Transient invaders can induce shifts between alternative stable states of microbial communities

Hysteretic and asynchronous regime shifts of bacterial and micro-eukaryotic communities driven by nutrient loading

Nutrient pollution is pervasive in many urban rivers, while restoration measures that reduce nutrient loading but fail to improve biological communities often lack effectiveness due to the indispensable role of biota, especially multi-taxa, in enhancing ecosystem stability and function. The investigation of the response patterns of multi-taxa to the nutrient loading in urban rivers is important for the recovery of biota structure and thus ecosystem function. However, little is known about the response patterns of multi-taxa and their impact on ecosystem structure and function in urban rivers. Here, the study, from the perspective of alternative stable states theory, showed the hysteretic response of both bacterial and micro-eukaryotic communities to nutrient loading based on the field investigation and environmental DNA metabarcoding. Bistability was shown to exist in both bacterial and micro-eukaryotic communities, demonstrating that the response of microbiota to nutrient loading was a regime shifts with hysteresis. Potential analysis then indicated that the increased nutrient loading drove regime shifts in the bacterial community and the micro-eukaryotic community towards a state dominated by anaerobic bacteria and benthic Bacillariophyta, respectively. High nutrient loading was found to reduce the relative abundance of metazoan, but increase that of eukaryotic algae, which made the trophic pyramid top-lighter and bottom-heavier, probably exacerbating the degradation of ecosystem function. It should be noted that, in response to the reduced nutrient loading, the recovery threshold of micro-eukaryotic communities (nutrient loading = ∼0.5) was lower than that of bacterial communities (nutrient loading = ∼1.2), demonstrating longer hysteresis of micro-eukaryotic communities. In addition, the markedly positive correlation between the status of microbial communities and N-related enzyme activities suggested the recovery of microbial communities probably will benefit the improvement of N-cycling functionality. The obtained results provide a deep insight into the collapse and recovery trajectories of multi-trophic microbiota to the nutrient loading gradient and their impact on the N transformation potential, therefore benefiting the restoration and management of urban rivers.

Meta-analysis reveals the effects of microbial inoculants on the biomass and diversity of soil microbial communities

Microbial inoculation involves transplanting microorganisms from their natural habitat to new plants or soils to improve plant performance, and it is being increasingly used in agriculture and ecological restoration. However, microbial inoculants can invade and alter the composition of native microbial communities; thus, a comprehensive analysis is urgently needed to understand the overall impact of microbial inoculants on the biomass, diversity, structure and network complexity of native communities. Here we provide a meta-analysis of 335 studies revealing a positive effect of microbial inoculants on soil microbial biomass. This positive effect was weakened by environmental stress and enhanced by the use of fertilizers and native inoculants. Although microbial inoculants did not alter microbial diversity, they induced major changes in the structure and bacterial composition of soil microbial communities, reducing the complexity of bacterial networks and increasing network stability. Finally, higher initial levels of soil nutrients amplified the positive impact of microbial inoculants on fungal biomass, actinobacterial biomass, microbial biomass carbon and microbial biomass nitrogen. Together, our results highlight the positive effects of microbial inoculants on soil microbial biomass, emphasizing the benefits of native inoculants and the important regulatory roles of soil nutrient levels and environmental stress.

Global epistasis and the emergence of function in microbial consortia

The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

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.

PDE-LEARN: Using deep learning to discover partial differential equations from noisy, limited data

In this paper, we introduce PDE-LEARN, a novel deep learning algorithm that can identify governing partial differential equations (PDEs) directly from noisy, limited measurements of a physical system of interest. PDE-LEARN uses a Rational Neural Network, U, to approximate the system response function and a sparse, trainable vector, ξ, to characterize the hidden PDE that the system response function satisfies. Our approach couples the training of U and ξ using a loss function that (1) makes U approximate the system response function, (2) encapsulates the fact that U satisfies a hidden PDE that ξ characterizes, and (3) promotes sparsity in ξ using ideas from iteratively reweighted least-squares. Further, PDE-LEARN can simultaneously learn from several data sets, allowing it to incorporate results from multiple experiments. This approach yields a robust algorithm to discover PDEs directly from realistic scientific data. We demonstrate the efficacy of PDE-LEARN by identifying several PDEs from noisy and limited measurements.

Relative dispersion ratios following fecal microbiota transplant elucidate principles governing microbial migration dynamics

Microorganisms frequently migrate from one ecosystem to another. Yet, despite the potential importance of this process in modulating the environment and the microbial ecosystem, our understanding of the fundamental forces that govern microbial dispersion is still lacking. Moreover, while theoretical models and in-vitro experiments have highlighted the contribution of species interactions to community assembly, identifying such interactions in vivo, specifically in communities as complex as the human gut, remains challenging. To address this gap, here we introduce a robust and rigorous computational framework, termed Relative Dispersion Ratio (RDR) analysis, and leverage data from well-characterized fecal microbiota transplant trials, to rigorously pinpoint dependencies between taxa during the colonization of human gastrointestinal tract. Our analysis identifies numerous pairwise dependencies between co-colonizing microbes during migration between gastrointestinal environments. We further demonstrate that identified dependencies agree with previously reported findings from in-vitro experiments and population-wide distribution patterns. Finally, we explore metabolic dependencies between these taxa and characterize the functional properties that facilitate effective dispersion. Collectively, our findings provide insights into the principles and determinants of community dynamics following ecological translocation, informing potential opportunities for precise community design.

Improving crop salt tolerance through soil legacy effects

Soil salinization poses a critical problem, adversely affecting plant development and sustainable agriculture. Plants can produce soil legacy effects through interactions with the soil environments. Salt tolerance of plants in saline soils is not only determined by their own stress tolerance but is also closely related to soil legacy effects. Creating positive soil legacy effects for crops, thereby alleviating crop salt stress, presents a new perspective for improving soil conditions and increasing productivity in saline farmlands. Firstly, the formation and role of soil legacy effects in natural ecosystems are summarized. Then, the processes by which plants and soil microbial assistance respond to salt stress are outlined, as well as the potential soil legacy effects they may produce. Using this as a foundation, proposed the application of salt tolerance mechanisms related to soil legacy effects in natural ecosystems to saline farmlands production. One aspect involves leveraging the soil legacy effects created by plants to cope with salt stress, including the direct use of halophytes and salt-tolerant crops and the design of cropping patterns with the specific crop functional groups. Another aspect focuses on the utilization of soil legacy effects created synergistically by soil microorganisms. This includes the inoculation of specific strains, functional microbiota, entire soil which legacy with beneficial microorganisms and tolerant substances, as well as the application of novel technologies such as direct use of rhizosphere secretions or microbial transmission mechanisms. These approaches capitalize on the characteristics of beneficial microorganisms to help crops against salinity. Consequently, we concluded that by the screening suitable salt-tolerant crops, the development rational cropping patterns, and the inoculation of safe functional soils, positive soil legacy effects could be created to enhance crop salt tolerance. It could also improve the practical significance of soil legacy effects in the application of saline farmlands.

