Microbial coexistence through chemical-mediated interactions

Engineering the T6SS of Pseudomonas for targeted delivery of antibacterial and antifungal effectors

BACKGROUND

Bacteria employ diverse molecular systems, such as the type VI secretion system (T6SS) to outcompete other microorganisms and adapt to ecological niches. The T6SS is a versatile nanomachine capable of delivering toxic effectors into neighboring cells, providing advantages in bacterial interactions. In recent years, T6SSs have been proposed as promising tools for engineering selective antimicrobial platforms.

RESULTS

In this study, we successfully engineered Pseudomonas putida KT2440 to heterologously express and release T6SS effectors. The expression of Tse1, an effector from Pseudomonas chlororaphis, induced sporulation in plant-beneficial Bacillus strains via a T6SS-dependent mechanism, particularly when Tse1 was paired with a PAAR protein. Similarly, the engineered strain effectively inhibited Aeromonas hydrophila growth using the phospholipase toxin TplE from Pseudomonas aeruginosa. Furthermore, antifungal activity was achieved by coexpressing Tfe2, an effector from Serratia marcescens, with VgrGs, resulting in increased reactive oxygen species levels and cellular damage in Botrytis cinerea. Importantly, the T6SS was also employed to deliver non-T6SS effectors such as chitosanase, demonstrating its versatility in degrading fungal cell walls.

CONCLUSIONS

Our findings demonstrate that the T6SS can be engineered to deliver both canonical and noncanonical effectors, providing a robust platform for targeted antibacterial and antifungal applications. The modularity of the system enables precise pairing of effectors with structural components such as VgrG and PAAR proteins, optimizing delivery efficiency. These engineered systems provide new opportunities for the development of biocontrol strategies in agriculture, microbiome modulation, and potential therapeutic applications. Future advancements in bioinformatics and protein engineering will further increase the specificity and functionality of T6SS-based delivery systems, offering innovative tools for managing microbial ecosystems and addressing global challenges in health and agriculture.

Can a microbial community become an evolutionary individual?

Microbial communities provide crucial services for human well-being, driving an interest in designing and controlling them towards optimised or novel functions. Unfortunately, promising strategies such as community breeding - sometimes referred to as 'directed evolution' or 'artificial community selection' - have shown limited success. A key issue is that microbial communities do not reliably exhibit heritable variation, limiting their capacity for adaptive evolution. In other words, microbial communities are not evolutionary individuals. Here, we provide an overview of the literature on evolutionary transitions in individuality and, with insights from paradigmatic organisms, build a multidimensional space in which the individuality of a multispecies community is characterised by three ecological traits: positive interactions, functional integration, and entrenchment. We then place microbial communities within this individuality space, explore how they can be directed toward increased individuality, and discuss how this perspective can help improve our approach to community breeding.

Disentangling the feedback loops driving spatial patterning in microbial communities

The properties of multispecies biofilms are determined by how species are arranged in space. How these patterns emerge is a complex and largely unsolved problem. Here, we synthesize the known factors affecting pattern formation, identify the interdependencies and feedback loops coupling them, and discuss approaches to disentangle their effects. Finally, we propose an interdisciplinary research program that could create a predictive understanding of pattern formation in microbial communities.

The architecture of theory and data in microbiome design: towards an S-matrix for microbiomes

Designing microbiomes for applications in health, bioengineering, and sustainability is intrinsically linked to a fundamental theoretical understanding of the rules governing microbial community assembly. Microbial ecologists have used a range of mathematical models to understand, predict, and control microbiomes, ranging from mechanistic models, putting microbial populations and their interactions as the focus, to purely statistical approaches, searching for patterns in empirical and experimental data. We review the success and limitations of these modeling approaches when designing novel microbiomes, especially when guided by (inevitably) incomplete experimental data. Although successful at predicting generic patterns of community assembly, mechanistic and phenomenological models tend to fall short of the precision needed to design and implement specific functionality in a microbiome. We argue that to effectively design microbiomes with optimal functions in diverse environments, ecologists should combine data-driven techniques with mechanistic models - a middle, third way for using theory to inform design.

Human microbiota peptides: important roles in human health

Covering: 1974 to 2024Human microbiota consist of a diverse array of microorganisms, such as bacteria, Eukarya, archaea, and viruses, which populate various parts of the human body and live in a cooperatively beneficial relationship with the host. They play a crucial role in supporting the functional balance of the microbiome. The coevolutionary progression has led to the development of specialized metabolites that have the potential to substitute traditional antibiotics in combating global health challenges. Although there has been a lot of research on the human microbiota, there is a considerable lack of understanding regarding the wide range of peptides that these microbial populations produce. Particularly noteworthy are the antibiotics that are uniquely produced by the human microbiome, especially by bacteria, to protect against invasive infections. This review seeks to fill this knowledge gap by providing a thorough understanding of various peptides, along with their in-depth biological importance in terms of human disorders. Advancements in genomics and the understanding of molecular mechanisms that control the interactions between microbiota and hosts have made it easier to find peptides that come from the human microbiome. We hope that this review will serve as a basis for developing new therapeutic approaches and personalized healthcare strategies. Additionally, it emphasizes the significance of these microbiota in the field of natural product discovery and development.

Life history strategies complement niche partitioning to support the coexistence of closely related Gilliamella species in the bee gut

The maintenance of bacterial diversity at both species and strain levels is crucial for the sustainability of honey bee gut microbiota and host health. Periodic or random fluctuation in diet typically alters the metabolic niches available to gut microbes, thereby continuously reshaping bacterial diversity and interspecific interactions. It remains unclear how closely related bacteria adapt to these fluctuations and maintain coexistence within the bee gut. Here, we demonstrate that the five predominant Gilliamella species associated with Apis cerana, a widely distributed Asiatic honey bee, have diverged in carbohydrate metabolism to adapt to distinct nutrient niches driven by dietary fluctuation. Specifically, the glycan-specialists gain improved growth on a pollen-rich diet, but are overall inferior in competition to non-glycan-specialist on either a simple sugar or sugar-pollen diet, when co-inoculated in the bee host and transmitted across generations. Strikingly, despite of their disadvantage in a high-sugar condition, the glycan-specialists are found prevalent in natural A. cerana guts. We further reveal that these bacteria have adopted a life history strategy characterized by high biomass yield on a low-concentration sugar diet, allowing them to thrive under poor nutritional conditions, such as when the bee hosts undergo periodical starvation. Transcriptome analyses indicate that the divergence in life history strategies is attributed to gene expression programming rather than genetic variation. This study highlights the importance of integrative metabolic strategies in carbohydrate utilization, which facilitate the coexistence of closely related Gilliamella species in a changing bee gut environment.

