Positive interactions are common among culturable bacteria

The use of biomimetic surfaces to reduce single- and dual-species biofilms of Escherichia coli and Pseudomonas putida

The ability of bacteria to adhere to and form biofilms on food contact surfaces poses serious challenges, as these may lead to the cross-contamination of food products. Biomimetic topographic surface modifications have been explored to enhance the antifouling performance of materials. In this study, the topography of two plant leaves, Brassica oleracea var. botrytis (cauliflower, CF) and Brassica oleracea capitate (white cabbage, WC), was replicated through wax moulding, and their antibiofilm potential was tested against single- and dual-species biofilms of Escherichia coli and Pseudomonas putida. Biomimetic surfaces exhibited higher roughness values (SaWC = 4.0 ± 1.0 μm and SaCF = 3.3 ± 1.0 μm) than the flat control (SaF = 0.6 ± 0.2 μm), whilst the CF surface demonstrated a lower interfacial free energy (ΔGiwi) than the WC surface (-100.08 mJ m-2 and -71.98 mJ m-2, respectively). The CF and WC surfaces had similar antibiofilm effects against single-species biofilms, achieving cell reductions of approximately 50% and 60% for E. coli and P. putida, respectively, compared to the control. Additionally, the biomimetic surfaces led to reductions of up to 60% in biovolume, 45% in thickness, and 60% in the surface coverage of single-species biofilms. For dual-species biofilms, only the E. coli strain growing on the WC surface exhibited a significant decrease in the cell count. However, confocal microscopy analysis revealed a 60% reduction in the total biovolume and surface coverage of mixed biofilms developed on both biomimetic surfaces. Furthermore, dual-species biofilms were mainly composed of P. putida, which reduced E. coli growth. Altogether, these results demonstrate that the surface properties of CF and WC biomimetic surfaces have the potential for reducing biofilm formation.

A Burkholderia cenocepacia-like environmental isolate strongly inhibits the plant fungal pathogen Zymoseptoria tritici

Fungal phytopathogens cause significant reductions in agricultural yields annually, and overusing chemical fungicides for their control leads to environmental pollution and the emergence of resistant pathogens. Exploring natural isolates with strong antagonistic effects against pathogens can improve our understanding of their ecology and develop new treatments for the future. We isolated and characterized a novel bacterial strain associated with the species Burkholderia cenocepacia, termed APO9, which strongly inhibits Zymoseptoria tritici, a commercially important pathogenic fungus causing Septoria tritici blotch in wheat. Additionally, this strain exhibits inhibitory activity against four other phytopathogens. We found that physical contact plays a crucial role for APO9's antagonistic capacity. Genome sequencing of APO9 and biosynthetic gene cluster (BGC) analysis identified nine classes of BGCs and three types of secretion systems (types II, III, and IV), which may be involved in the inhibition of Z. tritici and other pathogens. To identify genes driving APO9's inhibitory activity, we screened a library containing 1,602 transposon mutants and identified five genes whose inactivation reduced inhibition efficiency. One such gene encodes for a diaminopimelate decarboxylase located in a terpenoid biosynthesis gene cluster. Phylogenetic analysis revealed that while some of these genes are also found across the Burkholderia genus, as well as in other Betaproteobacteria, the combination of these genes is unique to the Burkholderia cepacia complex. These findings suggest that the inhibitory capacity of APO9 is complex and not limited to a single mechanism, and may play a role in the interaction between various Burkholderia species and various phytopathogens within diverse plant ecosystems.

IMPORTANCE

The detrimental effects of fungal pathogens on crop yields are substantial. The overuse of chemical fungicides contributes not only to environmental pollution but also to the emergence of resistant pathogens. Investigating natural isolates with strong antagonistic effects against pathogens can improve our understanding of their ecology and develop new treatments for the future. We discovered and examined a unique bacterial strain that demonstrates significant inhibitory activity against several phytopathogens. Our research demonstrates that this strain has a wide spectrum of inhibitory actions against plant pathogens, functioning through a complex mechanism. This plays a vital role in the interactions between plant microbiota and phytopathogens.

Pseudomonas putida as saviour for troubled Synechococcus elongatus in a synthetic co-culture - interaction studies based on a multi-OMICs approach

In their natural habitats, microbes rarely exist in isolation; instead, they thrive in consortia, where various interactions occur. In this study, a defined synthetic co-culture of the cyanobacterium S. elongatus cscB, which supplies sucrose to the heterotrophic P. putida cscRABY, is investigated to identify potential interactions. Initial experiments reveal a remarkable growth-promoting effect of the heterotrophic partner on the cyanobacterium, resulting in an up to 80% increase in the growth rate and enhanced photosynthetic capacity. Vice versa, the presence of the cyanobacterium has a neutral effect on P. putida cscRABY, highlighting the resilience of pseudomonads against stress and their potential as co-culture partners. Next, a suitable reference process reinforcing the growth-promoting effect is established in a parallel photobioreactor system, which sets the basis for the analysis of the co-culture at the transcriptome, proteome, and metabolome levels. In addition to several moderate changes, including alterations in the metabolism and stress response in both microbes, this comprehensive multi-OMICs approach strongly hints towards the exchange of further molecules beyond the unidirectional feeding with sucrose. Taken together, these findings provide valuable insights into the complex dynamics between both co-culture partners, indicating multi-level interactions, which can be employed for further streamlining of the co-cultivation system.

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Reducing the Bacterial Lag Phase Through Methylated Compounds: Insights from Algal-Bacterial Interactions

The bacterial lag phase is a key period for resuming growth. Despite its significance, the lag phase remains underexplored, particularly in environmental bacteria. Here, we explore the lag phase of the model marine bacterium Phaeobacter inhibens when it transitions from starvation to growth with a microalgal partner. Utilizing transcriptomics and 13 C-labeled metabolomics, our study reveals that methylated compounds, which are abundantly produced by microalgae, shorten the bacterial lag phase. Our findings underscore the significance of methyl groups as a limiting factor during the lag phase and demonstrate that methyl groups can be harvested from algal compounds and assimilated through the methionine cycle. Furthermore, we show that methylated compounds, characteristic of photosynthetic organisms, induce variable reductions in lag times among bacteria associated with algae and plants. These findings highlight the adjustability of the bacterial lag phase and emphasize the importance of studying bacteria in an environmental context.

One-Sentence Summary

Bacteria use algal compounds as a metabolic shortcut to transition from starvation to growth.

