Emergent coexistence in multispecies microbial communities

Environment-Organism Feedbacks Drive Changes in Ecological Interactions

Ecological interactions are foundational to our understanding of community composition and function. While interactions are known to change depending on the environmental context, it has generally been assumed that external environmental factors are responsible for driving these dependencies. Here, we derive a theoretical framework which instead focuses on how intrinsic environmental changes caused by the organisms themselves alter interaction values. Our central concept is the 'instantaneous interaction', which captures the feedback between the current environmental state and organismal growth, generating spatiotemporal context-dependencies as organisms modify their environment over time and/or space. We use small microbial communities to illustrate how this framework can predict time-dependencies in a toxin degradation system, and relate time- and spatial-dependencies in crossfeeding communities. By re-centring the relationship between organisms and their environment, our framework predicts the variations in interactions wherever intrinsic, organism-driven environmental change dominates over external drivers.

Temporal Changes in the Role of Species Sorting and Evolution Determine Community Dynamics

Evolutionary change within community members and shifts in species composition via species sorting contribute to community and trait dynamics. However, we do not understand when and how both processes contribute to community dynamics. Here, we estimated the contributions of species sorting and evolution over time (60 days) in bacterial communities of 24 species under selection by a ciliate predator. We found that species sorting contributed to increased community carrying capacity, while evolution contributed to decreased anti-predator defences. The relative roles of both processes changed over time, and our analysis indicates that if initial trait variation was in the direction of selection, species sorting prevailed, otherwise evolution drove phenotypic change. Furthermore, community composition, population densities and genomic evolution were affected by phenotypic match-mismatch combinations of predator and prey evolutionary history. Overall, our findings help to integrate when and how ecological and evolutionary processes structure communities.

Effects of snake fungal disease (ophidiomycosis) on the skin microbiome across two major experimental scales

Emerging infectious diseases are increasingly recognized as a significant threat to global biodiversity conservation. Elucidating the relationship between pathogens and the host microbiome could lead to novel approaches for mitigating disease impacts. Pathogens can alter the host microbiome by inducing dysbiosis, an ecological state characterized by a reduction in bacterial alpha diversity, an increase in pathobionts, or a shift in beta diversity. We used the snake fungal disease (SFD; ophidiomycosis), system to examine how an emerging pathogen may induce dysbiosis across two experimental scales. We used quantitative polymerase chain reaction, bacterial amplicon sequencing, and a deep learning neural network to characterize the skin microbiome of free-ranging snakes across a broad phylogenetic and spatial extent. Habitat suitability models were used to find variables associated with fungal presence on the landscape. We also conducted a laboratory study of northern watersnakes to examine temporal changes in the skin microbiome following inoculation with Ophidiomyces ophidiicola. Patterns characteristic of dysbiosis were found at both scales, as were nonlinear changes in alpha and alterations in beta diversity, although structural-level and dispersion changes differed between field and laboratory contexts. The neural network was far more accurate (99.8% positive predictive value [PPV]) in predicting disease state than other analytic techniques (36.4% PPV). The genus Pseudomonas was characteristic of disease-negative microbiomes, whereas, positive snakes were characterized by the pathobionts Chryseobacterium, Paracoccus, and Sphingobacterium. Geographic regions suitable for O. ophidiicola had high pathogen loads (>0.66 maximum sensitivity + specificity). We found that pathogen-induced dysbiosis of the microbiome followed predictable trends, that disease state could be classified with neural network analyses, and that habitat suitability models predicted habitat for the SFD pathogen.

Cell shape affects bacterial colony growth under physical confinement

Evidence from homogeneous liquid or flat-plate cultures indicates that biochemical cues are the primary modes of bacterial interaction with their microenvironment. However, these systems fail to capture the effect of physical confinement on bacteria in their natural habitats. Bacterial niches like the pores of soil, mucus, and infected tissues are disordered microenvironments with material properties defined by their internal pore sizes and shear moduli. Here, we use three-dimensional matrices that match the viscoelastic properties of gut mucus to test how altering the physical properties of their microenvironment influences the growth of bacteria under confinement. We find that low aspect ratio (spherical) bacteria form compact, spherical colonies under confinement while high aspect ratio (rod-shaped) bacteria push their progenies further outwards to create elongated colonies with a higher surface area, enabling increased access to nutrients. As a result, the population growth of high aspect ratio bacteria is, under the tested conditions, more robust to increased physical confinement compared to that of low aspect ratio bacteria. Thus, our experimental evidence supports that environmental physical constraints can play a selective role in bacterial growth based on cell shape.

A cross-systems primer for synthetic microbial communities

The design and use of synthetic communities, or SynComs, is one of the most promising strategies for disentangling the complex interactions within microbial communities, and between these communities and their hosts. Compared to natural communities, these simplified consortia provide the opportunity to study ecological interactions at tractable scales, as well as facilitating reproducibility and fostering interdisciplinary science. However, the effective implementation of the SynCom approach requires several important considerations regarding the development and application of these model systems. There are also emerging ethical considerations when both designing and deploying SynComs in clinical, agricultural or environmental settings. Here we outline current best practices in developing, implementing and evaluating SynComs across different systems, including a focus on important ethical considerations for SynCom research.

