Inhibitory interactions promote frequent bistability among competing bacteria

Deciphering population-level response under spatial drug heterogeneity on microhabitat structures

Bacteria and cancer cells live in a spatially heterogeneous environment, where migration shapes the microhabitat structures critical for colonization and metastasis. The interplay between growth, migration, and microhabitat structure complicates the prediction of population responses to drugs, such as clearance or sustained growth, posing a longstanding challenge. Here, we disentangle growth-migration dynamics and identify that population decline is determined by two decoupled terms: a spatial growth variation term and a microhabitat structure term. Notably, the microhabitat structure term can be interpreted as a dynamic-related centrality measure. For fixed spatial drug arrangements, we show that interpreting these centralities reveals how different network structures, even with identical edge densities, microhabitat numbers, and spatial heterogeneity, can lead to distinct population-level responses. Increasing edge density shifts the population response from growth to clearance, supporting an inversed centrality-connectivity relationship, and mirroring the effects of higher migration rates. Furthermore, we derive a sufficient condition for robust population decline across various spatial growth rate arrangements, regardless of spatial-temporal fluctuations induced by drugs. Additionally, we demonstrate that varying the maximum growth-to-death ratio, determined by drug-bacteria interactions, can lead to distinct population decline profiles and a minimal decline phase emerges. These findings address key challenges in predicting population-level responses and provide insights into divergent clinical outcomes under identical drug dosages. This work may offer a new method of interpreting treatment dynamics and potential approaches for optimizing spatially explicit drug dosing strategies.

Mining microbial and metabolic dark matter in extreme environments: a roadmap for harnessing the power of multi-omics data

Extreme environments such as hyperarid, hypersaline, hyperthermal environments, and the deep sea harbor diverse microbial communities, which are specially adapted to extreme conditions and are known as extremophiles. These extremophilic organisms have developed unique survival strategies, making them ideal models for studying microbial diversity, evolution, and adaptation to adversity. They also play critical roles in biogeochemical cycles. Additionally, extremophiles often produce novel bioactive compounds in response to corresponding challenging environments. Recent advances in technologies, including genomic sequencing and untargeted metabolomic analysis, have significantly enhanced our understanding of microbial diversity, ecology, evolution, and the genetic and physiological characteristics in extremophiles. The integration of advanced multi-omics technologies into culture-dependent research has notably improved the efficiency, providing valuable insights into the physiological functions and biosynthetic capacities of extremophiles. The vast untapped microbial resources in extreme environments present substantial opportunities for discovering novel natural products and advancing our knowledge of microbial ecology and evolution. This review highlights the current research status on extremophilic microbiomes, focusing on microbial diversity, ecological roles, isolation and cultivation strategies, and the exploration of their biosynthetic potential. Moreover, we emphasize the importance and potential of discovering more strain resources and metabolites, which would be boosted greatly by harnessing the power of multi-omics data.

Cooperative growth in microbial communities is a driver of multistability

Microbial communities often exhibit more than one possible stable composition for the same set of external conditions. In the human microbiome, these persistent changes in species composition and abundance are associated with health and disease states, but the drivers of these alternative stable states remain unclear. Here we experimentally demonstrate that a cross-kingdom community, composed of six species relevant to the respiratory tract, displays four alternative stable states each dominated by a different species. In pairwise coculture, we observe widespread bistability among species pairs, providing a natural origin for the multistability of the full community. In contrast with the common association between bistability and antagonism, experiments reveal many positive interactions within and between community members. We find that multiple species display cooperative growth, and modeling predicts that this could drive the observed multistability within the community as well as non-canonical pairwise outcomes. A biochemical screening reveals that glutamate either reduces or eliminates cooperativity in the growth of several species, and we confirm that such supplementation reduces the extent of bistability across pairs and reduces multistability in the full community. Our findings provide a mechanistic explanation of how cooperative growth rather than competitive interactions can underlie multistability in microbial communities.

Understanding phycosomal dynamics to improve industrial microalgae cultivation

Algal-bacterial interactions are ubiquitous in both natural and industrial systems, and the characterization of these interactions has been reinvigorated by potential applications in biosystem productivity. Different growth conditions can be used for operational functions, such as the use of low-quality water or high pH/alkalinity, and the altered operating conditions likely constrain microbial community structure and function in unique ways. However, research is necessary to better understand whether consortia can be designed to improve the productivity, processing, and sustainability of industrial-scale cultivations through different controls that can constrain microbial interactions for maximal light-driven outputs. The review highlights current knowledge and gaps for relevant operating conditions, as well as suggestions for near-term and longer-term improvements for large-scale cultivation and polyculture engineering.

A vast repertoire of secondary metabolites potentially influences community dynamics and biogeochemical processes in cold seeps

In deep-sea cold seeps, microbial communities thrive on the geological seepage of hydrocarbons and inorganic compounds, differing from photosynthetically driven ecosystems. However, their biosynthetic capabilities remain largely unexplored. Here, we analyzed 81 metagenomes, 33 metatranscriptomes, and 7 metabolomes derived from nine different cold seep areas to investigate their secondary metabolites. Cold seep microbiomes encode diverse and abundant biosynthetic gene clusters (BGCs). Most BGCs are affiliated with understudied bacteria and archaea, including key mediators of methane and sulfur cycling. The BGCs encode diverse antimicrobial compounds that potentially shape community dynamics and various metabolites predicted to influence biogeochemical cycling. BGCs from key players are widely distributed and highly expressed, with their abundance and expression levels varying with sediment depth. Sediment metabolomics reveals unique natural products, highlighting uncharted chemical potential and confirming BGC activity in these sediments. Overall, these results demonstrate that cold seep sediments serve as a reservoir of hidden natural products and sheds light on microbial adaptation in chemosynthetically driven ecosystems.

Manipulating the physical distance between cells during soil colonization reveals the importance of biotic interactions in microbial community assembly

BACKGROUND

Microbial communities are of tremendous importance for ecosystem functioning and yet we know little about the ecological processes driving the assembly of these communities in the environment. Here, we used an unprecedented experimental approach based on the manipulation of physical distance between neighboring cells during soil colonization to determine the role of bacterial interactions in soil community assembly. We hypothesized that experimentally manipulating the physical distance between bacterial cells will modify the interaction strengths leading to differences in microbial community composition, with increasing distance between neighbors favoring poor competitors.