Multi-Attribute Subset Selection enables prediction of representative phenotypes across microbial populations

The interpretation of complex biological datasets requires the identification of representative variables that describe the data without critical information loss. This is particularly important in the analysis of large phenotypic datasets (phenomics). Here we introduce Multi-Attribute Subset Selection (MASS), an algorithm which separates a matrix of phenotypes (e.g., yield across microbial species and environmental conditions) into predictor and response sets of conditions. Using mixed integer linear programming, MASS expresses the response conditions as a linear combination of the predictor conditions, while simultaneously searching for the optimally descriptive set of predictors. We apply the algorithm to three microbial datasets and identify environmental conditions that predict phenotypes under other conditions, providing biologically interpretable axes for strain discrimination. MASS could be used to reduce the number of experiments needed to identify species or to map their metabolic capabilities. The generality of the algorithm allows addressing subset selection problems in areas beyond biology.

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

Interwoven processes in fish development: microbial community succession and immune maturation

Fishes are hosts for many microorganisms that provide them with beneficial effects on growth, immune system development, nutrition and protection against pathogens. In order to avoid spreading of infectious diseases in aquaculture, prevention includes vaccinations and routine disinfection of eggs and equipment, while curative treatments consist in the administration of antibiotics. Vaccination processes can stress the fish and require substantial farmer's investment. Additionally, disinfection and antibiotics are not specific, and while they may be effective in the short term, they have major drawbacks in the long term. Indeed, they eliminate beneficial bacteria which are useful for the host and promote the raising of antibiotic resistance in beneficial, commensal but also in pathogenic bacterial strains. Numerous publications highlight the importance that plays the diversified microbial community colonizing fish (i.e., microbiota) in the development, health and ultimately survival of their host. This review targets the current knowledge on the bidirectional communication between the microbiota and the fish immune system during fish development. It explores the extent of this mutualistic relationship: on one hand, the effect that microbes exert on the immune system ontogeny of fishes, and on the other hand, the impact of critical steps in immune system development on the microbial recruitment and succession throughout their life. We will first describe the immune system and its ontogeny and gene expression steps in the immune system development of fishes. Secondly, the plurality of the microbiotas (depending on host organism, organ, and development stage) will be reviewed. Then, a description of the constant interactions between microbiota and immune system throughout the fish's life stages will be discussed. Healthy microbiotas allow immune system maturation and modulation of inflammation, both of which contribute to immune homeostasis. Thus, immune equilibrium is closely linked to microbiota stability and to the stages of microbial community succession during the host development. We will provide examples from several fish species and describe more extensively the mechanisms occurring in zebrafish model because immune system ontogeny is much more finely described for this species, thanks to the many existing zebrafish mutants which allow more precise investigations. We will conclude on how the conceptual framework associated to the research on the immune system will benefit from considering the relations between microbiota and immune system maturation. More precisely, the development of active tolerance of the microbiota from the earliest stages of life enables the sustainable establishment of a complex healthy microbial community in the adult host. Establishing a balanced host-microbiota interaction avoids triggering deleterious inflammation, and maintains immunological and microbiological homeostasis.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Deciphering the biotic and abiotic drivers of coalescence asymmetry between soil and manure microbiomes

Manure application improves soil fertility, yet its implications on the success of invasion of manure-borne microorganisms in the soil are poorly understood. Here, we assessed the importance of abiotic and biotic factors in modulating the extent to which manure-borne fungal and bacterial communities can invade resident soil microbial communities. For this purpose, we applied varying frequencies of two different amounts of manure to nine soils differing in physico-chemical properties, as well as in land-use history, over 180 days and monitored changes in bacterial and fungal communities. Variance partitioning revealed differential contributions of abiotic and biotic factors to invasion success, which together accounted for up to 82 % of the variance explained. We showed that the effects of interactions between biotic and abiotic factors increased with coalescence frequency and manure amount for the bacterial and fungal communities, respectively. Both abiotic and biotic factors were important for modulating coalescence asymmetry for the bacterial community, whereas abiotic factors had a greater effect on the fungal community. These results provide new insights into the drivers of coalescence events between manure and resident soil microbial communities. Moreover, our findings highlight the roles of the mixing ratio and frequency of coalescence events in modulating the survival of manure-borne microorganisms.

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.

Stepwise degradation of organic matters driven by microbial interactions in China΄s coastal wetlands: Evidence from carbon isotope analysis

The microbial "unseen majority" as drivers of carbon cycle represent a significant source of uncertain climate change. To comprehend the resilience of life forms on Earth to climate change, it is crucial to incorporate knowledge of intricate microbial interactions and their impact to carbon transformation. Combined with carbon stable isotope analysis and high-throughput sequencing technology, the underlying mechanism of microbial interactions for organic carbon degradation has been elucidated. Niche differentiation enabled archaea to coexist with bacteria mainly in a cooperative manner. Bacteria composed of specialists preferred to degrade lighter carbon, while archaea were capable of utilizing heavier carbon. Microbial resource-dependent interactions drove stepwise degradation of organic matter. Bacterial cooperation directly facilitated the degradation of algae-dominated particulate organic carbon, while competitive feeding of archaea caused by resource scarcity significantly promoted the mineralization of heavier particulate organic carbon and then the release of dissolved inorganic carbon. Meanwhile, archaea functioned as a primary decomposer and collaborated with bacteria in the gradual degradation of dissolved organic carbon. This study emphasized microbial interactions driving carbon cycle and provided new perspectives for incorporating microorganisms into carbon biogeochemical models.

High diversity, close genetic relatedness, and favorable living conditions benefit species co-occurrence of gut microbiota in Brandt's vole

Introduction

Revealing factors and mechanisms in determining species co-existence are crucial to community ecology, but studies using gut microbiota data are still lacking.

Methods

Using gut microbiota data of 556 Brandt's voles from 37 treatments in eight experiments, we examined the relationship of species co-occurrence of gut microbiota in Brandt's voles (Lasiopodomys brandtii) with genetic distance (or genetic relatedness), community diversity, and several environmental variables.

Results

We found that the species co-occurrence index (a larger index indicates a higher co-occurrence probability) of gut microbiota in Brandt's voles was negatively associated with the genetic distance between paired ASVs and the number of cohabitating voles in the experimental space (a larger number represents more crowding social stress), but positively with Shannon diversity index, grass diets (representing natural foods), and non-physical contact within an experimental space (representing less stress).

Discussion

Our study demonstrated that high diversity, close genetic relatedness, and favorable living conditions would benefit species co-occurrence of gut microbiota in hosts. Our results provide novel insights into factors and mechanisms that shape the community structure and function of gut microbiota and highlight the significance of preserving the biodiversity of gut microbiota.