DyMMM-LEAPS: An ML-based framework for modulating evenness and stability in synthetic microbial communities

There have been a growing number of computational strategies to aid in the design of synthetic microbial consortia. A framework to identify regions in parametric space to maximize two essential properties, evenness and stability, is critical. In this study, we introduce DyMMM-LEAPS (dynamic multispecies metabolic modeling-locating evenness and stability in large parametric space), an extension of the DyMMM framework. Our method explores the large parametric space of genetic circuits in synthetic microbial communities to identify regions of evenness and stability. Due to the high computational costs of exhaustive sampling, we utilize adaptive sampling and surrogate modeling to reduce the number of simulations required to map the vast space. Our framework predicts engineering targets and computes their operating ranges to maximize the probability of the engineered community to have high evenness and stability. We demonstrate our approach by simulating five cocultures and one three-strain culture with different social interactions (cooperation, competition, and predation) employing quorum-sensing-based genetic circuits. In addition to guiding circuit tuning, our pipeline gives an opportunity for a detailed analysis of pockets of evenness and stability for the circuit under investigation, which can further help dissect the relationship between the two properties. DyMMM-LEAPS is easily customizable and can be expanded to a larger community with more complex interactions.

Synthesis of recovery patterns in microbial communities across environments

BACKGROUND

Disturbances alter the diversity and composition of microbial communities. Yet a generalized empirical assessment of microbiome responses to disturbance across different environments is needed to understand the factors driving microbiome recovery, and the role of the environment in driving these patterns.

RESULTS

To this end, we combined null models with Bayesian generalized linear models to examine 86 time series of disturbed mammalian, aquatic, and soil microbiomes up to 50 days following disturbance. Overall, disturbances had the strongest effect on mammalian microbiomes, which lost taxa and later recovered their richness, but not their composition. In contrast, following disturbance, aquatic microbiomes tended away from their pre-disturbance composition over time. Surprisingly, across all environments, we found no evidence of increased compositional dispersion (i.e., variance) following disturbance, in contrast to the expectations of the Anna Karenina Principle.

CONCLUSIONS

This is the first study to systematically compare secondary successional dynamics across disturbed microbiomes, using a consistent temporal scale and modeling approach. Our findings show that the recovery of microbiomes is environment-specific, and helps to reconcile existing, environment-specific research into a unified perspective. Video Abstract.

Tracking arbuscular mycorrhizal fungi to their source: active inoculation and passive dispersal differentially affect community assembly in urban soils

Communities of arbuscular mycorrhizal (AM) fungi assemble passively over time via biotic and abiotic mechanisms. In degraded soils, AM fungal communities can assemble actively when humans manage mycorrhizas for ecosystem restoration. We investigated mechanisms of urban AM fungal community assembly in a 2-yr green roof experiment. We compared AM fungal communities in inoculated and uninoculated trays to samples from two potential sources: the inoculum and air. Active inoculation stimulated more distinct and diverse AM fungal communities, an effect that intensified over time. In the treatment trays, 45% of AM fungal taxa were detected in the inoculum, 2% were detected in aerial samples, 23% were detected in both inoculum and air, and 30% were not detected in either source. Passive dispersal of AM fungi likely resulted in the successful establishment of a small number of species, but active inoculation with native AM fungal species resulted in an immediate shift to a diverse and unique fungal community. When urban soils are constructed or modified by human activity, this is an opportunity for intervention with AM fungi that will persist and add diversity to that system.

Invasibility of a North American soil ecosystem to amphibian-killing fungal pathogens

North American salamanders are threatened by intercontinental spread of chytridiomycosis, a deadly disease caused by the fungal pathogen Batrachochytrium salamandrivorans (Bsal). To predict potential dispersal of Bsal spores to salamander habitats, we evaluated the capacity of soil microbial communities to resist invasion. We determined the degree of habitat invasibility using soils from five locations throughout the Great Smoky Mountains National Park, a region with a high abundance of susceptible hosts. Our experimental design consisted of replicate soil microcosms exposed to different propagule pressures of the non-native pathogen, Bsal, and an introduced but endemic pathogen, B. dendrobatidis (Bd). To compare growth and competitive interactions, we used quantitative PCR, live/dead cell viability assays, and full-length 16S rRNA sequencing. We found that soil microcosms with intact bacterial communities inhibited both Bsal and Bd growth, but inhibitory capacity diminished with increased propagule pressure. Bsal showed greater persistence than Bd. Linear discriminant analysis (LDA) identified the family Burkolderiaceae as increasing in relative abundance with the decline of both pathogens. Although our findings provide evidence of environmental filtering in soils, such barriers weakened in response to pathogen type and propagule pressure, showing that habitats vary their invasibility based on properties of their local microbial communities.

A taxonomy of multiple stable states in complex ecological communities

Natural systems are built from multiple interconnected units, making their dynamics, functioning and fragility notoriously hard to predict. A fragility scenario of particular relevance concerns so-called regime shifts: abrupt transitions from healthy to degraded ecosystem states. An explanation for these shifts is that they arise as transitions between alternative stable states, a process that is well-understood in few-species models. However, how multistability upscales with system complexity remains a debated question. Here, we identify that four different multistability regimes generically emerge in models of species-rich communities and other archetypical complex biological systems assuming random interactions. Across the studied models, each regime consistently emerges under a specific interaction scheme and leaves a distinct set of fingerprints in terms of the number of observed states, their species richness and their response to perturbations. Our results help clarify the conditions and types of multistability that can be expected to occur in complex ecological communities.

Lose-lose consequences of bacterial community-driven invasions in soil

BACKGROUND

Community-driven invasion, also known as community coalescence, occurs widely in natural ecosystems. Despite that, our knowledge about the process and mechanisms controlling community-driven invasion in soil ecosystems is lacking. Here, we performed a set of coalescence experiments in soil microcosms and assessed impacts up to 60 days after coalescence by quantifying multiple traits (compositional, functional, and metabolic) of the invasive and coalescent communities.

RESULTS

Our results showed that coalescences significantly triggered changes in the resident community's succession trajectory and functionality (carbohydrate metabolism), even when the size of the invasive community is small (~ 5% of the resident density) and 99% of the invaders failed to survive. The invasion impact was mainly due to the high suppression of constant residents (65% on average), leading to a lose-lose situation where both invaders and residents suffered with coalescence. Our results showed that surviving residents could benefit from the coalescence, which supports the theory of "competition-driven niche segregation" at the microbial community level. Furthermore, the result showed that both short- and long-term coalescence effects were predicted by similarity and unevenness indexes of compositional, functional, and metabolic traits of invasive communities. This indicates the power of multi-level traits in monitoring microbial community succession. In contrast, the varied importance of different levels of traits suggests that competitive processes depend on the composition of the invasive community.