RESULTS

We found significant differences in both bacterial community diversity, composition and co-occurrence networks after soil colonization that were related to physical distancing. We show that reducing distances between cells resulted in a loss of bacterial diversity, with at least 41% of the dominant OTUs being significantly affected by physical distancing. Our results suggest that physical distancing may differentially modulate competitiveness between neighboring species depending on the taxa present in the community. The mixing of communities that assembled at high and low cell densities did not reveal any "home field advantage" during coalescence. This confirms that the observed differences in competitiveness were due to biotic rather than abiotic filtering.

CONCLUSIONS

Our study demonstrates that the competitiveness of bacteria strongly depends on cell density and community membership, therefore highlighting the fundamental role of microbial interactions in the assembly of soil communities.

Harnessing regulatory networks in Actinobacteria for natural product discovery

Microbes typically live in complex habitats where they need to rapidly adapt to continuously changing growth conditions. To do so, they produce an astonishing array of natural products with diverse structures and functions. Actinobacteria stand out for their prolific production of bioactive molecules, including antibiotics, anticancer agents, antifungals, and immunosuppressants. Attention has been directed especially towards the identification of the compounds they produce and the mining of the large diversity of biosynthetic gene clusters (BGCs) in their genomes. However, the current return on investment in random screening for bioactive compounds is low, while it is hard to predict which of the millions of BGCs should be prioritized. Moreover, many of the BGCs for yet undiscovered natural products are silent or cryptic under laboratory growth conditions. To identify ways to prioritize and activate these BGCs, knowledge regarding the way their expression is controlled is crucial. Intricate regulatory networks control global gene expression in Actinobacteria, governed by a staggering number of up to 1000 transcription factors per strain. This review highlights recent advances in experimental and computational methods for characterizing and predicting transcription factor binding sites and their applications to guide natural product discovery. We propose that regulation-guided genome mining approaches will open new avenues toward eliciting the expression of BGCs, as well as prioritizing subsets of BGCs for expression using synthetic biology approaches.

ONE-SENTENCE SUMMARY

This review provides insights into advances in experimental and computational methods aimed at predicting transcription factor binding sites and their applications to guide natural product discovery.

The evolution of short- and long-range weapons for bacterial competition

Bacteria possess a diverse range of mechanisms for inhibiting competitors, including bacteriocins, tailocins, type VI secretion systems and contact-dependent inhibition (CDI). Why bacteria have evolved such a wide array of weapon systems remains a mystery. Here we develop an agent-based model to compare short-range weapons that require cell-cell contact, with long-range weapons that rely on diffusion. Our model predicts that contact weapons are useful when an attacking strain is outnumbered, facilitating invasion and establishment. By contrast, ranged weapons tend to be effective only when attackers are abundant. We test our predictions with the opportunistic pathogen Pseudomonas aeruginosa, which naturally carries multiple weapons, including CDI and diffusing tailocins. As predicted, short-range CDI can function at low and high frequencies, while long-range tailocins require high frequency and cell density to function effectively. Head-to-head competition experiments with the two weapon types further support our predictions: a tailocin attacker defeats CDI only when it is numerically dominant, but then we find it can be devastating. Finally, we show that the two weapons work well together when one strain employs both. We conclude that short- and long-range weapons serve different functions and allow bacteria to fight both as individuals and as a group.

Resource competition can explain simplicity in microbial community assembly

Predicting the composition and diversity of communities is a central goal in ecology. While community assembly is considered hard to predict, laboratory microcosms often follow a simple assembly rule based on the outcome of pairwise competitions. This assembly rule predicts that a species that is excluded by another species in pairwise competition cannot survive in a multispecies community with that species. Despite the empirical success of this bottom-up prediction, its mechanistic origin has remained elusive. In this study, we elucidate how this simple pattern in community assembly can emerge from resource competition. Our geometric analysis of a consumer-resource model shows that trio community assembly is always predictable from pairwise outcomes when one species grows faster than another species on every resource. We also identify all possible trio assembly outcomes under three resources and find that only two outcomes violate the assembly rule. Simulations demonstrate that pairwise competitions accurately predict trio assembly with up to 100 resources and the assembly of larger communities containing up to twelve species. We then further demonstrate accurate quantitative prediction of community composition using the harmonic mean of pairwise fractions. Finally, we show that cross-feeding between species does not decrease assembly rule prediction accuracy. Our findings highlight that simple community assembly can emerge even in ecosystems with complex underlying dynamics.

Emergent coexistence in multispecies microbial communities

Understanding the mechanisms that maintain microbial biodiversity is a critical aspiration in ecology. Past work on microbial coexistence has largely focused on species pairs, but it is unclear whether pairwise coexistence in isolation is required for coexistence in a multispecies community. To address this question, we conducted hundreds of pairwise competition experiments among the stably coexisting members of 12 different enrichment communities in vitro. To determine the outcomes of these experiments, we developed an automated image analysis pipeline to quantify species abundances. We found that competitive exclusion was the most common outcome, and it was strongly hierarchical and transitive. Because many species that coexist within a stable multispecies community fail to coexist in pairwise co-culture under identical conditions, we concluded that multispecies coexistence is an emergent phenomenon. This work highlights the importance of community context for understanding the origins of coexistence in complex ecosystems.

Multi-factorial examination of amplicon sequencing workflows from sample preparation to bioinformatic analysis

BACKGROUND

The development of sequencing technologies to evaluate bacterial microbiota composition has allowed new insights into the importance of microbial ecology. However, the variety of methodologies used among amplicon sequencing workflows leads to uncertainty about best practices as well as reproducibility and replicability among microbiome studies. Using a bacterial mock community composed of 37 soil isolates, we performed a comprehensive methodological evaluation of workflows, each with a different combination of methodological factors spanning sample preparation to bioinformatic analysis to define sources of artifacts that affect coverage, accuracy, and biases in the resulting compositional profiles.

RESULTS

Of the workflows examined, those using the V4-V4 primer set enabled the highest level of concordance between the original mock community and resulting microbiome sequence composition. Use of a high-fidelity polymerase, or a lower-fidelity polymerase with an increased PCR elongation time, limited chimera formation. Bioinformatic pipelines presented a trade-off between the fraction of distinct community members identified (coverage) and fraction of correct sequences (accuracy). DADA2 and QIIME2 assembled V4-V4 reads amplified by Taq polymerase resulted in the highest accuracy (100%) but had a coverage of only 52%. Using mothur to assemble and denoise V4-V4 reads resulted in a coverage of 75%, albeit with marginally lower accuracy (99.5%).

