Structure and evolution of Streptomyces interaction networks in soil and in silico

Factors that influence the caste ratio in a bacterial division of labour

Colonies of the bacterim Streptomyces coelicolor divide labour between cells that specialize in growth and sporulation and cells that specialize in antibiotic production. This division of labour arises owing to costly chromosome deletions in the antibiotic overproducers. However, the spatial distribution and temporal emergence of these mutations in S. coelicolor colonies remain unknown, or whether mutation frequency-which we liken to the caste ratio in social insects-is phenotypically plastic. To elucidate changes in the proportions of specialized cells (measured as the mutation frequency), we sampled S. coelicolor colonies grown under different conditions. Temporally, mutation frequency increased linearly with colony age and size. Spatially, mutations accumulated disproportionately in the colony centre, despite greater growth and sporulation at the periphery. Exposing colonies to sub-inhibitory concentrations of some antibiotics, a competitive cue in Streptomyces, increased mutation frequencies. Finally, direct competition with other Streptomyces that naturally produce antibiotics increased mutation frequencies, while also increasing spore production. Our findings provide insights into the intrinsic and environmental factors driving division of labour in Streptomyces colonies by showing that mutation frequencies are dynamic and responsive to the competitive environment. These results show that chromosome deletions are phenotypically plastic and suggest that Streptomyces can flexibly adjust their caste ratio.This article is part of the theme issue 'Division of labour as key driver of social evolution'.

Intraspecies warfare restricts strain coexistence in human skin microbiomes

Determining why only a fraction of encountered or applied strains engraft in a given person's microbiome is crucial for understanding and engineering these communities. Previous work has established that metabolic competition can restrict colonization success in vivo, but the relevance of bacterial warfare in preventing commensal engraftment has been less explored. Here, we demonstrate that intraspecies warfare presents a significant barrier to strain coexistence in the human skin microbiome by profiling 14,884 pairwise interactions between Staphylococcus epidermidis isolates cultured from eighteen people from six families. We find that intraspecies antagonisms are abundant, mechanistically diverse, independent of strain relatedness, and consistent with rapid evolution via horizontal gene transfer. Critically, these antagonisms are significantly depleted among strains residing on the same person relative to random assemblages, indicating a significant in vivo role. Together, our results emphasize that accounting for intraspecies warfare may be essential to the design of long-lasting probiotic therapeutics.

Taxonomy of Pseudomonas spp. determines interactions with Bacillus subtilis

Bacilli and pseudomonads are among the most well-studied microorganisms commonly found in soil and frequently co-isolated. Isolates from these two genera are frequently used as plant beneficial microorganisms; therefore, their interaction in the plant rhizosphere is relevant for agricultural applications. Despite this, no systematic approach has been employed to assess the coexistence of members from these genera. Here, we screened 720 fluorescent soil isolates for their effects on Bacillus subtilis pellicle formation in two types of media and found a predictor for interaction outcome in Pseudomonas taxonomy. Interactions were context-dependent, and both medium composition and culture conditions strongly influenced interactions. Negative interactions were associated with Pseudomonas capeferrum, Pseudomonas entomophila, and Pseudomonas protegens, and 2,4-diacetylphloroglucinol was confirmed as a strong (but not exclusive) inhibitor of B. subtilis. Non-inhibiting strains were closely related to Pseudomonas trivialis and Pseudomonas lini. Using such a non-inhibiting isolate, Pseudomonas P9_31, which increased B. subtilis pellicle formation demonstrated that the two species were spatially segregated in cocultures. Our study is the first one to propose an overall negative outcome from pairwise interactions between B. subtilis and fluorescent pseudomonads; hence, cocultures comprising members from these groups are likely to require additional microorganisms for coexistence.

IMPORTANCE

There is a strong interest in the microbial ecology field to predict interaction among microorganisms, whether two microbial isolates will promote each other's growth or compete for resources. Numerous studies have been performed based on surveying the available literature or testing phylogenetically diverse sets of species in synthetic communities. Here, a high throughput screening has been performed using 720 Pseudomonas isolates, and their impact on the biofilm formation of Bacillus subtilis was tested. The aim was to determine whether a majority of Pseudomonas will promote or inhibit the biofilms of B. subtilis in the co-cultures. This study reports that Pseudomonas taxonomy is a good predictor of interaction outcome, and only a minority of Pseudomonas isolates promote Bacillus biofilm establishment.

Multi-omics analysis of antagonistic interactions among free-living Pseudonocardia from diverse ecosystems

Actinomycetes are a phylogenetically diverse bacterial group which are widely distributed across terrestrial and aquatic ecosystems. Within this order, the genus Pseudonocardia and their specialised metabolites have been the focus of previous ecological studies due to their antagonistic interactions with other microorganisms and their mutualistic interactions with insects. However, the chemical ecology of free-living Pseudonocardia remains understudied. This study applies a multi-omics approach to investigate the chemical ecology of free-living actinomycetes from the genus Pseudonocardia. In a comparative genomics analysis, it was observed that the biosynthetic gene cluster family distribution was influenced mainly by phylogenetic distance rather than the geographic or ecological origin of strains. This finding was also observed in the mass spectrometry-based metabolomic profiles of nine Pseudonocardia species isolated from marine sediments and two terrestrial species. Antagonist interactions between these 11 species were examined, and matrix-assisted laser desorption/ionisation-mass spectrometry imaging was used to examine in situ chemical interactions between the Southern Ocean strains and their phylogenetically close relatives. Overall, it was demonstrated that phylogeny was the main predictor of antagonistic interactions among free-living Pseudonocardia. Moreover, two features at m/z 441.15 and m/z 332.20 were identified as metabolites related to these interspecies interactions.

Interspecific competition prevents the proliferation of social cheaters in an unstructured environment

Bacterial communities are intricate ecosystems in which various members interact, compete for resources, and influence each other's growth. Antibiotics intensify this complexity, posing challenges in maintaining biodiversity. In this study, we delved into the behavior of kin bacterial communities when subjected to antibiotic perturbations, with a particular focus on how interspecific interactions shape these responses. We hypothesized that social cheating-where resistant strains shield both themselves and neighboring cheaters-obstructed coexistence, especially when kin bacteria exhibited varied growth rates and antibiotic sensitivities. To explore potential pathways to coexistence, we incorporated a third bacterial member, anticipating a shift in the dynamics of community coexistence. Simulations and experimental bacterial communities confirmed our predictions, emphasizing the pivotal role of interspecific competition in promoting coexistence under antibiotic interference. These insights are crucial for understanding bacterial ecosystem stability, interpreting drug-microbiome interactions, and predicting bacterial community adaptations to environmental changes.