Framework nucleic acid strategy enables closer microbial contact for programming short-range interaction

Programming precise and specific microbial intraspecies or interspecies interaction would be powerful for microbial metabolic regulation, signal pathway mechanism understanding, and therapeutic application. However, it is still of great challenge to develop a simple and universal method to artificially encode the microbial interactions without interfering with the intrinsic cell metabolism. Here, we proposed an extensible and flexible framework nucleic acid strategy for encoding the specific and precise microbial interactions upon self-assembly. With this spatial manipulation tool, we propose the microbial spatial heterogeneity and short-range interaction mechanism that the microbial assembly facilitates the gene expressions of the surface sensors including flagella and pili in Pseudomonas aeruginosa, leading to a more sensitive response to quorum sensing. The microbial interaction programming strategy proposed in this work is expected to provide a powerful and designable nanoplatform for better understanding of distance-dependent bacterial communication networks.

Ecosystem stability relies on diversity difference between trophic levels

The stability of ecological communities has a profound impact on humans, ranging from individual health influenced by the microbiome to ecosystem services provided by fisheries. A long-standing goal of ecology is the elucidation of the interplay between biodiversity and ecosystem stability, with some ecologists warning of instability due to loss of species diversity while others arguing that greater diversity will instead lead to instability. Here, by considering a minimal two-level ecosystem with multiple predator and prey species, we show that stability does not depend on absolute diversity but rather on diversity differences between levels. We found that increasing diversity in either level first destabilizes but then stabilizes the community (i.e., a reentrant stability transition). We therefore find that it is the diversity difference between levels that is the key to stability, with the least stable communities having similar diversities in different levels. An analytical stability criterion is derived, demonstrating quantitatively that the critical diversity difference is determined by the correlation between how one level affects another and how it is affected in turn. Our stability criterion also applies to consumer-resource models with other forms of interaction such as cross-feeding. Finally, we show that stability depends on diversity differences in ecosystems with three trophic levels. Our finding of a nonmonotonic dependence of stability on diversity provides a natural explanation for the variety of diversity-stability relationships reported in the literature, and emphasizes the significance of level structure in predicting complex community behaviors.

Lake ecological restoration of vegetation removal mitigates algal blooms and alters landscape patterns of water and sediment bacteria

Elucidating the influences of ecological restoration measure of lakeshore vegetation removal on water quality and biological community is an important but underestimated subject. We adopted molecular and statistical tools to estimate ecological restoration performance in a plateau lake receiving vegetation removal and simultaneously investigated variabilities of bacterial communities in water and sediment. Significant decreases in lake trophic level and algal bloom degree followed notable decreases in water total nitrogen and total phosphorus after vegetation removal. Non-significant changes in sediment nutrients accompanied remarkable variabilities of abundance and composition of nutrient-cycling functional genes (NCFGs) of sediment bacteria. Taxonomic and phylogenetic α-diversities, functional redundancies, and dispersal potentials of bacteria in water and sediment decreased after vegetation removal, and community successions of water and sediment bacteria were separately significant and non-significant. There were opposite changes in ecological attributes of bacteria in water and sediment in response to vegetation removal, including niche breadth, species replacement, richness difference, community complexity, and community stability. Species replacement rather than richness difference affected more on taxonomic β-diversities of bacteria in water and sediment before and after vegetation removal, and determinism rather than stochasticity dominated bacterial community assemblage. Our results highlighted vegetation removal mitigated algal bloom and affected differently on landscapes of water and sediment bacteria. These findings point to dominant ecological mechanisms underlying landscape shifts in water and sediment bacteria in a disturbed lake receiving vegetation removal and have the potential to guide lake ecological restoration.

Intraspecific predator interference promotes biodiversity in ecosystems

Explaining biodiversity is a fundamental issue in ecology. A long-standing puzzle lies in the paradox of the plankton: many species of plankton feeding on a limited variety of resources coexist, apparently flouting the competitive exclusion principle (CEP), which holds that the number of predator (consumer) species cannot exceed that of the resources at a steady state. Here, we present a mechanistic model and demonstrate that intraspecific interference among the consumers enables a plethora of consumer species to coexist at constant population densities with only one or a handful of resource species. This facilitated biodiversity is resistant to stochasticity, either with the stochastic simulation algorithm or individual-based modeling. Our model naturally explains the classical experiments that invalidate the CEP, quantitatively illustrates the universal S-shaped pattern of the rank-abundance curves across a wide range of ecological communities, and can be broadly used to resolve the mystery of biodiversity in many natural ecosystems.

Long-term sheep grazing reduces fungal necromass carbon contribution to soil organic carbon in the desert steppe

Grazing has been shown to impact the soil environment and microbial necromass carbon (MNC), which in turn regulates soil organic carbon (SOC). However, the carbon sequestration potential of fungi and bacteria under different stocking rates remains unclear, limiting our understanding of soil carbon sequestration in grazing management. In 2004, we established grazing experiments in the desert steppe of northern China with four stocking rates. Our findings indicate that MNC decreased under moderate and heavy grazing, while light grazing did not significantly differ from no grazing. Notably, the reduction in fungal necromass carbon, rather than bacterial necromass carbon, was primarily responsible for the decreased contribution of MNC to SOC. This difference is attributed to the varying effects of sheep grazing on fungal and bacterial community characteristics, including richness, diversity, and composition. Thus, to accurately predict carbon dynamics in grassland ecosystems, it is essential to consider that the ecological impacts and carbon sequestration potential of microbial communities may vary with different grazing management practices.

Species pool and local assembly processes drive β diversity of ammonia-oxidizing and denitrifying microbial communities in rivers along a latitudinal gradient

Both regional species pool and local community assembly mechanism drive the microbial diversity patterns across geographical gradients. However, little has been done to separate their effects on the β diversity patterns of microbial communities involved in nitrogen (N) cycling in river ecosystems. Here, we use high-throughput sequencing of the archaeal amoA, bacterial amoA, nirK, and nirS genes, null model, and neutral community model to distinguish the relative importance of species pool and local assembly processes for ammonia-oxidizing and denitrifying communities in river wetlands along a latitudinal gradient in eastern China. Results indicated that the β diversity of the nirS-type denitrifying community co-varied with γ diversity and environmental heterogeneity, implying that regional species pool and heterogeneous selection explained variation in β diversity. However, the β diversity of ammonia-oxidizing and nirK-type denitrifying communities did not correlate with γ diversity and environmental heterogeneity. The continuous hump distribution of β deviation along the latitudinal gradient and the lower species dispersal rate indicated that the dispersal limitation shaped the variation in β diversity of ammonia-oxidizing and nirK-type denitrifying communities. Additionally, biotic interactions drove ammonia-oxidizing and nirS-type denitrifying communities by influencing species co-occurrence patterns. Our study highlights the importance of regional species pool and local community assembly processes in shaping geographical patterns of N-cycling microorganisms and extends knowledge of their adaptability to a continuously changing environment on a large scale.