CONCLUSIONS

Optimization of microbiome workflows is critical for accuracy and to support reproducibility and replicability among microbiome studies. These considerations will help reveal the guiding principles of microbial ecology and impact the translation of microbiome research to human and environmental health.

The reciprocal changes in dominant species with complete metabolic functions explain the decoupling phenomenon of microbial taxonomic and functional composition in a grassland

The decoupling of microbial functional and taxonomic components refers to the phenomenon that a drastic change in microbial taxonomic composition leads to no or only a gentle change in functional composition. Although many studies have identified this phenomenon, the mechanisms underlying it are still unclear. Here we demonstrate, using metagenomics data from a steppe grassland soil under different grazing and phosphorus addition treatments, that there is no “decoupling” in the variation of taxonomic and metabolic functional composition of the microbial community within functional groups at species level. In contrast, the high consistency and complementarity between the abundance and functional gene diversity of two dominant species made metabolic functions unaffected by grazing and phosphorus addition. This complementarity between the two dominant species shapes a bistability pattern that differs from functional redundancy in that only two species cannot form observable redundancy in a large microbial community. In other words, the “monopoly” of metabolic functions by the two most abundant species leads to the disappearance of functional redundancy. Our findings imply that for soil microbial communities, the impact of species identity on metabolic functions is much greater than that of species diversity, and it is more important to monitor the dynamics of key dominant microorganisms for accurately predicting the changes in the metabolic functions of the ecosystems.

Experimental community coalescence sheds light on microbial interactions in soil and restores impaired functions

BACKGROUND

Microbes typically live in communities where individuals can interact with each other in numerous ways. However, knowledge on the importance of these interactions is limited and derives mainly from studies using a limited number of species grown in coculture. Here, we manipulated soil microbial communities to assess the contribution of interactions between microorganisms for assembly of the soil microbiome.

RESULTS

By combining experimental removal (taxa depletion in the community) and coalescence (mixing of manipulated and control communities) approaches, we demonstrated that interactions between microorganisms can play a key role in determining their fitness during soil recolonization. The coalescence approach not only revealed the importance of density-dependent interactions in microbial community assembly but also allowed to restore partly or fully community diversity and soil functions. Microbial community manipulation resulted in shifts in both inorganic nitrogen pools and soil pH, which were related to the proportion of ammonia-oxidizing bacteria.

CONCLUSIONS

Our work provides new insights into the understanding of the importance of microbial interactions in soil. Our top-down approach combining removal and coalescence manipulation also allowed linking community structure and ecosystem functions. Furthermore, these results highlight the potential of manipulating microbial communities for the restoration of soil ecosystems. Video Abstract.

Balancing Trade-Offs Imposed by Growth Media and Mass Spectrometry for Bacterial Exometabolomics

The bacterial exometabolome consists of a vast array of specialized metabolites, many of which are only produced in response to specific environmental stimuli. For this reason, it is desirable to control the extracellular environment with a defined growth medium composed of pure ingredients. However, complex (undefined) media are expected to support the robust growth of a greater variety of microorganisms than defined media. Here, we investigate the trade-offs inherent to a range of complex and defined solid media for the growth of soil microorganisms, production of specialized metabolites, and detection of these compounds using direct infusion mass spectrometry. We find that complex media support growth of more soil microorganisms, as well as allowing for the detection of more previously discovered natural products as a fraction of total m/z features detected in each sample. However, the use of complex media often caused mass spectrometer injection failures and poor-quality mass spectra, which in some cases resulted in over a quarter of samples being removed from analysis. Defined media, while more limiting in growth, generated higher quality spectra and yielded more m/z features after background subtraction. These results inform future exometabolomic experiments requiring a medium that supports the robust growth of many soil microorganisms. IMPORTANCE Bacteria are capable of producing and secreting a rich diversity of specialized metabolites. Yet, much of their exometabolome remains hidden due to challenges associated with eliciting specialized metabolite production, labor-intensive sample preparation, and time-consuming analysis techniques. Using our versatile three-dimensional (3D)-printed culturing platform, SubTap, we demonstrate that rapid exometabolomic data collection from a diverse set of environmental bacteria is feasible. We optimized our platform by surveying Streptomyces isolated from soil on a variety of media types to assess viability, degree of specialized metabolite production, and compatibility with downstream LESA-DIMS analysis. Ultimately, this will enable data-rich experimentation, allowing for a better understanding of bacterial exometabolomes.

Climate-Driven Legacies in Simulated Microbial Communities Alter Litter Decomposition Rates

The mechanisms underlying diversity-functioning relationships have been a consistent area of inquiry in biogeochemistry since the 1950s. Though these mechanisms remain unresolved in soil microbiomes, many approaches at varying scales have pointed to the same notion—composition matters. Confronting the methodological challenge arising from the complexity of microbiomes, this study used the model DEMENTpy, a trait-based modeling framework, to explore trait-based drivers of microbiome-dependent litter decomposition. We parameterized DEMENTpy for five sites along a climate gradient in Southern California, United States, and conducted reciprocal transplant simulations analogous to a prior empirical study. The simulations demonstrated climate-dependent legacy effects of microbial communities on plant litter decomposition across the gradient. This result is consistent with the previous empirical study across the same gradient. An analysis of community-level traits further suggests that a 3-way tradeoff among resource acquisition, stress tolerance, and yield strategies influences community assembly. Simulated litter decomposition was predictable with two community traits (indicative of two of the three strategies) plus local environment, regardless of the system state (transient vs. equilibrium). Although more empirical confirmation is still needed, community traits plus local environmental factors (e.g., environment and litter chemistry) may robustly predict litter decomposition across spatial-temporal scales. In conclusion, this study offers a potential trait-based explanation for climate-dependent community effects on litter decomposition with implications for improved understanding of whole-ecosystem functioning across scales.

Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics

Persistently diverse microbial communities are one of biology’s great puzzles. Using a modeling framework that accommodates high mutation rates and a continuum of species traits, we studied microbial communities in which antagonistic interactions occur via the production of, inhibition of, and vulnerability to toxins (e.g., antibiotics). Mutation size and mobility enhanced microbial diversity and temporal persistence to extraordinarily high levels. These findings—including the discovery that the duration of the transient phase in community assembly provides a guide to equilibrial diversity—highlight the potentially critical role that antagonistic interactions play in promoting the diversity of bacterial systems. Such interactions, together with resource-driven interactions and spatial structure, may drive the enigmatic levels of biodiversity seen in microbial systems.