Positive associations fuel soil biodiversity and ecological networks worldwide

Microbial interactions are key to maintaining soil biodiversity. However, whether negative or positive associations govern the soil microbial system at a global scale remains virtually unknown, limiting our understanding of how microbes interact to support soil biodiversity and functions. Here, we explored ecological networks among multitrophic soil organisms involving bacteria, protists, fungi, and invertebrates in a global soil survey across 20 regions of the planet and found that positive associations among both pairs and triads of soil taxa governed global soil microbial networks. We further revealed that soil networks with greater levels of positive associations supported larger soil biodiversity and resulted in lower network fragility to withstand potential perturbations of species losses. Our study provides unique evidence of the widespread positive associations between soil organisms and their crucial role in maintaining the multitrophic structure of soil biodiversity worldwide.

Ecological dependencies and the illusion of cooperation in microbial communities

Ecological dependencies - where organisms rely on other organisms for survival - are a ubiquitous feature of life on earth. Multicellular hosts rely on symbionts to provide essential vitamins and amino acids. Legume plants similarly rely on nitrogen-fixing rhizobia to convert atmospheric nitrogen to ammonia. In some cases, dependencies can arise via loss-of-function mutations that allow one partner to benefit from the actions of another. It is common in microbiology to label ecological dependencies between species as cooperation - making it necessary to invoke cooperation-specific frameworks to explain the phenomenon. However, in many cases, such traits are not (at least initially) cooperative, because they are not selected for because of the benefits they confer on a partner species. In contrast, dependencies in microbial communities may originate from fitness benefits gained from genomic-streamlining (i.e. Black Queen Dynamics). Here, we outline how the Black Queen Hypothesis predicts the formation of metabolic dependencies via loss-of-function mutations in microbial communities, without needing to invoke any cooperation-specific explanations. Furthermore we outline how the Black Queen Hypothesis can act as a blueprint for true cooperation as well as discuss key outstanding questions in the field. The nature of interactions in microbial communities can predict the ability of natural communities to withstand and recover from disturbances. Hence, it is vital to gain a deeper understanding of the factors driving these dynamic interactions over evolutionary time.

Sparse species interactions reproduce abundance correlation patterns in microbial communities

During the last decades, macroecology has identified broad-scale patterns of abundances and diversity of microbial communities and put forward some potential explanations for them. However, these advances are not paralleled by a full understanding of the dynamical processes behind them. In particular, abundance fluctuations of different species are found to be correlated, both across time and across communities in metagenomic samples. Reproducing such correlations through appropriate population models remains an open challenge. The present paper tackles this problem and points to sparse species interactions as a necessary mechanism to account for them. Specifically, we discuss several possibilities to include interactions in population models and recognize Lotka-Volterra constants as a successful ansatz. For this, we design a Bayesian inference algorithm to extract sets of interaction constants able to reproduce empirical probability distributions of pairwise correlations for diverse biomes. Importantly, the inferred models still reproduce well-known single-species macroecological patterns concerning abundance fluctuations across both species and communities. Endorsed by the agreement with the empirically observed phenomenology, our analyses provide insights into the properties of the networks of microbial interactions, revealing that sparsity is a crucial feature.

Microbial diversity and ecological complexity emerging from environmental variation and horizontal gene transfer in a simple mathematical model

Microbiomes are generally characterized by high diversity of coexisting microbial species and strains that remains stable within a broad range of conditions. However, under fixed conditions, microbial ecology conforms with the exclusion principle under which two populations competing for the same resource within the same niche cannot coexist because the less fit population inevitably goes extinct. To explore the conditions for stabilization of microbial diversity, we developed a simple mathematical model consisting of two competing populations that could exchange a single gene allele via horizontal gene transfer (HGT). We found that, although in a fixed environment, with unbiased HGT, the system obeyed the exclusion principle, in an oscillating environment, within large regions of the phase space bounded by the rates of reproduction and HGT, the two populations coexist. Moreover, depending on the parameter combination, all three major types of symbiosis obtained, namely, pure competition, host-parasite relationship and mutualism. In each of these regimes, certain parameter combinations provided for synergy, that is, a greater total abundance of both populations compared to the abundance of the winning population in the fixed environments. These findings show that basic phenomena that are universal in microbial communities, environmental variation and HGT, provide for stabilization of microbial diversity and ecological complexity.

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.

Trojan horselike T6SS effector TepC mediates both interference competition and exploitative competition

The type VI secretion system (T6SS) is a bacterial weapon capable of delivering antibacterial effectors to kill competing cells for interference competition, as well as secreting metal ion scavenging effectors to acquire essential micronutrients for exploitation competition. However, no T6SS effectors that can mediate both interference competition and exploitation competition have been reported. In this study, we identified a unique T6SS-1 effector in Yersinia pseudotuberculosis named TepC, which plays versatile roles in microbial communities. First, secreted TepC acts as a proteinaceous siderophore that binds to iron and mediates exploitative competition. Additionally, we discovered that TepC has DNase activity, which gives it both contact-dependent and contact-independent interference competition abilities. In conditions where iron is limited, the iron-loaded TepC is taken up by target cells expressing the outer membrane receptor TdsR. For kin cells encoding the cognate immunity protein TipC, TepC facilitates iron acquisition, and its toxic effects are neutralized. On the other hand, nonkin cells lacking TipC are enticed to uptake TepC and are killed by its DNase activity. Therefore, we have uncovered a T6SS effector, TepC, that functions like a "Trojan horse" by binding to iron ions to provide a valuable resource to kin cells, whereas punishing cheaters that do not produce public goods. This lure-to-kill mechanism, mediated by a bifunctional T6SS effector, may offer new insights into the molecular mechanisms that maintain stability in microbial communities.

Emergent antibiotic persistence in a spatially structured synthetic microbial mutualism

Antibiotic persistence (heterotolerance) allows a subpopulation of bacteria to survive antibiotic-induced killing and contributes to the evolution of antibiotic resistance. Although bacteria typically live in microbial communities with complex ecological interactions, little is known about how microbial ecology affects antibiotic persistence. Here, we demonstrated within a synthetic two-species microbial mutualism of Escherichia coli and Salmonella enterica that the combination of cross-feeding and community spatial structure can emergently cause high antibiotic persistence in bacteria by increasing the cell-to-cell heterogeneity. Tracking ampicillin-induced death for bacteria on agar surfaces, we found that E. coli forms up to 55 times more antibiotic persisters in the cross-feeding coculture than in monoculture. This high persistence could not be explained solely by the presence of S. enterica, the presence of cross-feeding, average nutrient starvation, or spontaneous resistant mutations. Time-series fluorescent microscopy revealed increased cell-to-cell variation in E. coli lag time in the mutualistic co-culture. Furthermore, we discovered that an E. coli cell can survive antibiotic killing if the nearby S. enterica cells on which it relies die first. In conclusion, we showed that the high antibiotic persistence phenotype can be an emergent phenomenon caused by a combination of cross-feeding and spatial structure. Our work highlights the importance of considering spatially structured interactions during antibiotic treatment and understanding microbial community resilience more broadly.