CONCLUSIONS

Our results shed light on the process and consequence of community coalescences and highlight that resource competition between invaders and residents plays a critical role in soil microbial community coalescences. These findings provide valuable insights for understanding and predicting soil microbial community succession in frequently disturbed natural and agroecosystems. Video Abstract.

Data-driven prediction of colonization outcomes for complex microbial communities

Microbial interactions can lead to different colonization outcomes of exogenous species, be they pathogenic or beneficial in nature. Predicting the colonization of exogenous species in complex communities remains a fundamental challenge in microbial ecology, mainly due to our limited knowledge of the diverse mechanisms governing microbial dynamics. Here, we propose a data-driven approach independent of any dynamics model to predict colonization outcomes of exogenous species from the baseline compositions of microbial communities. We systematically validate this approach using synthetic data, finding that machine learning models can predict not only the binary colonization outcome but also the post-invasion steady-state abundance of the invading species. Then we conduct colonization experiments for commensal gut bacteria species Enterococcus faecium and Akkermansia muciniphila in hundreds of human stool-derived in vitro microbial communities, confirming that the data-driven approaches can predict the colonization outcomes in experiments. Furthermore, we find that while most resident species are predicted to have a weak negative impact on the colonization of exogenous species, strongly interacting species could significantly alter the colonization outcomes, e.g., Enterococcus faecalis inhibits the invasion of E. faecium invasion. The presented results suggest that the data-driven approaches are powerful tools to inform the ecology and management of microbial communities.

Evaluating the role of rhizosphere microbial home-field advantage in Betula luminifera adaptation to antimony mining areas

It has been established that the coevolution of plants and the rhizosphere microbiome in response to abiotic stress can result in the recruitment of specific functional microbiomes. However, the potential of inoculated rhizosphere microbiomes to enhance plant fitness and the inheritance of adaptive traits in subsequent generations remains unclear. In this study, cross-inoculation trials were conducted using seeds, rhizosphere microbiome, and in situ soil collected from areas of Betula luminifera grown in both antimony mining and control sites. Compared to the control site, plants originating from mining areas exhibited stronger adaptive traits, specifically manifested as significant increases in hundred-seed weight, specific surface area, and germination rate, as well as markedly enhanced seedling survival rate and biomass. Inoculation with mining microbiomes could enhance the fitness of plants in mining sites through a "home-field advantage" while also improving the fitness of plants originating from control sites. During the initial phase of seedling development, bacteria play a crucial role in promoting growth, primarily due to their mechanisms of metal resistance and nutrient cycling. This study provided evidence that the outcomes of long-term coevolution between plants and the rhizosphere microbiome in mining areas can be passed on to future generations. Moreover, it has been demonstrated that transgenerational inheritance and rhizosphere microbiome inoculation are important factors in improving the adaptability of plants in mining areas. The findings have important implications for vegetation restoration and ecological environment improvement in mining areas.

Survival of a microbial inoculant in soil after recurrent inoculations

Microbial inoculants are attracting growing interest in agriculture, but their efficacy remains unreliable in relation to their poor survival, partly due to the competition with the soil resident community. We hypothesised that recurrent inoculation could gradually alleviate this competition and improve the survival of the inoculant while increasing its impact on the resident bacterial community. We tested the effectiveness of such strategy with four inoculation sequences of Pseudomonas fluorescens strain B177 in soil microcosms with increasing number and frequency of inoculation, compared to a non-inoculated control. Each sequence was carried out at two inoculation densities (106 and 108 cfu.g soil-1). The four-inoculation sequence induced a higher abundance of P. fluorescens, 2 weeks after the last inoculation. No impact of inoculation sequences was observed on the resident community diversity and composition. Differential abundance analysis identified only 28 out of 576 dominants OTUs affected by the high-density inoculum, whatever the inoculation sequence. Recurrent inoculations induced a strong accumulation of nitrate, not explained by the abundance of nitrifying or nitrate-reducing microorganisms. In summary, inoculant density rather than inoculation pattern matters for inoculation effect on the resident bacterial communities, while recurrent inoculation allowed to slightly enhance the survival of the inoculant and strongly increased soil nitrate content.

Richness and density jointly determine context dependence in bacterial interactions

Pairwise interactions are often used to predict features of complex microbial communities due to the challenge of measuring multi-species interactions in high dimensional contexts. This assumes that interactions are unaffected by community context. Here, we used synthetic bacterial communities to investigate that assumption by observing how interactions varied across contexts. Interactions were most often weakly negative and showed a phylogenetic signal among genera. Community richness and total density emerged as strong predictors of interaction strength and contributed to an attenuation of interactions as richness increased. Population level and per-capita measures of interactions both displayed such attenuation, suggesting factors beyond systematic changes in population size were involved; namely, changes to the interactions themselves. Nevertheless, pairwise interactions retained some explanatory power across contexts, provided those contexts were not substantially divergent in richness. These results suggest that understanding the emergent properties of microbial interactions can improve our ability to predict the features of microbial communities.

Soil microbiome analysis supports claims of ineffectiveness of Pseudomonas fluorescens D7 as a biocontrol agent of Bromus tectorum

IMPORTANCE

Cheatgrass is one of North America's most problematic invasive species. Invasion by this annual grass alters ecosystem structure and function and has proven very challenging to remove with traditional approaches. Commercially available bioherbicides, like P. fluorescens D7, are applied with the goal of providing lasting control from a single application. However, experimental results suggest that this bioherbicide has limited efficacy under field conditions. Potential explanations for variable efficacy include a failure of this bioherbicide to establish in the soil microbiome. However, to our knowledge, no data exist to support or refute this hypothesis. Here, we use a deep-sequencing approach to better understand the effects of this bioherbicide on the soil microbiome and screen for P. fluorescens at 18 months post-application.

Competition for shared resources increases dependence on initial population size during coalescence of gut microbial communities

The long-term success of introduced populations depends on their initial size and ability to compete against existing residents, but it remains unclear how these factors collectively shape colonization. Here, we investigate how initial population (propagule) size and resource competition interact during community coalescence by systematically mixing eight pairs of in vitro microbial communities at ratios that vary over six orders of magnitude, and we compare our results to a neutral ecological model. Although the composition of the resulting co-cultures deviated substantially from neutral expectations, each co-culture contained species whose relative abundance depended on propagule size even after ~40 generations of growth. Using a consumer-resource model, we show that this dose-dependent colonization can arise when resident and introduced species have high niche overlap and consume shared resources at similar rates. This model predicts that propagule size will have larger, longer-lasting effects in diverse communities in which niche overlap is higher, and we experimentally confirm that strain isolates show stronger dose dependence when introduced into diverse communities than in pairwise co-culture. This work shows how neutral-like colonization dynamics can emerge from non-neutral resource competition and have lasting effects on the outcomes of community coalescence.