The assembly and maintenance of microbial diversity in natural communities, despite the abundance of toxin-based antagonistic interactions, presents major challenges for biological understanding. A common framework for investigating such antagonistic interactions involves cyclic dominance games with pairwise interactions. The incorporation of higher-order interactions in such models permits increased levels of microbial diversity, especially in communities in which antibiotic-producing, sensitive, and resistant strains coexist. However, most such models involve a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which well represent the highly interlinked, quickly evolving, and continuous nature of microbial phenotypic space. Here, we present an alternative vision of spatial dynamics for microbial communities based on antagonistic interactions—one in which a large number of species interact in continuous phenotypic space, are capable of rapid mutation, and engage in both direct and higher-order interactions mediated by production of and resistance to antibiotics. Focusing on toxin production, vulnerability, and inhibition among species, we observe highly divergent patterns of diversity and spatial community dynamics. We find that species interaction constraints (rather than mobility) best predict spatiotemporal disturbance regimes, whereas community formation time, mobility, and mutation size best explain patterns of diversity. We also report an intriguing relationship among community formation time, spatial disturbance regimes, and diversity dynamics. This relationship, which suggests that both higher-order interactions and rapid evolution are critical for the origin and maintenance of microbial diversity, has broad-ranging links to the maintenance of diversity in other systems.

Negative interactions determine Clostridioides difficile growth in synthetic human gut communities

Understanding the principles of colonization resistance of the gut microbiome to the pathogen Clostridioides difficile will enable the design of defined bacterial therapeutics. We investigate the ecological principles of community resistance to C. difficile using a synthetic human gut microbiome. Using a dynamic computational model, we demonstrate that C. difficile receives the largest number and magnitude of incoming negative interactions. Our results show that C. difficile is in a unique class of species that display a strong negative dependence between growth and species richness. We identify molecular mechanisms of inhibition including acidification of the environment and competition over resources. We demonstrate that Clostridium hiranonis strongly inhibits C. difficile partially via resource competition. Increasing the initial density of C. difficile can increase its abundance in the assembled community, but community context determines the maximum achievable C. difficile abundance. Our work suggests that the C. difficile inhibitory potential of defined bacterial therapeutics can be optimized by designing communities featuring a combination of mechanisms including species richness, environment acidification, and resource competition.

Eco-Evolutionary Dynamics in Microbial Communities from Spontaneous Fermented Foods

Eco-evolutionary forces are the key drivers of ecosystem biodiversity dynamics. This resulted in a large body of theory, which has partially been experimentally tested by mimicking evolutionary processes in the laboratory. In the first part of this perspective, we outline what model systems are used for experimental testing of eco-evolutionary processes, ranging from simple microbial combinations and, more recently, to complex natural communities. Microbial communities of spontaneous fermented foods are a promising model system to study eco-evolutionary dynamics. They combine the complexity of a natural community with extensive knowledge about community members and the ease of manipulating the system in a laboratory setup. Due to rapidly developing sequencing techniques and meta-omics approaches incorporating data in building ecosystem models, the diversity in these communities can be analysed with relative ease while hypotheses developed in simple systems can be tested. Here, we highlight several eco-evolutionary questions that are addressed using microbial communities from fermented foods. These questions relate to analysing species frequencies in space and time, the diversity-stability relationship, niche space and community coalescence. We provide several hypotheses of the influence of these factors on community evolution specifying the experimental setup of studies where microbial communities of spontaneous fermented food are used.

Niche partitioning facilitates coexistence of closely related honey bee gut bacteria

Ecological processes underlying bacterial coexistence in the gut are not well understood. Here, we disentangled the effect of the host and the diet on the coexistence of four closely related Lactobacillus species colonizing the honey bee gut. We serially passaged the four species through gnotobiotic bees and in liquid cultures in the presence of either pollen (bee diet) or simple sugars. Although the four species engaged in negative interactions, they were able to stably coexist, both in vivo and in vitro. However, coexistence was only possible in the presence of pollen, and not in simple sugars, independent of the environment. Using metatranscriptomics and metabolomics, we found that the four species utilize different pollen-derived carbohydrate substrates indicating resource partitioning as the basis of coexistence. Our results show that despite longstanding host association, gut bacterial interactions can be recapitulated in vitro providing insights about bacterial coexistence when combined with in vivo experiments.

Multi-stable bacterial communities exhibit extreme sensitivity to initial conditions

Microbial communities can have dramatically different compositions even among similar environments. This might be due to the existence of multiple alternative stable states, yet there exists little experimental evidence supporting this possibility. Here, we gathered a large collection of absolute population abundances capturing population dynamics in one- to four-strain communities of soil bacteria with a complex life cycle in a feast-or-famine environment. This dataset led to several observations: (i) some pairwise competitions resulted in bistability with a separatrix near a 1:1 initial ratio across a range of population densities; (ii) bistability propagated to multi-stability in multispecies communities; and (iii) replicate microbial communities reached different stable states when starting close to initial conditions separating basins of attraction, indicating finite-sized regions where the dynamics are unpredictable. The generalized Lotka-Volterra equations qualitatively captured most competition outcomes but were unable to quantitatively recapitulate the observed dynamics. This was partly due to complex and diverse growth dynamics in monocultures that ranged from Allee effects to nonmonotonic behaviors. Overall, our results highlight that multi-stability might be generic in multispecies communities and, combined with ecological noise, can lead to unpredictable community assembly, even in simple environments.

Towards an ecosystem model of infectious disease

Increasingly intimate associations between human society and the natural environment are driving the emergence of novel pathogens, with devastating consequences for humans and animals alike. Prior to emergence, these pathogens exist within complex ecological systems that are characterized by trophic interactions between parasites, their hosts and the environment. Predicting how disturbance to these ecological systems places people and animals at risk from emerging pathogens-and the best ways to manage this-remains a significant challenge. Predictive systems ecology models are powerful tools for the reconstruction of ecosystem function but have yet to be considered for modelling infectious disease. Part of this stems from a mistaken tendency to forget about the role that pathogens play in structuring the abundance and interactions of the free-living species favoured by systems ecologists. Here, we explore how developing and applying these more complete systems ecology models at a landscape scale would greatly enhance our understanding of the reciprocal interactions between parasites, pathogens and the environment, placing zoonoses in an ecological context, while identifying key variables and simplifying assumptions that underly pathogen host switching and animal-to-human spillover risk. As well as transforming our understanding of disease ecology, this would also allow us to better direct resources in preparation for future pandemics.