Intraspecific cooperation allows the survival of Staphylococcus aureus staff: a novel strategy for disease relapse

BACKGROUND

The contribution of interspecies interactions between coinfecting pathogens to chronic refractory infection by affecting pathogenicity is well established. However, little is known about the impact of intraspecific interactions on infection relapse, despite the cross-talk of different strains within one species is more common in clinical infection. We reported a case of chronic refractory pulmonary infection relapse, caused by two methicillin-sensitive S. aureus (MSSA) strains (SA01 and SA02) and revealed a novel strategy for relapse via intraspecific cooperation.

METHODS

The hemolytic ability, growth curve, biofilm formation, virulence genes and response of G. mellonella larvae to S. aureus infection were analysed to confirm this hypothesis.

RESULTS

SA02 hemolytic activity was inhibited by SA01, along with the expression of hemolysin genes and the virulence factor Hla. Additionally, SA01 significantly enhanced the biofilm formation of SA02. AIP-RNAIII may be a possible pathway for this interaction. Compared with mono-infection, a worse outcome (decreased larval survival and increased microbial burden) of the two MSSA strains coinfected with G. mellonella confirmed that intraspecific interactions indeed enhanced bacterial survival in vivo.

CONCLUSION

The intraspecific interaction of S. aureus could lead to chronic refractory infection via pathogenicity changes.

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

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

Enhanced catabolism of glycine betaine and derivatives provides improved osmotic stress protection in Methylorubrum extorquens PA1

Integration of metabolites into the overall metabolic network of a cell requires careful coordination dependent upon the ultimate usage of the metabolite. Different stoichiometric needs, and thus pathway fluxes, must exist for compounds destined for diverse uses, such as carbon sources, nitrogen sources, or stress-protective agents. Herein, we expand upon our previous work that highlighted the nature of glycine betaine (GB) metabolism in Methylobacteria to examine the utilization of GB-derivative compounds dimethylglycine (DMG) and sarcosine into Methylorubrum extorquens in different metabolic capacities, including as sole nitrogen and/or carbon sources. We isolated gain-of-function mutations that allowed M. extorquens PA1 to utilize dimethylglycine as a carbon source and dimethylglycine and sarcosine as nitrogen source. Characterization of mutants demonstrated selection for variants of the AraC-like regulator Mext_3735 that confer constitutive expression of the GB metabolic gene cluster, allowing direct utilization of the downstream GB derivatives. Finally, among the distinct isolates examined, we found that catabolism of the osmoprotectant used for selection (GB or dimethylglycine) enhanced osmotic stress resistance provided in the presence of that particular osmolyte. Thus, access to the carbon and nitrogen and osmoprotective effects of GB and DMG are made readily accessible through adaptive mutations. In M. extorquens PA1, the limitations to exploiting this group of compounds appear to exist predominantly at the levels of gene regulation and functional activity, rather than being constrained by transport or toxicity.IMPORTANCEOsmotic stress is a common challenge for bacteria colonizing the phyllosphere, where glycine betaine (GB) can be found as a prevalent osmoprotectant. Though Methylorubrum extorquens PA1 cannot use GB or its demethylation products, dimethylglycine (DMG) and sarcosine, as a sole carbon source, utilization is highly selectable via single nucleotide changes for both GB and DMG growth. The innate inability to use these compounds is due to limited flux through steps in the pathway and regulatory constraints. Herein, the characterization of the transcriptional regulator, Mext_3735 (GbdR), expands our understanding of the various roles in which GB derivatives can be used in M. extorquens PA1. Interestingly, increased catabolism of GB and derivatives does not interfere with, but rather improves, the ability of cells to thrive under increased salt stress conditions, suggesting that metabolic flux improves stress tolerance rather than providing a distinct tension between uses.

Revisiting the invasion paradox: Resistance-richness relationship is driven by augmentation and displacement trends

Host-associated resident microbiota can protect their host from pathogens-a community-level trait called colonization resistance. The effect of the diversity of the resident community in previous studies has shown contradictory results, with higher diversity either strengthening or weakening colonization resistance. To control the confounding factors that may lead to such contradictions, we use mathematical simulations with a focus on species interactions and their impact on colonization resistance. We use a mediator-explicit model that accounts for metabolite-mediated interactions to perform in silico invasion experiments. We show that the relationship between colonization resistance and species richness of the resident community is not monotonic because it depends on two underlying trends as the richness of the resident community increases: a decrease in instances of augmentation (invader species added, without driving out resident species) and an increase in instances of displacement (invader species added, driving out some of the resident species). These trends hold consistently under different parameters, regardless of the number of compounds that mediate interactions between species or the proportion of the facilitative versus inhibitory interactions among species. Our results show a positive correlation between resistance and diversity in low-richness communities and a negative correlation in high-richness communities, offering an explanation for the seemingly contradictory trend in the resistance-diversity relationship in previous reports.

Resource competition predicts assembly of gut bacterial communities in vitro

Microbial community dynamics arise through interspecies interactions, including resource competition, cross-feeding and pH modulation. The individual contributions of these mechanisms to community structure are challenging to untangle. Here we develop a framework to estimate multispecies niche overlaps by combining metabolomics data of individual species, growth measurements in spent media and mathematical models. We applied our framework to an in vitro model system comprising 15 human gut commensals in complex media and showed that a simple model of resource competition accounted for most pairwise interactions. Next, we built a coarse-grained consumer-resource model by grouping metabolomic features depleted by the same set of species and showed that this model predicted the composition of 2-member to 15-member communities with reasonable accuracy. Furthermore, we found that incorporation of cross-feeding and pH-mediated interactions improved model predictions of species coexistence. Our theoretical model and experimental framework can be applied to characterize interspecies interactions in bacterial communities in vitro.

