Microbial community interactions on a chip.

Multispecies microbial communities drive most ecosystems on Earth. Chemical and biological interactions within these communities can affect the survival of individual members and the entire community. However, the prohibitively high number of possible interactions within a microbial community has made the characterization of factors that influence community development challenging. Here, we report a Microbial Community Interaction (µCI) device to advance the systematic study of chemical and biological interactions within a microbial community. The µCI creates a combinatorial landscape made up of an array of triangular wells interconnected with circular wells, which each contains either a different chemical or microbial strain, generating chemical gradients and revealing biological interactions. Bacillus cereus UW85 containing green fluorescent protein provided the "target" readout in the triangular wells, and antibiotics or microorganisms in adjacent circular wells are designated the "variables." The µCI device revealed that gentamicin and vancomycin are antagonistic to each other in inhibiting the target B. cereus UW85, displaying weaker inhibitory activity when used in combination than alone. We identified three-member communities constructed with isolates from the plant rhizosphere that increased or decreased the growth of B. cereus. The µCI device enables both strain-level and community-level insight. The scalable geometric design of the µCI device enables experiments with high combinatorial efficiency, thereby providing a simple, scalable platform for systematic interrogation of three-factor interactions that influence microorganisms in solitary or community life.

Interspecies Interaction of Bacteria Listeria monocytogenes, Yersinia pseudotuberculosis, and Marine Saprotrophs during Long-Term Culturing in Biofilms.

All bacterial strains studied retained the viability and ability to form both mono- and polycultural biofilms under conditions of long-term culturing in artificial seawater at 6°C and without addition of nutrients. Bacillus sp. and Pseudomonas japonica presumably stimulated the growth and reproduction of the pathogenic bacteria Listeria monocytogenes and Yersinia pseudotuberculosis. Preserved cell viability in a monoculture biofilm for a long period without adding a food source can indicate allolysis. At the same time, in a polycultural biofilm, the metabolites secreted by saprotrophic strains can stimulate the growth of L. monocytogenes and Y. pseudotuberculosis.

A Mathematical Model of Diel Activity and Long Time Survival in Phototrophic Mixed-Species Subaerial Biofilms.

Subaerial biofilms (SAB) are intricate microbial communities living on terrestrial surfaces, of interest in a variety of contexts including cultural heritage preservation, microbial ecology, biogeochemical cycling, and biotechnology. Here we propose a mathematical model aimed at better understanding the interplay between cyanobacteria and heterotrophic bacteria, common microbial SAB constituents, and their mutual dependence on local environmental conditions. SABs are modeled as thin mixed biofilm-liquid water layers sitting on stone. A system of ordinary differential equations regulates the dynamics of key SAB components: cyanobacteria, heterotrophs, polysaccharides and decayed biomass, as well as cellular levels of organic carbon, nitrogen and energy. These components are interconnected through a network of energetically dominant metabolic pathways, modeled with limitation terms reflecting the impact of biotic and abiotic factors. Daily cylces of temperature, humidity, and light intensity are considered as input model variables that regulate microbial activity by influencing water availability and metabolic kinetics. Relevant physico-chemical processes, including pH regulation, further contribute to a description of the SAB ecology. Numerical simulations explore the dynamics of SABs in a real-world context, revealing distinct daily activity periods shaped by water activity and light availability, as well as longer time scale survivability conditions. Results also suggest that heterotrophs could play a substantial role in decomposing non-volatile carbon compounds and regulating pH, thus influencing the overall composition and stability of the biofilm.

Microbial interactions in mixed-species biofilms on the surfaces of Baijiu brewing environments.

