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All animals carry specialized microbiomes, and their gut microbiota are continuously released into the environment through excretion of waste. Here we propose the meta-gut as a novel conceptual framework that addresses the ability of the gut microbiome released from an animal to function outside the host and alter biogeochemical processes mediated by microbes. We demonstrate this dynamic in the hippopotamus (hippo) and the pools they inhabit. We used natural field gradients and experimental approaches to examine fecal and pool water microbial communities and aquatic biogeochemistry across a range of hippo inputs. Sequencing using 16S RNA methods revealed community coalescence between hippo gut microbiomes and the active microbial communities in hippo pools that received high inputs of hippo feces. The shared microbiome between the hippo gut and the waters into which they excrete constitutes a meta-gut system that could influence the biogeochemistry of recipient ecosystems and provide a reservoir of gut microbiomes that could influence other hosts. We propose that meta-gut dynamics may also occur where other animal species congregate in high densities, particularly in aquatic environments.

Diet can impact host health through changes to the gut microbiota, yet we lack mechanistic understanding linking nutrient availability and microbiota composition. Here, we use thousands of microbial communities culturedin vitrofrom human feces to uncover simple assembly rules and develop a predictive model of community composition upon addition of single nutrients from central carbon metabolism to a complex medium. Community membership was largely determined by the donor feces, whereas relative abundances were determined by the supplemental carbon source. The absolute abundance of most taxa was independent of the supplementing nutrient, due to the ability of fast-growing organisms to quickly exhaust their niche in the complex medium and then exploit and monopolize the supplemental carbon source. Relative abundances of dominant taxa could be predicted from the nutritional preferences and growth dynamics of species in isolation, and exceptions were consistent with strain-level variation in growth capabilities. Our study reveals that community assembly follows simple rules of nutrient utilization dynamics and provides a predictive framework for manipulating gut commensal communities through nutritional perturbations.

Microbial interactions are expected to modulate microbial diversity, but whether they inhibit or stimulate further diversity in complex microbial communities, and how, remains poorly understood. By assembling microbial communities in multiple identical habitats with a single limiting nutrient, here we provide direct evidence for the role of microbial niche construction and cross-feeding in driving a positive relationship between community diversity and focal lineage diversity in microbial communities. Combining these experiments with simulations, we show that this positive relationship is not inevitable but depends on the underlying metabolic structure of by-product secretions and uptake between different taxonomic levels.

Microbial communities are highly diverse, and understanding the factors that promote and modulate this diversity is a major area of research in microbial ecology. Recent work has proposed a reductionist perspective to microbial coexistence, where pairwise coexistence between strains in isolation is required for their coexistence in a more complex community. In this view, species exclusion in pairwise co-culture would preclude their coexistence in a more complex community too. An alternative view is that coexistence is a more complex property of the entire community, requiring the presence of additional community members. If this view were correct, competitive exclusion in pairwise co-culture would not necessarily preclude species coexistence in more complex community contexts. Empirically testing these alternative hypotheses is complicated by the intractably high microbial diversity of most natural communities, and the challenges of reconstituting every pair of coexisting species under the exact same habitat where their community of origin was assembled. To address this challenge, we have experimentally reconstituted all possible pairwise co-cultures between stably coexisting species from 13 different, low-diversity microbial enrichment communities, which had previously been assembled in a well-controlled synthetic habitat. We find that, when isolated from the rest of their community members, most species pairs fail to coexist. This result highlights the importance of community context for microbial coexistence and indicates that pairwise exclusion may not reflect the ability of species to coexist in more complex, multispecies ecosystems., This work was partially funded by Young Investigator Award RGY0077/2016 from the Human Frontier Science Program (to A.S.). C, C.-Y. was supported by the Graduate Student Fellowship for Studying Abroad from the Ministry of Education, Taiwan.

Directed evolution has been used for decades to engineer biological systems at or below the organismal level. Above the organismal level, a small number of studies have attempted to artificially select microbial ecosystems, with uneven and generally modest success. Our theoretical understanding of artificial ecosystem selection is limited, particularly for large assemblages of asexual organisms, and we know little about designing efficient methods to direct their evolution. Here, we have developed a flexible modeling framework that allows us to systematically probe any arbitrary selection strategy on any arbitrary set of communities and selected functions. By artificially selecting hundreds of in-silico microbial metacommunities under identical conditions, we first show that the main breeding methods used to date, which do not necessarily let communities to reach their ecological equilibrium, are outperformed by a simple screen of sufficiently mature communities. We then identify a range of alternative directed evolution strategies that, particularly when applied in combination, are well suited for the top-down engineering of large, diverse, and stable microbial consortia. Our results emphasize that directed evolution allows an ecological structure-function landscape to be navigated in search for dynamically stable and ecologically resilient communities with desired quantitative attributes.