Oxidative stress changes interactions between 2 bacterial species from competitive to facilitative

Knowing how species interact within microbial communities is crucial to predicting and controlling community dynamics, but interactions can depend on environmental conditions. The stress-gradient hypothesis (SGH) predicts that species are more likely to facilitate each other in harsher environments. Even if the SGH gives some intuition, quantitative modeling of the context-dependency of interactions requires understanding the mechanisms behind the SGH. In this study, we show with both experiments and a theoretical analysis that varying the concentration of a single compound, linoleic acid (LA), modifies the interaction between 2 bacterial species, Agrobacterium tumefaciens and Comamonas testosteroni, from competitive at a low concentration, to facilitative at higher concentrations where LA becomes toxic for one of the 2 species. We demonstrate that the mechanism behind facilitation is that one species is able to reduce reactive oxygen species (ROS) that are produced spontaneously at higher concentrations of LA, allowing for short-term rescue of the species that is sensitive to ROS and longer coexistence in serial transfers. In our system, competition and facilitation between species can occur simultaneously, and changing the concentration of a single compound can alter the balance between the two.

Horizontal gene transfer is predicted to overcome the diversity limit of competing microbial species

Natural microbial ecosystems harbor substantial diversity of competing species. Explaining such diversity is challenging, because in classic theories it is extremely infeasible for a large community of competing species to stably coexist in homogeneous environments. One important aspect mostly overlooked in these theories, however, is that microbes commonly share genetic materials with their neighbors through horizontal gene transfer (HGT), which enables the dynamic change of species growth rates due to the fitness effects of the mobile genetic elements (MGEs). Here, we establish a framework of species competition by accounting for the dynamic gene flow among competing microbes. Combining theoretical derivation and numerical simulations, we show that in many conditions HGT can surprisingly overcome the biodiversity limit predicted by the classic model and allow the coexistence of many competitors, by enabling dynamic neutrality of competing species. In contrast with the static neutrality proposed by previous theories, the diversity maintained by HGT is highly stable against random perturbations of microbial fitness. Our work highlights the importance of considering gene flow when addressing fundamental ecological questions in the world of microbes and has broad implications for the design and engineering of complex microbial consortia.

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.

Low-level resource partitioning supports coexistence among functionally redundant bacteria during successional dynamics

Members of microbial communities can substantially overlap in substrate use. However, what enables functionally redundant microorganisms to coassemble or even stably coexist remains poorly understood. Here, we show that during unstable successional dynamics on complex, natural organic matter, functionally redundant bacteria can coexist by partitioning low-concentration substrates even though they compete for one simple, dominant substrate. We allowed ocean microbial communities to self-assemble on leachates of the brown seaweed Fucus vesiculosus and then analyzed the competition among 10 taxonomically diverse isolates representing two distinct stages of the succession. All, but two isolates, exhibited an average of 90% ± 6% pairwise overlap in resource use, and functional redundancy of isolates from the same assembly stage was higher than that from between assembly stages, leading us to construct a simpler four-isolate community with two isolates from each of the early and late stages. We found that, although the short-term dynamics of the four-isolate communities in F. vesiculosus leachate was dependent on initial isolate ratios, in the long term, the four isolates stably coexist in F. vesiculosus leachate, albeit with some strains at low abundance. We therefore explored the potential for nonredundant substrate use by genomic content analysis and RNA expression patterns. This analysis revealed that the four isolates mainly differed in peripheral metabolic pathways, such as the ability to degrade pyrimidine, leucine, and tyrosine, as well as aromatic substrates. These results highlight the importance of fine-scale differences in metabolic strategies for supporting the frequently observed coexistence of large numbers of rare organisms in natural microbiomes.

Growth, tolerance, and enzyme activities of Trichoderma strains in culture media added with a pyrethroids-based insecticide

The application of pyrethroids and carbamates represents an environmental risk and may exert adverse effects on beneficial microorganisms such as Trichoderma, which contribute to the biocontrol of several fungal phytopathogens. This research evaluated the tolerance of several strains of Trichoderma to a selected culture medium contaminated with a commercial insecticide (H24®) composed of pyrethroids, permethrin and prallethrin, and carbamate propoxur, and determined the influence of this insecticide on the release of enzymes such as chitinases, peroxidases, and endoglucanases by a consortium of selected Trichoderma strains grown in liquid culture medium. Four out of 10 Trichoderma strains showed tolerance to 200ppm (∼48.3% of growth) of the commercial insecticide after 96h of exposure to a contaminated solid medium. After eight days of growth in liquid culture, the insecticide enhanced extracellular protein content and peroxidase activities in the Trichoderma consortium but decreased both chitinase and glucanase activities. These fungal responses should be considered when implementing strategies that combine alternative pesticides and fungal biocontrollers for managing fungal phytopathogens.

Stable States of a Microbial Community Are Formed by Dynamic Metabolic Networks with Members Functioning to Achieve Both Robustness and Plasticity

A more detailed understanding of the mechanisms underlying the formation of microbial communities is essential for the efficient management of microbial ecosystems. The stable states of microbial communities are commonly perceived as static and, thus, have not been extensively examined. The present study investigated stabilizing mechanisms, minority functions, and the reliability of quantitative ana-lyses, emphasizing a metabolic network perspective. A bacterial community, formed by batch transferred cultures supplied with phenol as the sole carbon and energy source and paddy soil as the inoculum, was analyzed using a principal coordinate ana-lysis (PCoA), mathematical models, and quantitative parameters defined as growth activity, community-changing activity, community-forming activity, vulnerable force, and resilience force depending on changes in the abundance of operational taxonomic units (OTUs) using 16S rRNA gene amplicon sequences. PCoA showed succession states until the 3rd transferred cultures and stable states from the 5th to 10th transferred cultures. Quantitative parameters indicated that the bacterial community was dynamic irrespective of the succession and stable states. Three activities fluctuated under stable states. Vulnerable and resilience forces were detected under the succession and stable states, respectively. Mathematical models indicated the construction of metabolic networks, suggesting the stabilizing mechanism of the community structure. Thirteen OTUs coexisted during stable states, and were recognized as core OTUs consisting of majorities, middle-class, and minorities. The abundance of the middle-class changed, whereas that of the others did not, which indicated that core OTUs maintained metabolic networks. Some extremely low abundance OTUs were consistently exchanged, suggesting a role for scavengers. These results indicate that stable states were formed by dynamic metabolic networks with members functioning to achieve robustness and plasticity.

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.

Ecology theory disentangles microbial dichotomies

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

Temporal variability in nutrient use among Streptomyces suggests dynamic niche partitioning

Soil bacteria spend significant periods in dormant or semi-dormant states that are interrupted by resource pulses which can lead to periods of rapid growth and intense nutrient competition. Microbial populations have evolved diverse strategies to circumvent competitive interactions and facilitate coexistence. Here, we show that nutrient use of soilborne Streptomyces is temporally partitioned during experimental resource pulses, leading to reduced niche overlap, and potential coexistence. Streptomyces grew rapidly on the majority of distinct 95 carbon sources but varied in which individual resources were utilized in the first 24 h. Only a handful of carbon sources (19 out of 95) were consistently utilized (>95% of isolates) most rapidly in the first 24 h. These consistently utilized carbon sources also generated the majority of biomass accumulated by isolates. Our results shed new light on a novel mechanism microbes may employ to alleviate competitive interactions by temporally partitioning the consumption of carbon resources. As competitive interactions have been proposed to drive the suppression of disease-causing microbes in agronomic soils, our findings may hold widespread implications for soil management for plant health.