Environmental microorganisms commonly inhabit dense multispecies biofilms, fostering mutualistic relationships and co-evolution. However, the mechanisms underlying biofilm formation and microbial interactions within the Baijiu fermentation microecosystem remain poorly understood. Hence, the objective of this study was to investigate the composition, structure, and interactions of microorganisms residing in biofilms on environmental surfaces in Baijiu production. The results revealed a shift in the bacteria-fungi interaction network following fermentation, transitioning from a cooperative/symbiotic relationship to a competitive/antagonistic dynamic. Core microbiota within the biofilms comprised lactic acid bacteria (LAB), yeast, and filamentous fungi. From the environmental surface samples, we isolated two strains of LAB (Lactiplantibacillus pentosus EB27 and Pediococcus pentosaceus EB35) and one strain of yeast (Pichia kudriavzevii EF8), all displaying remarkable biofilm formation and fermentation potential. Co-culturing LAB and yeast demonstrated a superior capacity for dual-species biofilm formation compared to mono-species biofilms. The dual-species biofilm displayed a two-layer structure, with LAB in the lower layer and serving as the foundation for the yeast community in the upper layer. The upper layer exhibited a dense distribution of yeast, enhancing aerobic respiration. Metabolic activities in the dual-species biofilm, such as ABC transporter, oxidative phosphorylation, citric acid cycle, sulfur metabolism, glycine, serine, threonine metabolism, lysine degradation, and cysteine and methionine metabolism, showed significant alterations compared to LAB mono-species biofilms. Moreover, bacterial chemotaxis, starch, and sucrose metabolism in the dual-species biofilm exhibited distinct patterns from those observed in the yeast mono-species biofilm. This study demonstrated that a core microbiota with fermentation potential may exist in the form of a biofilm on the surface of a Baijiu brewing environment. These findings provide a novel strategy for employing synthetic stable microbiotas in the intelligent brewing of Baijiu.

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.

Cell-cell transfer of adaptation traits benefits kin and actor in a cooperative microbe.

Microbes face many physical, chemical, and biological insults from their environments. In response, cells adapt, but whether they do so cooperatively is poorly understood. Here, we use a model social bacterium, Myxococcus xanthus, to ask whether adapted traits are transferable to naïve kin. To do so we isolated cells adapted to detergent stresses and tested for trait transfer. In some cases, strain-mixing experiments increased sibling fitness by transferring adaptation traits. This cooperative behavior depended on a kin recognition system called outer membrane exchange (OME) because mutants defective in OME could not transfer adaptation traits. Strikingly, in mixed stressed populations, the transferred trait also benefited the adapted (actor) cells. This apparently occurred by alleviating a detergent-induced stress response in kin that otherwise killed actor cells. Additionally, this adaptation trait when transferred also conferred resistance against a lipoprotein toxin delivered to targeted kin. Based on these and other findings, we propose a model for stress adaptation and how OME in myxobacteria promotes cellular cooperation in response to environmental stresses.

Strategies to enhance production of metabolites in microbial co-culture systems.

Increasing evidence shows that microbial synthesis plays an important role in producing high value-added products. However, microbial monoculture generally hampers metabolites production and limits scalability due to the increased metabolic burden on the host strain. In contrast, co-culture is a more flexible approach to improve the environmental adaptability and reduce the overall metabolic burden. The well-defined co-culturing microbial consortia can tap their metabolic potential to obtain yet-to-be discovered and pre-existing metabolites. This review focuses on the use of a co-culture strategy and its underlying mechanisms to enhance the production of products. Notably, the significance of comprehending the microbial interactions, diverse communication modes, genetic information, and modular co-culture involved in co-culture systems were highlighted. Furthermore, it addresses the current challenges and outlines potential future directions for microbial co-culture. This review provides better understanding the diversity and complexity of the interesting interaction and communication to advance the development of co-culture techniques.

Deciphering the core microbes and their interactions in spontaneous Baijiu fermentation: A comprehensive review.