Recent advances in robotics and affordable genomic sequencing technologies have made it possible to establish and quantitatively track the assembly of enrichment communities in high-throughput. By conducting community assembly experiments in up to thousands of synthetic habitats, where the extrinsic sources of variation among replicates can be controlled, we can now study the reproducibility and predictability of microbial community assembly at different levels of organization, and its relationship with nutrient composition and other ecological drivers. Through a dialog with mathematical models, high-throughput enrichment communities are bringing us closer to the goal of developing a quantitative predictive theory of microbial community assembly. In this short review, we present an overview of recent research on this growing field, highlighting the connection between theory and experiments and suggesting directions for future work.

A major open question in microbiome research is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, here we ask whether communities assembled in a mixed nutrient environment can be predicted from those assembled in every single nutrient in isolation. To that end, we first formulate a quantitative null model of community assembly in a mixture of nutrients that recruit species independently. We then test the model predictions by assembling replicate communities in synthetic environments that contain either a pair of nutrients, or each nutrient in isolation. We find that the null, naturally additive model generally predicts well the family-level community composition. However, we also identify systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family-level of taxonomy. Pairs of more-similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (e.g. one sugar and one organic acid). A simple dominance rule emerges, where we find that sugars generally dominate organic acids. This simple dominance rule extends to most families and most sugar-organic acid pairs in our experiment. Our results suggest that regularities in the ways nutrients interact may help us predict how microbial communities respond to changes in nutrient composition.

Directed evolution is a form of artificial selection that has been used for decades to find biomolecules and organisms with new or enhanced functional traits. Directed evolution can be conceptualized as a guided exploration of the genotype–phenotype map, where genetic variants with desirable phenotypes are first selected and then mutagenized to search the genotype space for an even better mutant. In recent years, the idea of applying artificial selection to microbial communities has gained momentum. In this article, we review the main limitations of artificial selection when applied to large and diverse collectives of asexually dividing microbes and discuss how the tools of directed evolution may be deployed to engineer communities from the top down. We conceptualize directed evolution of microbial communities as a guided exploration of an ecological structure–function landscape and propose practical guidelines for navigating these ecological landscapes.

Directed evolution has been used for decades to engineer biological systems from the top-down. Generally, it has been applied at or below the organismal level, by iteratively sampling the mutational landscape in a guided search for genetic variants of higher function. Above the organismal level, a small number of studies have attempted to artificially select microbial communities and ecosystems, with uneven and generally modest success. Our theoretical understanding of artificial ecosystem selection is still limited, particularly for large assemblages of asexual organisms, and we know little about designing efficient methods to direct their evolution. To address this issue, we have developed a flexible modeling framework that allows us to systematically probe any arbitrary selection strategy on any arbitrary set of communities and selected functions, in a wide range of ecological conditions. By artificially selecting hundreds ofin-silicomicrobial metacommunities under identical conditions, we examine the fundamental limits of the two main breeding methods used so far, and prescribe modifications that significantly increase their power. We identify a range of directed evolution strategies that, particularly when applied in combination, are better suited for the top-down engineering of large, diverse, and stable microbial consortia. Our results emphasize that directed evolution allows an ecological structure-function landscape to be navigated in search for dynamically stable and ecologically and functionally resilient high-functioning communities.

Natural selection favours individuals who maximise their own reproductive success and that of their close relatives. From this perspective, cooperation that benefits individuals of a different species represents an evolutionary conundrum. The theory of mutualism seeks to resolve this puzzle, and it posits that there must be downstream benefits to cooperators that offset any costs inherently associated with interspecific cooperation. Thus, individuals should only further the survival and fecundity of their interspecific partners if this generates additional return benefits, such as food, shelter or protection. A major challenge for the evolution of mutualism is when the ecological niches of partner species overlap, as this creates a tension between the benefits of exchanging services and the costs of competing for shared resources. Here we study the extent to which niche expansion, in which cooperation augments the common pool of resources, can resolve this problem. We find that niche expansion facilitates the evolution of mutualism, especially when populations are at high densities. Further, we show that niche expansion can promote the evolution of reproductive restraint, in which a focal species adaptively sacrifices its own growth rate to increase the density of partner species. We interpret these results in the context of microbial community interactions, which are often characterized by yield-enhancing exchanges of nutrients, termed ‘cross-feeding’. Our findings suggest that yield-enhancing mutualisms are more prevalent in stable habitats with a constant supply of resources, where populations typically live at high densities, but such mutualisms are particularly vulnerable to the emergence of cheats. In general, our findings highlight the need to integrate both temporal and spatial dynamics in the analysis of mutualisms.