Arbuscular mycorrhizal fungi equalize differences in plant fitness and facilitate plant species coexistence through niche differentiation

Mycorrhizal fungi are essential to the establishment of the vast majority of plant species but are often conceptualized with contradictory roles in plant community assembly. On the one hand, host-specific mycorrhizal fungi may allow a plant to be competitively dominant by enhancing growth. On the other hand, host-specific mycorrhizal fungi with different functional capabilities may increase nutrient niche partitioning, allowing plant species to coexist. Here, to resolve the balance of these two contradictory forces, we used a controlled greenhouse study to manipulate the presence of two main types of mycorrhizal fungus, ectomycorrhizal fungi and arbuscular mycorrhizal fungi, and used a range of conspecific and heterospecific competitor densities to investigate the role of mycorrhizal fungi in plant competition and coexistence. We find that the presence of arbuscular mycorrhizal fungi equalizes fitness differences between plants and stabilizes competition to create conditions for host species coexistence. Our results show how below-ground mutualisms can shift outcomes of plant competition and that a holistic view of plant communities that incorporates their mycorrhizal partners is important in predicting plant community dynamics.

Microalgae Enhances the Adaptability of Epiphytic Bacteria to Sulfamethoxazole Stress and Proliferation of Antibiotic Resistance Genes Mediated by Integron

The transmission of ARGs in the microalgae-associated epiphytic bacteria remains unclear under antibiotic exposure, apart from altering the microbial community structure. In this study, Chlorella vulgaris cocultured with bacteria screened from surface water was examined to explore the spread of ARGs in the presence of sulfamethoxazole (SMX). The extracellular polymers released by Chlorella vulgaris could reduce antibiotic-induced collateral damage to bacteria, thus increasing the diversity of the microalgae-associated epiphytic bacteria. The abundances of sul1 and intI1 in the phycosphere at 1 mg/L SMX dose increased by 290 and 28 times, respectively. Metagenomic sequencing further confirmed that SMX bioaccumulation stimulated the horizontal transfer of sul1 mediated by intI1 in the microalgae-associated epiphytic bacteria, while reactive oxygen species (ROS)-mediated oxidative stress induced the SOS response and thus enhanced the transformation of sul1 in the J group. This is the first study to verify that microalgae protect bacteria from antibiotic damage and hinder the spread of ARGs mediated by SOS response, while the transfer of ARGs mediated by integron is promoted due to the bioaccumulation of SMX in the phycosphere. The results contribute to present comprehensive understanding of the risk of ARG proliferation by the presence of emerging contaminants residues in river.

Toxin-Antitoxin Systems Reflect Community Interactions Through Horizontal Gene Transfer

Bacterial evolution through horizontal gene transfer (HGT) reflects their community interactions. In this way, HGT networks do well at mapping community interactions, but offer little toward controlling them-an important step in the translation of synthetic strains into natural contexts. Toxin-antitoxin (TA) systems serve as ubiquitous and diverse agents of selection; however, their utility is limited by their erratic distribution in hosts. Here we examine the heterogeneous distribution of TAs as a consequence of their mobility. By systematically mapping TA systems across a 10,000 plasmid network, we find HGT communities have unique and predictable TA signatures. We propose these TA signatures arise from plasmid competition and have further potential to signal the degree to which plasmids, hosts, and phage interact. To emphasize these relationships, we construct an HGT network based solely on TA similarity, framing specific selection markers in the broader context of bacterial communities. This work both clarifies the evolution of TA systems and unlocks a common framework for manipulating community interactions through TA compatibility.

Predicting the first steps of evolution in randomly assembled communities

Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.

Exploiting microbial competition to promote plant health

The host-associated microbiota can promote colonization resistance against pathogens via a mechanism termed 'nutrient blocking', as highlighted in a recent article by Spragge et al. This implies that greater metabolic overlap between commensal taxa and pathogens leads to disease suppression. Here, we discuss future avenues for how this principle can be exploited in the rhizosphere microbiota to promote plant health.

Modeling tumors as complex ecosystems

Many cancers resist therapeutic intervention. This is fundamentally related to intratumor heterogeneity: multiple cell populations, each with different phenotypic signatures, coexist within a tumor and its metastases. Like species in an ecosystem, cancer populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity or predict its consequences. Here, we propose that the generalized Lotka-Volterra model (GLV), a standard tool to describe species-rich ecological communities, provides a suitable framework to model the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties provide a new understanding of the disease. We discuss potential extensions of the model and their application to phenotypic plasticity, cancer-immune interactions, and metastatic growth. Our work outlines a set of questions and a road map for further research in cancer ecology.

Characterizing a stable five-species microbial community for use in experimental evolution and ecology

Model microbial communities are regularly used to test ecological and evolutionary theory as they are easy to manipulate and have fast generation times, allowing for large-scale, high-throughput experiments. A key assumption for most model microbial communities is that they stably coexist, but this is rarely tested experimentally. Here we report the (dis)assembly of a five-species microbial community from a metacommunity of soil microbes that can be used for future experiments. Using reciprocal invasion-from-rare experiments we show that all species can coexist and we demonstrate that the community is stable for a long time (~600 generations). Crucially for future work, we show that each species can be identified by their plate morphologies, even after >1 year in co-culture. We characterise pairwise species interactions and produce high-quality reference genomes for each species. This stable five-species community can be used to test key questions in microbial ecology and evolution.