Distribution and ecology of the generalist lactic acid bacterium Carnobacterium maltaromaticum in different freshwater habitats: Metabolic and antagonistic abilities

We explored the distribution, metabolic and antagonistic activities of Carnobacterium maltaromaticum, isolated from freshwater locations in Denmark during winter or early spring. This species was widely distributed in such habitats although it was relatively rare in low pH locations. Isolates possessed a diverse metabolism, potentially enabling functional capacities independent of habitat. The intraspecies competition showed a relatively high degree of mostly low-intensity interactions, which overall were not correlated with phylogeny or location. Only a few isolates exhibited broad-spectrum inhibition activity, targeting species from other genera and families, including one isolate that exhibited a broad inhibitory activity due to H2 O2 production. Bioinformatic analyses revealed that the frequency of bacteriocinogenic systems was low, and only one unmodified bacteriocin, piscicolin 126, correlated with phenotypic antagonistic activity. Furthermore, most potential bacteriocin gene complexes were not complete. Overall, this study showed C. maltaromaticum to be a generalist (nomadic) species with a constant presence in freshwater habitats, especially those with pH values >5. General metabolic properties did not suggest a strong degree of adaptation to the freshwater environment, and bacteriocin-mediated antagonistic activities appeared to play a minimal ecological role.

Statistical prediction of microbial metabolic traits from genomes

The metabolic activity of microbial communities is central to their role in biogeochemical cycles, human health, and biotechnology. Despite the abundance of sequencing data characterizing these consortia, it remains a serious challenge to predict microbial metabolic traits from sequencing data alone. Here we culture 96 bacterial isolates individually and assay their ability to grow on 10 distinct compounds as a sole carbon source. Using these data as well as two existing datasets, we show that statistical approaches can accurately predict bacterial carbon utilization traits from genomes. First, we show that classifiers trained on gene content can accurately predict bacterial carbon utilization phenotypes by encoding phylogenetic information. These models substantially outperform predictions made by constraint-based metabolic models automatically constructed from genomes. This result solidifies our current knowledge about the strong connection between phylogeny and metabolic traits. However, phylogeny-based predictions fail to predict traits for taxa that are phylogenetically distant from any strains in the training set. To overcome this we train improved models on gene presence/absence to predict carbon utilization traits from gene content. We show that models that predict carbon utilization traits from gene presence/absence can generalize to taxa that are phylogenetically distant from the training set either by exploiting biochemical information for feature selection or by having sufficiently large datasets. In the latter case, we provide evidence that a statistical approach can identify putatively mechanistic genes involved in metabolic traits. Our study demonstrates the potential power for predicting microbial phenotypes from genotypes using statistical approaches.

Phylogenetically related soil actinomycetes distinguish isolation sites by their metabolic activities

Soil environments are inhabited by microorganisms adapted to its diversified microhabitats. The metabolic activity of individual strains/populations reflects resources available at a particular spot, quality of which may not comply with broad soil characteristics. To explore the potential of individual strains to adapt to particular micro-niches of carbon sources, a set of 331 Actinomycetia strains were collected at ten sites differing in vegetation, soil pH, organic matter content and quality. The strains were isolated on the same complex medium with neutral pH and their metabolites analyzed by UHPLC and LC-MS/MS in spent cultivation medium (metabolic profiles). For all strains, their metabolic profiles correlated with soil pH and organic matter content of the original sites. In comparison, strains phylogeny based on either 16S rRNA or the beta-subunit of DNA-dependent RNA polymerase (rpoB) genes was partially correlated with soil organic matter content but not soil pH at the sites. Antimicrobial activities of strains against Kocuria rhizophila, Escherichia coli, and Saccharomyces cerevisiae were both site- and phylogeny-dependent. The precise adaptation of metabolic profiles to overall sites characteristics was further supported by the production of locally specific bioactive metabolites and suggested that carbon resources represent a significant selection pressure connected to specific antibiotic activities.

Methyl halide transferase-based gas reporters for quantification of filamentous bacteria in microdroplet emulsions

The application of microfluidic techniques in experimental and environmental studies is a rapidly emerging field. Water-in-oil microdroplets can serve readily as controllable micro-vessels for studies that require spatial structure. In many applications, it is useful to monitor cell growth without breaking or disrupting the microdroplets. To this end, optical reporters based on color, fluorescence, or luminescence have been developed. However, optical reporters suffer from limitations when used in microdroplets such as inaccurate readings due to strong background interference or limited sensitivity during early growth stages. In addition, optical detection is typically not amenable to filamentous or biofilm-producing organisms that have significant nonlinear changes in opacity and light scattering during growth. To overcome such limitations, we show that volatile methyl halide gases produced by reporter cells expressing a methyl halide transferase (MHT) can serve as an alternative nonoptical detection approach suitable for microdroplets. In this study, an MHT-labeled Streptomyces venezuelae reporter strain was constructed and characterized. Protocols were established for the encapsulation and incubation of S. venezuelae in microdroplets. We observed the complete life cycle for S. venezuelae including the vegetative expansion of mycelia, mycelial fragmentation, and late-stage sporulation. Methyl bromide (MeBr) production was detected by gas chromatography-mass spectrometry (GC-MS) from S. venezuelae gas reporters incubated in either liquid suspension or microdroplets and used to quantitatively estimate bacterial density. Overall, using MeBr production as a means of quantifying bacterial growth provided a 100- to 1,000-fold increase in sensitivity over optical or fluorescence measurements of a comparable reporter strain expressing fluorescent proteins. IMPORTANCE Quantitative measurement of bacterial growth in microdroplets in situ is desirable but challenging. Current optical reporter systems suffer from limitations when applied to filamentous or biofilm-producing organisms. In this study, we demonstrate that volatile methyl halide gas production can serve as a quantitative nonoptical growth assay for filamentous bacteria encapsulated in microdroplets. We constructed an S. venezuelae gas reporter strain and observed a complete life cycle for encapsulated S. venezuelae in microdroplets, establishing microdroplets as an alternative growth environment for Streptomyces spp. that can provide spatial structure. We detected MeBr production from both liquid suspension and microdroplets with a 100- to 1,000-fold increase in signal-to-noise ratio compared to optical assays. Importantly, we could reliably detect bacteria with densities down to 106 CFU/mL. The combination of quantitative gas reporting and microdroplet systems provides a valuable approach to studying fastidious organisms that require spatial structure such as those found typically in soils.

Genome-resolved metagenomics provides insights into the ecological roles of the keystone taxa in heavy-metal-contaminated soils

Microorganisms that exhibit resistance to environmental stressors, particularly heavy metals, have the potential to be used in bioremediation strategies. This study aimed to explore and identify microorganisms that are resistant to heavy metals in soil environments as potential candidates for bioremediation. Metagenomic analysis was conducted using microbiome metagenomes obtained from the rhizosphere of soil contaminated with heavy metals and mineral-affected soil. The analysis resulted in the recovery of a total of 175 metagenome-assembled genomes (MAGs), 73 of which were potentially representing novel taxonomic levels beyond the genus level. The constructed ecological network revealed the presence of keystone taxa, including Rhizobiaceae, Xanthobacteraceae, Burkholderiaceae, and Actinomycetia. Among the recovered MAGs, 50 were associated with these keystone taxa. Notably, these MAGs displayed an abundance of genes conferring resistance to heavy metals and other abiotic stresses, particularly those affiliated with the keystone taxa. These genes were found to combat excessive accumulation of zinc/manganese, arsenate/arsenite, chromate, nickel/cobalt, copper, and tellurite. Furthermore, the keystone taxa were found to utilize both organic and inorganic energy sources, such as sulfur, arsenic, and carbon dioxide. Additionally, these keystone taxa exhibited the ability to promote vegetation development in re-vegetated mining areas through phosphorus solubilization and metabolite secretion. In summary, our study highlights the metabolic adaptability and ecological significance of microbial keystone taxa in mineral-affected soils. The MAGs associated with keystone taxa exhibited a markedly higher number of genes related to abiotic stress resistance and plant growth promotion compared to non-keystone taxa MAGs.