To develop a quantitative theory that can predict how microbiomes assemble, and how they respond to perturbations, we must identify which descriptive features of microbial communities are reproducible and predictable, which are unpredictable, and why. The emergent metagenomic structure of communities is often quantitatively convergent in similar habitats, with highly similar fractions of the metagenome being devoted to the same metabolic pathways. By contrast, the species-level taxonomic composition is often highly variable even in replicate environments. The mechanisms behind these patterns are not yet understood. By studying the self-assembly of hundreds of communities in replicate, synthetic habitats, we show that the reproducibility of microbial community assembly reflects an emergent metabolic structure, which is quantitatively predictable from first-principles, genome-scale metabolic models. Taxonomic variability within functional groups arises through multistability in population dynamics, and the species-level community composition is predictably governed by the mutual competitive exclusion of two sub-dominant strains. Our findings provide a mechanistic bridge between microbial community structure at different levels of organization, and show that the evolutionary conservation of metabolic traits, both in terms of growth responses and niches constructed, can be leveraged to quantitatively predict the taxonomic and metabolic structure of microbial communities.

Summary For microbiome biology to become a more predictive science, we must identify which descriptive features of microbial communities are reproducible and predictable, which are not, and why. We address this question by experimentally studying parallelism and convergence in microbial community assembly in replicate glucose-limited habitats. Here, we show that the previously observed family-level convergence in these habitats reflects a reproducible metabolic organization, where the ratio of the dominant metabolic groups can be explained from a simple resource-partitioning model. In turn, taxonomic divergence among replicate communities arises from multistability in population dynamics. Multistability can also lead to alternative functional states in closed ecosystems but not in metacommunities. Our findings empirically illustrate how the evolutionary conservation of quantitative metabolic traits, multistability, and the inherent stochasticity of population dynamics, may all conspire to generate the patterns of reproducibility and variability at different levels of organization that are commonplace in microbial community assembly.

When a more complex, functionally integrated entity emerges from the association of simpler, initially independent entities, a major evolutionary transition has occurred. Transitions that result from the association of different species include the evolution of the eukaryotic cell and some obligate mutualisms. Recent studies are revolutionizing our understanding of how these intimate interspecific associations come to be, revealing how and to what extent each partner contributes to the relationship, and how partners mediate conflict. Here, we review work on the evolution of mutualistic symbioses in the context of transitions in individuality and highlight how a better mechanistic understanding of the ecological drivers of host-symbiont interdependencies can help elucidate the evolutionary path to symbiotic organismality.

Organisms modify their environments in ways that can be beneficial or detrimental not only to themselves but also to others sharing the same environment. Such niche-constructing or niche-destroying activities are often due to the production or consumption of environmental factors, such as resources, wastes, or toxins, which ultimately influence the ecology and evolution of social interactions. We present a new, four-way classification of social behaviors where individual behaviors are categorized into producing/consuming an environmental factor, as well as into helping/harming others. Although not immediately obvious, dispersal (the act of moving within a habitat or between habitats) is another mechanism by which organisms modify their environment. An explicit representation of such environmentally mediated interactions is key to capturing realistic system complexity and can reveal some unexpected outcomes in social dilemmas.

Interchanging species of similar function Under natural conditions, bacteria form mixed, interacting communities. Understanding how such communities assemble and stabilize is important in a range of contexts, from biotechnological applications to what happens in our guts. Goldford et al. sampled the microbial communities from soil and plants containing hundreds to thousands of sequence variants. The organisms were passaged after culture in low concentrations of single carbon sources and were cross-fed with each other's metabolites; then, the resulting communities were sequenced using 16S ribosomal RNA, and the outcomes were modeled mathematically. The mix of species that survived under steady conditions converged reproducibly to reflect the experimentally imposed conditions rather than the mix of species initially inoculated—although at coarse phylogenetic levels, taxonomic patterns persisted. Science , this issue p. 469

Summary Microbes perform many costly biological functions that benefit themselves, and may also benefit neighbouring cells. Losing the ability to perform such functions can be advantageous due to cost savings, but when they are essential for growth, organisms become dependent on ecological partners to compensate for those losses. When multiple functions may be lost, the ecological outcomes are potentially diverse, including independent organisms only; one-way dependency, where one partner performs all functions and others none; or mutual interdependency where partners perform complementary essential functions. What drives these different outcomes? We develop a model where organisms perform ‘leaky’ functions that provide both private and public benefits to explore the consequences of privatization level, costs and essentiality on influencing these outcomes. We show that mutual interdependency is favoured at intermediate levels of privatization for a broad range of conditions. One-way dependency, in contrast, is only favoured when privatization is low and loss-of-function benefits are accelerating. Our results suggest an interplay between privatization level and shape of benefits from loss in driving microbial dependencies. Given the ubiquity of microbial functions that are inevitably leaked and the ease of mutational inactivation, our findings may help to explain why microbial interdependencies are common in nature.