Microbial Dormancy Supports Multi-Species Coexistence Under Resource Fluctuations

The ability for microbes to enter dormant states is adaptive under resource fluctuations and has been linked to the maintenance of diversity. Nevertheless, the mechanism by which microbial dormancy gives rise to the density-dependent feedbacks required for stable coexistence under resource fluctuations is not well understood. Via analysis of consumer-resource models, we show that the stable coexistence of dormancy and non-dormancy strategists is a consequence of the former benefiting more from resource fluctuations while simultaneously reducing overall resource variability, which sets up the requisite negative frequency dependence. Moreover, we find that dormants can coexist alongside gleaner and opportunist strategies in a competitive-exclusion-defying case of three species coexistence on a single resource. This multi-species coexistence is typically characterised by non-simple assembly rules that cannot be predicted from pairwise competition outcomes. The diversity maintained via this three-way trade-off represents a novel phenomenon that is ripe for further theoretical and empirical inquiry.

Cross-protection and cross-feeding between Enterobacter and Comamonas promoting their coexistence and cadmium tolerance in Oryza sativa L

Metabolic cross-feeding is a pervasive interaction between bacteria to acquire novel phenotypes. However, our current understanding of the survival mechanism for cross-feeding in cocultured bacterial biofilms under heavy-metal conditions remains limited. Herein, we found that Comamonas sp. A23 produces L-phenylalanine to activate the L-phenylalanine degradation pathway in Enterobacter sp. A11, enhancing biofilm formation and cadmium [Cd(II)] immobilization in A11. The genes responsible for L-phenylalanine-degradation (paaK) and cell attachment and aggregation (csgAD) are essential for biofilm formation and Cd(II) immobilization in A11 induced by L-phenylalanine. The augmentation of A11 biofilms, in turn, protects A23 under Cd(II) and H2O2 stresses. The plant-based experiments demonstrate that the induction of two rice Cd(II) transporters, OsCOPT4 and OsBCP1, by A11 and A23 enhances rice resistance against Cd(II) and H2O2 stresses. Overall, our findings unveil the mutual dependence between bacteria and rice on L-phenylalanine cross-feeding for survival under abiotic stress.

Insight into farming native microbiome by bioinoculant in soil-plant system

Applying beneficial microorganisms (BM) as bioinoculants presents a promising soil-amendment strategy while impacting the native microbiome, which jointly alters soil-plant performance. Leveraging the untapped potential of native microbiomes alongside bioinoculants may enable farmers to sustainably regulate soil-plant systems via natural bioresources. This review synthesizes literature on native microbiome responses to BMs and their interactive effects on soil and plant performance. We highlight that native microbiomes harbor both microbial "helpers" that can improve soil fertility and plant productivity, as well as "inhibitors" that hinder these benefits. To harness the full potential of resident microbiome, it is crucial to elucidate their intricate synergistic and antagonistic interplays with introduced BMs and clarify the conditions that facilitate durable BM-microbiome synergies. Hence, we indicate current challenges in predicting these complex microbial interactions and propose corresponding strategies for microbiome breeding via BM bioinoculant. Overall, fully realizing the potential of BMs requires clarifying their interactions with native soil microbiomes and judiciously engineering microbiome to harness helpful microbes already present within agroecosystems.

Connecting microbial community assembly and function

Microbial ecology is moving away from purely descriptive analyses to experiments that can determine the underlying mechanisms driving changes in community assembly and function. More species-rich microbial communities generally have higher functional capabilities depending on if there is positive selection of certain species or complementarity among different species. When building synthetic communities or laboratory enrichment cultures, there are specific choices that can increase the number of species able to coexist. Higher resource complexity or the addition of physical niches are two of the many factors leading to greater biodiversity and associated increases in functional capabilities. We can use principles from community ecology and knowledge of microbial physiology to generate improved microbiomes for use in medicine, agriculture, or environmental management.

Substrate complexity buffers negative interactions in a synthetic community of leaf litter degraders

Leaf litter microbes collectively degrade plant polysaccharides, influencing land-atmosphere carbon exchange. An open question is how substrate complexity-defined as the structure of the saccharide and the amount of external processing by extracellular enzymes-influences species interactions. We tested the hypothesis that monosaccharides (i.e. xylose) promote negative interactions through resource competition, and polysaccharides (i.e. xylan) promote neutral or positive interactions through resource partitioning or synergism among extracellular enzymes. We assembled a three-species community of leaf litter-degrading bacteria isolated from a grassland site in Southern California. In the polysaccharide xylan, pairs of species stably coexisted and grew equally in coculture and in monoculture. Conversely, in the monosaccharide xylose, competitive exclusion and negative interactions prevailed. These pairwise dynamics remained consistent in a three-species community: all three species coexisted in xylan, while only two species coexisted in xylose, with one species capable of using peptone. A mathematical model showed that in xylose these dynamics could be explained by resource competition. Instead, the model could not predict the coexistence patterns in xylan, suggesting other interactions exist during biopolymer degradation. Overall, our study shows that substrate complexity influences species interactions and patterns of coexistence in a synthetic microbial community of leaf litter degraders.