Construction and Modeling of a Coculture Microplate for Real-Time Measurement of Microbial Interactions

The dynamic structures of microbial communities emerge from the complex network of interactions between their constituent microorganisms. Quantitative measurements of these interactions are important for understanding and engineering ecosystem structure. Here, we present the development and application of the BioMe plate, a redesigned microplate device in which pairs of wells are separated by porous membranes. BioMe facilitates the measurement of dynamic microbial interactions and integrates easily with standard laboratory equipment. We first applied BioMe to recapitulate recently characterized, natural symbiotic interactions between bacteria isolated from the Drosophila melanogaster gut microbiome. Specifically, the BioMe plate allowed us to observe the benefit provided by two Lactobacillus strains to an Acetobacter strain. We next explored the use of BioMe to gain quantitative insight into the engineered obligate syntrophic interaction between a pair of Escherichia coli amino acid auxotrophs. We integrated experimental observations with a mechanistic computational model to quantify key parameters associated with this syntrophic interaction, including metabolite secretion and diffusion rates. This model also allowed us to explain the slow growth observed for auxotrophs growing in adjacent wells by demonstrating that, under the relevant range of parameters, local exchange between auxotrophs is essential for efficient growth. The BioMe plate provides a scalable and flexible approach for the study of dynamic microbial interactions. IMPORTANCE Microbial communities participate in many essential processes from biogeochemical cycles to the maintenance of human health. The structure and functions of these communities are dynamic properties that depend on poorly understood interactions among different species. Unraveling these interactions is therefore a crucial step toward understanding natural microbiota and engineering artificial ones. Microbial interactions have been difficult to measure directly, largely due to limitations of existing methods to disentangle the contribution of different organisms in mixed cocultures. To overcome these limitations, we developed the BioMe plate, a custom microplate-based device that enables direct measurement of microbial interactions, by detecting the abundance of segregated populations of microbes that can exchange small molecules through a membrane. We demonstrated the possible application of the BioMe plate for studying both natural and artificial consortia. BioMe is a scalable and accessible platform that can be used to broadly characterize microbial interactions mediated by diffusible molecules.

Evolution of genome fragility enables microbial division of labor

Division of labor can evolve when social groups benefit from the functional specialization of its members. Recently, a novel means of coordinating the division of labor was found in the antibiotic-producing bacterium Streptomyces coelicolor, where specialized cells are generated through large-scale genomic re-organization. We investigate how the evolution of a genome architecture enables such mutation-driven division of labor, using a multiscale computational model of bacterial evolution. In this model, bacterial behavior-antibiotic production or replication-is determined by the structure and composition of their genome, which encodes antibiotics, growth-promoting genes, and fragile genomic loci that can induce chromosomal deletions. We find that a genomic organization evolves, which partitions growth-promoting genes and antibiotic-coding genes into distinct parts of the genome, separated by fragile genomic loci. Mutations caused by these fragile sites mostly delete growth-promoting genes, generating sterile, and antibiotic-producing mutants from weakly-producing progenitors, in agreement with experimental observations. This division of labor enhances the competition between colonies by promoting antibiotic diversity. These results show that genomic organization can co-evolve with genomic instabilities to enable reproductive division of labor.

Competitive interactions between culturable bacteria are highly non-additive

Microorganisms are found in diverse communities whose structure and function are determined by interspecific interactions. Just as single species seldom exist in isolation, communities as a whole are also constantly challenged and affected by external species. Though much work has been done on characterizing how individual species affect each other through pairwise interactions, the joint effects of multiple species on a single (focal) species remain underexplored. As such, it is still unclear how single-species effects combine to a community-level effect on a species of interest. To explore this relationship, we assayed thousands of communities of two, three, and four bacterial species, measuring the effect of single, pairs of, and trios of 61 affecting species on six different focal species. We found that when multiple species each have a negative effect on a focal species, their joint effect is typically not given by the sum of the effects of individual affecting species. Rather, they are dominated by the strongest individual-species effect. Therefore, while joint effects of multiple species are often non-additive, they can still be derived from the effects of individual species, making it plausible to map complex interaction networks based on pairwise measurements. This finding is important for understanding the fate of species introduced into an occupied environment and is relevant for applications in medicine and agriculture, such as probiotics and biocontrol agents, as well as for ecological questions surrounding migrating and invasive species.

Extracellular DNAses Facilitate Antagonism and Coexistence in Bacterial Competitor-Sensing Interference Competition

Over the last 4 decades, the rate of discovery of novel antibiotics has decreased drastically, ending the era of fortuitous antibiotic discovery. A better understanding of the biology of bacteriogenic toxins potentially helps to prospect for new antibiotics. To initiate this line of research, we quantified antagonists from two different sites at two different depths of soil and found the relative number of antagonists to correlate with the bacterial load and carbon-to-nitrogen (C/N) ratio of the soil. Consecutive studies show the importance of antagonist interactions between soil isolates and the lack of a predicted role for nutrient availability and, therefore, support an in situ role in offense for the production of toxins in environments of high bacterial loads. In addition, the production of extracellular DNAses (exDNases) and the ability to antagonize correlate strongly. Using an in domum-developed probabilistic cellular automaton model, we studied the consequences of exDNase production for both coexistence and diversity within a dynamic equilibrium. Our model demonstrates that exDNase-producing isolates involved in amensal interactions act to stabilize a community, leading to increased coexistence within a competitor-sensing interference competition environment. Our results signify that the environmental and biological cues that control natural-product formation are important for understanding antagonism and community dynamics, structure, and function, permitting the development of directed searches and the use of these insights for drug discovery. IMPORTANCE Ever since the first observation of antagonism by microorganisms by Ernest Duchesne (E. Duchesne, Contribution à l'étude de la concurrence vitale chez les microorganisms. Antagonism entre les moisissures et les microbes, These pour obtenir le grade de docteur en medicine, Lyon, France, 1897), many scientists successfully identified and applied bacteriogenic bioactive compounds from soils to cure infection. Unfortunately, overuse of antibiotics and the emergence of clinical antibiotic resistance, combined with a lack of discovery, have hampered our ability to combat infections. A deeper understanding of the biology of toxins and the cues leading to their production may elevate the success rate of the much-needed discovery of novel antibiotics. We initiated this line of research and discovered that bacterial reciprocal antagonism is associated with exDNase production in isolates from environments with high bacterial loads, while diversity may increase in environments of lower bacterial loads.