Modular Molecular Weaponry Plays a Key Role in Competition Within an Environmental Vibrio cholerae Population

The type VI secretion system (T6SS) operons of Vibrio cholerae contain extraordinarily diverse arrays of toxic effector and cognate immunity genes, which are thought to play an important role in the environmental lifestyle and adaptation of this human pathogen. Through the T6SS, proteinaceous "spears" tipped with antibacterial effectors are injected into adjacent cells, killing those not possessing immunity proteins to these effectors. Here, we investigate the T6SS-mediated dynamics of bacterial competition within a single environmental population of V. cholerae. We show that numerous members of a North American V. cholerae population possess strain-specific repertoires of cytotoxic T6SS effector and immunity genes. Using pairwise competition assays, we demonstrate that the vast majority of T6SS-mediated duels end in stalemates between strains with different T6SS repertoires. However, horizontally acquired effector and immunity genes can significantly alter the outcome of these competitions. Frequently observed horizontal gene transfer events can both increase or reduce competition between distantly related strains by homogenizing or diversifying the T6SS repertoire. Our results also suggest temperature-dependent outcomes in T6SS competition, with environmental isolates faring better against a pathogenic strain under native conditions than under those resembling a host-associated environment. Taken altogether, these interactions produce density-dependent fitness effects and a constant T6SS-mediated arms race in individual V. cholerae populations, which could ultimately preserve intraspecies diversity. Since T6SSs are widespread, we expect within-population diversity in T6SS repertoires and the resulting competitive dynamics to be a common theme in bacterial species harboring this machinery.

Formation, characterization and modeling of emergent synthetic microbial communities

Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form stable microbial communities. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains that depended on the medium. To unravel the underlying metabolic interactions, flux balance analysis was used to model microbial growth and identify potential metabolic exchanges involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. A fast growth rate is identified as one factor that can provide an advantage for maintaining presence in the community. Final community selection can also depend on selective antagonistic relationships and metabolic exchanges. Revealing the mechanisms of interaction among plant-associated microorganisms provides insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic communities with desired biological functions.

Experimental Evolution of Interference Competition

The importance of interference competition, where individuals compete through antagonistic traits such as the production of toxins, has long been recognized by ecologists, yet understanding how these types of interactions evolve remains limited. Toxin production is thought to be beneficial when competing with a competitor. Here, we explore if antagonism can evolve by long-term selection of the toxin (pyocin) producing strain Pseudomonas aeruginosa PAO1 in the presence (or absence) of one of three clinical isolates of the same species (Recipient) over ten serial transfers. We find that inhibition decreases in the absence of a recipient. In the presence of a recipient, antagonism evolved to be different depending on the recipient used. Our study shows that the evolution of interference competition by toxins can decrease or increase, experimentally demonstrating the importance of this type of interaction for the evolution of species interactions.

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.

Limitation by a shared mutualist promotes coexistence of multiple competing partners

Although mutualisms are often studied as simple pairwise interactions, they typically involve complex networks of interacting species. How multiple mutualistic partners that provide the same service and compete for resources are maintained in mutualistic networks is an open question. We use a model bacterial community in which multiple 'partner strains' of Escherichia coli compete for a carbon source and exchange resources with a 'shared mutualist' strain of Salmonella enterica. In laboratory experiments, competing E. coli strains readily coexist in the presence of S. enterica, despite differences in their competitive abilities. We use ecological modeling to demonstrate that a shared mutualist can create temporary resource niche partitioning by limiting growth rates, even if yield is set by a resource external to a mutualism. This mechanism can extend to maintain multiple competing partner species. Our results improve our understanding of complex mutualistic communities and aid efforts to design stable microbial communities.

Gut-derived Flavonifractor species variants are differentially enriched during in vitro incubation with quercetin

Flavonoids are a common component of the human diet with widely reported health-promoting properties. The gut microbiota transforms these compounds affecting the overall metabolic outcome of flavonoid consumption. Flavonoid-degrading bacteria are often studied in pure and mixed cultures but the multiple interactions between quercetin-degraders and the rest of the community have been overlooked. In this study, a comparative metataxonomic analysis of fecal communities supplemented with the flavonoid quercetin led us to identify a potential competitive exclusion interaction between two sequence variants related to the flavonoid-degrading species, Flavonifractor plautii, that belong to the same genus but different species. During incubation of fecal slurries with quercetin, the relative abundance of these two variants was inversely correlated; one variant, ASV_65f4, increased in relative abundance in half of the libraries and the other variant, ASV_a45d, in the other half. This pattern was also observed with 6 additional fecal samples that were transplanted into germ-free mice fed two different diets. Mouse's diet did not change the pattern of dominance of either variant, and initial relative abundances did not predict which one ended up dominating. Potential distinct metabolic capabilities of these two Flavonifractor-related species were evidenced, as only one variant, ASV_65f4, became consistently enriched in complex communities supplemented with acetate but without quercetin. Genomic comparison analysis of the close relatives of each variant revealed that ASV_65f4 may be an efficient utilizer of ethanolamine which is formed from the phospholipid phosphatidylethanolamine that is abundant in the gut and feces. Other discordant features between ASV_65f4- and ASV_a45d-related groups may be the presence of flagellar and galactose-utilization genes, respectively. Overall, we showed that the Flavonifractor genus harbors variants that present a pattern of negative co-occurrence and that may have different metabolic and morphological traits, whether these differences affect the dynamic of quercetin degradation warrants further investigation.

Why is cyclic dominance so rare?

Natural populations can contain multiple types of coexisting individuals. How does natural selection maintain such diversity within and across populations? A popular theoretical basis for the maintenance of diversity is cyclic dominance, illustrated by the rock-paper-scissor game. However, it appears difficult to find cyclic dominance in nature. Why is this the case? Focusing on continuously produced novel mutations, we theoretically addressed the rareness of cyclic dominance. We developed a model of an evolving population and studied the formation of cyclic dominance. Our results showed that the chance for cyclic dominance to emerge is lower when the newly introduced type is similar to existing types compared to the introduction of an unrelated type. This suggests that cyclic dominance is more likely to evolve through the assembly of unrelated types whereas it rarely evolves within a community of similar types.