Microbial collaborations and conflicts: unraveling interactions in the gut ecosystem

The human gut microbiota constitutes a vast and complex community of microorganisms. The myriad of microorganisms present in the intestinal tract exhibits highly intricate interactions, which play a crucial role in maintaining the stability and balance of the gut microbial ecosystem. These interactions, in turn, influence the overall health of the host. The mammalian gut microbes have evolved a wide range of mechanisms to suppress or even eliminate their competitors for nutrients and space. Simultaneously, extensive cooperative interactions exist among different microbes to optimize resource utilization and enhance their own fitness. This review will focus on the competitive mechanisms among members of the gut microorganisms and discuss key modes of actions, including bacterial secretion systems, bacteriocins, membrane vesicles (MVs) etc. Additionally, we will summarize the current knowledge of the often-overlooked positive interactions within the gut microbiota, and showcase representative machineries. This information will serve as a reference for better understanding the complex interactions occurring within the mammalian gut environment. Understanding the interaction dynamics of competition and cooperation within the gut microbiota is crucial to unraveling the ecology of the mammalian gut microbial communities. Targeted interventions aimed at modulating these interactions may offer potential therapeutic strategies for disease conditions.

Photo-addressable microwell devices for rapid functional screening and isolation of pathogen inhibitors from bacterial strain libraries

Discovery of new strains of bacteria that inhibit pathogen growth can facilitate improvements in biocontrol and probiotic strategies. Traditional, plate-based co-culture approaches that probe microbial interactions can impede this discovery as these methods are inherently low-throughput, labor-intensive, and qualitative. We report a second-generation, photo-addressable microwell device, developed to iteratively screen interactions between candidate biocontrol agents existing in bacterial strain libraries and pathogens under increasing pathogen pressure. Microwells (0.6 pl volume) provide unique co-culture sites between library strains and pathogens at controlled cellular ratios. During sequential screening iterations, library strains are challenged against increasing numbers of pathogens to quantitatively identify microwells containing strains inhibiting the highest numbers of pathogens. Ring-patterned 365 nm light is then used to ablate a photodegradable hydrogel membrane and sequentially release inhibitory strains from the device for recovery. Pathogen inhibition with each recovered strain is validated, followed by whole genome sequencing. To demonstrate the rapid nature of this approach, the device was used to screen a 293-membered biovar 1 agrobacterial strain library for strains inhibitory to the plant pathogen Agrobacterium tumefaciens sp. 15955. One iterative screen revealed nine new inhibitory strains. For comparison, plate-based methods did not uncover any inhibitory strains from the library (n = 30 plates). The novel pathogen-challenge screening mode developed here enables rapid selection and recovery of strains that effectively suppress pathogen growth from bacterial strain libraries, expanding this microwell technology platform toward rapid, cost-effective, and scalable screening for probiotics, biocontrol agents, and inhibitory molecules that can protect against known or emerging pathogens.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Microbial interactions shape cheese flavour formation

Cheese fermentation and flavour formation are the result of complex biochemical reactions driven by the activity of multiple microorganisms. Here, we studied the roles of microbial interactions in flavour formation in a year-long Cheddar cheese making process, using a commercial starter culture containing Streptococcus thermophilus and Lactococcus strains. By using an experimental strategy whereby certain strains were left out from the starter culture, we show that S. thermophilus has a crucial role in boosting Lactococcus growth and shaping flavour compound profile. Controlled milk fermentations with systematic exclusion of single Lactococcus strains, combined with genomics, genome-scale metabolic modelling, and metatranscriptomics, indicated that S. thermophilus proteolytic activity relieves nitrogen limitation for Lactococcus and boosts de novo nucleotide biosynthesis. While S. thermophilus had large contribution to the flavour profile, Lactococcus cremoris also played a role by limiting diacetyl and acetoin formation, which otherwise results in an off-flavour when in excess. This off-flavour control could be attributed to the metabolic re-routing of citrate by L. cremoris from diacetyl and acetoin towards α-ketoglutarate. Further, closely related Lactococcus lactis strains exhibited different interaction patterns with S. thermophilus, highlighting the significance of strain specificity in cheese making. Our results highlight the crucial roles of competitive and cooperative microbial interactions in shaping cheese flavour profile.

Metabolic interactions affect the biomass of synthetic bacterial biofilm communities

IMPORTANCE

Co-occurrence network analysis is an effective tool for predicting complex networks of microbial interactions in the natural environment. Using isolates from a rhizosphere, we constructed multi-species biofilm communities and investigated co-occurrence patterns between microbial species in genome-scale metabolic models and in vitro experiments. According to our results, metabolic exchanges and resource competition may partially explain the co-occurrence network analysis results found in synthetic bacterial biofilm communities.

Metabolic exchanges are ubiquitous in natural microbial communities

Microbial communities drive global biogeochemical cycles and shape the health of plants and animals-including humans. Their structure and function are determined by ecological and environmental interactions that govern the assembly, stability and evolution of microbial communities. A widely held view is that antagonistic interactions such as competition predominate in microbial communities and are ecologically more important than synergistic interactions-for example, mutualism or commensalism. Over the past decade, however, a more nuanced picture has emerged, wherein bacteria, archaea and fungi exist within interactive networks in which they exchange essential and non-essential metabolites. These metabolic interactions profoundly impact not only the physiology, ecology and evolution of the strains involved, but are also central to the functioning of many, if not all, microbiomes. Therefore, we advocate for a balanced view of microbiome ecology that encompasses both synergistic and antagonistic interactions as key forces driving the structure and dynamics within microbial communities.

Mutualism reduces the severity of gene disruptions in predictable ways across microbial communities

Predicting evolution in microbial communities is critical for problems from human health to global nutrient cycling. Understanding how species interactions impact the distribution of fitness effects for a focal population would enhance our ability to predict evolution. Specifically, does the type of ecological interaction, such as mutualism or competition, change the average effect of a mutation (i.e., the mean of the distribution of fitness effects)? Furthermore, how often does increasing community complexity alter the impact of species interactions on mutant fitness? To address these questions, we created a transposon mutant library in Salmonella enterica and measured the fitness of loss of function mutations in 3,550 genes when grown alone versus competitive co-culture or mutualistic co-culture with Escherichia coli and Methylorubrum extorquens. We found that mutualism reduces the average impact of mutations, while competition had no effect. Additionally, mutant fitness in the 3-species communities can be predicted by averaging the fitness in each 2-species community. Finally, we discovered that in the mutualism S. enterica obtained vitamins and more amino acids than previously known. Our results suggest that species interactions can predictably impact fitness effect distributions, in turn suggesting that evolution may ultimately be predictable in multi-species communities.