Biosynthetic gene cluster profiling predicts the positive association between antagonism and phylogeny in Bacillus

Understanding the driving forces and intrinsic mechanisms of microbial competition is a fundamental question in microbial ecology. Despite the well-established negative correlation between exploitation competition and phylogenetic distance, the process of interference competition that is exemplified by antagonism remains controversial. Here, we studied the genus Bacillus, a commonly recognized producer of multifarious antibiotics, to explore the role of phylogenetic patterns of biosynthetic gene clusters (BGCs) in mediating the relationship between antagonism and phylogeny. Comparative genomic analysis revealed a positive association between BGC distance and phylogenetic distance. Antagonistic tests demonstrated that the inhibition phenotype positively correlated with both phylogenetic and predicted BGC distance, especially for antagonistic strains possessing abundant BGCs. Mutant-based verification showed that the antagonism was dependent on the BGCs that specifically harbored by the antagonistic strain. These findings highlight that BGC-phylogeny coherence regulates the positive correlation between congeneric antagonism and phylogenetic distance, which deepens our understanding of the driving force and intrinsic mechanism of microbial interactions.

Sculpting the soil microbiota

Soil is a living ecosystem, the health of which depends on fine interactions among its abiotic and biotic components. These form a delicate equilibrium maintained through a multilayer network that absorbs certain perturbations and guarantees soil functioning. Deciphering the principles governing the interactions within soils is of critical importance for their management and conservation. Here, we focus on soil microbiota and discuss the complexity of interactions that impact the composition and function of soil microbiota and their interaction with plants. We discuss how physical aspects of soils influence microbiota composition and how microbiota-plant interactions support plant growth and responses to nutrient deficiencies. We predict that understanding the principles determining the configuration and functioning of soil microbiota will contribute to the design of microbiota-based strategies to preserve natural resources and develop more environmentally friendly agricultural practices.

Resolving the conflict between antibiotic production and rapid growth by recognition of peptidoglycan of susceptible competitors

Microbial communities employ a variety of complex strategies to compete successfully against competitors sharing their niche, with antibiotic production being a common strategy of aggression. Here, by systematic evaluation of four non-ribosomal peptides/polyketide (NRPs/PKS) antibiotics produced by Bacillus subtilis clade, we revealed that they acted synergistically to effectively eliminate phylogenetically distinct competitors. The production of these antibiotics came with a fitness cost manifested in growth inhibition, rendering their synthesis uneconomical when growing in proximity to a phylogenetically close species, carrying resistance against the same antibiotics. To resolve this conflict and ease the fitness cost, antibiotic production was only induced by the presence of a peptidoglycan cue from a sensitive competitor, a response mediated by the global regulator of cellular competence, ComA. These results experimentally demonstrate a general ecological concept - closely related communities are favoured during competition, due to compatibility in attack and defence mechanisms.

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

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

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

Wet-dry cycles protect surface-colonizing bacteria from major antibiotic classes

Diverse antibiotic compounds are abundant in microbial habitats undergoing recurrent wet-dry cycles, such as soil, root and leaf surfaces, and the built environment. These antibiotics play a central role in microbial warfare and competition, thus affecting population dynamics and the composition of natural microbial communities. Yet, the impact of wet-dry cycles on bacterial response to antibiotics has been scarcely explored. Using the bacterium E. coli as a model organism, we show through a combination of experiments and computational modeling, that wet-dry cycles protect bacteria from beta-lactams. This is due to the combined effect of several mechanisms including tolerance induced by high salt concentrations and slow cell-growth, which are inherently associated with microscopic surface wetness-a hydration state typical to 'dry' periods. Moreover, we find evidence for a cross-protection effect, where lethal doses of antibiotic considerably increase bacterial survival during the dry periods. This work focuses on beta-lactams, yet similar protection was observed for additional major antibiotic classes. Our findings shed new light on how we understand bacterial response to antibiotics, with broad implications for population dynamics, interspecies interactions, and the evolution of antibiotic resistance in vast terrestrial microbial habitats.

The evolution of strategy in bacterial warfare via the regulation of bacteriocins and antibiotics

Bacteria inhibit and kill one another with a diverse array of compounds, including bacteriocins and antibiotics. These attacks are highly regulated, but we lack a clear understanding of the evolutionary logic underlying this regulation. Here, we combine a detailed dynamic model of bacterial competition with evolutionary game theory to study the rules of bacterial warfare. We model a large range of possible combat strategies based upon the molecular biology of bacterial regulatory networks. Our model predicts that regulated strategies, which use quorum sensing or stress responses to regulate toxin production, will readily evolve as they outcompete constitutive toxin production. Amongst regulated strategies, we show that a particularly successful strategy is to upregulate toxin production in response to an incoming competitor’s toxin, which can be achieved via stress responses that detect cell damage (competition sensing). Mirroring classical game theory, our work suggests a fundamental advantage to reciprocation. However, in contrast to classical results, we argue that reciprocation in bacteria serves not to promote peaceful outcomes but to enable efficient and effective attacks.

Soil actinobacteria tend to have neutral interactions with other co-occurring microorganisms, especially under oligotrophic conditions

Actinobacteria produce a variety of secondary metabolites that can influence the survival or behaviour of other organisms. The understanding of the ecological roles of actinobacteria has significantly improved in the past decades, but a systematic insight into the interactions between actinobacteria and other microbes in nature is warranted. Here, we studied the pairwise effects of actinobacteria on other microbes isolated from red soils under different nutritional conditions. We found that neutral effects dominated the interactions, accounting for 68.1% of the interactions in eutrophic conditions and for a significantly higher proportion (86.2%) in oligotrophic conditions. High nutrient levels boosted active metabolism of actinobacteria and generally made them more aggressive, supporting the stress gradient hypothesis. The secondary metabolites produced by actinobacteria played a pivotal role in interference competition with other microbes, of which the role of desferrioxamine siderophores could not be ignored. Niche overlap seemed to be another cause of competition, notably under oligotrophic conditions. Moreover, the large-scale phylogeny had a much greater impact on the interaction than the location origin of the microbes. These results provide an understanding of the coexistence of actinobacteria with other microbes in nature and suggest neutrality as a key mechanism for maintaining microbial diversity in soils.

Roadmap on biology in time varying environments

Biological organisms experience constantly changing environments, from sudden changes in physiology brought about by feeding, to the regular rising and setting of the Sun, to ecological changes over evolutionary timescales. Living organisms have evolved to thrive in this changing world but the general principles by which organisms shape and are shaped by time varying environments remain elusive. Our understanding is particularly poor in the intermediate regime with no separation of timescales, where the environment changes on the same timescale as the physiological or evolutionary response. Experiments to systematically characterize the response to dynamic environments are challenging since such environments are inherently high dimensional. This roadmap deals with the unique role played by time varying environments in biological phenomena across scales, from physiology to evolution, seeking to emphasize the commonalities and the challenges faced in this emerging area of research.