Exploring spatial segregation induced by competition avoidance as driving mechanism for emergent coexistence in microbial communities

This study investigates the role of spatial segregation, prompted by competition avoidance, as a key mechanism for emergent coexistence within microbial communities. Recognizing these communities as complex adaptive systems, we challenge the sufficiency of mean-field pairwise interaction models, and we consider the impact of spatial dynamics. We developed an individual-based spatial simulation depicting bacterial movement through a pattern of random walks influenced by competition avoidance, leading to the formation of spatially segregated clusters. This model was integrated with a Lotka-Volterra metapopulation framework focused on competitive interactions. Our findings reveal that spatial segregation combined with low diffusion rates and high compositional heterogeneity among patches can lead to emergent coexistence in microbial communities. This reveals a novel mechanism underpinning the formation of stable, coexisting microbe clusters, which is nonetheless incapable of promoting coexistence in the case of isolated pairs of species. This study underscores the importance of considering spatial factors in understanding the dynamics of microbial ecosystems.

Metabolomics and Microbial Metabolism: Toward a Systematic Understanding

Over the past decades, our understanding of microbial metabolism has increased dramatically. Metabolomics, a family of techniques that are used to measure the quantities of small molecules in biological samples, has been central to these efforts. Advances in analytical chemistry have made it possible to measure the relative and absolute concentrations of more and more compounds with increasing levels of certainty. In this review, we highlight how metabolomics has contributed to understanding microbial metabolism and in what ways it can still be deployed to expand our systematic understanding of metabolism. To that end, we explain how metabolomics was used to (a) characterize network topologies of metabolism and its regulation networks, (b) elucidate the control of metabolic function, and (c) understand the molecular basis of higher-order phenomena. We also discuss areas of inquiry where technological advances should continue to increase the impact of metabolomics, as well as areas where our understanding is bottlenecked by other factors such as the availability of statistical and modeling frameworks that can extract biological meaning from metabolomics data.

Gradient boosted regression as a tool to reveal key drivers of temporal dynamics in a synthetic yeast community

Microbial communities are vital to our lives, yet their ecological functioning and dynamics remain poorly understood. This understanding is crucial for assessing threats to these systems and leveraging their biotechnological applications. Given that temporal dynamics are linked to community functioning, this study investigated the drivers of community succession in the wine yeast community. We experimentally generated population dynamics data and used it to create an interpretable model with a gradient boosted regression tree approach. The model was trained on temporal data of viable species populations in various combinations, including pairs, triplets, and quadruplets, and was evaluated for predictive accuracy and input feature importance. Key findings revealed that the inoculation dosage of non-Saccharomyces species significantly influences their performance in mixed cultures, while Saccharomyces cerevisiae consistently dominates regardless of initial abundance. Additionally, we observed multispecies interactions where the dynamics of Wickerhamomyces anomalus were influenced by Torulaspora delbrueckii in pairwise cultures, but this interaction was altered by the inclusion of S. cerevisiae. This study provides insights into yeast community succession and offers valuable machine learning-based analysis techniques applicable to other microbial communities, opening new avenues for harnessing microbial communities.

Predicting the First Steps of Evolution in Randomly Assembled Communities

Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.

Intestinal colonization resistance in the context of environmental, host, and microbial determinants

Microbial communities that colonize the human gastrointestinal (GI) tract defend against pathogens through a mechanism known as colonization resistance (CR). Advances in technologies such as next-generation sequencing, gnotobiotic mouse models, and bacterial cultivation have enhanced our understanding of the underlying mechanisms and the intricate microbial interactions involved in CR. Rather than being attributed to specific microbial clades, CR is now understood to arise from a dynamic interplay between microbes and the host and is shaped by metabolic, immune, and environmental factors. This evolving perspective underscores the significance of contextual factors, encompassing microbiome composition and host conditions, in determining CR. This review highlights recent research that has shifted its focus toward elucidating how these factors interact to either promote or impede enteric infections. It further discusses future research directions to unravel the complex relationship between host, microbiota, and environmental determinants in safeguarding against GI infections to promote human health.

Distribution characteristics and microbial synergistic degradation potential of polyethylene and polypropylene in freshwater estuarine sediments

The microbial degradation of polyethylene (PE) and polypropylene (PP) resins in rivers and lakes has emerged as a crucial issue in the management of microplastics. This study revealed that as the flow rate decreased longitudinally, ammonia nitrogen (NH4+-N), heavy fraction of organic carbon (HFOC), and small-size microplastics (< 1 mm) gradually accumulated in the deep and downstream estuarine sediments. Based on their surface morphology and carbonyl index, these sediments were identified as the potential hot zone for PE/PP degradation. Within the identified hot zone, concentrations of PE/PP-degrading genes, enzymes, and bacteria were significantly elevated compared to other zones, exhibiting strong intercorrelations. Analysis of niche differences revealed that the accumulation of NH4+-N and HFOC in the hot zone facilitated the synergistic coexistence of key bacteria responsible for PE/PP degradation within biofilms. The findings of this study offer a novel insight and comprehensive understanding of the distribution characteristics and synergistic degradation potential of PE/PP in natural freshwater environments.