Diversity loss from multiple interacting disturbances is regime-dependent

Anthropogenic activities expose many ecosystems to multiple novel disturbances simultaneously. Despite this, how biodiversity responds to simultaneous disturbances remains unclear, with conflicting empirical results on their interactive effects. Here, we experimentally test how one disturbance (an invasive species) affects the diversity of a community over multiple levels of another disturbance regime (pulse mortality). Specifically, we invade stably coexisting bacterial communities under four different pulse frequencies, and compare their final resident diversity to uninvaded communities under the same pulse mortality regimes. Our experiment shows that the disturbances synergistically interact, such that the invader significantly reduces resident diversity at high pulse frequency, but not at low. This work therefore highlights the need to study simultaneous disturbance effects over multiple disturbance regimes as well as to carefully document unmanipulated disturbances, and may help explain the conflicting results seen in previous multiple-disturbance work.

Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes

Microbiome engineering offers the potential to leverage microbial communities to improve outcomes in human health, agriculture, and climate. To translate this potential into reality, it is crucial to reliably predict community composition and function. But a brute force approach to cataloging community function is hindered by the combinatorial explosion in the number of ways we can combine microbial species. An alternative is to parameterize microbial community outcomes using simplified, mechanistic models, and then extrapolate these models beyond where we have sampled. But these approaches remain data-hungry, as well as requiring an a priori specification of what kinds of mechanisms are included and which are omitted. Here, we resolve both issues by introducing a mechanism-agnostic approach to predicting microbial community compositions and functions using limited data. The critical step is the identification of a sparse representation of the community landscape. We then leverage this sparsity to predict community compositions and functions, drawing from techniques in compressive sensing. We validate this approach on in silico community data, generated from a theoretical model. By sampling just [Formula: see text]1% of all possible communities, we accurately predict community compositions out of sample. We then demonstrate the real-world application of our approach by applying it to four experimental datasets and showing that we can recover interpretable, accurate predictions on composition and community function from highly limited data.

Statistically learning the functional landscape of microbial communities

Microbial consortia exhibit complex functional properties in contexts ranging from soils to bioreactors to human hosts. Understanding how community composition determines function is a major goal of microbial ecology. Here we address this challenge using the concept of community-function landscapes-analogues to fitness landscapes-that capture how changes in community composition alter collective function. Using datasets that represent a broad set of community functions, from production/degradation of specific compounds to biomass generation, we show that statistically inferred landscapes quantitatively predict community functions from knowledge of species presence or absence. Crucially, community-function landscapes allow prediction without explicit knowledge of abundance dynamics or interactions between species and can be accurately trained using measurements from a small subset of all possible community compositions. The success of our approach arises from the fact that empirical community-function landscapes appear to be not rugged, meaning that they largely lack high-order epistatic contributions that would be difficult to fit with limited data. Finally, we show that this observation holds across a wide class of ecological models, suggesting community-function landscapes can be efficiently inferred across a broad range of ecological regimes. Our results open the door to the rational design of consortia without detailed knowledge of abundance dynamics or interactions.

Deep discovery informs difficult deployment in plant microbiome science

Plant-associated microbiota can extend plant immune system function, improve nutrient acquisition and availability, and alleviate abiotic stresses. Thus, naturally beneficial microbial therapeutics are enticing tools to improve plant productivity. The basic definition of plant microbiota across species and ecosystems, combined with the development of reductionist experimental models and the manipulation of plant phenotypes with microbes, has fueled interest in its translation to agriculture. However, the great majority of microbes exhibiting plant-productivity traits in the lab and greenhouse fail in the field. Therapeutic microbes must reach détente, the establishment of uneasy homeostasis, with the plant immune system, invade heterogeneous pre-established plant-associated communities, and persist in a new and potentially remodeled community. Environmental conditions can alter community structure and thus impact the engraftment of therapeutic microbes. We survey recent breakthroughs, challenges, and opportunities in translating beneficial microbes from the lab to the field.

Phylogenetic distance-decay patterns are not explained by local community assembly processes in freshwater lake microbial communities

While water and sediment microbial communities exhibit pronounced spatio-temporal patterns in freshwater lakes, the underlying drivers are yet poorly understood. Here, we evaluated the importance of spatial and temporal variation in abiotic environmental factors for bacterial and microeukaryotic community assembly and distance-decay relationships in water and sediment niches in Hongze Lake. By sampling across the whole lake during both Autumn and Spring sampling time points, we show that only bacterial sediment communities were governed by deterministic community assembly processes due to abiotic environmental drivers. Nevertheless, consistent distance-decay relationships were found with both bacterial and microeukaryotic communities, which were relatively stable with both sampling time points. Our results suggest that spatio-temporal variation in environmental factors was important in explaining mainly bacterial community assembly in the sediment, possibly due lesser disturbance. However, clear distance-decay patterns emerged also when the community assembly was stochastic. Together, these results suggest that abiotic environmental factors do not clearly drive the spatial structuring of lake microbial communities, highlighting the need to understand the role of other potential drivers, such as spatial heterogeneity and biotic species interactions.

Microbiome Interconnectedness throughout Environments with Major Consequences for Healthy People and a Healthy Planet

Microbiomes have highly important roles for ecosystem functioning and carry out key functions that support planetary health, including nutrient cycling, climate regulation, and water filtration. Microbiomes are also intimately associated with complex multicellular organisms such as humans, other animals, plants, and insects and perform crucial roles for the health of their hosts. Although we are starting to understand that microbiomes in different systems are interconnected, there is still a poor understanding of microbiome transfer and connectivity. In this review we show how microbiomes are connected within and transferred between different habitats and discuss the functional consequences of these connections. Microbiome transfer occurs between and within abiotic (e.g., air, soil, and water) and biotic environments, and can either be mediated through different vectors (e.g., insects or food) or direct interactions. Such transfer processes may also include the transmission of pathogens or antibiotic resistance genes. However, here, we highlight the fact that microbiome transmission can have positive effects on planetary and human health, where transmitted microorganisms potentially providing novel functions may be important for the adaptation of ecosystems.