Ancient Antibiotics, Ancient Resistance

As the spread of antibiotic resistance threatens our ability to treat infections, avoiding the return of a preantibiotic era requires the discovery of new drugs. While therapeutic use of antibiotics followed by the inevitable selection of resistance is a modern phenomenon, these molecules and the genetic determinants of resistance were in use by environmental microbes long before humans discovered them. In this review, we discuss evidence that antibiotics and resistance were present in the environment before anthropogenic use, describing techniques including direct sampling of ancient DNA and phylogenetic analyses that are used to reconstruct the past. We also pay special attention to the ecological and evolutionary forces that have shaped the natural history of antibiotic biosynthesis, including a discussion of competitive versus signaling roles for antibiotics, proto-resistance, and substrate promiscuity of biosynthetic and resistance enzymes. Finally, by applying an evolutionary lens, we describe concepts governing the origins and evolution of biosynthetic gene clusters and cluster-associated resistance determinants. These insights into microbes' use of antibiotics in nature, a game they have been playing for millennia, can provide inspiration for discovery technologies and management strategies to combat the growing resistance crisis.

Competition Sensing Changes Antibiotic Production in Streptomyces

Bacteria secrete antibiotics to inhibit their competitors, but the presence of competitors can determine whether these toxins are produced. Here, we study the role of the competitive and resource environment on antibiotic production in Streptomyces, bacteria renowned for their production of antibiotics.

One of the most important ways that bacteria compete for resources and space is by producing antibiotics that inhibit competitors. Because antibiotic production is costly, the biosynthetic gene clusters coordinating their synthesis are under strict regulatory control and often require “elicitors” to induce expression, including cues from competing strains. Although these cues are common, they are not produced by all competitors, and so the phenotypes causing induction remain unknown. By studying interactions between 24 antibiotic-producing strains of streptomycetes, we show that strains commonly inhibit each other’s growth and that this occurs more frequently if strains are closely related. Next, we show that antibiotic production is more likely to be induced by cues from strains that are closely related or that share secondary metabolite biosynthetic gene clusters (BGCs). Unexpectedly, antibiotic production is less likely to be induced by competitors that inhibit the growth of a focal strain, indicating that cell damage is not a general cue for induction. In addition to induction, antibiotic production often decreases in the presence of a competitor, although this response was not associated with genetic relatedness or overlap in BGCs. Finally, we show that resource limitation increases the chance that antibiotic production declines during competition. Our results reveal the importance of social cues and resource availability in the dynamics of interference competition in streptomycetes.

Building clone-consistent ecosystem models

Many ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency. Although clone consistency can always be achieved with sufficient assumptions, we argue that it is important to explicitly name and consider the assumptions made: They may not be justified or limit the applicability of models and the generality of the results obtained with them. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities. Finally, our insights point to new relevant forms of general models for theoretical ecology. Our framework thus provides a systematic way of comprehending ecological models, which can guide a wide range of studies.

Structured environments foster competitor coexistence by manipulating interspecies interfaces

Natural environments, like soils or the mammalian gut, frequently contain microbial consortia competing within a niche, wherein many species contain genetically encoded mechanisms of interspecies competition. Recent computational work suggests that physical structures in the environment can stabilize local competition between species that would otherwise be subject to competitive exclusion under isotropic conditions. Here we employ Lotka-Volterra models to show that interfacial competition localizes to physical structures, stabilizing competitive ecological networks of many species, even with significant differences in the strength of competitive interactions between species. Within a limited range of parameter space, we show that for stable communities the length-scale of physical structure inversely correlates with the width of the distribution of competitive fitness, such that physical environments with finer structure can sustain a broader spectrum of interspecific competition. These results highlight the potentially stabilizing effects of physical structure on microbial communities and lay groundwork for engineering structures that stabilize and/or select for diverse communities of ecological, medical, or industrial utility.

The biogeography of Streptomyces in New Zealand enabled by high-throughput sequencing of genus-specific rpoB amplicons

We evaluated Streptomyces biogeography in soils along a 1200 km latitudinal transect across New Zealand (NZ). Streptomyces diversity was examined using high-throughput sequencing of rpoB amplicons generated with a Streptomyces specific primer set. We detected 1287 Streptomyces rpoB operational taxonomic units (OTUs) with 159 ± 92 (average ± SD) rpoB OTUs per site. Only 12% (n = 149) of these OTUs matched rpoB sequences from cultured specimens (99% nucleotide identity cutoff). Streptomyces phylogenetic diversity (Faith's PD) was correlated with soil pH, mean annual temperature and plant community richness (Spearman's r: 0.77, 0.64 and -0.79, respectively; P < 0.05), but not with latitude. In addition, soil pH and plant community richness both explained significant variation in Streptomyces beta diversity. Streptomyces communities exhibited both high dissimilarity and strong dominance of one or a few species at each site. Taken together, these results suggest that dispersal limitation due to competitive interactions limits the colonization success of spores that relocate to new sites. Cultivated Streptomyces isolates represent a major source of clinically useful antibiotics, but only a small fraction of extant diversity within the genus have been identified and most species of Streptomyces have yet to be described.

Hypergraph Clustering Based on Game-Theory for Mining Microbial High-Order Interaction Module

Microbial community is ubiquitous in nature, which has a great impact on the living environment and human health. All these effects of microbial communities on the environment and their hosts are often referred to as the functions of these communities, which depend largely on the composition of the communities. The study of microbial higher-order module can help us understand the dynamic development and evolution process of microbial community and explore community function. Considering that traditional clustering methods depend on the number of clusters or the influence of data that does not belong to any cluster, this paper proposes a hypergraph clustering algorithm based on game theory to mine the microbial high-order interaction module (HCGI), and the hypergraph clustering problem naturally turns into a clustering game problem, the partition of network modules is transformed into finding the critical point of evolutionary stability strategy (ESS). The experimental results show HCGI does not depend on the number of classes, and can get more conservative and better quality microbial clustering module, which provides reference for researchers and saves time and cost. The source code of HCGI in this paper can be downloaded from https://github.com/ylm0505/HCGI.

Inhibitions Dominate but Stimulations and Growth Rescues Are Not Rare Among Bacterial Isolates from Grains of Forest Soil

Soil is a complex environment made of multiple microhabitats in which a wide variety of microorganisms co-exist and interact to form dynamic communities. While the abiotic factors that regulate the structure of these communities are now quite well documented, our knowledge of how bacteria interact with each other within these communities is still insufficient. Literature reveals so far contradictory results and is mainly focused on antagonistic interactions. To start filling this gap, we isolated 35 different bacterial isolates from grains of soil assuming that, at this scale, these bacteria would have been likely interacting in their natural habitat. We tested pairwise interactions between all isolates from each grain and scored positive and negative interactions. We compared the effects of simultaneous versus delayed co-inoculations, allowing or not to a strain to modify first its environment. One hundred fifty-seven interactions, either positive or negative, were recorded among the 525 possible one's. Members of the Bacillus subtilis, Pseudomonas and Streptomyces genera were responsible for most inhibitions, while positive interactions occurred between isolates of the Bacillales order and only in delayed inoculation conditions. Antagonist isolates had broad spectral abilities to acquire nutrients from organic and inorganic matter, while inhibited isolates tended to have little potentials. Despite an overall domination of antagonistic interactions (87%), a third of the isolates were able to stimulate or rescue the growth of other isolates, suggesting that cooperation between bacteria may be underestimated.