When can higher-order interactions produce stable coexistence?

Most ecological models are based on the assumption that species interact in pairs. Diverse communities, however, can have higher-order interactions, in which two or more species jointly impact the growth of a third species. A pitfall of the common pairwise approach is that it misses the higher-order interactions potentially responsible for maintaining natural diversity. Here, we explore the stability properties of systems where higher-order interactions guarantee that a specified set of abundances is a feasible equilibrium of the dynamics. Even these higher-order interactions which lead to equilibria do not necessarily produce stable coexistence. Instead, these systems are more likely to be stable when the pairwise interactions are weak or facilitative. Correlations between the pairwise and higher-order interactions, however, do permit robust coexistence even in diverse systems. Our work not only reveals the challenges in generating stable coexistence through higher-order interactions but also uncovers interaction patterns that can enable diversity.

Soil microbial community fragmentation reveals indirect effects of fungicide exposure mediated by biotic interactions between microorganisms

Fungicides are used worldwide to improve crop yields, but they can affect non-target soil microorganisms which are essential for ecosystem functioning. Microorganisms form complex communities characterized by a myriad of interspecies interactions, yet it remains unclear to what extent non-target microorganisms are indirectly affected by fungicides through biotic interactions with sensitive taxa. To quantify such indirect effects, we fragmented a soil microbial community by filtration to alter biotic interactions and compared the effect of the fungicide hymexazol between fractions in soil microcosms. We postulated that OTUs which are indirectly affected would exhibit a different response to the fungicide across the fragmented communities. We found that hymexazol primarily affected bacterial and fungal communities through indirect effects, which were responsible for more than 75% of the shifts in relative abundance of the dominant microbial OTUs after exposure to an agronomic dose of hymexazol. However, these indirect effects decreased for the bacterial community when hymexazol doses increased. Our results also suggest that N-cycling processes such as ammonia oxidation can be impacted indirectly by fungicide application. This work sheds light on the indirect impact of fungicide exposure on soil microorganisms through biotic interactions, which underscores the need for higher-tier risk assessment. ENVIRONMENTAL IMPLICATION: In this study, we used a novel approach based on the fragmentation of the soil microbial community to determine to which extent fungicide application could indirectly affect fungi and bacteria through biotic interactions. To assess off-target effects of fungicide on soil microorganisms, we selected hymexazol, which is used worldwide to control a variety of fungal plant pathogens, and exposed arable soil to the recommended field rate, as well as to higher rates. Our findings show that at least 75% of hymexazol-impacted microbial OTUs were indirectly affected, therefore emphasizing the importance of tiered risk assessment.

Oral-gut microbial transmission promotes diabetic coronary heart disease

BACKGROUND

Diabetes is a predominant driver of coronary artery disease worldwide. This study aims to unravel the distinct characteristics of oral and gut microbiota in diabetic coronary heart disease (DCHD). Simultaneously, we aim to establish a causal link between the diabetes-driven oral-gut microbiota axis and increased susceptibility to diabetic myocardial ischemia-reperfusion injury (MIRI).

METHODS

We comprehensively investigated the microbial landscape in the oral and gut microbiota in DCHD using a discovery cohort (n = 183) and a validation chohort (n = 68). Systematically obtained oral (tongue-coating) and fecal specimens were subjected to metagenomic sequencing and qPCR analysis, respectively, to holistically characterize the microbial consortia. Next, we induced diabetic MIRI by administering streptozotocin to C57BL/6 mice and subsequently investigated the potential mechanisms of the oral-gut microbiota axis through antibiotic pre-treatment followed by gavage with specific bacterial strains (Fusobacterium nucleatum or fecal microbiota from DCHD patients) to C57BL/6 mice.

RESULTS

Specific microbial signatures such as oral Fusobacterium nucleatum and gut Lactobacillus, Eubacterium, and Roseburia faecis, were identified as potential microbial biomarkers in DCHD. We further validated that oral Fusobacterium nucleatum and gut Lactobacillus are increased in DCHD patients, with a positive correlation between the two. Experimental evidence revealed that in hyperglycemic mice, augmented Fusobacterium nucleatum levels in the oral cavity were accompanied by an imbalance in the oral-gut axis, characterized by an increased coexistence of Fusobacterium nucleatum and Lactobacillus, along with elevated cardiac miRNA-21 and a greater extent of myocardial damage indicated by TTC, HE, TUNEL staining, all of which contributed to exacerbated MIRI.

CONCLUSION

Our findings not only uncover dysregulation of the oral-gut microbiota axis in diabetes patients but also highlight the pivotal intermediary role of the increased abundance of oral F. nucleatum and gut Lactobacillus in exacerbating MIRI. Targeting the oral-gut microbiota axis emerges as a potent strategy for preventing and treating DCHD. Oral-gut microbial transmission constitutes an intermediate mechanism by which diabetes influences myocardial injury, offering new insights into preventing acute events in diabetic patients with coronary heart disease.