On the De Novo Emergence of Ecological Interactions during Evolutionary Diversification: A Conceptual Framework and Experimental Test

AbstractEcological interactions are crucial to the structure and function of biological communities, but we lack a causal understanding of the forces shaping their emergence during evolutionary diversification. Here we provide a conceptual framework linking different modes of diversification (e.g., ecological diversification), which depend on environmental characteristics, to the evolution of different forms of ecological interactions (e.g., resource partitioning) in asexual lineages. We tested the framework by examining the net interactions in communities of Pseudomonas aeruginosa produced via experimental evolution in nutritionally simple (SIM) or complex (COM) environments by contrasting the productivity and competitive fitness of whole evolved communities relative to their component isolates. As expected, we found that nutritional complexity drove the evolution of communities with net positive interactions whereas SIM communities had similar performance as their component isolates. A follow-up experiment revealed that high fitness in two COM communities was driven by rare variants (frequency <0.1%) that antagonized PA14, the ancestral strain and common competitor used in fitness assays. Our study suggests that the evolution of de novo ecological interactions in asexual lineages is predictable at a broad scale from environmental conditions. Further, our work demonstrates that rare variants can disproportionately impact the function of relatively simple microbial communities.

Dynamic social interactions and keystone species shape the diversity and stability of mixed-species biofilms - an example from dairy isolates

Identifying interspecies interactions in mixed-species biofilms is a key challenge in microbial ecology and is of paramount importance given that interactions govern community functionality and stability. We previously reported a bacterial four-species biofilm model comprising Stenotrophomonas rhizophila, Bacillus licheniformis, Microbacterium lacticum, and Calidifontibacter indicus that were isolated from the surface of a dairy pasteuriser after cleaning and disinfection. These bacteria produced 3.13-fold more biofilm mass compared to the sum of biofilm masses in monoculture. The present study confirms that the observed community synergy results from dynamic social interactions, encompassing commensalism, exploitation, and amensalism. M. lacticum appears to be the keystone species as it increased the growth of all other species that led to the synergy in biofilm mass. Interactions among the other three species (in the absence of M. lacticum) also contributed towards the synergy in biofilm mass. Biofilm inducing effects of bacterial cell-free-supernatants were observed for some combinations, revealing the nature of the observed synergy, and addition of additional species to dual-species combinations confirmed the presence of higher-order interactions within the biofilm community. Our findings provide understanding of bacterial interactions in biofilms which can be used as an interaction-mediated approach for cultivating, engineering, and designing synthetic bacterial communities.

Genome content predicts the carbon catabolic preferences of heterotrophic bacteria

Heterotrophic bacteria-bacteria that utilize organic carbon sources-are taxonomically and functionally diverse across environments. It is challenging to map metabolic interactions and niches within microbial communities due to the large number of metabolites that could serve as potential carbon and energy sources for heterotrophs. Whether their metabolic niches can be understood using general principles, such as a small number of simplified metabolic categories, is unclear. Here we perform high-throughput metabolic profiling of 186 marine heterotrophic bacterial strains cultured in media containing one of 135 carbon substrates to determine growth rates, lag times and yields. We show that, despite high variability at all levels of taxonomy, the catabolic niches of heterotrophic bacteria can be understood in terms of their preference for either glycolytic (sugars) or gluconeogenic (amino and organic acids) carbon sources. This preference is encoded by the total number of genes found in pathways that feed into the two modes of carbon utilization and can be predicted using a simple linear model based on gene counts. This allows for coarse-grained descriptions of microbial communities in terms of prevalent modes of carbon catabolism. The sugar-acid preference is also associated with genomic GC content and thus with the carbon-nitrogen requirements of their encoded proteome. Our work reveals how the evolution of bacterial genomes is structured by fundamental constraints rooted in metabolism.

Synthesizing microbial biodiversity

The diversity of microbial ecosystems is linked to crucial ecological processes and functions. Despite its significance, the ecological mechanisms responsible for the initiation and maintenance of microbiome diversity are still not fully understood. The primary challenge lies in the difficulty of isolating, monitoring, and manipulating the complex and interrelated ecological processes that modulate the diversity of microbial communities in their natural habitats. Synthetic ecology experiments provide a suitable alternative for investigating the mechanisms behind microbial biodiversity in controlled laboratory settings, as the environment can be systematically and modularly manipulated by adding and removing components. This enables the testing of hypotheses and the advancement of predictive theories. In this review, we present an overview of recent progress toward achieving this goal.

Microbial interactions in theory and practice: when are measurements compatible with models?

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.

Environmental fluctuations explain the universal decay of species-abundance correlations with phylogenetic distance

Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches-which combine phylogenetic relationships between species with community ecology-have the potential to disentangle such forces but are often hard to connect with quantitative predictions from theoretical models. On the other hand, macroecology, which focuses on statistical patterns of abundance and diversity, provides natural connections with theoretical models but often neglects interspecific correlations and interactions. Here, we propose a unified framework combining both such approaches to analyze microbial communities. In particular, by using both cross-sectional and longitudinal metagenomic data for species abundances, we reveal the existence of an empirical macroecological law establishing that correlations in species-abundance fluctuations across communities decay from positive to null values as a function of phylogenetic dissimilarity in a consistent manner across ecologically distinct microbiomes. We formulate three variants of a mechanistic model-each relying on alternative ecological forces-that lead to radically different predictions. From these analyses, we conclude that the empirically observed macroecological pattern can be quantitatively explained as a result of shared population-independent fluctuating resources, i.e., environmental filtering and not as a consequence of, e.g., species competition. Finally, we show that the macroecological law is also valid for temporal data of a single community and that the properties of delayed temporal correlations can be reproduced as well by the model with environmental filtering.