Investigation of the Ecological Roles of Putative Keystone Taxa during Tailing Revegetation

Metal contamination released from tailings is a global environmental concern. Although phytoremediation is a promising remediation method, its practice is often impeded by the adverse tailing geochemical conditions, which suppress biological activities. The ecosystem services provided by indigenous microorganisms could alter environmental conditions and facilitate revegetation in tailings. During the process, the keystone taxa of the microbial community are assumed an essential role in regulating the community composition and functions. The identity and the environmental functions of the keystone taxa during tailing revegetation, however, remain unelucidated. The current study compared the microbial community composition and interactions of two contrasting stibnite (Sb₂S₃) tailings, one revegetated and one unvegetated. The microbial interaction networks and keystone taxa were significantly different in the two tailings. Similar keystone taxa were also identified in other revegetated tailings, but not in their corresponding unvegetated tailings. Metagenome-assembled genomes (MAGs) indicated that the keystone taxa in the revegetated tailing may use both organic and inorganic energy sources (e.g., sulfur, arsenic, and antimony). They could also facilitate plant growth since a number of plant-growth-promoting genes, including phosphorus solubilization and siderophore production genes, were encoded. The current study suggests that keystone taxa may play important roles in tailing revegetation by providing nutrients, such as P and Fe, and promoting plant growth.

The Evolution and Ecology of Bacterial Warfare

Bacteria have evolved a wide range of mechanisms to harm and kill their competitors, including chemical, mechanical and biological weapons. Here we review the incredible diversity of bacterial weapon systems, which comprise antibiotics, toxic proteins, mechanical weapons that stab and pierce, viruses, and more. The evolution of bacterial weapons is shaped by many factors, including cell density and nutrient abundance, and how strains are arranged in space. Bacteria also employ a diverse range of combat behaviours, including pre-emptive attacks, suicidal attacks, and reciprocation (tit-for-tat). However, why bacteria carry so many weapons, and why they are so often used, remains poorly understood. By comparison with animals, we argue that the way that bacteria live - often in dense and genetically diverse communities - is likely to be key to their aggression as it encourages them to dig in and fight alongside their clonemates. The intensity of bacterial aggression is such that it can strongly affect communities, via complex coevolutionary and eco-evolutionary dynamics, which influence species over space and time. Bacterial warfare is a fascinating topic for ecology and evolution, as well as one of increasing relevance. Understanding how bacteria win wars is important for the goal of manipulating the human microbiome and other important microbial systems.

Stabilization of extensive fine-scale diversity by ecologically driven spatiotemporal chaos

It has recently become apparent that the diversity of microbial life extends far below the species level to the finest scales of genetic differences. Remarkably, extensive fine-scale diversity can coexist spatially. How is this diversity stable on long timescales, despite selective or ecological differences and other evolutionary processes? Most work has focused on stable coexistence or assumed ecological neutrality. We present an alternative: extensive diversity maintained by ecologically driven spatiotemporal chaos, with no assumptions about niches or other specialist differences between strains. We study generalized Lotka-Volterra models with antisymmetric correlations in the interactions inspired by multiple pathogen strains infecting multiple host strains. Generally, these exhibit chaos with increasingly wild population fluctuations driving extinctions. But the simplest spatial structure, many identical islands with migration between them, stabilizes a diverse chaotic state. Some strains (subspecies) go globally extinct, but many persist for times exponentially long in the number of islands. All persistent strains have episodic local blooms to high abundance, crucial for their persistence as, for many, their average population growth rate is negative. Snapshots of the abundance distribution show a power law at intermediate abundances that is essentially indistinguishable from the neutral theory of ecology. But the dynamics of the large populations are much faster than birth-death fluctuations. We argue that this spatiotemporally chaotic "phase" should exist in a wide range of models, and that even in rapidly mixed systems, longer-lived spores could similarly stabilize a diverse chaotic phase.

Mining the Biosynthetic Potential for Specialized Metabolism of a Streptomyces Soil Community

The diversity and distribution of specialized metabolite gene clusters within a community of bacteria living in the same soil habitat are poorly documented. Here we analyzed the genomes of 8 Streptomyces isolated at micro-scale from a forest soil that belong to the same species or to different species. The results reveal high levels of diversity, with a total of 261 biosynthesis gene clusters (BGCs) encoding metabolites such as terpenes, polyketides (PKs), non-ribosomal peptides (NRPs) and ribosomally synthesized and post-translationally modified peptides (RiPPs) with potential bioactivities. A significant part of these BGCs (n = 53) were unique to only one strain when only 5 were common to all strains. The metabolites belong to very diverse chemical families and revealed that a large diversity of metabolites can potentially be produced in the community. Although that analysis of the global metabolome using GC-MS revealed that most of the metabolites were shared between the strains, they exhibited a specific metabolic pattern. We also observed that the presence of these accessory pathways might result from frequent loss and gain of genes (horizontal transfer), showing that the potential of metabolite production is a dynamic phenomenon in the community. Sampling Streptomyces at the community level constitutes a good frame to discover new biosynthetic pathways and it appears as a promising reservoir for the discovery of new bioactive compounds.

Toward a dynamical understanding of microbial communities

The challenge of moving beyond descriptions of microbial community composition to the point where understanding underlying eco-evolutionary dynamics emerges is daunting. While it is tempting to simplify through use of model communities composed of a small number of types, there is a risk that such strategies fail to capture processes that might be specific and intrinsic to complexity of the community itself. Here, we describe approaches that embrace this complexity and show that, in combination with metagenomic strategies, dynamical insight is increasingly possible. Arising from these studies is mounting evidence of rapid eco-evolutionary change among lineages and a sense that processes, particularly those mediated by horizontal gene transfer, not only are integral to system function, but are central to long-term persistence. That such dynamic, systems-level insight is now possible, means that the study and manipulation of microbial communities can move to new levels of inquiry. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Nested structure of intraspecific competition network in Carnobacterium maltaromaticum

While competition targeting food-borne pathogens is being widely documented, few studies have focused on competition among non-pathogenic food bacteria. Carnobacterium maltaromaticum is a genetically diverse lactic acid bacterium known for comprising several bacteriocinogenic strains with bioprotective potentialities against the food-borne pathogen Listeria monocytogenes. The aim of our study is to examine the network properties of competition among a collection of 73 strains of C. maltaromaticum and to characterize their individual interaction potential. The performed high-throughput competition assays, investigating 5 329 pairwise interactions, showed that intraspecific competition was major in C. maltaromaticum with approximately 56% of the sender strains antagonizing at least one receiver strain. A high diversity of inhibitory and sensitivity spectra was identified along with a majority of narrow inhibitory as well as sensitivity spectra. Through network analysis approach, we determined the highly nested architecture of C. maltaromaticum competition network, thus showing that competition in this species is determined by both the spectrum width of the inhibitory activity of sender strains and the spectrum width of the sensitivity of receiver strains. This study provides knowledge of the competition network in C. maltaromaticum that could be used in rational assembly of compatible microbial strains for the design of mixed starter cultures.