Assessing microbiome population dynamics using wild-type isogenic standardized hybrid (WISH)-tags

Microbiomes feature recurrent compositional structures under given environmental conditions. However, these patterns may conceal diverse underlying population dynamics that require intrastrain resolution. Here we developed a genomic tagging system, termed wild-type isogenic standardized hybrid (WISH)-tags, that can be combined with quantitative polymerase chain reaction and next-generation sequencing for microbial strain enumeration. We experimentally validated the performance of 62 tags and showed that they can be differentiated with high precision. WISH-tags were introduced into model and non-model bacterial members of the mouse and plant microbiota. Intrastrain priority effects were tested using one species of isogenic barcoded bacteria in the murine gut and the Arabidopsis phyllosphere, both with and without microbiota context. We observed colonization resistance against late-arriving strains of Salmonella Typhimurium in the mouse gut, whereas the phyllosphere accommodated Sphingomonas latecomers in a manner proportional to their presence at the late inoculation timepoint. This demonstrates that WISH-tags are a resource for deciphering population dynamics underlying microbiome assembly across biological systems.

More than the sum of its parts: uncovering emerging effects of microbial interactions in complex communities

Microbial communities are not only shaped by the diversity of microorganisms and their individual metabolic potential, but also by the vast amount of intra- and interspecies interactions that can occur pairwise interactions among microorganisms, we suggest that more attention should be drawn towards the effects on the entire microbiome that emerge from individual interactions between community members. The production of certain metabolites that can be tied to a specific microbe-microbe interaction might subsequently influence the physicochemical parameters of the habitat, stimulate a change in the trophic network of the community or create new micro-habitats through the formation of biofilms, similar to the production of antimicrobial substances which might negatively affect only one microorganism but cause a ripple effect on the abundance of other community members. Here, we argue that combining established as well as innovative laboratory and computational methods is needed to predict novel interactions and assess their secondary effects. Such efforts will enable future microbiome studies to expand our knowledge on the dynamics of complex microbial communities.

Host genotype-specific rhizosphere fungus enhances drought resistance in wheat

BACKGROUND

The severity and frequency of drought are expected to increase substantially in the coming century and dramatically reduce crop yields. Manipulation of rhizosphere microbiomes is an emerging strategy for mitigating drought stress in agroecosystems. However, little is known about the mechanisms underlying how drought-resistant plant recruitment of specific rhizosphere fungi enhances drought adaptation of drought-sensitive wheats. Here, we investigated microbial community assembly features and functional profiles of rhizosphere microbiomes related to drought-resistant and drought-sensitive wheats by amplicon and shotgun metagenome sequencing techniques. We then established evident linkages between root morphology traits and putative keystone taxa based on microbial inoculation experiments. Furthermore, root RNA sequencing and RT-qPCR were employed to explore the mechanisms how rhizosphere microbes modify plant response traits to drought stresses.

RESULTS

Our results indicated that host plant signature, plant niche compartment, and planting site jointly contribute to the variation of soil microbiome assembly and functional adaptation, with a relatively greater effect of host plant signature observed for the rhizosphere fungi community. Importantly, drought-resistant wheat (Yunhan 618) possessed more diverse bacterial and fungal taxa than that of the drought-sensitive wheat (Chinese Spring), particularly for specific fungal species. In terms of microbial interkingdom association networks, the drought-resistant variety possessed more complex microbial networks. Metagenomics analyses further suggested that the enriched rhizosphere microbiomes belonging to the drought-resistant cultivar had a higher investment in energy metabolism, particularly in carbon cycling, that shaped their distinctive drought tolerance via the mediation of drought-induced feedback functional pathways. Furthermore, we observed that host plant signature drives the differentiation in the ecological role of the cultivable fungal species Mortierella alpine (M. alpina) and Epicoccum nigrum (E. nigrum). The successful colonization of M. alpina on the root surface enhanced the resistance of wheats in response to drought stresses via activation of drought-responsive genes (e.g., CIPK9 and PP2C30). Notably, we found that lateral roots and root hairs were significantly suppressed by co-colonization of a drought-enriched fungus (M. alpina) and a drought-depleted fungus (E. nigrum).

CONCLUSIONS

Collectively, our findings revealed host genotypes profoundly influence rhizosphere microbiome assembly and functional adaptation, as well as it provides evidence that drought-resistant plant recruitment of specific rhizosphere fungi enhances drought tolerance of drought-sensitive wheats. These findings significantly underpin our understanding of the complex feedbacks between plants and microbes during drought, and lay a foundation for steering "beneficial keystone biome" to develop more resilient and productive crops under climate change. Video Abstract.

Mapping combinatorial expression perturbations to growth in Escherichia coli

The connection between growth and gene expression has often been considered in a single gene. Repurposing a drug-drug interaction model, the multidimensional effects of several simultaneous gene expression perturbations on growth have been examined in the model bacteria Escherichia coli.

On the limits to invasion prediction using coexistence outcomes

The dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while individual survival probability in coexistence dynamics can be fairly closely translated into invader colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.

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.