Geometry of ecological coexistence and niche differentiation

A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze consumer resource models using geometric arguments. This has led to broadly applicable principles such as Tilman's R * and species coexistence cones. Here, we extend these arguments by constructing a novel geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species which may coexist and enumerate ecologically-stable steady states and transitions between them. Collectively, these results provide a framework for understanding the role of species traits within niche theory.

Redox signaling-driven modulation of microbial biosynthesis and biocatalysis

Microbial communication can drive coordinated functions through sensing, analyzing and processing signal information, playing critical roles in biomanufacturing and life evolution. However, it is still a great challenge to develop effective methods to construct a microbial communication system with coordinated behaviors. Here, we report an electron transfer triggered redox communication network consisting of three building blocks including signal router, optical verifier and bio-actuator for microbial metabolism regulation and coordination. In the redox communication network, the Fe3+/Fe2+ redox signal can be dynamically and reversibly transduced, channeling electrons directly and specifically into bio-actuator cells through iron oxidation pathway. The redox communication network drives gene expression of electron transfer proteins and simultaneously facilitates the critical reducing power regeneration in the bio-actuator, thus enabling regulation of microbial metabolism. In this way, the redox communication system efficiently promotes the biomanufacturing yield and CO2 fixation rate of bio-actuator. Furthermore, the results demonstrate that this redox communication strategy is applicable both in co-culture and microbial consortia. The proposed electron transfer triggered redox communication strategy in this work could provide an approach for reducing power regeneration and metabolic optimization and could offer insights into improving biomanufacturing efficiency.

Geometry of ecological coexistence and niche differentiation

A fundamental problem in ecology is to understand how competition shapes biodiversity and species coexistence. Historically, one important approach for addressing this question has been to analyze consumer resource models using geometric arguments. This has led to broadly applicable principles such as Tilman's R^{*} and species coexistence cones. Here, we extend these arguments by constructing a geometric framework for understanding species coexistence based on convex polytopes in the space of consumer preferences. We show how the geometry of consumer preferences can be used to predict species which may coexist and enumerate ecologically stable steady states and transitions between them. Collectively, these results provide a framework for understanding the role of species traits within niche theory.

Partner-assisted artificial selection of a secondary function for efficient bioremediation

Microbial enzymes can address diverse challenges such as degradation of toxins. However, if the function of interest does not confer a sufficient fitness effect on the producer, the enzymatic function cannot be improved in the host cells by a conventional selection scheme. To overcome this limitation, we propose an alternative scheme, termed "partner-assisted artificial selection" (PAAS), wherein the population of enzyme producers is assisted by function-dependent feedback from an accessory population. Simulations investigating the efficiency of toxin degradation reveal that this strategy supports selection of improved degradation performance, which is robust to stochasticity in the model parameters. We observe that conventional considerations still apply in PAAS: more restrictive bottlenecks lead to stronger selection but add uncertainty. Overall, we offer a guideline for successful implementation of PAAS and highlight its potentials and limitations.

Periodic temporal environmental variations induce coexistence in resource competition models

Natural ecosystems, in particular on the microbial scale, are inhabited by a large number of species. The population size of each species is affected by interactions of individuals with each other and by spatial and temporal changes in environmental conditions, such as resource abundance. Here, we use a generic population dynamics model to study how, and under what conditions, a periodic temporal environmental variation can alter an ecosystem's composition and biodiversity. We demonstrate that using timescale separation allows one to qualitatively predict the long-term population dynamics of interacting species in varying environments. We show that the notion of Tilman's R* rule, a well-known principle that applies for constant environments, can be extended to periodically varying environments if the timescale of environmental changes (e.g., seasonal variations) is much faster than the timescale of population growth (doubling time in bacteria). When these timescales are similar, our analysis shows that a varying environment deters the system from reaching a steady state, and stable coexistence between multiple species becomes possible. Our results posit that biodiversity can in part be attributed to natural environmental variations.

Resource competition can explain simplicity in microbial community assembly

Predicting the composition and diversity of communities is a central goal in ecology. While community assembly is considered hard to predict, laboratory microcosms often follow a simple assembly rule based on the outcome of pairwise competitions. This assembly rule predicts that a species that is excluded by another species in pairwise competition cannot survive in a multispecies community with that species. Despite the empirical success of this bottom-up prediction, its mechanistic origin has remained elusive. In this study, we elucidate how this simple pattern in community assembly can emerge from resource competition. Our geometric analysis of a consumer-resource model shows that trio community assembly is always predictable from pairwise outcomes when one species grows faster than another species on every resource. We also identify all possible trio assembly outcomes under three resources and find that only two outcomes violate the assembly rule. Simulations demonstrate that pairwise competitions accurately predict trio assembly with up to 100 resources and the assembly of larger communities containing up to twelve species. We then further demonstrate accurate quantitative prediction of community composition using the harmonic mean of pairwise fractions. Finally, we show that cross-feeding between species does not decrease assembly rule prediction accuracy. Our findings highlight that simple community assembly can emerge even in ecosystems with complex underlying dynamics.

Transcriptomic response of Sinorhizobium meliloti to the predatory attack of Myxococcus xanthus

Bacterial predation impacts microbial community structures, which can have both positive and negative effects on plant and animal health and on environmental sustainability. Myxococcus xanthus is an epibiotic soil predator with a broad range of prey, including Sinorhizobium meliloti, which establishes nitrogen-fixing symbiosis with legumes. During the M. xanthus-S. meliloti interaction, the predator must adapt its transcriptome to kill and lyse the target (predatosome), and the prey must orchestrate a transcriptional response (defensome) to protect itself against the biotic stress caused by the predatory attack. Here, we describe the transcriptional changes taking place in S. meliloti in response to myxobacterial predation. The results indicate that the predator induces massive changes in the prey transcriptome with up-regulation of protein synthesis and secretion, energy generation, and fatty acid (FA) synthesis, while down-regulating genes required for FA degradation and carbohydrate transport and metabolism. The reconstruction of up-regulated pathways suggests that S. meliloti modifies the cell envelop by increasing the production of different surface polysaccharides (SPSs) and membrane lipids. Besides the barrier role of SPSs, additional mechanisms involving the activity of efflux pumps and the peptide uptake transporter BacA, together with the production of H₂O₂ and formaldehyde have been unveiled. Also, the induction of the iron-uptake machinery in both predator and prey reflects a strong competition for this metal. With this research we complete the characterization of the complex transcriptional changes that occur during the M. xanthus-S. meliloti interaction, which can impact the establishment of beneficial symbiosis with legumes.