Home-based microbial solution to boost crop growth in low-fertility soil

Soil microbial inoculants are expected to boost crop productivity under climate change and soil degradation. However, the efficiency of native vs commercialized microbial inoculants in soils with different fertility and impacts on resident microbial communities remain unclear. We investigated the differential plant growth responses to native synthetic microbial community (SynCom) and commercial plant growth-promoting rhizobacteria (PGPR). We quantified the microbial colonization and dynamic of niche structure to emphasize the home-field advantages for native microbial inoculants. A native SynCom of 21 bacterial strains, originating from three typical agricultural soils, conferred a special advantage in promoting maize growth under low-fertility conditions. The root : shoot ratio of fresh weight increased by 78-121% with SynCom but only 23-86% with PGPRs. This phenotype correlated with the potential robust colonization of SynCom and positive interactions with the resident community. Niche breadth analysis revealed that SynCom inoculation induced a neutral disturbance to the niche structure. However, even PGPRs failed to colonize the natural soil, they decreased niche breadth and increased niche overlap by 59.2-62.4%, exacerbating competition. These results suggest that the home-field advantage of native microbes may serve as a basis for engineering crop microbiomes to support food production in widely distributed poor soils.

Modulation of antibiotic effects on microbial communities by resource competition

Antibiotic treatment significantly impacts the human gut microbiota, but quantitative understanding of how antibiotics affect community diversity is lacking. Here, we build on classical ecological models of resource competition to investigate community responses to species-specific death rates, as induced by antibiotic activity or other growth-inhibiting factors such as bacteriophages. Our analyses highlight the complex dependence of species coexistence that can arise from the interplay of resource competition and antibiotic activity, independent of other biological mechanisms. In particular, we identify resource competition structures that cause richness to depend on the order of sequential application of antibiotics (non-transitivity), and the emergence of synergistic and antagonistic effects under simultaneous application of multiple antibiotics (non-additivity). These complex behaviors can be prevalent, especially when generalist consumers are targeted. Communities can be prone to either synergism or antagonism, but typically not both, and antagonism is more common. Furthermore, we identify a striking overlap in competition structures that lead to non-transitivity during antibiotic sequences and those that lead to non-additivity during antibiotic combination. In sum, our results establish a broadly applicable framework for predicting microbial community dynamics under deleterious perturbations.

Data-driven prediction of colonization outcomes for complex microbial communities

Complex microbial interactions can lead to different colonization outcomes of exogenous species, be they pathogenic or beneficial in nature. Predicting the colonization of exogenous species in complex communities remains a fundamental challenge in microbial ecology, mainly due to our limited knowledge of the diverse physical, biochemical, and ecological processes governing microbial dynamics. Here, we proposed a data-driven approach independent of any dynamics model to predict colonization outcomes of exogenous species from the baseline compositions of microbial communities. We systematically validated this approach using synthetic data, finding that machine learning models (including Random Forest and neural ODE) can predict not only the binary colonization outcome but also the post-invasion steady-state abundance of the invading species. Then we conducted colonization experiments for two commensal gut bacteria species Enterococcus faecium and Akkermansia muciniphila in hundreds of human stool-derived in vitro microbial communities, confirming that the data-driven approach can successfully predict the colonization outcomes. Furthermore, we found that while most resident species were predicted to have a weak negative impact on the colonization of exogenous species, strongly interacting species could significantly alter the colonization outcomes, e.g., the presence of Enterococcus faecalis inhibits the invasion of E. faecium . The presented results suggest that the data-driven approach is a powerful tool to inform the ecology and management of complex microbial communities.

Environmental microbiome engineering for the mitigation of climate change

Environmental microbiome engineering is emerging as a potential avenue for climate change mitigation. In this process, microbial inocula are introduced to natural microbial communities to tune activities that regulate the long-term stabilization of carbon in ecosystems. In this review, we outline the process of environmental engineering and synthesize key considerations about ecosystem functions to target, means of sourcing microorganisms, strategies for designing microbial inocula, methods to deliver inocula, and the factors that enable inocula to establish within a resident community and modify an ecosystem function target. Recent work, enabled by high-throughput technologies and modeling approaches, indicate that microbial inocula designed from the top-down, particularly through directed evolution, may generally have a higher chance of establishing within existing microbial communities than other historical approaches to microbiome engineering. We address outstanding questions about the determinants of inocula establishment and provide suggestions for further research about the possibilities and challenges of environmental microbiome engineering as a tool to combat climate change.

Alternative stable states, nonlinear behavior, and predictability of microbiome dynamics

BACKGROUND

Microbiome dynamics are both crucial indicators and potential drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as "dysbiosis" in human microbiomes.

METHODS

We integrated theoretical frameworks and empirical analyses with the aim of anticipating drastic shifts of microbial communities. We monitored 48 experimental microbiomes for 110 days and observed that various community-level events, including collapse and gradual compositional changes, occurred according to a defined set of environmental conditions. We analyzed the time-series data based on statistical physics and non-linear mechanics to describe the characteristics of the microbiome dynamics and to examine the predictability of major shifts in microbial community structure.

RESULTS

We confirmed that the abrupt community changes observed through the time-series could be described as shifts between "alternative stable states" or dynamics around complex attractors. Furthermore, collapses of microbiome structure were successfully anticipated by means of the diagnostic threshold defined with the "energy landscape" analysis of statistical physics or that of a stability index of nonlinear mechanics.

CONCLUSIONS

The results indicate that abrupt microbiome events in complex microbial communities can be forecasted by extending classic ecological concepts to the scale of species-rich microbial systems. Video Abstract.

A symbiotic physical niche in Drosophila melanogaster regulates stable association of a multi-species gut microbiota

The gut is continuously invaded by diverse bacteria from the diet and the environment, yet microbiome composition is relatively stable over time for host species ranging from mammals to insects, suggesting host-specific factors may selectively maintain key species of bacteria. To investigate host specificity, we used gnotobiotic Drosophila, microbial pulse-chase protocols, and microscopy to investigate the stability of different strains of bacteria in the fly gut. We show that a host-constructed physical niche in the foregut selectively binds bacteria with strain-level specificity, stabilizing their colonization. Primary colonizers saturate the niche and exclude secondary colonizers of the same strain, but initial colonization by Lactobacillus species physically remodels the niche through production of a glycan-rich secretion to favor secondary colonization by unrelated commensals in the Acetobacter genus. Our results provide a mechanistic framework for understanding the establishment and stability of a multi-species intestinal microbiome.