Climate warming enhances microbial network complexity by increasing bacterial diversity and fungal interaction strength in litter decomposition

Microbial communities are important drivers of plant litter decomposition; however, the mechanisms of microbial co-occurrence networks and their network interaction dynamics in response to climate warming in wetlands remain unclear. Here, we conducted a 1.5-year warming experiment on the bacterial and fungal communities involved in litter decomposition in a typical wetland. The results showed that warming accelerated the decomposition of litter and had a greater effect on the diversity of bacteria than on that of fungi. Dominant bacterial communities, such as Bacteroidia, Alphaproteobacteria, and Actinobacteria, and dominant fungal communities, such as Leotiomycetes and Sordariomycetes, showed significant positive correlations with lignin and cellulose. Co-occurrence networks revealed that the average path length and betweenness centrality under warming conditions increased in the bacterial community but decreased in the fungal community. Both bacterial and fungal networks in the 2.0 °C warming treatment had the highest ratio of positive links (58.53 % and 98.14 %), indicating that moderate warming can promote the positive correlations and symbiotic relationships observed in the microbial community. This also suggests that small-world characteristics and weak-link advantages accelerate diffusion, and scale-free features facilitate propagation in microbial communities in response to climate warming. Logistic growth and Lotka-Volterra competition models revealed that climate warming enhances microbial network complexity mainly by increasing bacterial diversity and fungal interaction strength in litter decomposition. However, the symbiotic relationship decreased slightly under 4.0 °C warming, indicating that climate warming is a random attack rather than a targeted attack, and the microbial network has strong resistance to random attack, as shown by the highly robust dynamic performance of the microbial network in litter decomposition. Overall, the microbial community in litter decomposition responded to climate warming and shifted its network interactions, leading to further changes in emergent network topology and dynamics, thus accelerating litter decomposition in wetlands.

Robustness versus productivity during evolutionary community assembly: short-term synergies and long-term trade-offs

The realization that evolutionary feedbacks need to be considered to fully grasp ecological dynamics has sparked interest in the effect of evolution on community properties like coexistence and productivity. However, little is known about the evolution of community robustness and productivity along diversification processes in species-rich systems. We leverage the recent structural approach to coexistence together with adaptive dynamics to study such properties and their relationships in a general trait-based model of competition on a niche axis. We show that the effects of coevolution on coexistence are two-fold and contrasting depending on the time scale considered. In the short term, evolution of niche differentiation strengthens coexistence, while long-term diversification leads to niche packing and decreased robustness. Moreover, we find that coevolved communities tend to be on average more robust and more productive than non-evolutionary assemblages. We illustrate how our theoretical predictions echo in observed empirical patterns and the implications of our results for empiricists and applied ecologists. We suggest that some of our results such as the improved robustness of Evolutionarily Stable Communities could be tested experimentally in suitable model systems.

Dietary carotenoid supplementation has long-term and community-wide effects on the amphibian skin microbiome

The amphibian skin microbiome plays a crucial role in host immunity and pathogen defence, yet we know little about the environmental drivers of skin microbial variation across host individuals. Inter-individual variation in the availability of micro-nutrients such as dietary carotenoids, which are involved in amphibian immunity, may be one factor that influences skin microbial assembly across different life history stages. We compared the effect of four carotenoid supplementation regimes during different life stages on the adult skin microbiome using a captive population of the critically endangered southern corroboree frog, Pseudophryne corroboree. We applied 16S rRNA sequencing paired with joint-species distribution models to examine the effect of supplementation on taxon abundances. We found that carotenoid supplementation had subtle yet taxonomically widespread effects on the skin microbiome, even 4.5 years post supplementation. Supplementation during any life-history stage tended to have a positive effect on the number of bacterial taxa detected, although explanatory power was low. Some genera were sensitive to supplementation pre-metamorphosis, but most demonstrated either additive or dominant effects, whereby supplementation during one life history stage had intermediate or similar effects, respectively, to supplementation across life. Carotenoid supplementation increased abundances of taxa belonging to lactic acid bacteria, including Lactococcus and Enterococcus, a group of bacteria that have previously been linked to protection against the amphibian fungal pathogen Batrachochytrium dendrobatidis (Bd). While the fitness benefits of these microbial shifts require further study, these results suggest a fundamental relationship between nutrition and the amphibian skin microbiome which may be critical to amphibian health and the development of novel conservation strategies.

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.

Ecology theory disentangles microbial dichotomies

Microbes are often discussed in terms of dichotomies such as copiotrophic/oligotrophic and fast/slow-growing microbes, defined using the characterisation of microbial growth in isolated cultures. The dichotomies are usually qualitative and/or study-specific, sometimes precluding clear-cut results interpretation. We can unravel microbial dichotomies as life history strategies by combining ecology theory with Monod curves, a laboratory mathematical tool of bacterial physiology that relates the specific growth rate of a microbe with the concentration of a limiting nutrient. Fitting of Monod curves provides quantities that directly correspond to key parameters in ecological theories addressing species coexistence and diversity, such as r/K selection theory, resource competition and community structure theory and the CSR triangle of life strategies. The resulting model allows us to reconcile the copiotrophic/oligotrophic and fast/slow-growing dichotomies as different subsamples of a life history strategy triangle that also includes r/K strategists. We also used the number of known carbon sources together with community structure theory to partially explain the diversity of heterotrophic microbes observed in metagenomics experiments. In sum, we propose a theoretical framework for the study of natural microbial communities that unifies several existing proposals. Its application would require the integration of metagenomics, metametabolomics, Monod curves and carbon source data.