Metabolic cooperation between conspecific genotypic groups contributes to bacterial fitness

Microbial interactions are important for the survival of species and the stability of the microbial ecosystem. Although bacteria have diverse conspecific genotypes in the natural microbial ecosystem, little is known about whether wild-type strains within species would interact with each other and how the intraspecific interaction influences the growth of the species. In this work, using Lactobacillus acetotolerans, a dominant species with diverse conspecific genotypes in natural food fermentation ecosystems as a case, we studied the interactions between different genotypic groups of this species. In interspecific and intraspecific pairwise cocultures, the growth of L. acetotolerans decreased, but the increase of the phylogenetic similarity would reduce this negative effect, indicating a potential intraspecific interaction of this species. Meanwhile, the strain classification method affected the analysis of intraspecific interactions, which can be efficiently demonstrated using 99.5% average nucleotide identity (ANI) as the strain-level classification method. Using this ANI classification method, we revealed the population fitness significantly increased in cocultures of different genotypic groups. Facilitation involving 11 amino acids was identified between different ANI genotypic groups, which was beneficial for increasing population fitness. This work revealed that wild-type conspecific strains could interact with each other via cooperative metabolic changes and benefit each other to increase fitness. It shed new light on the survival and stability of species in natural microbial ecosystems.

Sporulation Activated via σW Protects Bacillus from a Tse1 Peptidoglycan Hydrolase Type VI Secretion System Effector

Within bacterial communities, community members engage in interactions employing diverse offensive and defensive tools to reach coexistence. Extracellular-matrix production and sporulation are defensive mechanisms used by Bacillus subtilis cells when they interact with Pseudomonas chlororaphis strains expressing a type VI secretion system (T6SS). Here, we define Tse1 as the main toxin mobilized by the Pseudomonas chlororaphis T6SS that triggers sporulation in Bacillus subtilis. We characterize Tse1 as a peptidoglycan hydrolase that indirectly alters the dynamics and functionality of the Bacillus cell membrane. We also delineate the response of Bacillus cells to Tse1, which through the coordinated actions of the extracellular sigma factor σW and the cytoplasmic histidine kinases KinA and KinB, culminates in activation of the sporulation cascade. We propose that this cellular developmental response permits bacilli to defend against the toxicity of T6SS-mobilized Tse1 effector. IMPORTANCE The study of bacterial interactions is helping to define species-specific strategies used to modulate the competition dynamics underlying the development of community compositions. In this study, we deciphered the role of Pseudomonas T6SS when competing with Bacillus and the mechanism by which a T6SS-toxin modifies Bacillus physiology. We found that Pseudomonas triggers Bacillus sporulation by injecting through T6SS a toxin that we called Tse1. We found that Tse1 is a hydrolase that degrades Bacillus peptidoglycan and indirectly damages Bacillus membrane functionality. In addition, we demonstrated the mechanism by which Bacillus cells increase the sporulation rate upon recognition of the presence of Tse1. Interestingly, asporogenic Bacillus cells are more sensitive to T6SS activity, which led us to propose sporulation as a last resort of bacilli to overcome this family of toxins.

Controlling the human microbiome

We coexist with a vast number of microbes that live in and on our bodies. Those microbes and their genes are collectively known as the human microbiome, which plays important roles in human physiology and diseases. We have acquired extensive knowledge of the organismal compositions and metabolic functions of the human microbiome. However, the ultimate proof of our understanding of the human microbiome is reflected in our ability to manipulate it for health benefits. To facilitate the rational design of microbiome-based therapies, there are many fundamental questions to be addressed at the systems level. Indeed, we need a deep understanding of the ecological dynamics associated with such a complex ecosystem before we rationally design control strategies. In light of this, this review discusses progress from various fields, e.g., community ecology, network science, and control theory, that are helping us make progress toward the ultimate goal of controlling the human microbiome.

Metabolic models of human gut microbiota: Advances and challenges

The human gut is a complex ecosystem consisting of hundreds of microbial species interacting with each other and with the human host. Mathematical models of the gut microbiome integrate our knowledge of this system and help to formulate hypotheses to explain observations. The generalized Lotka-Volterra model has been widely used for this purpose, but it does not describe interaction mechanisms and thus does not account for metabolic flexibility. Recently, models that explicitly describe gut microbial metabolite production and consumption have become popular. These models have been used to investigate the factors that shape gut microbial composition and to link specific gut microorganisms to changes in metabolite concentrations found in diseases. Here, we review how such models are built and what we have learned so far from their application to human gut microbiome data. In addition, we discuss current challenges of these models and how these can be addressed in the future.

Ecological landscapes guide the assembly of optimal microbial communities

Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia.

The contrasting roles of nitric oxide drive microbial community organization as a function of oxygen presence

Microbial assemblages are omnipresent in the biosphere, forming communities on the surfaces of roots and rocks and within living tissues. These communities can exhibit strikingly beautiful compositional structures, with certain members reproducibly occupying particular spatiotemporal microniches. Despite this reproducibility, we lack the ability to explain these spatial patterns. We hypothesize that certain spatial patterns in microbial communities may be explained by the exchange of redox-active metabolites whose biological function is sensitive to microenvironmental gradients. To test this, we developed a simple community consisting of synthetic Pseudomonas aeruginosa strains with a partitioned denitrification pathway: a strict consumer and strict producer of nitric oxide (NO), a key pathway intermediate. Because NO can be both toxic or beneficial depending on the amount of oxygen present, this system provided an opportunity to investigate whether dynamic oxygen gradients can tune metabolic cross-feeding and fitness outcomes in a predictable fashion. Using a combination of genetic analysis, controlled growth environments, and imaging, we show that oxygen availability dictates whether NO cross-feeding is deleterious or mutually beneficial and that this organizing principle maps to the microscale. More generally, this work underscores the importance of considering the double-edged and microenvironmentally tuned roles redox-active metabolites can play in shaping microbial communities.