Ecological insights into the underlying evolutionary patterns of biofilm formation from biological wastewater treatment systems: Red or Black Queen Hypothesis?

Interspecies interactions and phylogenetic distances were studied to reveal the underlying evolutionary adaptations of biofilms sourced from wastewater treatment processes. Based on 380 pairwise cocultures of 40 strains from two microbial aggregates (surface-attached and mobile aggregates [flocs]) at two substrate concentrations (LB broth and 0.1× LB broth), interspecies interactions were explored using biofilm classification schemes. There was a strong source-dependence of biofilm development formed by the monocultures, that is, a higher biofilm formation potential for strains from attached aggregates than for those from sludge flocs at both substrate concentrations. Interestingly, the results showed that total biofilm reduction was dominant in the dual-species biofilm sourced from flocs in both LB broth (67.37%) and 0.1× LB broth (64.21%), indicating high interspecific competition in mobile aggregates and the independence of substrate concentrations. However, biofilm reduction was higher (33.68%) than induction (19.37%) for the biofilms formed by surface-attached aggregates in LB broth, while the opposite trend was apparent in 0.1× LB broth, suggesting the occurrence of indeterministic processes for biofilm formation and important roles of substrate concentrations. In addition, the more closely related phylogenetic relationships of cocultures from mobile aggregates were consistent with higher competition compared with those from surface-attached aggregates. Overall, the underlying evolutionary patterns of biofilms formed from mobile aggregates consistently followed the essence of the "Red Queen Hypothesis," while biofilms developed from surface-attached aggregates were not deterministic. This study advanced our understanding of biofilm-related treatment processes using the principles of microbial ecology.

Insights into Antagonistic Interactions of Multidrug Resistant Bacteria in Mangrove Sediments from the South Indian State of Kerala

Antibiotic resistance is a global issue which is magnified by interspecies horizontal gene transfer. Understanding antibiotic resistance in bacteria in a natural setting is crucial to check whether they are multidrug resistant (MDR) and possibly avoid outbreaks. In this study, we have isolated several antibiotic-resistant bacteria (ARB) (n = 128) from the mangroves in Kerala, India. ARBs were distributed based on antibiotics (p = 1.6 × 10^-5). The 16S rRNA gene characterization revealed dominance by Bacillaceae (45%), Planococcaceae (22.5%), and Enterobacteriaceae (17.5%). A high proportion of the isolates were MDR (75%) with maximum resistance to methicillin (70%). Four isolates affiliated to plant-growth promoters, probiotics, food, and human pathogens were resistant to all antibiotics indicating the seriousness and prevalence of MDR. A significant correlation (R = 0.66; p = 2.5 × 10^-6) was observed between MDR and biofilm formation. Antagonist activity was observed in 62.5% isolates. Gram-positive isolates were more susceptible to antagonism (75.86%) than gram-negative (36.36%) isolates. Antagonism interactions against gram-negative isolates were lower (9.42%) when compared to gram-positive isolates (89.85%). Such strong antagonist activity can be harnessed for inspection of novel antimicrobial mechanisms and drugs. Our study shows that MDR with strong biofilm formation is prevalent in natural habitat and if acquired by deadly pathogens may create havoc in public health.

Higher-Order Interaction between Species Inhibits Bacterial Invasion of a Phototroph-Predator Microbial Community

The composition of an ecosystem is thought to be important for determining its resistance to invasion. Studies of natural ecosystems, from plant to microbial communities, have found that more diverse communities are more resistant to invasion. In some cases, more diverse communities resist invasion by more completely consuming the resources necessary for the invader. We show that Escherichia coli can successfully invade cultures of the alga Chlamydomonas reinhardtii (phototroph) or the ciliate Tetrahymena thermophila (predator) but cannot invade a community where both are present. The invasion resistance of the algae-ciliate community arises from a higher-order interaction between species (interaction modification) that is unrelated to resource consumption. We show that the mode of this interaction is the algal inhibition of bacterial aggregation, which leaves bacteria vulnerable to predation. This mode requires both the algae and the ciliate to be present and provides an example of invasion resistance through an interaction modification.

Evolutionary dynamics of natural product biosynthesis in bacteria

Covering: 2008 up to 2019The forces of biochemical adaptive evolution operate at the level of genes, manifesting in complex phenotypes and the global biodiversity of proteins and metabolites. While evolutionary histories have been deciphered for some other complex traits, the origins of natural product biosynthesis largely remain a mystery. This fundamental knowledge gap is surprising given the many decades of research probing the genetic, chemical, and biophysical mechanisms of bacterial natural product biosynthesis. Recently, evolutionary thinking has begun to permeate this otherwise mechanistically dominated field. Natural products are now sometimes referred to as 'specialized' rather than 'secondary' metabolites, reinforcing the importance of their biological and ecological functions. Here, we review known evolutionary mechanisms underlying the overwhelming chemical diversity of bacterial secondary metabolism, focusing on enzyme promiscuity and the evolution of enzymatic domains that enable metabolic traits. We discuss the mechanisms that drive the assembly of natural product biosynthetic gene clusters and propose formal definitions for 'specialized' and 'secondary' metabolism. We further explore how biosynthetic gene clusters evolve to synthesize related molecular species, and in turn how the biological and ecological roles that emerge from metabolic diversity are acted on by selection. Finally, we reconcile chemical, functional, and genetic data into an evolutionary model, the dynamic chemical matrix evolutionary hypothesis, in which the relationships between chemical distance, biomolecular activity, and relative fitness shape adaptive landscapes.

Inhibitory interaction networks among coevolved Streptomyces populations from prairie soils

Soil microbes live within highly complex communities, where community composition, function, and evolution are the product of diverse interactions among community members. Analysis of the complex networks of interactions within communities has the potential to shed light on community stability, functioning, and evolution. However, we have little understanding of the variation in interaction networks among coevolved soil populations. We evaluated networks of antibiotic inhibitory interactions among sympatric Streptomyces communities from prairie soil. Inhibition networks differed significantly in key network characteristics from expectations under null models, largely reflecting variation among Streptomyces in the number of sympatric populations that they inhibited. Moreover, networks of inhibitory interactions within Streptomyces communities differed significantly from each other, suggesting unique network structures among soil communities from different locations. Analyses of tri-partite interactions (triads) showed that some triads were significantly over- or under- represented, and that communities differed in ‘preferred’ triads. These results suggest that local processes generate distinct structures among sympatric Streptomyces inhibition networks in soil. Understanding the properties of microbial interaction networks that generate competitive and functional capacities of soil communities will shed light on the ecological and coevolutionary history of sympatric populations, and provide a foundation for more effective management of inhibitory capacities of soil microbial communities.