An ecological framework for the analysis of prebiotic chemical reaction networks

It is becoming widely accepted that very early in life's origin, even before the emergence of genetic encoding, reaction networks of diverse small chemicals might have manifested key properties of life, namely self-propagation and adaptive evolution. To explore this possibility, we formalize the dynamics of chemical reaction networks within the framework of chemical ecosystem ecology. To capture the idea that life-like chemical systems are maintained out of equilibrium by fluxes of energy-rich food chemicals, we model chemical ecosystems in well-mixed compartments that are subject to constant dilution by a solution with a fixed concentration of input chemicals. Modelling all chemical reactions as fully reversible, we show that seeding an autocatalytic cycle with tiny amounts of one or more of its member chemicals results in logistic growth of all member chemicals in the cycle. This finding justifies drawing an instructive analogy between an autocatalytic cycle and a biological species. We extend this finding to show that pairs of autocatalytic cycles can exhibit competitive, predator-prey, or mutualistic associations just like biological species. Furthermore, when there is stochasticity in the environment, particularly in the seeding of autocatalytic cycles, chemical ecosystems can show complex dynamics that can resemble evolution. The evolutionary character is especially clear when the network architecture results in ecological precedence, which makes a system's trajectory historically contingent on the order in which cycles are seeded. For all its simplicity, the framework developed here helps explain the onset of adaptive evolution in prebiotic chemical reaction networks, and can shed light on the origin of key biological attributes such as thermodynamic irreversibility and genetic encoding.

Microbial Species Coexistence Depends on the Host Environment

Organisms and their resident microbial communities form a complex and mostly stable ecosystem. It is known that the specific composition and abundance of certain bacterial species affect host health and fitness, but the processes that lead to these microbial patterns are unknown. We investigate this by deconstructing the simple microbiome of the freshwater polyp Hydra We contrast the performance of its two main bacterial associates, Curvibacter and Duganella, on germfree hosts with two in vitro environments over time. We show that interactions within the microbiome but also the host environment lead to the observed species frequencies and abundances. More specifically, we find that both microbial species can only stably coexist in the host environment, whereas Duganella outcompetes Curvibacter in both in vitro environments irrespective of initial starting frequencies. While Duganella seems to benefit through secretions of Curvibacter, its competitive effect on Curvibacter depends upon direct contact. The competition might potentially be mitigated through the spatial distribution of the two microbial species on the host, which would explain why both species stably coexist on the host. Interestingly, the relative abundances of both species on the host do not match the relative abundances reported previously nor the overall microbiome carrying capacity as reported in this study. Both observations indicate that rare microbial community members might be relevant for achieving the native community composition and carrying capacity. Our study highlights that for dissecting microbial interactions the specific environmental conditions need to be replicated, a goal difficult to achieve with in vitro systems.IMPORTANCE This work studies microbial interactions within the microbiome of the simple cnidarian Hydra and investigates whether microbial species coexistence and community stability depend on the host environment. We find that the outcome of the interaction between the two most dominant bacterial species in Hydra's microbiome differs depending on the environment and results in a stable coexistence only in the host context. The interactive ecology between the host and the two most dominant microbes, but also the less abundant members of the microbiome, is critically important for achieving the native community composition. This indicates that the metaorganism environment needs to be taken into account when studying microbial interactions.

Community dynamics of duckweed-associated bacteria upon inoculation of plant growth-promoting bacteria

Plant growth-promoting bacteria (PGPB) have recently been demonstrated as a promising agent to improve wastewater treatment and biomass production efficiency of duckweed hydrocultures. With a view to their reliable use in aqueous environments, this study analysed the plant colonization dynamics of PGPB and the ecological consequences for the entire duckweed-associated bacterial community. A PGPB strain, Aquitalea magnusonii H3, was inoculated to duckweed at different cell densities or timings in the presence of three environmental bacterial communities. The results showed that strain H3 improved duckweed growth by 11.7–32.1% in five out of nine experiments. Quantitative-PCR and amplicon sequencing analyses showed that strain H3 successfully colonized duckweed after 1 and 3 d of inoculation in all cultivation tests. However, it significantly decreased in number after 7 d, and similar bacterial communities were observed on duckweed regardless of H3 inoculation. Predicted metagenome analysis suggested that genes related to bacterial chemotactic motility and surface attachment systems are consistently enriched through community assembly on duckweed. Taken together, strain H3 dominantly colonized duckweed for a short period and improved duckweed growth. However, the inoculation of the PGPB did not have a lasting impact due to the strong resilience of the natural duckweed microbiome.

Understanding the evolution of interspecies interactions in microbial communities

Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Predicting Microbiome Function Across Space Is Confounded by Strain-Level Differences and Functional Redundancy Across Taxa

Variation in the microbiome among individual organisms may play a critical role in the relative susceptibility of those organisms to infection, disease, and death. However, predicting microbiome function is difficult because of spatial and temporal variation in microbial diversity, and taxonomic diversity is not predictive of microbiome functional diversity. Addressing this issue may be particularly important when addressing pandemic diseases, such as the global amphibian die-off associated with Bd. Some of the most important factors in probiotic development for disease treatment are whether bacteria with desired function can be found on native amphibians in the local environment. To address this issue, we isolated, sequenced, and assayed the cutaneous bacterial communities of Plethodon cinereus along a gradient of land use change. Our results suggest that cutaneous community composition, but not overall diversity, change with changes in land use, but this does not correspond to significant change in Bd-inhibitory function. We found that Bd-inhibition is a functionally redundant trait, but that level of inhibition varies over phylogenetic, spatial, and temporal scales. This research provides further evidence for the importance of continued examination of amphibian microbial communities across environmental gradients, including biotic and abiotic interactions, when considering disease dynamics.

Regime Shifts in a Phage-Bacterium Ecosystem and Strategies for Its Control

The competition between bacteria often involves both nutrients and phage predators and may give rise to abrupt regime shifts between the alternative stable states characterized by different species compositions. While such transitions have been previously studied in the context of competition for nutrients, the case of phage-induced bistability between competing bacterial species has not been considered yet. Here we demonstrate a possibility of regime shifts in well-mixed phage-bacterium ecosystems. In one of the bistable states, the fast-growing bacteria competitively exclude the slow-growing ones by depleting their common nutrient. Conversely, in the second state, the slow-growing bacteria with a large burst size generate such a large phage population that the other species cannot survive. This type of bistability can be realized as the competition between a strain of bacteria protected from phage by abortive infection and another strain with partial resistance to phage. It is often desirable to reliably control the state of microbial ecosystems, yet bistability significantly complicates this task. We discuss successes and limitations of one control strategy in which one adds short pulses to populations of individual species. Our study proposes a new type of phage therapy, where introduction of the phage is supplemented by the addition of a partially resistant host bacteria.IMPORTANCE Phage-microbe communities play an important role in human health as well as natural and industrial environments. Here we show that these communities can assume several alternative species compositions separated by abrupt regime shifts. Our model predicts these regime shifts in the competition between bacterial strains protected by two different phage defense mechanisms: abortive infection/CRISPR and partial resistance. The history dependence caused by regime shifts greatly complicates the task of manipulation and control of a community. We propose and study a successful control strategy via short population pulses aimed at inducing the desired regime shifts. In particular, we predict that a fast-growing pathogen could be eliminated by a combination of its phage and a slower-growing susceptible host.