The Host-specific Microbiota is Required for Diet-Specific Metabolic Homeostasis

In complex mammals, the importance and host-specificity of microbial communities have been demonstrated through their positive effects on host immune fitness or performance. However, whether host metabolic physiology homeostasis depends on a specific bacterial community exclusive to the host remains unclear. Here, we show that the coevolved host-specific microbiota is required to maintain diet-specific flexible and sufficient metabolic homeostasis through a high colonization rate, modulating gut metabolites, and related targets. Using germ-free (GF) mice, we tested whether the fitness benefiting the host metabolic phenotype of microbiota was host-specific. We demonstrated that GF mice associated with exogenous microbiota (human microbiota (HM)), which exhibited different and reduced gut microbial species diversity, significantly elevated metabolic rate, and exhibited metabolic insufficiency, all characteristics of GF mice. Strikingly, the absence of the host-specific microbiome attenuated high-fat diet-specific metabolism features. Different diets caused different metabolic changes in only host-specific microbiota-associated mice, not the host-microbiota mismatched mice. While RNA sequencing revealed subtle changes in the expression of genes in the liver, GF mice and HM mice showed considerably altered expression of genes associated with metabolic physiology compared to GF mice associated with host-specific microbiota. The effect of diet outweighed microbiota in the liver transcriptome. These changes occurred in the setting of decreased luminal short-chain fatty acids (SCFAs) and the secondary bile acid (BAs) pool and downstream gut signaling targets in HM and GF mice, which affects whole-body metabolism. These data indicate that a foreign microbial community provides little metabolic benefit to the host when compared to a host-specific microbiome, due to the colonization selection pressure and microbiota-derived metabolites dysfunction. Overall, microbiome fitness effects on the host metabolic phenotype were host-specific. Understanding the impact of the host-specificity of the microbiome on metabolic homeostasis may provide important insights for building a better probiotic.

Highlights

Microbiome fitness effects on the host metabolic phenotype were host-specific in mammals.Human microbiota-associated mice exhibited lower host metabolic fitness or performance, and similar functional costs in GF mice.Different diets cause different metabolic changes only in host-specific microbiota-associated mice, not the host-microbiota mismatched mice.The defective gut microbiota in host-specific microbiota, microbial metabolites and related targets likely drive the metabolic homeostasis.

Building modern coexistence theory from the ground up: The role of community assembly

Modern coexistence theory (MCT) is one of the leading methods to understand species coexistence. It uses invasion growth rates-the average, per-capita growth rate of a rare species-to identify when and why species coexist. Despite significant advances in dissecting coexistence mechanisms when coexistence occurs, MCT relies on a 'mutual invasibility' condition designed for two-species communities but poorly defined for species-rich communities. Here, we review well-known issues with this component of MCT and propose a solution based on recent mathematical advances. We propose a clear framework for expanding MCT to species-rich communities and for understanding invasion resistance as well as coexistence, especially for communities that could not be analysed with MCT so far. Using two data-driven community models from the literature, we illustrate the utility of our framework and highlight the opportunities for bridging the fields of community assembly and species coexistence.

Metabolic similarity and the predictability of microbial community assembly

When microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically similar environments lead to predictable similarities in community composition. To that end, we measured the growth rate and by-product profile of a library of proteobacterial strains in a large number of single nutrient environments. We found that growth rates and secretion profiles were positively correlated across environments when the supplied substrate was metabolically similar. By analyzing hundreds of in-vitro communities experimentally assembled in an array of different synthetic environments, we then show that metabolically similar substrates select for taxonomically similar communities. These findings lead us to propose and then validate a comparative approach for quantitatively predicting the effects of novel substrates on the composition of complex microbial consortia.

The Architecture of Metabolic Networks Constrains the Evolution of Microbial Resource Hierarchies

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often use them sequentially according to a preference hierarchy, resulting in well-known patterns of diauxic growth. In theory, the evolutionary diversification of metabolic hierarchies could represent a mechanism supporting coexistence and biodiversity by enabling temporal segregation of niches. Despite this ecologically critical role, the extent to which substrate preference hierarchies can evolve and diversify remains largely unexplored. Here, we used genome-scale metabolic modeling to systematically explore the evolution of metabolic hierarchies across a vast space of metabolic network genotypes. We find that only a limited number of metabolic hierarchies can readily evolve, corresponding to the most commonly observed hierarchies in genome-derived models. We further show how the evolution of novel hierarchies is constrained by the architecture of central metabolism, which determines both the propensity to change ranks between pairs of substrates and the effect of specific reactions on hierarchy evolution. Our analysis sheds light on the genetic and mechanistic determinants of microbial metabolic hierarchies, opening new research avenues to understand their evolution, evolvability, and ecology.