The human microbiome is a vast reservoir of microbial diversity and increasingly recognized to have a fundamental role in human health. In polymicrobial communities, the presence of one species can modulate the demography (i.e., growth and distribution) of other species. These demographic impacts generate feedbacks in multispecies interactions, which can be magnified in spatially structured populations (e.g., host-associated communities). Here, we argue that demographic feedbacks between species are central to microbiome development, shaping whether and how potential metabolic interactions come to be realized between expanding lineages of bacteria. Understanding how demographic feedbacks tune metabolic interactions and in turn shape microbiome structure and function is now a key challenge to our abilities to better manage microbiome health.

Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing competition and antibiotics leads to increasing competitive release of the antibiotic-resistant strain, hitting a mutualistic community of cross-feeding species with antibiotics leads to a mutualistic suppression effect where both susceptible and resistant species are harmed. We next show that the impact of antibiotics is further governed by emergent spatial feedbacks within communities. Mutualistic cross-feeding communities can rescue susceptible members by subsidizing their growth inside the biofilm despite lack of access to the nutrient-rich and high-antibiotic growing front. Moreover, we show that antibiotic detoxification by resistant cells can protect nearby susceptible cells, but such cross-protection is more effective in mutualistic communities because mutualism drives mixing of resistant and susceptible cells. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. Understanding how the interplay between microbial metabolic interactions and community spatial structuring shapes the outcome of antibiotic treatment can be key to effectively leverage the power of antibiotics and promote microbiome health., Author summary Pathogens -microorganisms that make us sick- often live within dynamic and complex multispecies communities, where they may not only compete for limiting resources but also exchange beneficial resources or services with other resident species. While antibiotics are commonly used to get rid of such harmful microbes, the community-wide effects of antibiotic treatment and its consequences for antibiotic resistance are still not well understood. How do competitive or mutually beneficial interactions between antibiotic resistant and susceptible species influence community resistance to antibiotics? Here we investigate this question using a computational model. We find that antibiotic exposure favours the resistant lineage when resistant and susceptible strains are competitors but harms both types when they are mutualists. With antibiotic-detoxifying resistant cells, cross-protection of susceptible cells is more effective in mutualistic communities because mutualism drives mixing of susceptible and resistant cells. In contrast, competition leads to their segregation, precluding susceptible cells to profit from their competitor’s local detoxification. Our findings highlight that knowing not only what species are present but also how they interact with each other and arrange themselves in space is central to understanding antibiotic resistance and to informing the development of strategies that promote microbiome health.

Microbes perform many costly biological functions that benefit themselves, and may also benefit neighbouring cells. Losing the ability to perform such functions can be advantageous due to cost savings, but when they are essential for growth, organisms become dependent on ecological partners to compensate for those losses. When multiple functions may be lost, the ecological outcomes are potentially diverse, including independent organisms only; one-way dependency, where one partner performs all functions and others none; or mutual interdependency where partners perform complementary essential functions. What drives these different outcomes? We develop a model where organisms perform 'leaky' functions that provide both private and public benefits to explore the consequences of privatization level, costs and essentiality on influencing these outcomes. We show that mutual interdependency is favoured at intermediate levels of privatization for a broad range of conditions. One-way dependency, in contrast, is only favoured when privatization is low and loss-of-function benefits are accelerating. Our results suggest an interplay between privatization level and shape of benefits from loss in driving microbial dependencies. Given the ubiquity of microbial functions that are inevitably leaked and the ease of mutational inactivation, our findings may help to explain why microbial interdependencies are common in nature.

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.

Methionine adenosyltransferase from Euglena gracilis (MATX) is a recently discovered member of the MAT family of proteins that synthesize S-adenosylmethionine. Heterologous overexpression of MATX in Escherichia coli rendered the protein mostly in inclusion bodies under all conditions tested. Therefore, a refolding and purification procedure from these aggregates was developed to characterize the enzyme. Maximal recovery was obtained using inclusion bodies devoid of extraneous proteins by washing under mild urea (2 M) and detergent (5%) concentrations. Refolding was achieved in two steps following solubilization in the presence of Mg2+; chaotrope dilution to, This work was supported by grants of the Ministerio de Ciencia e Innovación (BFU2008-00666 and BFU2009-08977 to M.A.P.).

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.