Spatial structure increases the benefits of antibiotic production in Streptomyces

Bacteria in the soil compete for limited resources. One of the ways they might do this is by producing antibiotics, but the metabolic costs of antibiotics and their low concentrations have caused uncertainty about the ecological role of these products for the bacteria that produce them. Here, we examine the benefits of streptomycin production by the filamentous bacterium Streptomyces griseus. We first provide evidence that streptomycin production enables S. griseus to kill and invade the susceptible species, S. coelicolor, but not a streptomycin‐resistant mutant of this species. Next, we show that the benefits of streptomycin production are density dependent, because production scales positively with cell number, and frequency dependent, with a threshold of invasion of S. griseus at around 1%. Finally, using serial transfer experiments where spatial structure is either maintained or destroyed, we show that spatial structure reduces the threshold frequency of invasion by more than 100‐fold, indicating that antibiotic production can permit invasion from extreme rarity. Our results show that streptomycin is both an offensive and defensive weapon that facilitates invasion into occupied habitats and also protects against invasion by competitors. They also indicate that the benefits of antibiotic production rely on ecological interactions occurring at small local scales.

Uncovering the rules of microbial community invasions

Understanding the ecological and evolutionary processes determining the outcome of biological invasions has been the subject of decades of research with most work focusing on macro-organisms. In the context of microbes, invasions remain poorly understood despite being increasingly recognized as important. To shed light on the factors affecting the success of microbial community invasions, we perform simulations using an individual-based nearly neutral model that combines ecological and evolutionary processes. Our simulations qualitatively recreate many empirical patterns and lead to a description of five general rules of invasion: (1) larger communities evolve better invaders and better defenders; (2) where invader and resident fitness difference is large, invasion success is essentially deterministic; (3) propagule pressure contributes to invasion success, if and only if, invaders and residents are competitively similar; (4) increasing the diversity of invaders has a similar effect to increasing the number of invaders; and (5) more diverse communities more successfully resist invasion.

Local biotic interactions drive species-specific divergence in soil bacterial communities

It is well accepted that environmental heterogeneity and dispersal are key factors determining soil bacterial community composition, yet little is known about the role of local biotic interactions. Here we address this issue with an abundance-manipulation experiment that was conducted in a semiarid grassland. We manually increased the abundance of six randomly chosen resident bacterial species in separate, closed, communities and allowed the communities to recover in situ for 1 year. The single episode of increase in the abundance of different species drove species-specific community divergence accompanied by a decline in local diversity. Four of the six added species caused a decrease in the abundance of their closely related species, suggesting an important role of interspecific competition in driving the observed community divergence. Our results also suggested a lack of effective population regulations to force the relative abundance of manipulated species to revert to original level, which would allow persistence of the divergence among soil bacterial communities. We concluded that biotic interactions were important in determining soil bacterial community composition, which could result in substantial variation in soil bacterial community composition in abiotically homogenous environment.

Microbial coexistence through chemical-mediated interactions

Many microbial functions happen within communities of interacting species. Explaining how species with disparate growth rates can coexist is important for applications such as manipulating host-associated microbiota or engineering industrial communities. Here, we ask how microbes interacting through their chemical environment can achieve coexistence in a continuous growth setup (similar to an industrial bioreactor or gut microbiota) where external resources are being supplied. We formulate and experimentally constrain a model in which mediators of interactions (e.g. metabolites or waste-products) are explicitly incorporated. Our model highlights facilitation and self-restraint as interactions that contribute to coexistence, consistent with our intuition. When interactions are strong, we observe that coexistence is determined primarily by the topology of facilitation and inhibition influences not their strengths. Importantly, we show that consumption or degradation of chemical mediators moderates interaction strengths and promotes coexistence. Our results offer insights into how to build or restructure microbial communities of interest.

Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior

The manipulation and engineering of microbiomes could lead to improved human health, environmental sustainability, and agricultural productivity. However, microbiomes have proven difficult to alter in predictable ways, and their emergent properties are poorly understood. The history of biology has demonstrated the power of model systems to understand complex problems such as gene expression or development. Therefore, a defined and genetically tractable model community would be useful to dissect microbiome assembly, maintenance, and processes. We have developed a tractable model rhizosphere microbiome, designated THOR, containing Pseudomonas koreensis, Flavobacterium johnsoniae, and Bacillus cereus, which represent three dominant phyla in the rhizosphere, as well as in soil and the mammalian gut. The model community demonstrates emergent properties, and the members are amenable to genetic dissection. We propose that THOR will be a useful model for investigations of community-level interactions.

The quest to manipulate microbiomes has intensified, but many microbial communities have proven to be recalcitrant to sustained change. Developing model communities amenable to genetic dissection will underpin successful strategies for shaping microbiomes by advancing an understanding of community interactions. We developed a model community with representatives from three dominant rhizosphere taxa, the Firmicutes, Proteobacteria, and Bacteroidetes. We chose Bacillus cereus as a model rhizosphere firmicute and characterized 20 other candidates, including “hitchhikers” that coisolated with B. cereus from the rhizosphere. Pairwise analysis produced a hierarchical interstrain-competition network. We chose two hitchhikers, Pseudomonas koreensis from the top tier of the competition network and Flavobacterium johnsoniae from the bottom of the network, to represent the Proteobacteria and Bacteroidetes, respectively. The model community has several emergent properties, induction of dendritic expansion of B. cereus colonies by either of the other members, and production of more robust biofilms by the three members together than individually. Moreover, P. koreensis produces a novel family of alkaloid antibiotics that inhibit growth of F. johnsoniae, and production is inhibited by B. cereus. We designate this community THOR, because the members are the hitchhikers of the rhizosphere. The genetic, genomic, and biochemical tools available for dissection of THOR provide the means to achieve a new level of understanding of microbial community behavior.