The spontaneous Baijiu fermentation system harbors a complex microbiome that is highly dynamic in time and space and varies depending on the Jiuqu starters and environmental factors. The intricate microbiota presents in the fermentation environment is responsible for carrying out various reactions. These reactions necessitate the interaction among the core microbes to influence the community function, ultimately shaping the distinct Baijiu styles through the process of spontaneous fermentation. Numerous studies have been conducted to enhance our understanding of the diversity, succession, and function of microbial communities with the aim of improving fermentation manipulation. However, a comprehensive and critical assessment of the core microbes and their interaction remains one of the significant challenges in the Baijiu fermentation industry. This paper focuses on the fermentation properties of core microbes. We discuss the state of the art of microbial traceability, highlighting the crucial role of environmental and starter microbiota in the Baijiu brewing microbiome. Also, we discuss the various interactions between microbes in the Baijiu production system and propose a potential conceptual framework that involves constructing predictive network models to simplify and quantify microbial interactions using co-culture models. This approach offers effective strategies for understanding the core microbes and their interactions, thus beneficial for the management of microbiota and the regulation of interactions in Baijiu fermentation processes.

GEM-based computational modeling for exploring metabolic interactions in a microbial community.

Microbial communities play fundamental roles in every complex ecosystem, such as soil, sea and the human body. The stability and diversity of the microbial community depend precisely on the composition of the microbiota. Any change in the composition of these communities affects microbial functions. An important goal of studying the interactions between species is to understand the behavior of microbes and their responses to perturbations. These interactions among species are mediated by the exchange of metabolites within microbial communities. We developed a computational model for the microbial community that has a separate compartment for exchanging metabolites. This model can predict possible metabolites that cause competition, commensalism, and mutual interactions between species within a microbial community. Our constraint-based community metabolic modeling approach provides insights to elucidate the pattern of metabolic interactions for each common metabolite between two microbes. To validate our approach, we used a toy model and a syntrophic co-culture of Desulfovibrio vulgaris and Methanococcus maripaludis, as well as another in co-culture between Geobacter sulfurreducens and Rhodoferax ferrireducens. For a more general evaluation, we applied our algorithm to the honeybee gut microbiome, composed of seven species, and the epiphyte strain Pantoea eucalypti 299R. The epiphyte strain Pe299R has been previously studied and cultured with six different phyllosphere bacteria. Our algorithm successfully predicts metabolites, which imply mutualistic, competitive, or commensal interactions. In contrast to OptCom, MRO, and MICOM algorithms, our COMMA algorithm shows that the potential for competitive interactions between an epiphytic species and Pe299R is not significant. These results are consistent with the experimental measurements of population density and reproductive success of the Pe299R strain.

Interactions between pili affect the outcome of bacterial competition driven by the type VI secretion system.

The bacterial type VI secretion system (T6SS) is a widespread, kin-discriminatory weapon capable of shaping microbial communities. Due to the system's dependency on contact, cellular interactions can lead to either competition or kin protection. Cell-to-cell contact is often accomplished via surface-exposed type IV pili (T4Ps). In Vibrio cholerae, these T4Ps facilitate specific interactions when the bacteria colonize natural chitinous surfaces. However, it has remained unclear whether and, if so, how these interactions affect the bacterium's T6SS-mediated killing. In this study, we demonstrate that pilus-mediated interactions can be harnessed by T6SS-equipped V. cholerae to kill non-kin cells under liquid growth conditions. We also show that the naturally occurring diversity of pili determines the likelihood of cell-to-cell contact and, consequently, the extent of T6SS-mediated competition. To determine the factors that enable or hinder the T6SS's targeted reduction of competitors carrying pili, we developed a physics-grounded computational model for autoaggregation. Collectively, our research demonstrates that T4Ps involved in cell-to-cell contact can impose a selective burden when V. cholerae encounters non-kin cells that possess an active T6SS. Additionally, our study underscores the significance of T4P diversity in protecting closely related individuals from T6SS attacks through autoaggregation and spatial segregation.

Enhanced surface colonisation and competition during bacterial adaptation to a fungus.