Inter-bacterial mutualism promoted by public goods in a system characterized by deterministic temperature variation

Mutualism is commonly observed in nature but not often reported for bacterial communities. Although abiotic stress is thought to promote microbial mutualism, there is a paucity of research in this area. Here, we monitor microbial communities in a quasi-natural composting system, where temperature variation (20 °C-70 °C) is the main abiotic stress. Genomic analyses and culturing experiments provide evidence that temperature selects for slow-growing and stress-tolerant strains (i.e., Thermobifida fusca and Saccharomonospora viridis), and mutualistic interactions emerge between them and the remaining strains through the sharing of cobalamin. Comparison of 3000 bacterial pairings reveals that mutualism is common (~39.1%) and competition is rare (~13.9%) in pairs involving T. fusca and S. viridis. Overall, our work provides insights into how high temperature can favour mutualism and reduce competition at both the community and species levels.

Legionella relative abundance in shower hose biofilms is associated with specific microbiome members

Legionella are natural inhabitants of building plumbing biofilms, where interactions with other microorganisms influence their survival, proliferation, and death. Here, we investigated the associations of Legionella with bacterial and eukaryotic microbiomes in biofilm samples extracted from 85 shower hoses of a multiunit residential building. Legionella spp. relative abundance in the biofilms ranged between 0-7.8%, of which only 0-0.46% was L. pneumophila. Our data suggest that some microbiome members were associated with high (e.g. Chthonomonas, Vrihiamoeba) or low (e.g. Aquabacterium, Vannella) Legionella relative abundance. The correlations of the different Legionella variants (30 Zero-Radius OTUs detected) showed distinct patterns, suggesting separate ecological niches occupied by different Legionella species. This study provides insights into the ecology of Legionella with respect to: (i) the colonization of a high number of real shower hoses biofilm samples; (ii) the ecological meaning of associations between Legionella and co-occurring bacterial/eukaryotic organisms; (iii) critical points and future directions of microbial-interaction-based-ecological-investigations.

Evolutionary modeling suggests that addictions may be driven by competition-induced microbiome dysbiosis

Recent studies revealed mechanisms by which the microbiome affects its host's brain, behavior and wellbeing, and that dysbiosis - persistent microbiome-imbalance - is associated with the onset and progress of various chronic diseases, including addictive behaviors. Yet, understanding of the ecological and evolutionary processes that shape the host-microbiome ecosystem and affect the host state, is still limited. Here we propose that competition dynamics within the microbiome, associated with host-microbiome mutual regulation, may promote dysbiosis and aggravate addictive behaviors. We construct a mathematical framework, modeling the dynamics of the host-microbiome ecosystem in response to alterations. We find that when this ecosystem is exposed to substantial perturbations, the microbiome may shift towards a composition that reinforces the new host state. Such a positive feedback loop augments post-perturbation imbalances, hindering attempts to return to the initial equilibrium, promoting relapse episodes and prolonging addictions. We show that the initial microbiome composition is a key factor: a diverse microbiome enhances the ecosystem's resilience, whereas lower microbiome diversity is more prone to lead to dysbiosis, exacerbating addictions. This framework provides evolutionary and ecological perspectives on host-microbiome interactions and their implications for host behavior and health, while offering verifiable predictions with potential relevance to clinical treatments.

Metabolic interaction models recapitulate leaf microbiota ecology

Resource allocation affects the structure of microbiomes, including those associated with living hosts. Understanding the degree to which this dependency determines interspecies interactions may advance efforts to control host-microbiome relationships. We combined synthetic community experiments with computational models to predict interaction outcomes between plant-associated bacteria. We mapped the metabolic capabilities of 224 leaf isolates from Arabidopsis thaliana by assessing the growth of each strain on 45 environmentally relevant carbon sources in vitro. We used these data to build curated genome-scale metabolic models for all strains, which we combined to simulate >17,500 interactions. The models recapitulated outcomes observed in planta with >89% accuracy, highlighting the role of carbon utilization and the contributions of niche partitioning and cross-feeding in the assembly of leaf microbiomes.

Microbial Interaction is Among the Key Factors for Isolation of Previous Uncultured Microbes

Pure cultivation of microbes is still limited by the challenges of microbial uncultivability, with most microbial strains unable to be cultivated under standard laboratory conditions. The experience accumulated from advanced techniques such as in situ cultivation has identified that microbial interactions exist in natural habitats but are absent in laboratory cultures. These microbial interactions are likely one of the key factors in isolating previously uncultured microbes. The need for better knowledge of the mechanisms operating in microbial interactions has led to various experiments that have utilized microbial interactions in different approaches to microbial cultivation. These new attempts to understand microbial interactions not only present a new perspective on microbial uncultivability but also provide an opportunity to access uncultured phylogenetically novel microbes with their potential biotechnology applications. In this review, we focus on studies of the mechanisms of microbial interaction where the growth of other microbes is affected. Additionally, we review some successful applications of microbial interactions in cultivation methods, an approach that can play an important role in the bioprospecting of untapped microbial resources.

Guild and Niche Determination Enable Targeted Alteration of the Microbiome

Microbiome science has greatly contributed to our understanding of microbial life and its essential roles for the environment and human health1-5. However, the nature of microbial interactions and how microbial communities respond to perturbations remains poorly understood, resulting in an often descriptive and correlation-based approach to microbiome research6-8. Achieving causal and predictive microbiome science would require direct functional measurements in complex communities to better understand the metabolic role of each member and its interactions with others. In this study we present a new approach that integrates transcription and translation measurements to predict competition and substrate preferences within microbial communities, consequently enabling the selective manipulation of the microbiome. By performing metatranscriptomic (metaRNA-Seq) and metatranslatomic (metaRibo-Seq) analysis in complex samples, we classified microbes into functional groups (i.e. guilds) and demonstrated that members of the same guild are competitors. Furthermore, we predicted preferred substrates based on importer proteins, which specifically benefited selected microbes in the community (i.e. their niche) and simultaneously impaired their competitors. We demonstrated the scalability of microbial guild and niche determination to natural samples and its ability to successfully manipulate microorganisms in complex microbiomes. Thus, the approach enhances the design of pre- and probiotic interventions to selectively alter members within microbial communities, advances our understanding of microbial interactions, and paves the way for establishing causality in microbiome science.