A shared limiting resource leads to competitive exclusion in a cross-feeding system

Species interactions and coexistence are often dependent upon environmental conditions. When two cross-feeding bacteria exchange essential nutrients, the addition of a cross-fed nutrient to the environment can release one species from its dependence on the other. Previous studies suggest that continued coexistence depends on relative growth rates: coexistence is maintained if the slower-growing species is released from its dependence on the other, but if the faster-growing species is released, the slower-growing species will be lost (a hypothesis that we call 'feed the faster grower' or FFG). Using invasion-from-rare experiments with two reciprocally cross-feeding bacteria, genome-scale metabolic modelling and classical ecological models, we explored the potential for coexistence when one cross-feeder became independent. We found that whether nutrient addition shifted an interaction from mutualism to commensalism or parasitism depended on whether the nutrient that limited total growth was required by one or both species. Parasitism resulted when both species required the growth-limiting resource. Importantly, coexistence was only lost when the interaction became parasitism, and the obligate species had a slower growth rate. Under these restricted conditions, the FFG hypothesis applied. Our results contribute to a mechanistic understanding of how resources can be manipulated to alter interactions and coexistence in microbial communities.

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community

The composition of the human gut microbiome is well resolved, but predictive understanding of its dynamics is still lacking. Here, we followed a bottom-up strategy to explore human gut community dynamics: we established a synthetic community composed of three representative human gut isolates (Roseburia intestinalis L1-82, Faecalibacterium prausnitzii A2-165 and Blautia hydrogenotrophica S5a33) and explored their interactions under well-controlled conditions in vitro. Systematic mono- and pair-wise fermentation experiments confirmed competition for fructose and cross-feeding of formate. We quantified with a mechanistic model how well tri-culture dynamics was predicted from mono-culture data. With the model as reference, we demonstrated that strains grown in co-culture behaved differently than those in mono-culture and confirmed their altered behavior at the transcriptional level. In addition, we showed with replicate tri-cultures and simulations that dominance in tri-culture sensitively depends on the initial conditions. Our work has important implications for gut microbial community modeling as well as for ecological interaction detection from batch cultures.

Our gut is home to trillions of microorganisms, most of them bacteria, which have an important impact on our body. During healthy periods, these microorganisms help our digestion, protect our cells, and compete against disease-causing bacteria. But specific communities of gut bacteria are linked to many diseases.

We already have a good knowledge of the bacterial composition present in a wide range of human guts, but how the different bacterial species within such communities affect each other, has so far been unclear. Future disease treatments may be able to steer ‘bad’ communities to healthier mixtures. For this to happen we need to know how species interact and how these interactions change the behavior of the whole community.

To investigate this further, D'hoe, Vet, Faust et al. studied three common species of gut bacteria under controlled conditions in the laboratory. The different species were either grown alone, in pairs or together, and the number of bacteria and the concentration of nutrients were measured over time. The results showed that when grown alone or together, their behavior changed.

D'hoe et al. then used a mathematical model to estimate the rates at which species multiplied and consumed nutrients. This model was able to predict the dynamics of each of the species grown alone. However, the data from bacteria grown in pairs was needed to predict the dynamics of bacteria grown as a group of three. Next, D'hoe et al. compared the activity of genes between bacteria grown alone or together, and discovered several differences.

This suggests that bacterial species affect each other greatly, and community behavior cannot be predicted from knowledge of its members alone. Therefore, studying bacteria in isolation is not enough to understand the complex environments of our guts, which are inhabited not by three but hundreds of bacterial species. In future, interactions between bacteria will need to be studied to ultimately be able to shift the gut community into better shapes.

Deciphering microbial interactions in synthetic human gut microbiome communities

The ecological forces that govern the assembly and stability of the human gut microbiota remain unresolved. We developed a generalizable model-guided framework to predict higher-dimensional consortia from time-resolved measurements of lower-order assemblages. This method was employed to decipher microbial interactions in a diverse human gut microbiome synthetic community. We show that pairwise interactions are major drivers of multi-species community dynamics, as opposed to higher-order interactions. The inferred ecological network exhibits a high proportion of negative and frequent positive interactions. Ecological drivers and responsive recipient species were discovered in the network. Our model demonstrated that a prevalent positive and negative interaction topology enables robust coexistence by implementing a negative feedback loop that balances disparities in monospecies fitness levels. We show that negative interactions could generate history-dependent responses of initial species proportions that frequently do not originate from bistability. Measurements of extracellular metabolites illuminated the metabolic capabilities of monospecies and potential molecular basis of microbial interactions. In sum, these methods defined the ecological roles of major human-associated intestinal species and illuminated design principles of microbial communities.

Using Cultivated Microbial Communities To Dissect Microbiome Assembly: Challenges, Limitations, and the Path Ahead

As troves of microbiome sequencing data provide improved resolution of patterns of microbial diversity, new approaches are needed to understand what controls these patterns. Many microbial ecologists are using cultivated model microbial communities to address this challenge.

As troves of microbiome sequencing data provide improved resolution of patterns of microbial diversity, new approaches are needed to understand what controls these patterns. Many microbial ecologists are using cultivated model microbial communities to address this challenge. These systems provide opportunities to identify drivers of microbiome assembly, but key challenges and limitations need to be carefully considered in their development, implementation, and interpretation. How well do model microbial communities mimic in vitro communities in terms of taxonomic diversity, trophic levels, intraspecific diversity, and the abiotic environment? What are the best ways to manipulate and measure inputs and outputs in model community experiments? In this perspective, I briefly address some of these challenges on the basis of our experience developing fermented food model communities. Future work integrating genetic and molecular approaches with cultivated model microbial communities will allow microbial ecology to develop a more mechanistic understanding of microbiome diversity.

Synthetic microbial ecology and the dynamic interplay between microbial genotypes

Assemblages of microbial genotypes growing together can display surprisingly complex and unexpected dynamics and result in community-level functions and behaviors that are not readily expected from analyzing each genotype in isolation. This complexity has, at least in part, inspired a discipline of synthetic microbial ecology. Synthetic microbial ecology focuses on designing, building and analyzing the dynamic behavior of ‘ecological circuits’ (i.e. a set of interacting microbial genotypes) and understanding how community-level properties emerge as a consequence of those interactions. In this review, we discuss typical objectives of synthetic microbial ecology and the main advantages and rationales of using synthetic microbial assemblages. We then summarize recent findings of current synthetic microbial ecology investigations. In particular, we focus on the causes and consequences of the interplay between different microbial genotypes and illustrate how simple interactions can create complex dynamics and promote unexpected community-level properties. We finally propose that distinguishing between active and passive interactions and accounting for the pervasiveness of competition can improve existing frameworks for designing and predicting the dynamics of microbial assemblages.