Biotic Interactions in Soil are Underestimated Drivers of Microbial Carbon Use Efficiency

Microbial carbon use efficiency (CUE)-the balance between microbial growth and respiration-strongly impacts microbial mediated soil carbon storage and is sensitive to many well-studied abiotic environmental factors. However, surprisingly, little work has examined how biotic interactions in soil may impact CUE. Here, we review the theoretical and empirical lines of evidence exploring how biotic interactions affect CUE through the lens of life history strategies. Fundamentally, the CUE of a microbial population is constrained by population density and carrying capacity, which, when reached, causes species to grow more quickly and less efficiently. When microbes engage in interspecific competition, they accelerate growth rates to acquire limited resources and release secondary chemicals toxic to competitors. Such processes are not anabolic and thus constrain CUE. In turn, antagonists may activate one of a number of stress responses that also do not involve biomass production, potentially further reducing CUE. In contrast, facilitation can increase CUE by expanding species realized niches, mitigating environmental stress and reducing production costs of extracellular enzymes. Microbial interactions at higher trophic levels also influence CUE. For instance, predation on microbes can positively or negatively impact CUE by changing microbial density and the outcomes of interspecific competition. Finally, we discuss how plants select for more or less efficient microbes under different contexts. In short, this review demonstrates the potential for biotic interactions to be a strong regulator of microbial CUE and additionally provides a blueprint for future research to address key knowledge gaps of ecological and applied importance for carbon sequestration.

Resource availability drives bacteria community resistance to pathogen invasion via altering bacterial pairwise interactions

Microbial interactions within resident communities are a major determinant of resistance to pathogen invasion. Yet, interactions vary with environmental conditions, raising the question of how community composition and environments interactively shape invasion resistance. Here, we use resource availability (RA) as a model parameter altering the resistance of model bacterial communities to invasion by the plant pathogenic bacterium Ralstonia solanacearum. We found that at high RA, interactions between resident bacterial species were mainly driven by the direct antagonism, in terms of the means of invader inhibition. Consequently, the competitive resident communities with a higher production of antibacterial were invaded to a lesser degree than facilitative communities. At low RA, bacteria produced little direct antagonist potential, but facilitative communities reached a relatively higher community productivity, which showed higher resistance to pathogen invasion than competitive communities with lower productivities. This framework may lay the basis to understand complex microbial interactions and biological invasion as modulated by the dynamic changes of environmental resource availability.

Toward FAIR Representations of Microbial Interactions

Despite an ever-growing number of data sets that catalog and characterize interactions between microbes in different environments and conditions, many of these data are neither easily accessible nor intercompatible. These limitations present a major challenge to microbiome research by hindering the streamlined drawing of inferences across studies. Here, we propose guiding principles to make microbial interaction data more findable, accessible, interoperable, and reusable (FAIR). We outline specific use cases for interaction data that span the diverse space of microbiome research, and discuss the untapped potential for new insights that can be fulfilled through broader integration of microbial interaction data. These include, among others, the design of intercompatible synthetic communities for environmental, industrial, or medical applications, and the inference of novel interactions from disparate studies. Lastly, we envision potential trajectories for the deployment of FAIR microbial interaction data based on existing resources, reporting standards, and current momentum within the community.

Classifying Interactions in a Synthetic Bacterial Community Is Hindered by Inhibitory Growth Medium

Predicting the fate of a microbial community and its member species relies on understanding the nature of their interactions. However, designing simple assays that distinguish between interaction types can be challenging. Here, we performed spent medium assays based on the predictions of a mathematical model to decipher the interactions among four bacterial species: Agrobacterium tumefaciens, Comamonas testosteroni, Microbacterium saperdae, and Ochrobactrum anthropi. While most experimental results matched model predictions, the behavior of C. testosteroni did not: its lag phase was reduced in the pure spent media of A. tumefaciens and M. saperdae but prolonged again when we replenished our growth medium. Further experiments showed that the growth medium actually delayed the growth of C. testosteroni, leading us to suspect that A. tumefaciens and M. saperdae could alleviate this inhibitory effect. There was, however, no evidence supporting such "cross-detoxification," and instead, we identified metabolites secreted by A. tumefaciens and M. saperdae that were then consumed or "cross-fed" by C. testosteroni, shortening its lag phase. Our results highlight that even simple, defined growth media can have inhibitory effects on some species and that such negative effects need to be included in our models. Based on this, we present new guidelines to correctly distinguish between different interaction types such as cross-detoxification and cross-feeding. IMPORTANCE Communities of microbes colonize virtually every place on earth. Ultimately, we strive to predict and control how these communities behave, for example, if they reside in our guts and make us sick. But precise control is impossible unless we can identify exactly how their member species interact with one another. To find a systematic way to measure interactions, we started very simply with a small community of four bacterial species and carefully designed experiments based on a mathematical model. This first attempt accurately mapped out interactions for all species except one. By digging deeper, we understood that our method failed for that species as it was suffering in the growth medium that we chose. A revised model that considered that growth media can be harmful could then make more accurate predictions. What we have learned with these four species can now be applied to decipher interactions in larger communities.

Even allocation of benefits stabilizes microbial community engaged in metabolic division of labor

Microbial communities execute metabolic pathways to drive global nutrient cycles. Within a community, functionally specialized strains can perform different yet complementary steps within a linear pathway, a phenomenon termed metabolic division of labor (MDOL). However, little is known about how such metabolic behaviors shape microbial communities. Here, we derive a theoretical framework to define the assembly of a community that degrades an organic compound through MDOL. The framework indicates that to ensure community stability, the strains performing the initial steps should hold a growth advantage (m) over the "private benefit" (n) of the strain performing the last step. The steady-state frequency of the last strain is then determined by the quotient of n and m. Our experiments show that the framework accurately predicts the assembly of our synthetic consortia that degrade naphthalene through MDOL. Our results provide insights for designing and managing stable microbial systems for metabolic pathway optimization.

Evaluation of inhibitory compounds produced by bacteria isolated from a hydrogen-producing bioreactor during the self-fermentation of wheat straw

AIMS

The objective of this study was to evaluate the inhibitory activity of compounds secreted by bacteria isolated from a hydrogen-producing bioreactor to understand how these microorganisms interact in this community.

METHODS AND RESULTS

In vitro inhibitory assays were performed using samples secreted by bacteria subject to different treatments to determine if their inhibitory effect was due to organic acids, non-proteinaceous compounds, or bacteriocin-like inhibitory substances (BLIS). Bacterial isolated were suppressed 43%, 30%, and 27% by neutralized, precipitated, and non-neutralized cell-free supernatants, respectively. Non-hydrogen producers (Non-H₂ P) LAB (Lactobacillus plantarum LB1, L. pentosus LB7, Pediococcus acidilactici LB4) and hydrogen producers (H₂ P) LAB (Enterococcus faecium F) were inhibited by the production of organic acids, non-proteinaceous compounds, and BLIS. Meanwhile, the obligate anaerobe H₂ P (Clostridium beijerinckii B) inhibited by the production of non-proteinaceous compounds and BLIS. The presence of BLIS was confirmed when proteolytic enzymes affected the inhibitory activity of secreted proteins in values ranging from 20 to 42%. The BLIS produced by L. plantarum LB1, P. acidilactici LB4, L. pentosus LB7, and E. faecium F showed molecular masses of ~ 11 kDa, 25 kDa, 20 kDa, and 11 kDa, respectively.