Acidity drives volatile metabolites in the spontaneous fermentation of sesame flavor-type baijiu

Environmental factors play an important role in contributing to intricate compositional dynamics and volatile metabolites in food fermentation. However, our understanding of which and how environmental factors affect volatile metabolites during sesame flavor-type baijiu fermentation is poor. Here, we examined the effects of environmental factors on the bacterial and fungal community to determine how changes in representative factors impact the microbial structure, diversity, and volatile metabolites in three fermentations. Results showed that bacterial community (ANOSIM: R = 0.79, P = 0.001), fungal community (ANOSIM: R = 0.65, P = 0.001), and volatile metabolites (ANOSIM: R = 0.84, P = 0.001) were significantly different in three fermentations. Acidity, ethanol, and moisture negatively impacted bacterial composition and diversity (P < 0.05). The fungal diversity and structure were positively and significantly affected by acidity (path coefficient, b = 0.54 for diversity, b = 0.35 for structure, P < 0.05). The fungal community rather than the bacterial community was the strongest driver of volatile metabolites. Fungal structure and diversity were equally important for the composition and content of volatile metabolites (structure: b = 0.50, diversity: b = 0.56, P < 0.05). 66 % of variations in volatile metabolites could be explained. Altogether these results indicated that acidity strongly drove volatile metabolites by modulating fungal structure and diversity. This work provides insights into managing volatile metabolites by regulating initial acidity in sesame flavor-type baijiu fermentation.

Comparative Analysis of Core Microbiome Assignments: Implications for Ecological Synthesis

The concept of a core microbiome has been broadly used to refer to the consistent presence of a set of taxa across multiple samples within a given habitat. The assignment of taxa to core microbiomes can be performed by several methods based on the abundance and occupancy (i.e., detection across samples) of individual taxa. These approaches have led to methodological inconsistencies, with direct implications for ecological interpretation. Here, we reviewed a set of methods most commonly used to infer core microbiomes in divergent systems. We applied these methods using large data sets and analyzed simulations to determine their accuracy in core microbiome assignments. Our results show that core taxa assignments vary significantly across methods and data set types, with occupancy-based methods most accurately defining true core membership. We also found the ability of these methods to accurately capture core assignments to be contingent on the distribution of taxon abundance and occupancy in the data set. Finally, we provide specific recommendations for further studies using core taxa assignments and discuss the need for unifying methodical approaches toward data processing to advance ecological synthesis. IMPORTANCE Different methods are commonly used to assign core microbiome membership, leading to methodological inconsistencies across studies. In this study, we review a set of the most commonly used core microbiome assignment methods and compare their core assignments using both simulated and empirical data. We report inconsistent classifications from commonly applied core microbiome assignment methods. Furthermore, we demonstrate the implication that variable core assignments may have on downstream ecological interpretations. Although we still lack a standardized approach to core taxa assignments, our study provides a direction to properly test core assignment methods and offers advances in model parameterization and method choice across distinct data types.

Engineering plant microbiomes by integrating eco-evolutionary principles into current strategies

Engineering plant microbiomes has the potential to improve plant health in a rapid and sustainable way. Rapidly changing climates and relatively long timelines for plant breeding make microbiome engineering an appealing approach to improving food security. However, approaches that have shown promise in the lab have not resulted in wide-scale implementation in the field. Here, we suggest the use of an integrated approach, combining mechanistic molecular and genetic knowledge, with ecological and evolutionary theory, to target knowledge gaps in plant microbiome engineering that may facilitate translatability of approaches into the field. We highlight examples where understanding microbial community ecology is essential for a holistic understanding of the efficacy and consequences of microbiome engineering. We also review examples where understanding plant-microbe evolution could facilitate the design of plants able to recruit specific microbial communities. Finally, we discuss possible trade-offs in plant-microbiome interactions that should be considered during microbiome engineering efforts so as not to introduce off-target negative effects. We include classic and emergent approaches, ranging from microbial inoculants to plant breeding to host-driven microbiome engineering, and address areas that would benefit from multidisciplinary approaches.

Microbial Inoculants as Plant Biostimulants: A Review on Risk Status

Modern agriculture systems are copiously dependent on agrochemicals such as chemical fertilizers and pesticides intended to increase crop production and yield. The indiscriminate use of these chemicals not only affects the growth of plants due to the accumulation of toxic compounds, but also degrades the quality and life-supporting properties of soil. There is a dire need to develop some green approach that can resolve these issues and restore soil fertility and sustainability. The use of plant biostimulants has emerged as an environmentally friendly and acceptable method to increase crop productivity. Biostimulants contain biological substances which may be capable of increasing or stimulating plant growth in an eco-friendly manner. They are mostly biofertilizers that provide nutrients and protect plants from environmental stresses such as drought and salinity. In contrast to the protection of crop products, biostimulants not only act on the plant's vigor but also do not respond to direct actions against pests or diseases. Plant biostimulants improve nutrient mobilization and uptake, tolerance to stress, and thus crop quality when applied to plants directly or in the rhizospheric region. They foster plant growth and development by positively affecting the crop life-cycle starting from seed germination to plant maturity. Legalized application of biostimulants causes no hazardous effects on the environment and primarily provides nutrition to plants. It nurtures the growth of soil microorganisms, which leads to enhanced soil fertility and also improves plant metabolism. Additionally, it may positively influence the exogenous microbes and alter the equilibrium of the microfloral composition of the soil milieu. This review frequently cites the characterization of microbial plant biostimulants that belong to either a high-risk group or are closely related to human pathogens such as Pueudomonas, Klebsiella, Enterobacter, Acinetobacter, etc. These related pathogens cause ailments including septicemia, gastroenteritis, wound infections, inflammation in the respiratory system, meningitis, etc., of varied severity under different conditions of health status such as immunocompromized and comorbidity. Thus it may attract the related concern to review the risk status of biostimulants for their legalized applications in agriculture. This study mainly emphasizes microbial plant biostimulants and their safe application concerns.

Impact of Plant-Beneficial Bacterial Inocula on the Resident Bacteriome: Current Knowledge and Future Perspectives

The inoculation of plant growth-promoting bacteria (PGPB) as biofertilizers is one of the most efficient and sustainable strategies of rhizosphere manipulation leading to increased plant biomass and yield and improved plant health, as well as the ameliorated nutritional value of fruits and edible seeds. During the last decades, exciting, but heterogeneous, results have been obtained growing PGPB inoculated plants under controlled, stressful, and open field conditions. On the other hand, the possible impact of the PGPB deliberate release on the resident microbiota has been less explored and the little available information is contradictory. This review aims at filling this gap: after a brief description of the main mechanisms used by PGPB, we focus our attention on the process of PGPB selection and formulation and we provide some information on the EU regulation for microbial inocula. Then, the concept of PGPB inocula as a tool for rhizosphere engineering is introduced and the possible impact of bacterial inoculant on native bacterial communities is discussed, focusing on those bacterial species that are included in the EU regulation and on other promising bacterial species that are not yet included in the EU regulation.