Universal gut microbial relationships in the gut microbiome of wild baboons

Ecological relationships between bacteria mediate the services that gut microbiomes provide to their hosts. Knowing the overall direction and strength of these relationships is essential to learn how ecology scales up to affect microbiome assembly, dynamics, and host health. However, whether bacterial relationships are generalizable across hosts or personalized to individual hosts is debated. Here, we apply a robust, multinomial logistic-normal modeling framework to extensive time series data (5534 samples from 56 baboon hosts over 13 years) to infer thousands of correlations in bacterial abundance in individual baboons and test the degree to which bacterial abundance correlations are 'universal'. We also compare these patterns to two human data sets. We find that, most bacterial correlations are weak, negative, and universal across hosts, such that shared correlation patterns dominate over host-specific correlations by almost twofold. Further, taxon pairs that had inconsistent correlation signs (either positive or negative) in different hosts always had weak correlations within hosts. From the host perspective, host pairs with the most similar bacterial correlation patterns also had similar microbiome taxonomic compositions and tended to be genetic relatives. Compared to humans, universality in baboons was similar to that in human infants, and stronger than one data set from human adults. Bacterial families that showed universal correlations in human infants were often universal in baboons. Together, our work contributes new tools for analyzing the universality of bacterial associations across hosts, with implications for microbiome personalization, community assembly, and stability, and for designing microbiome interventions to improve host health.

Bacterial-fungal interactions and their impact on microbial pathogenesis

Microbial communities of the human microbiota exhibit diverse effects on human health and disease. Microbial homeostasis is important for normal physiological functions and changes to the microbiota are associated with many human diseases including diabetes, cancer, and colitis. In addition, there are many microorganisms that are either commensal or acquired from environmental reservoirs that can cause diverse pathologies. Importantly, the balance between health and disease is intricately connected to how members of the microbiota interact and affect one another's growth and pathogenicity. However, the mechanisms that govern these interactions are only beginning to be understood. In this review, we outline bacterial-fungal interactions in the human body, including examining the mechanisms by which bacteria govern fungal growth and virulence, as well as how fungi regulate bacterial pathogenesis. We summarize advances in the understanding of chemical, physical, and protein-based interactions, and their role in exacerbating or impeding human disease. We focus on the three fungal species responsible for the majority of systemic fungal infections in humans: Candida albicans, Cryptococcus neoformans, and Aspergillus fumigatus. We conclude by summarizing recent studies that have mined microbes for novel antimicrobials and antivirulence factors, highlighting the potential of the human microbiota as a rich resource for small molecule discovery.

Niche Modification by Sulfate-Reducing Bacteria Drives Microbial Community Assembly in Anoxic Marine Sediments

Sulfate-reducing bacteria (SRB) are essential functional microbial taxa for degrading organic matter (OM) in anoxic marine environments. However, there are little experimental data regarding how SRB regulates microbial communities. Here, we applied a top-down microbial community management approach by inhibiting SRB to elucidate their contributions to the microbial community during OM degradation. Based on the highly replicated microcosms (n = 20) of five different incubation stages, we found that many microbial community properties were influenced after inhibiting SRB, including the composition, structure, network, and community assembly processes. We also found a strong coexistence pattern between SRB and other abundant phylogenetic lineages via positive frequency-dependent selection. The relative abundances of the families Synergistaceae, Peptostreptococcaceae, Dethiosulfatibacteraceae, Prolixibacteraceae, Marinilabiliaceae, and Marinifilaceae were simultaneously suppressed after inhibiting SRB during OM degradation. A close association between SRB and the order Marinilabiliales among coexisting taxa was most prominent. They contributed to preserved modules during network successions, were keystone nodes mediating the networked community, and contributed to homogeneous ecological selection. The molybdate tolerance test of the isolated strains of Marinilabiliales showed that inhibited SRB (not the inhibitor of SRB itself) triggered a decrease in the relative abundance of Marinilabiliales. We also found that inhibiting SRB resulted in reduced pH, which is unsuitable for the growth of most Marinilabiliales strains, while the addition of pH buffer (HEPES) in SRB-inhibited treatment microcosms restored the pH and the relative abundances of these bacteria. These data supported that SRB could modify niches to affect species coexistence. IMPORTANCE Our model offers insight into the ecological properties of SRB and identifies a previously undocumented dimension of OM degradation. This targeted inhibition approach could provide a novel framework for illustrating how functional microbial taxa associate the composition and structure of the microbial community, molecular ecological network, and community assembly processes. These findings emphasize the importance of SRB during OM degradation. Our results proved the feasibility of the proposed study framework, inhibiting functional taxa at the community level, for illustrating when and to what extent functional taxa can contribute to ecosystem services.

Metapangenomics of wild and cultivated banana microbiome reveals a plethora of host-associated protective functions

BACKGROUND

Microbiomes are critical to plants, promoting growth, elevating stress tolerance, and expanding the plant's metabolic repertoire with novel defense pathways. However, generally microbiomes within plant tissues, which intimately interact with their hosts, remain poorly characterized. These endospheres have become a focus in banana (Musa spp.)-an important plant for study of microbiome-based disease protection. Banana is important to global food security, while also being critically threatened by pandemic diseases. Domestication and clonal propagation are thought to have depleted protective microbiomes, whereas wild relatives may hold promise for new microbiome-based biological controls. The goal was to compare metapangenomes enriched from 7 Musa genotypes, including wild and cultivated varieties grown in sympatry, to assess the host associations with root and leaf endosphere functional profiles.

RESULTS

Density gradients successfully generated culture-free microbial enrichment, dominated by bacteria, with all together 24,325 species or strains distinguished, and 1.7 million metagenomic scaffolds harboring 559,108 predicted gene clusters. About 20% of sequence reads did not match any taxon databases and ~ 62% of gene clusters could not be annotated to function. Most taxa and gene clusters were unshared between Musa genotypes. Root and corm tissues had significantly richer endosphere communities that were significantly different from leaf communities. Agrobacterium and Rhizobium were the most abundant in all samples while Chitinophagia and Actinomycetia were more abundant in roots and Flavobacteria in leaves. At the bacterial strain level, there were > 2000 taxa unique to each of M. acuminata (AAA genotype) and M. balbisiana (B-genotype), with the latter 'wild' relatives having richer taxa and functions. Gene ontology functional enrichment showed core beneficial functions aligned with those of other plants but also many specialized prospective beneficial functions not reported previously. Some gene clusters with plant-protective functions showed signatures of phylosymbiosis, suggesting long-standing associations or heritable microbiomes in Musa.

CONCLUSIONS

Metapangenomics revealed key taxa and protective functions that appeared to be driven by genotype, perhaps contributing to host resistance differences. The recovery of rich novel taxa and gene clusters provides a baseline dataset for future experiments in planta or in vivo bacterization or engineering of wild host endophytes.