Bacterial-fungal interactions influence microbial community performance of most ecosystems and elicit specific microbial behaviours, including stimulating specialised metabolite production. Here, we use a co-culture experimental evolution approach to investigate bacterial adaptation to the presence of a fungus, using a simple model of bacterial-fungal interactions encompassing the bacterium Bacillus subtilis and the fungus Aspergillus niger. We find in one evolving population that B. subtilis was selected for enhanced production of the lipopeptide surfactin and accelerated surface spreading ability, leading to inhibition of fungal expansion and acidification of the environment. These phenotypes were explained by specific mutations in the DegS-DegU two-component system. In the presence of surfactin, fungal hyphae exhibited bulging cells with delocalised secretory vesicles possibly provoking an RlmA-dependent cell wall stress. Thus, our results indicate that the presence of the fungus selects for increased surfactin production, which inhibits fungal growth and facilitates the competitive success of the bacterium.

Arbuscular mycorrhizal fungi and Streptomyces: brothers in arms to shape the structure and function of the hyphosphere microbiome in the early stage of interaction.

BACKGROUND: Fungi and bacteria coexist in a wide variety of environments, and their interactions are now recognized as the norm in most agroecosystems. These microbial communities harbor keystone taxa, which facilitate connectivity between fungal and bacterial communities, influencing their composition and functions. The roots of most plants are associated with arbuscular mycorrhizal (AM) fungi, which develop dense networks of hyphae in the soil. The surface of these hyphae (called the hyphosphere) is the region where multiple interactions with microbial communities can occur, e.g., exchanging or responding to each other's metabolites. However, the presence and importance of keystone taxa in the AM fungal hyphosphere remain largely unknown. RESULTS: Here, we used in vitro and pot cultivation systems of AM fungi to investigate whether certain keystone bacteria were able to shape the microbial communities growing in the hyphosphere and potentially improved the fitness of the AM fungal host. Based on various AM fungi, soil leachates, and synthetic microbial communities, we found that under organic phosphorus (P) conditions, AM fungi could selectively recruit bacteria that enhanced their P nutrition and competed with less P-mobilizing bacteria. Specifically, we observed a privileged interaction between the isolate Streptomyces sp. D1 and AM fungi of the genus Rhizophagus, where (1) the carbon compounds exuded by the fungus were acquired by the bacterium which could mineralize organic P and (2) the in vitro culturable bacterial community residing on the surface of hyphae was in part regulated by Streptomyces sp. D1, primarily by inhibiting the bacteria with weak P-mineralizing ability, thereby enhancing AM fungi to acquire P. CONCLUSIONS: This work highlights the multi-functionality of the keystone bacteria Streptomyces sp. D1 in fungal-bacteria and bacterial-bacterial interactions at the hyphal surface of AM fungi. Video Abstract.

Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation.

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two Escherichia coli mutants that are metabolically dependent (due to an inability to synthesize essential amino acids) but competitively grow on a shared substrate. The analysis of the E. coli binary consortium using our model not only showed how interactions between the two amino acid auxotrophic mutants are controlled by the dynamic shifts in limiting substrates but also enabled quantifying previously uncharacterizable complex aspects of microbial interactions, such as asymmetry in interactions. Our approach can be extended to other ecological systems to model their environment-dependent interspecies interactions from growth kinetics.IMPORTANCEModeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.

Bacterial interactions on nutrient-rich surfaces in the gut lumen.

The intestinal lumen is a turbulent, semi-fluid landscape where microbial cells and nutrient-rich particles are distributed with high heterogeneity. Major questions regarding the basic physical structure of this dynamic microbial ecosystem remain unanswered. Most gut microbes are non-motile, and it is unclear how they achieve optimum localization relative to concentrated aggregations of dietary glycans that serve as their primary source of energy. In addition, a random spatial arrangement of cells in this environment is predicted to limit sustained interactions that drive co-evolution of microbial genomes. The ecological consequences of random versus organized microbial localization have the potential to control both the metabolic outputs of the microbiota and the propensity for enteric pathogens to participate in proximity-dependent microbial interactions. Here, we review evidence suggesting that several bacterial species adopt organized spatial arrangements in the gut via adhesion. We highlight examples where localization could contribute to antagonism or metabolic interdependency in nutrient degradation, and we discuss imaging- and sequencing-based technologies that have been used to assess the spatial positions of cells within complex microbial communities.

Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.

Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbiology. Different methods, relying on experimental or mathematical approaches based on the diverse properties of bacteria, are currently employed to study these interactions. Recently, the use of metabolic networks to understand the interactions between bacterial pairs has increased, highlighting the relevance of this approach in characterizing bacteria. In this study, we leverage the representation of bacteria through their metabolic networks to build a predictive model aimed at reducing the number of experimental assays required for designing bacterial consortia with specific behaviors. Our novel method for predicting cross-feeding or competition interactions between pairs of microorganisms utilizes metabolic network features. Machine learning classifiers are employed to determine the type of interaction from automatically reconstructed metabolic networks. Several algorithms were assessed and selected based on comprehensive testing and careful separation of manually compiled data sets obtained from literature sources. We used different classification algorithms, including K Nearest Neighbors, XGBoost, Support Vector Machine, and Random Forest, tested different parameter values, and implemented several data curation approaches to reduce the biological bias associated with our data set, ultimately achieving an accuracy of over 0.9. Our method holds substantial potential to advance the understanding of community behavior and contribute to the development of more effective approaches for consortia design.IMPORTANCEUnderstanding bacterial interactions at the community level is critical for microbiology, and leveraging metabolic networks presents an efficient and effective approach. The introduction of this novel method for predicting interactions through machine learning classifiers has the potential to advance the field by reducing the number of experimental assays required and contributing to the development of more effective bacterial consortia.

Swimming towards each other: the role of chemotaxis in bacterial interactions.

Chemotaxis allows microorganisms to direct movement in response to chemical stimuli. Bacteria use this behaviour to develop spatial associations with animals and plants, and even larger microbes. However, current theory suggests that constraints imposed by the limits of chemotactic sensory systems will prevent sensing of chemical gradients emanating from cells smaller than a few micrometres, precluding the utility of chemotaxis in interactions between individual bacteria. Yet, recent evidence has revealed surprising levels of bacterial chemotactic precision, as well as a role for chemotaxis in metabolite exchange between bacterial cells. If indeed widespread, chemotactic sensing between bacteria could represent an important, but largely overlooked, phenotype within interbacterial interactions, and play a significant role in shaping cooperative and competitive relationships.

Minorities drive growth resumption in cross-feeding microbial communities.

Microbial communities are fundamental to life on Earth. Different strains within these communities are often connected by a highly connected metabolic network, where the growth of one strain depends on the metabolic activities of other community members. While distributed metabolic functions allow microbes to reduce costs and optimize metabolic pathways, they make them metabolically dependent. Here, we hypothesize that such dependencies can be detrimental in situations where the external conditions change rapidly, as they often do in natural environments. After a shift in external conditions, microbes need to remodel their metabolism, but they can only resume growth once partners on which they depend have also adapted to the new conditions. It is currently not well understood how microbial communities resolve this dilemma and how metabolic interactions are reestablished after an environmental shift. To address this question, we investigated the dynamical responses to environmental perturbation by microbial consortia with distributed anabolic functions. By measuring the regrowth times at the single-cell level in spatially structured communities, we found that metabolic dependencies lead to a growth delay after an environmental shift. However, a minority of cells-those in the immediate neighborhood of their metabolic partners-can regrow quickly and come to numerically dominate the community after the shift. The spatial arrangement of a microbial community is thus a key factor in determining the communities' ability to maintain metabolic interactions and growth in fluctuating conditions. Our results suggest that environmental fluctuations can limit the emergence of metabolic dependencies between microorganisms.

