that a host and its microbiome evolve as a single cooperative unit of selection (i.e., a superorganism). We argue that the hologenome is based on overly restrictive assumptions which render it an approach of little research utility. A host plus its microbiome is more effectively viewed as an ecological community of organisms that encompasses a broad range of interactions (parasitic to mutualistic), patterns of transmission (horizontal to vertical), and levels of fidelity among partners. The hologenome requires high partner fidelity if it is to evolve as a unit. However, even when this is achieved by particular host-microbe pairs, it is unlikely to hold for the entire host microbiome, and therefore the community is unlikely to evolve as a hologenome. Both mutualistic and antagonistic (fitness conflict) evolution can occur among constituent members of the community, not just adaptations at the "hologenome" level, and there is abundant empirical evidence for such divergence of selective interests among members of host-microbiome communities. We believe that the concepts and methods of ecology, genetics, and evolutionary biology will continue to provide a well-grounded intellectual framework for researching host-microbiome communities, without recourse to the limiting assumption that selection acts predominantly at the holobiont level.

Challenges in microbial ecology: building predictive understanding of community function and dynamics

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.

Stress as a Normal Cue in the Symbiotic Environment

All multicellular hosts form associations with groups of microorganisms. These microbial communities can be taxonomically diverse and dynamic, and their persistence is due to robust, and sometimes coevolved, host-microbe and microbe-microbe interactions. Chemical and physical sources of stress are prominently situated in this molecular exchange, as cues for cellular responses in symbiotic microbes. Stress in the symbiotic environment may arise from three sources: host tissues, microbe-induced immune responses, or other microbes in the host environment. The responses of microbes to these stresses can be general or highly specialized, and collectively may contribute to the stability of the symbiotic system. In this review, we highlight recent work that emphasizes the role of stress as a cue in the symbiotic environment of plants and animals.

Human symbionts inject and neutralize antibacterial toxins to persist in the gut

The human gut microbiome is a dynamic and densely populated microbial community that can provide important benefits to its host. Cooperation and competition for nutrients among its constituents only partially explain community composition and interpersonal variation. Notably, certain human-associated Bacteroidetes--one of two major phyla in the gut--also encode machinery for contact-dependent interbacterial antagonism, but its impact within gut microbial communities remains unknown. Here we report that prominent human gut symbionts persist in the gut through continuous attack on their immediate neighbors. Our analysis of just one of the hundreds of species in these communities reveals 12 candidate antibacterial effector loci that can exist in 32 combinations. Through the use of secretome studies, in vitro bacterial interaction assays and multiple mouse models, we uncover strain-specific effector/immunity repertoires that can predict interbacterial interactions in vitro and in vivo, and find that some of these strains avoid contact-dependent killing by accumulating immunity genes to effectors that they do not encode. Effector transmission rates in live animals can exceed 1 billion events per minute per gram of colonic contents, and multiphylum communities of human gut commensals can partially protect sensitive strains from these attacks. Together, these results suggest that gut microbes can determine their interactions through direct contact. An understanding of the strategies human gut symbionts have evolved to target other members of this community may provide new approaches for microbiome manipulation.

Bacteroides fragilis type VI secretion systems use novel effector and immunity proteins to antagonize human gut Bacteroidales species

Type VI secretion systems (T6SSs) are multiprotein complexes best studied in Gram-negative pathogens where they have been shown to inhibit or kill prokaryotic or eukaryotic cells and are often important for virulence. We recently showed that T6SS loci are also widespread in symbiotic human gut bacteria of the order Bacteroidales, and that these T6SS loci segregate into three distinct genetic architectures (GA). GA1 and GA2 loci are present on conserved integrative conjugative elements (ICE) and are transferred and shared among diverse human gut Bacteroidales species. GA3 loci are not contained on conserved ICE and are confined to Bacteroides fragilis Unlike GA1 and GA2 T6SS loci, most GA3 loci do not encode identifiable effector and immunity proteins. Here, we studied GA3 T6SSs and show that they antagonize most human gut Bacteroidales strains analyzed, except for B. fragilis strains with the same T6SS locus. A combination of mutation analyses,trans-protection analyses, and in vitro competition assays, allowed us to identify novel effector and immunity proteins of GA3 loci. These proteins are not orthologous to known proteins, do not contain identified motifs, and most have numerous predicted transmembrane domains. Because the genes encoding effector and immunity proteins are contained in two variable regions of GA3 loci, GA3 T6SSs of the species B. fragilis are likely the source of numerous novel effector and immunity proteins. Importantly, we show that the GA3 T6SS of strain 638R is functional in the mammalian gut and provides a competitive advantage to this organism.

Resource-dependent attenuation of species interactions during bacterial succession

Bacterial communities are vital for many economically and ecologically important processes. The role of bacterial community composition in determining ecosystem functioning depends critically on interactions among bacterial taxa. Several studies have shown that, despite a predominance of negative interactions in communities, bacteria are able to display positive interactions given the appropriate evolutionary or ecological conditions. We were interested in how interspecific interactions develop over time in a naturalistic setting of low resource supply rates. We assembled aquatic bacterial communities in microcosms and assayed the productivity (respiration and growth) and substrate degradation while tracking community composition. The results demonstrated that while bacterial communities displayed strongly negative interactions during the early phase of colonisation and acclimatisation to novel biotic and abiotic factors, this antagonism declined over time towards a more neutral state. This was associated with a shift from use of labile substrates in early succession to use of recalcitrant substrates later in succession, confirming a crucial role of resource dynamics in linking interspecific interactions with ecosystem functioning.

Two Poplar-Associated Bacterial Isolates Induce Additive Favorable Responses in a Constructed Plant-Microbiome System

The biological function of the plant-microbiome system is the result of contributions from the host plant and microbiome members. The Populus root microbiome is a diverse community that has high abundance of β- and γ-Proteobacteria, both classes which include multiple plant-growth promoting representatives. To understand the contribution of individual microbiome members in a community, we studied the function of a simplified community consisting of Pseudomonas and Burkholderia bacterial strains isolated from Populus hosts and inoculated on axenic Populus cutting in controlled laboratory conditions. Both strains increased lateral root formation and root hair production in Arabidopsis plate assays and are predicted to encode for different functions related to growth and plant growth promotion in Populus hosts. Inoculation individually, with either bacterial isolate, increased root growth relative to uninoculated controls, and while root area was increased in mixed inoculation, the interaction term was insignificant indicating additive effects of root phenotype. Complementary data including photosynthetic efficiency, whole-transcriptome gene expression and GC-MS metabolite expression data in individual and mixed inoculated treatments indicate that the effects of these bacterial strains are unique and additive. These results suggest that the function of a microbiome community may be predicted from the additive functions of the individual members.