Microbial invasion of a toxic medium is facilitated by a resident community but inhibited as the community co-evolves

Predicting whether microbial invaders will colonize an environment is critical for managing natural and engineered ecosystems, and controlling infectious disease. Invaders often face competition by resident microbes. But how invasions play out in communities dominated by facilitative interactions is less clear. We previously showed that growth medium toxicity can promote facilitation between four bacterial species, as species that cannot grow alone rely on others to survive. Following the same logic, here we allowed other bacterial species to invade the four-species community and found that invaders could more easily colonize a toxic medium when the community was present. In a more benign environment instead, invasive species that could survive alone colonized more successfully when the residents were absent. Next, we asked whether early colonists could exclude future ones through a priority effect, by inoculating the invaders into the resident community only after its members had co-evolved for 44 weeks. Compared to the ancestral community, the co-evolved resident community was more competitive toward invaders and less affected by them. Our experiments show how communities may assemble by facilitating one another in harsh, sterile environments, but that arriving after community members have co-evolved can limit invasion success.

Interactions between Bacterial Inoculants and Native Soil Bacterial Community: the Case of Spore-forming Bacillus spp

Microbial diversity can restrict the invasion and impact of alien microbes into soils via resource competition. However, this theory has not been tested on various microbial invaders with different ecological traits, particularly spore-forming bacteria. Here we investigated the survival capacity of two introduced spore-forming bacteria, Bacillus mycoides (BM) and B. pumillus (BP) and their impact on the soil microbiome niches with low and high diversity. We hypothesized that higher soil bacterial diversity would better restrict Bacillus survival via resource competition, and the invasion would alter the resident bacterial communities' niches only if inoculants do not escape competition with the soil community (e.g. through sporulation). Our findings showed that BP could not survive as viable propagules and transiently impacted the bacterial communities' niche structure. This may be linked to its poor resource usage and low growth rate. Having better resource use capacities, BM better survived in soil, though its survival was weakly related to the remaining resources left for them by the soil community. BM strongly affected the community niche structure, ultimately in less diverse communities. These findings show that the inverse diversity-invasibility relationship can be valid for some spore-forming bacteria, but only when they have sufficient resource use capacity.

Colonization of Penicillium oxalicum SL2 in Pb-contaminated paddy soil and its immobilization effect on soil Pb

Penicillium oxalicum SL2 (SL2) is a previously screened Pb-tolerant fungus that can promote crops growth. The relationship between SL2 colonization and Pb immobilization was studied to provide a theoretical basis for microbial remediation of Pb-contaminated paddy soil. In this study, green fluorescent protein (GFP) labeled SL2 was inoculated into different Pb-contaminated paddy soils (S1-S6). The Pb extracted from the soil by HNO₃, EDTA and CaCl₂ were used to characterize the available Pb. The results showed that the colonization of SL2 was divided into lag phase (0-7 days), growth phase (7-30 days), and mortality phase (30-90 days). SL2 colonized well in sandy soils rich in clay and total phosphorus with initial pH of 4.5-7.0. In addition, SL2 increased soil pH and decreased soil Eh, which was beneficial to immobilize Pb. In different soils, the highest percentages of CaCl₂-Pb, EDTA-Pb, and HNO₃-Pb immobilized by SL2 were 34.34%-40.53%, 17.05%-20.11%, and 7.39%-15.62%, respectively. Pearson correlation analysis showed that the percentages of CaCl₂-Pb and EDTA-Pb immobilized by SL2 were significantly positively correlated with the number of SL2 during the growth phase. SL2 mainly immobilized Pb in the growth phase and a higher peak number of SL2 was beneficial to the immobilization of Pb.

Ecosystem consequences of introducing plant growth promoting rhizobacteria to managed systems and potential legacy effects

The rapidly growing industry of crop biostimulants leverages the application of plant growth promoting rhizobacteria (PGPR) to promote plant growth and health. However, introducing nonnative rhizobacteria may impact other aspects of ecosystem functioning and have legacy effects; these potential consequences are largely unexplored. Nontarget consequences of PGPR may include changes in resident microbiomes, nutrient cycling, pollinator services, functioning of other herbivores, disease suppression, and organic matter persistence. Importantly, we lack knowledge of whether these ecosystem effects may manifest in adjacent ecosystems. The introduced PGPR can leave a functional legacy whether they persist in the community or not. Legacy effects include shifts in resident microbiomes and their temporal dynamics, horizontal transfer of genes from the PGPR to resident taxa, and changes in resident functional groups and interaction networks. Ecosystem functions may be affected by legacies PGPR leave following niche construction, such as when PGPR alter soil pH that in turn alters biogeochemical cycling rates. Here, we highlight new research directions to elucidate how introduced PGPR impact resident microbiomes and ecosystem functions and their capacity for legacy effects.

Temporal dynamics of the soil bacterial community following Bacillus invasion

Microbial inoculants are constantly introduced into the soil as the deployment of sustainable agricultural practices increases. These introductions might induce soil native communities’ dynamics, influencing their assembly process. We followed the impact and successional trajectories of native soil communities of different diversity levels to the invasion by Bacillus mycoides M2E15 (BM) and B. pumilus ECOB02 (BP). Whereas the impact was more substantial when the invader survived (BM), the transient presence of BP also exerted tangible effects on soil bacterial diversity. Community assembly analyses revealed that deterministic processes primarily drove community turnover. This selection acted stronger in highly diverse communities invaded by BM than in those invaded by BP. We showed that resident bacterial communities exhibit patterns of secondary succession following invasions, even if the latter are unsuccessful. Furthermore, the intensification of biotic interactions in more diverse communities might strengthen the deterministic selection upon invasion in communities with higher diversity.

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Microbial invaders altered soil bacterial diversity regardless of their survival

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The impact was more pronounced when the invader was established

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Deterministic selection primarily drove community turnover following invasion

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The dynamic of invaded community showed pattern of secondary succession

Ecological and Evolutionary Implications of Microbial Dispersal

Dispersal is simply defined as the movement of species across space and time. Despite this terse definition, dispersal is an essential process with direct ecological and evolutionary implications that modulate community assembly and turnover. Seminal ecological studies have shown that environmental context (e.g., local edaphic properties, resident community), dispersal timing and frequency, and species traits, collectively account for patterns of species distribution resulting in either their persistence or unsuccessful establishment within local communities. Despite the key importance of this process, relatively little is known about how dispersal operates in microbiomes across divergent systems and community types. Here, we discuss parallels of macro- and micro-organismal ecology with a focus on idiosyncrasies that may lead to novel mechanisms by which dispersal affects the structure and function of microbiomes. Within the context of ecological implications, we revise the importance of short- and long-distance microbial dispersal through active and passive mechanisms, species traits, and community coalescence, and how these align with recent advances in metacommunity theory. Conversely, we enumerate how microbial dispersal can affect diversification rates of species by promoting gene influxes within local communities and/or shifting genes and allele frequencies via migration or de novo changes (e.g., horizontal gene transfer). Finally, we synthesize how observed microbial assemblages are the dynamic outcome of both successful and unsuccessful dispersal events of taxa and discuss these concepts in line with the literature, thus enabling a richer appreciation of this process in microbiome research.