Spatial-temporal dynamics of a microbial cooperative behavior resistant to cheating.

Much of our understanding of bacterial behavior stems from studies in liquid culture. In nature, however, bacteria frequently live in densely packed spatially-structured communities. How does spatial structure affect bacterial cooperative behaviors? In this work, we examine rhamnolipid production-a cooperative and virulent behavior of Pseudomonas aeruginosa. Here we show that, in striking contrast to well-mixed liquid culture, rhamnolipid gene expression in spatially-structured colonies is strongly associated with colony specific growth rate, and is impacted by perturbation with diffusible quorum signals. To interpret these findings, we construct a data-driven statistical inference model which captures a length-scale of bacterial interaction that develops over time. Finally, we find that perturbation of P. aeruginosa swarms with quorum signals preserves the cooperating genotype in competition, rather than creating opportunities for cheaters. Overall, our data demonstrate that the complex response to spatial localization is key to preserving bacterial cooperative behaviors.

A novel Trichoderma asperellum strain DQ-1 promotes tomato growth and induces resistance to gray mold caused by Botrytis cinerea.

Gray mold caused by Botrytis cinerea is a major cause of economic losses during tomato production. In this study, we obtained 23 Trichoderma strains from tomato rhizosphere soil and their inhibitory effects on B. cinerea and the promoting effects on tomato growth were determined. Among them, the inhibition rate of strain DQ-1 on B. cinerea was 88.56%; compared with the control group, after treatment with strain DQ-1, the seeds germination rate and root length of tomato increased by 5.55 and 37.86%. The induced disease resistance of strain DQ-1 was evaluated by pot experiments. The disease incidence (DI) and disease severity index (DSI) of tomato pre-inoculated with strain DQ-1 and then inoculated with B. cinerea were reduced by 38 and 64% compared with the control. Furthermore, we detected the expression levels of tomato disease resistance related genes PR2 and TPX, ethylene pathway related genes ETR1 and CTR1 and jasmonic acid pathway related genes LOX1 and PAL in challenging and non-challenging inoculation treatments. The results showed that the tomato treated with strain DQ-1 triggered the system acquired resistance (SAR) and induced systemic resistance (ISR) pathway, thereby enhancing the disease resistance of tomato. Then the strain DQ-1 was identified as Trichoderma asperellum based on morphological characteristics and phylogenetic information. This study suggests that the novel T. asperellum strain DQ-1 can be a potential candidate for the biological control of gray mold in tomato.

The role of competition versus cooperation in microbial community coalescence.

New microbial communities often arise through the mixing of two or more separately assembled parent communities, a phenomenon that has been termed "community coalescence". Understanding how the interaction structures of complex parent communities determine the outcomes of coalescence events is an important challenge. While recent work has begun to elucidate the role of competition in coalescence, that of cooperation, a key interaction type commonly seen in microbial communities, is still largely unknown. Here, using a general consumer-resource model, we study the combined effects of competitive and cooperative interactions on the outcomes of coalescence events. To do so, we simulate coalescence events between pairs of communities with different degrees of competition for shared carbon resources and cooperation through cross-feeding on leaked metabolic by-products (facilitation). We also study how structural and functional properties of post-coalescence communities evolve when they are subjected to repeated coalescence events. We find that in coalescence events, the less competitive and more cooperative parent communities contribute a higher proportion of species to the new community because of their superior ability to deplete resources and resist invasions. Consequently, when a community is subjected to repeated coalescence events, it gradually evolves towards being less competitive and more cooperative, as well as more speciose, robust and efficient in resource use. Encounters between microbial communities are becoming increasingly frequent as a result of anthropogenic environmental change, and there is great interest in how the coalescence of microbial communities affects environmental and human health. Our study provides new insights into the mechanisms behind microbial community coalescence, and a framework to predict outcomes based on the interaction structures of parent communities.