Large-scale identification of pathogen essential genes during coinfection with sympatric and allopatric microbes

Recent evidence suggests that the genes an organism needs to survive in an environment drastically differ when alone or in a community. However, it is not known if there are universal functions that enable microbes to persist in a community and if there are functions specific to interactions between microbes native to the same (sympatric) or different (allopatric) environments. Here, we ask how the essential functions of the oral pathogen Aggregatibacter actinomycetemcomitans change during pairwise coinfection in a murine abscess with each of 15 microbes commonly found in the oral cavity and 10 microbes that are not. A. actinomycetemcomitans was more abundant when coinfected with allopatric than with sympatric microbes, and this increased fitness correlated with expanded metabolic capacity of the coinfecting microbes. Using transposon sequencing, we discovered that 33% of the A. actinomycetemcomitans genome is required for coinfection fitness. Fifty-nine "core" genes were required across all coinfections and included genes necessary for aerobic respiration. The core genes were also all required in monoinfection, indicating the essentiality of these genes cannot be alleviated by a coinfecting microbe. Furthermore, coinfection with some microbes, predominately sympatric species, induced the requirement for over 100 new community-dependent essential genes. In contrast, in other coinfections, predominately with nonoral species, A. actinomycetemcomitans required 50 fewer genes than in monoinfection, demonstrating that some allopatric microbes can drastically alleviate gene essentialities. These results expand our understanding of how diverse microbes alter growth and gene essentiality within polymicrobial infections.

Massive Gene Flux Drives Genome Diversity between Sympatric Streptomyces Conspecifics

Horizontal gene transfer is a rapid and efficient way to diversify bacterial gene pools. Currently, little is known about this gene flux within natural soil populations. Using comparative genomics of Streptomyces strains belonging to the same species and isolated at microscale, we reveal frequent transfer of a significant fraction of the pangenome. We show that it occurs at a time scale enabling the population to diversify and to cope with its changing environment, notably, through the production of public goods.

In this work, by comparing genomes of closely related individuals of Streptomyces isolated at a spatial microscale (millimeters or centimeters), we investigated the extent and impact of horizontal gene transfer in the diversification of a natural Streptomyces population. We show that despite these conspecific strains sharing a recent common ancestor, all harbored significantly different gene contents, implying massive and rapid gene flux. The accessory genome of the strains was distributed across insertion/deletion events (indels) ranging from one to several hundreds of genes. Indels were preferentially located in the arms of the linear chromosomes (ca. 12 Mb) and appeared to form recombination hot spots. Some of them harbored biosynthetic gene clusters (BGCs) whose products confer an inhibitory capacity and may constitute public goods that can favor the cohesiveness of the bacterial population. Moreover, a significant proportion of these variable genes were either plasmid borne or harbored signatures of actinomycete integrative and conjugative elements (AICEs). We propose that conjugation is the main driver for the indel flux and diversity in Streptomyces populations.

Spatial structure increases the benefits of antibiotic production in Streptomyces

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

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

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

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

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

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

A chemical defence against phage infection

The arms race between bacteria and the phages that infect them drives the continual evolution of diverse anti-phage defences. Previously described anti-phage systems have highly varied defence mechanisms^1-11; however, all mechanisms rely on protein components to mediate defence. Here we report a chemical anti-phage defence system that is widespread in Streptomyces. We show that three naturally produced molecules that insert into DNA are able to block phage replication, whereas molecules that target DNA by other mechanisms do not. Because double-stranded DNA phages are the most numerous group in the biosphere and the production of secondary metabolites by bacteria is ubiquitous¹², this mechanism of anti-phage defence probably has a major evolutionary role in shaping bacterial communities.

Additivity of inhibitory effects in multidrug combinations

From natural ecology^1-4 to clinical therapy^5-8, cells are often exposed to mixtures of multiple drugs. Two competing null models are used to predict the combined effect of drugs: response additivity (Bliss) and dosage additivity (Loewe)^9-11. Here, noting that these models diverge with increased number of drugs, we contrast their predictions with growth measurements of four phylogenetically distant microorganisms including Escherichia coli, Staphylococcus aureus, Enterococcus faecalis and Saccharomyces cerevisiae, under combinations of up to ten different drugs. In all species, as the number of drugs increases, Bliss maintains accuracy while Loewe systematically loses its predictive power. The total dosage required for growth inhibition, which Loewe predicts should be fixed, steadily increases with the number of drugs, following a square-root scaling. This scaling is explained by an approximation to Bliss where, inspired by R. A. Fisher's classical geometric model¹², dosages of independent drugs add up as orthogonal vectors rather than linearly. This dose-orthogonality approximation provides results similar to Bliss, yet uses the dosage language as in Loewe and is hence easier to implement and intuit. The rejection of dosage additivity in favour of effect additivity and dosage orthogonality provides a framework for understanding how multiple drugs and stressors add up in nature and the clinic.

Control of Specialized Metabolism by Signaling and Transcriptional Regulation: Opportunities for New Platforms for Drug Discovery?

Specialized metabolites are bacterially produced small molecules that have an extraordinary diversity of important biological activities. They are useful as biochemical probes of living systems, and they have been adapted for use as drugs for human afflictions ranging from infectious diseases to cancer. The biosynthetic genes for these molecules are controlled by a dense network of regulatory mechanisms: Cell-cell signaling and nutrient sensing are conspicuous features of this network. While many components of these mechanisms have been identified, important questions about their biological roles remain shrouded in mystery. In addition to identifying new molecules and solving their mechanisms of action (a central preoccupation in this field), we suggest that addressing questions of quorum sensing versus diffusion sensing and identifying the dominant nutritional and environmental cues for specialized metabolism are important directions for research.

Micro-scale intermixing: a requisite for stable and synergistic co-establishment in a four-species biofilm

Microorganisms frequently coexist in complex multispecies communities, where they distribute non-randomly, reflective of the social interactions that occur. It is therefore important to understand how social interactions and local spatial organization influences multispecies biofilm succession. Here the localization of species pairs was analyzed in three dimensions in a reproducible four-species biofilm model, to study the impact of spatial positioning of individual species on the temporal development of the community. We found, that as the biofilms developed, species pairs exhibited distinct intermixing patterns unique to the four-member biofilms. Higher biomass and more intermixing were found in four-species biofilms compared to biofilms with fewer species. Intriguingly, in local regions within the four member biofilms where Microbacterium oxydans was scant, both biomass and intermixing of all species were lowered, compared to regions where M. oxydans was present at typical densities. Our data suggest that Xanthomonas retroflexus and M. oxydans, both low abundant biofilm-members, intermixed continuously during the development of the four-species biofilm, hereby facilitating their own establishment. In turn, this seems to have promoted distinct spatial organization of Stenotrophomonas rhizophila and Paenibacillus amylolyticus enabling enhanced growth of all four species. Here local intermixing of bacteria advanced the temporal development of a multi-species biofilm.