Farm-scale differentiation of active microbial colonizers

Microbial movement is important for replenishing lost soil microbial biodiversity and driving plant root colonization, particularly in managed agricultural soils, where microbial diversity and composition can be disrupted. Despite abundant survey-type microbiome data in soils, which are obscured by legacy DNA and microbial dormancy, we do not know how active microbial pools are shaped by local soil properties, agricultural management, and at differing spatial scales. To determine how active microbial colonizers are shaped by spatial scale and environmental conditions, we deployed microbial traps (i.e. sterile soil enclosed by small pore membranes) containing two distinct soil types (forest; agricultural), in three neighboring locations, assessing colonization through 16S rRNA gene and fungal ITS amplicon sequencing. Location had a greater impact on fungal colonizers (R2 = 0.31 vs. 0.26), while the soil type within the microbial traps influenced bacterial colonizers more (R2 = 0.09 vs. 0.02). Bacterial colonizers showed greater colonization consistency (within-group similarity) among replicate communities. Relative to bacterial colonizers, fungal colonizers shared a greater compositional overlap to sequences from the surrounding local bulk soil (R2 = 0.08 vs. 0.29), suggesting that these groups respond to distinct environmental constraints and that their in-field management may differ. Understanding how environmental constraints and spatial scales impact microbial recolonization dynamics and community assembly are essential for identifying how soil management can be used to shape agricultural microbiomes.

Fast growth can counteract antibiotic susceptibility in shaping microbial community resilience to antibiotics

SignificanceAntibiotic exposure stands among the most used interventions to drive microbial communities away from undesired states. How the ecology of microbial communities shapes their recovery-e.g., posttreatment shifts toward Clostridioides difficile infections in the gut-after antibiotic exposure is poorly understood. We study community response to antibiotics using a model community that can reach two alternative states. Guided by theory, our experiments show that microbial growth following antibiotic exposure can counteract antibiotic susceptibility in driving transitions between alternative community states. This makes it possible to reverse the outcome of antibiotic exposure through modifying growth dynamics, including cooperative growth, of community members. Our research highlights the relevance of simple ecological models to better understand the long-term effects of antibiotic treatment.

In vitro interaction network of a synthetic gut bacterial community

A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM¹²) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM¹² interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, Enterococcus faecalis KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM¹² interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.

The legacy of microbial inoculants in agroecosystems and potential for tackling climate change challenges

Microbial inoculations contribute to reducing agricultural systems' environmental footprint by supporting sustainable production and regulating climate change. However, the indirect and cascading effects of microbial inoculants through the reshaping of soil microbiome are largely overlooked. By discussing the underlying mechanisms of plant- and soil-based microbial inoculants, we suggest that a key challenge in microbial inoculation is to understand their legacy on indigenous microbial communities and the corresponding impacts on agroecosystem functions and services relevant to climate change. We explain how these legacy effects on the soil microbiome can be understood by building on the mechanisms driving microbial invasions and placing inoculation into the context of ecological succession and community assembly. Overall, we advocate that generalizing field trials to systematically test inoculants' effectiveness and developing knowledge anchored in the scientific field of biological/microbial invasion are two essential requirements for applying microbial inoculants in agricultural ecosystems to tackle climate change challenges.

Population Differences and Host Species Predict Variation in the Diversity of Host-Associated Microbes in Hydra

Most animals co-exist with diverse host-associated microbial organisms that often form complex communities varying between individuals, habitats, species and higher taxonomic levels. Factors driving variation in the diversity of host-associated microbes are complex and still poorly understood. Here, we describe the bacterial composition of field-collected Hydra, a freshwater cnidarian that forms stable associations with microbial species in the laboratory and displays complex interactions with components of the microbiota. We sampled Hydra polyps from 21 Central European water bodies and identified bacterial taxa through 16S rRNA sequencing. We asked whether diversity and taxonomic composition of host-associated bacteria depends on sampling location, habitat type, host species or host reproductive mode (sexual vs. asexual). Bacterial diversity was most strongly explained by sampling location, suggesting that the source environment plays an important role in the assembly of bacterial communities associated with Hydra polyps. We also found significant differences between host species in their bacterial composition that partly mirrored variations observed in lab strains. Furthermore, we detected a minor effect of host reproductive mode on bacterial diversity. Overall, our results suggest that extrinsic (habitat identity) factors predict the diversity of host-associated bacterial communities more strongly than intrinsic (species identity) factors, however, only a combination of both factors determines microbiota composition in Hydra.

Limited Pairwise Synergistic and Antagonistic Interactions Impart Stability to Microbial Communities

One of the central goals of ecology is to explain and predict coexistence of species. In this context, microbial communities provide a model system where community structure can be studied in environmental niches and in laboratory conditions. A community of microbial population is stabilized by interactions between participating species. However, the nature of these stabilizing interactions has remained largely unknown. Theory and experiments have suggested that communities are stabilized by antagonistic interactions between member species, and destabilized by synergistic interactions. However, experiments have also revealed that a large fraction of all the interactions between species in a community are synergistic in nature. To understand the relative significance of the two types of interactions (synergistic vs. antagonistic) between species, we perform simulations of microbial communities with a small number of participating species using two frameworks—a replicator equation and a Lotka-Volterra framework. Our results demonstrate that synergistic interactions between species play a critical role in maintaining diversity in cultures. These interactions are critical for the ability of the communities to survive perturbations and maintain diversity. We follow up the simulations with quantification of the extent to which synergistic and antagonistic interactions are present in a bacterial community present in a soil sample. Overall, our results show that community stability is largely achieved with the help of synergistic interactions between participating species. However, we perform experiments to demonstrate that antagonistic interactions, in specific circumstances, can also contribute toward community stability.

Putting microbial interactions back into community contexts

Microbial interactions are key aspects of the biology of microbiomes. Recently, there has been a shift in the field towards studying interactions in more representative contexts, whether using multispecies model microbial communities or by looking at interactions in situ. Across diverse microbial systems, these studies have begun to identify common interaction mechanisms. These mechanisms include interactions related to toxic molecules, nutrient competition and cross-feeding, access to metals, signaling pathways, pH changes, and interactions within biofilms. Leveraging technological innovations, many of these studies have used an interdisciplinary approach combining genetic, metabolomic, imaging, and/or microfluidic techniques to gain insight into mechanisms of microbial interactions and into the impact of these interactions on microbiomes.

Functional attractors in microbial community assembly

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.