CONCLUSIONS

It was demonstrated antagonistic interactions between Lactobacillus- Enterococcus, and Pediococcus-Enterococcus species, generated by the secretion of organic acids, non-proteinaceous compounds, and BLIS.

SIGNIFICANCE AND IMPACT OF THE STUDY

We report the interactions between LAB isolated from hydrogen-producing bioreactors. These interactions might impact the dynamics of the microbial population during hydrogen generation. Our work lays a foundation for strategies that allow controlling bacteria that can affect hydrogen production.

Substrate Utilization and Competitive Interactions Among Soil Bacteria Vary With Life-History Strategies

Microorganisms have evolved various life-history strategies to survive fluctuating resource conditions in soils. However, it remains elusive how the life-history strategies of microorganisms influence their processing of organic carbon, which may affect microbial interactions and carbon cycling in soils. Here, we characterized the genomic traits, exometabolite profiles, and interactions of soil bacteria representing copiotrophic and oligotrophic strategists. Isolates were selected based on differences in ribosomal RNA operon (rrn) copy number, as a proxy for life-history strategies, with pairs of "high" and "low" rrn copy number isolates represented within the Micrococcales, Corynebacteriales, and Bacillales. We found that high rrn isolates consumed a greater diversity and amount of substrates than low rrn isolates in a defined growth medium containing common soil metabolites. We estimated overlap in substrate utilization profiles to predict the potential for resource competition and found that high rrn isolates tended to have a greater potential for competitive interactions. The predicted interactions positively correlated with the measured interactions that were dominated by negative interactions as determined through sequential growth experiments. This suggests that resource competition was a major force governing interactions among isolates, while cross-feeding of metabolic secretion likely contributed to the relatively rare positive interactions observed. By connecting bacterial life-history strategies, genomic features, and metabolism, our study advances the understanding of the links between bacterial community composition and the transformation of carbon in soils.

Dynamic proteome allocation regulates the profile of interaction of auxotrophic bacterial consortia

Microbial ecosystems are composed of multiple species in constant metabolic exchange. A pervasive interaction in microbial communities is metabolic cross-feeding and occurs when the metabolic burden of producing costly metabolites is distributed between community members, in some cases for the benefit of all interacting partners. In particular, amino acid auxotrophies generate obligate metabolic inter-dependencies in mixed populations and have been shown to produce a dynamic profile of interaction that depends upon nutrient availability. However, identifying the key components that determine the pair-wise interaction profile remains a challenging problem, partly because metabolic exchange has consequences on multiple levels, from allocating proteomic resources at a cellular level to modulating the structure, function and stability of microbial communities. To evaluate how ppGpp-mediated resource allocation drives the population-level profile of interaction, here we postulate a multi-scale mathematical model that incorporates dynamics of proteome partition into a population dynamics model. We compare our computational results with experimental data obtained from co-cultures of auxotrophic Escherichia coli K12 strains under a range of amino acid concentrations and population structures. We conclude by arguing that the stringent response promotes cooperation by inhibiting the growth of fast-growing strains and promoting the synthesis of metabolites essential for other community members.

Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas

Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.

Construction of Environmental Synthetic Microbial Consortia: Based on Engineering and Ecological Principles

In synthetic biology, engineering principles are applied to system design. The development of synthetic microbial consortia represents the intersection of synthetic biology and microbiology. Synthetic community systems are constructed by co-cultivating two or more microorganisms under certain environmental conditions, with broad applications in many fields including ecological restoration and ecological theory. Synthetic microbial consortia tend to have high biological processing efficiencies, because the division of labor reduces the metabolic burden of individual members. In this review, we focus on the environmental applications of synthetic microbial consortia. Although there are many strategies for the construction of synthetic microbial consortia, we mainly introduce the most widely used construction principles based on cross-feeding. Additionally, we propose methods for constructing synthetic microbial consortia based on traits and spatial structure from the perspective of ecology to provide a basis for future work.

Gut-Microbiome Composition in Response to Phenylketonuria Depends on Dietary Phenylalanine in BTBR Pahenu2 Mice

Phenylketonuria (PKU) is a metabolic disorder caused by a hepatic enzyme deficiency causing high blood and brain levels of the amino acid Phenylalanine (Phe), leading to severe cognitive and psychological deficits that can be prevented, but not completely, by dietary treatment. The behavioral outcome of PKU could be affected by the gut-microbiome-brain axis, as diet is one of the major drivers of the gut microbiome composition. Gut-microbiome alterations have been reported in treated patients with PKU, although the question remains whether this is due to PKU, the dietary treatment, or their interaction. We, therefore, examined the effects of dietary Phe restriction on gut-microbiome composition and relationships with behavioral outcome in mice. Male and female BTBR Pah^enu2 mice received either a control diet (normal protein, “high” Phe), liberalized Phe-restricted (33% natural protein restriction), or severe Phe-restricted (75% natural protein restriction) diet with protein substitutes for 10 weeks (n = 14 per group). Their behavioral performance was examined in an open field test, novel and spatial object location tests, and a balance beam. Fecal samples were collected and sequenced for the bacterial 16S ribosomal RNA (rRNA) region. Results indicated that PKU on a high Phe diet reduced Shannon diversity significantly and altered the microbiome composition compared with wild-type animals. Phe-restriction prevented this loss in Shannon diversity but changed community composition even more than the high-Phe diet, depending on the severity of the restriction. Moreover, on a taxonomic level, we observed the highest number of differentially abundant genera in animals that received 75% Phe-restriction. Based on correlation analyses with differentially abundant taxa, the families Entereococacceae, Erysipelotrichaceae, Porphyromonadaceae, and the genus Alloprevotella showed interesting relationships with either plasma Phe levels and/or object memory. According to our results, these bacterial taxa could be good candidates to start examining the microbial metabolic potential and probiotic properties in the context of PKU. We conclude that PKU leads to an altered gut microbiome composition in mice, which is least severe on a liberalized Phe-restricted diet. This may suggest that the current Phe-restricted diet for PKU patients could be optimized by taking dietary effects on the microbiome into account.