Microbiome rescue: directing resilience of environmental microbial communities

Earth's climate crisis threatens to disrupt ecosystem services and destabilize food security. Microbiome management will be a crucial component of a comprehensive strategy to maintain stable microbinal functions for ecosystems and plants in the face of climate change. Microbiome rescue is the directed, community-level recovery of microbial populations and functions lost after an environmental disturbance. Microbiome rescue aims to propel a resilience trajectory for community functions. Rescue can be achieved via demographic, functional, adaptive, or evolutionary recovery of disturbance-sensitive populations. Various ecological mechanisms support rescue, including dispersal, reactivation from dormancy, functional redundancy, plasticity, and diversification, and these mechanisms can interact. Notably, controlling microbial reactivation from dormancy is a potentially fruitful but underexplored target for rescue.

"What I cannot create, I do not understand": elucidating microbe-microbe interactions to facilitate plant microbiome engineering

Plant-microbe interactions are important for both physiological and pathological processes. Despite the significance of plant-microbe interactions, microbe-microbe interactions themselves represent an important, complex, dynamic network that warrants deeper investigation. To understand how microbe-microbe interactions affect plant microbiomes, one approach is to systematically understand all the factors involved in successful engineering of a microbial community. This follows the physicist Richard Feynman's declaration: "what I cannot create, I do not understand". This review highlights recent studies that focus on aspects that we believe are important for building (ergo understanding) microbe-microbe interactions in the plant environment, including pairwise screening, intelligent application of cross-feeding models, spatial distributions of microbes, and understudied interactions between bacteria and fungi, phages, and protists. We offer a framework for systematic collection and centralized integration of data of plant microbiomes that could organize all the factors that can help ecologists understand microbiomes and help synthetic ecologists engineer beneficial microbiomes.

Core Species Derived from Multispecies Interactions Facilitate the Immobilization of Cadmium

Microbial consortia have opened new avenues for heavy-metal remediation. However, the limited understanding of the overall effect of interspecific interactions on remediation efficacy hinders its application. Here, the effects of multispecies growth and biofilm formation on Cd immobilization were explored from direct and multiple interactions through random combinations of two or three rhizosphere bacteria. In monocultures, Cd stress resulted in an average decrease in planktonic biomass of 26%, but through cooperation, the decrease was attenuated in dual (21%) and triple cultures (13%), possibly involving an increase in surface polysaccharides. More than 65% of the co-cultures exhibited induction of biofilm formation under Cd stress, which further enhanced the role of biofilms in Cd immobilization. Notably, excellent biofilm-forming ability or extensive social induction makes Pseudomonas putida and Brevundimonas diminuta stand out in multispecies biofilm formation and Cd immobilization. These two core species significantly increase the colonization of soil microorganisms on rice roots compared to the control, resulting in a 40% decrease in Cd uptake by rice. Our study enhances the understanding of bacterial interactions under Cd stress and provides a novel strategy for adjusting beneficial soil consortia for heavy-metal remediation.

The potential to produce tropodithietic acid by Phaeobacter inhibens affects the assembly of microbial biofilm communities in natural seawater

Microbial secondary metabolites play important roles in biotic interactions in microbial communities and yet, we do not understand how these compounds impact the assembly and development of microbial communities. To address the implications of microbial secondary metabolite production on biotic interactions in the assembly of natural seawater microbiomes, we constructed a model system where the assembly of a natural seawater biofilm community was influenced by the addition of the marine biofilm forming Phaeobacter inhibens that can produce the antibiotic secondary metabolite tropodithietic acid (TDA), or a mutant incapable of TDA production. Because of the broad antibiotic activity of TDA, we hypothesized that the potential of P. inhibens to produce TDA would strongly affect both biofilm and planktonic community assembly patterns. We show that 1.9 % of the microbial composition variance across both environments could be attributed to the presence of WT P. inhibens, and especially genera of the Bacteriodetes were increased by the presence of the TDA producer. Moreover, network analysis with inferred putative microbial interactions revealed that P. inhibens mainly displayed strong positive associations with genera of the Flavobacteriaceae and Alteromonadaceae, and that P. inhibens acts as a keystone OTU in the biofilm exclusively due to its potential to produce TDA. Our results demonstrate the potential impact of microbial secondary metabolites on microbial interactions and assembly dynamics of complex microbial communities.

Frenemies of the soil: Bacillus and Pseudomonas interspecies interactions

Bacillus and Pseudomonas ubiquitously occur in natural environments and are two of the most intensively studied bacterial genera in the soil. They are often coisolated from environmental samples, and as a result, several studies have experimentally cocultured bacilli and pseudomonads to obtain emergent properties. Even so, the general interaction between members of these genera is virtually unknown. In the past decade, data on interspecies interactions between natural isolates of Bacillus and Pseudomonas has become more detailed, and now, molecular studies permit mapping of the mechanisms behind their pairwise ecology. This review addresses the current knowledge about microbe-microbe interactions between strains of Bacillus and Pseudomonas and discusses how we can attempt to generalize the interaction on a taxonomic and molecular level.

Microbes to support plant health: understanding bioinoculant success in complex conditions

A promising, sustainable way to enhance plant health and productivity is by leveraging beneficial microbes. Beneficial microbes are natural soil residents with proven benefits for plant performance and health. When applied in agriculture to improve crop yield and performance, these microbes are commonly referred to as bioinoculants. Yet, despite their promising properties, bioinoculant efficacy can vary dramatically in the field, hampering their applicability. Invasion of the rhizosphere microbiome is a critical determinant for bioinoculant success. Invasion is a complex phenomenon that is shaped by interactions with the local, resident microbiome and the host plant. Here, we explore all of these dimensions by cross-cutting ecological theory and molecular biology of microbial invasion in the rhizosphere. We refer to the famous Chinese philosopher and strategist Sun Tzu, who believed that solutions for problems require deep understanding of the problems themselves, to review the major biotic factors determining bioinoculant effectiveness.

Determinants of synergistic cell-cell interactions in bacteria

Bacteria are ubiquitous and colonize virtually every conceivable habitat on earth. To achieve this, bacteria require different metabolites and biochemical capabilities. Rather than trying to produce all of the needed materials by themselves, bacteria have evolved a range of synergistic interactions, in which they exchange different commodities with other members of their local community. While it is widely acknowledged that synergistic interactions are key to the ecology of both individual bacteria and entire microbial communities, the factors determining their establishment remain poorly understood. Here we provide a comprehensive overview over our current knowledge on the determinants of positive cell-cell interactions among bacteria. Taking a holistic approach, we review the literature on the molecular mechanisms bacteria use to transfer commodities between bacterial cells and discuss to which extent these mechanisms favour or constrain the successful establishment of synergistic cell-cell interactions. In addition, we analyse how these different processes affect the specificity among interaction partners. By drawing together evidence from different disciplines that study the focal question on different levels of organisation, this work not only summarizes the state of the art in this exciting field of research, but also identifies new avenues for future research.