Polarization of microbial communities between competitive and cooperative metabolism

Unravelling microbial interactions in a synthetic broad bean paste microbial community

The biotic factors governing the assembly and functionality of broad bean paste microbiota remain largely unexplored due to its highly complex fermentation ecosystem. This study constructed a synthetic community comprising Zygosaccharomyces rouxii, Staphylococcus carnosus, Bacillus subtilis, Bacillus amyloliquefaciens, Tetragenococcus halophilus and Weissella confusa, representing key microorganisms involved in broad bean paste fermentation. The generalized Lotka-Volterra (gLV) model revealed that the microbial interaction network among the six species was dominated by pairwise interactions. The abundances of most species in the multi-species communities at 2 and 4 days were accurately predicted using the gLV model, based on pairwise species combinations outcomes. Among pairwise interactions, negative interactions (57 %) were significantly more prevalent than positive interactions (37 %), with the former generally being stronger. Subsequent investigations demonstrated that the tested Z. rouxii inhibited acid accumulation by acid-producing bacteria, while the two strains belonging to the genus Bacillus stimulated lactic acid bacteria growth and lactic acid accumulation. The sequential inoculation strategy, informed by the interaction network, enhanced the synthetic community's bioaugmentation in broad bean paste, significantly improving ester and mellow flavors, reducing unpleasant odors, and increasing volatile flavor substances to 9.43 times that of natural fermentation. Overall, this study revealed the interaction network of six key microorganisms in broad bean paste using the gLV model and guided the application of the synthetic community in its fermentation, significantly enhancing flavor quality.

Rhizosphere metabolite dynamics in continuous cropping of vineyards: Impact on microflora diversity and co-occurrence networks

The metabolism of the crop rhizosphere affects microflora diversity and nutrient cycling. However, understanding rhizosphere metabolism in suitable crops within arid desert environments and its impact on microflora interactions remains limited. Through metagenomic and non-targeted metabolomic sequencing of rhizosphere soils from one uncultivated land and four vineyards with cropping years of 5, 10, 15 and 20 years, the critical importance of rhizosphere metabolites in maintaining bacterial and fungal diversity was elucidated. The results revealed that Nocardioides, Streptomyces, and Solirubrobacter were the relatively abundant bacterial genera in rhizosphere soils, while Rhizophagus, Glomus, and Pseudogymnoascus were the relatively abundant fungal genera. The composition of rhizosphere metabolic changed significantly during the continuous cropping of grapevines. Dimethylglycine, Formononetin, and Dehydroepiandrosterone were the most important metabolites. Enrichment analysis revealed significant involvement of metabolic pathways such as biosynthesis of amino acids, unsaturated fatty acids, and linoleic acid metabolism. Procrustes analysis highlighted stronger correlations between rhizosphere metabolites and bacterial community compared to those of fungal community. This suggests distinct responses of microflora to crop-released chemical elements across different soil habitats. Co-occurrence network analysis demonstrated complex associations between rhizosphere metabolites and soil microflora, the positive correlations between rhizosphere metabolites and microflora networks predominated over negative correlations. Partial least squares path model indicated that the effect of cropping years on rhizosphere metabolites was greater than that on bacterial microflora diversity. Futhermore, pH, total phosphorus, and alkali-hydrolyzed nitrogen were the key environmental factors affecting rhizosphere metabolites and microbial diversity. These results deepen our valuable insights into the complex biological processes that rhizosphere metabolites influence on microorganisms, and provide strong support for maintaining microbial diversity in farmland soils in arid regions.

Marine plastic exposure triggers rapid recruitment of plastic-degrading bacteria and accelerates polymer-specific transformations

Plastic pollution in marine ecosystems is a growing concern, yet the degradation behavior of different plastic types and their interactions with microbial communities remain poorly understood. This study investigated the degradation kinetics and microbial colonization of four widely used plastic materials, surgical masks (most made of PP), PET bottles, PS foam, and PP cups, over 40 days of seawater exposure in the Central Atlantic of Morocco. Mass loss measurement revealed distinct degradation patterns, with PS foam showing the highest mass loss (13 %), followed by PET bottles (5 %), likely due to environmental stressors that promote mechanical fragmentation. Surgical masks and PP cups exhibited minimal degradation, retaining nearly all their original mass, as well as limited extent of biodegradation. Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction (XRD) analyses showed the formation of oxidative functional groups on PP cups and significant structural changes in PS foam and PET, particularly in their crystalline structures, correlating with their higher mass reduction rates. SEM/EDX biofilm imaging confirmed extensive microbial colonization, particularly on PS and PET surfaces. Using 16S rRNA metabarcoding, we identified a striking enrichment of Exiguobacterium, followed by Pseudomonas, Acinetobacter and Bacillus genera, containing reported plastic degrading strains, which were strongly correlated with the accelerated breakdown of plastics. However, its role in accelerating plastic breakdown in this study remains unclear and may warrant further investigation. Co-occurrence network analysis revealed a progressive shift in microbial community structure, evolving from highly interconnected networks at day 0 to more specialized, modular clusters by day 40, dominated by Proteobacteria and Firmicutes. Atomic Absorption Spectrometry (AAS) demonstrated significant heavy metal accumulation on plastic surfaces, potentially influencing microbial colonization and activity. While the observed fragmentation of PS foam and PET highlights the susceptibility of certain plastics to environmental stressors, this study also positions microbial colonization as a potential contributor to plastic surface changes, providing novel insights into the interplay between microbial communities and plastic degradation in marine environments.

Cross-feeding creates tipping points in microbiome diversity

A key unresolved question in microbial ecology is how the extraordinary diversity of microbiomes emerges from the interactions among their many functionally distinct populations. This process is driven in part by the cross-feeding networks that help to structure these systems, in which consumers use resources to fuel their metabolism, creating by-products which can be used by others in the community. Understanding the effects of cross-feeding presents a major challenge, as it creates complex interdependencies between populations which can be hard to untangle. We address this problem using the tools of network science to develop a structural microbial community model. Using methods from percolation theory, we identify feasible community states for cross-feeding network structures in which the needs of consumers are met by metabolite production across the community. We identify tipping points at which small changes in structure can cause the catastrophic collapse of cross-feeding networks and abrupt declines in microbial community diversity. Our results are an example of a well-defined tipping point in a complex ecological system and provide insight into the fundamental processes shaping microbiomes and their robustness. We further demonstrate this by considering how network attacks affect community diversity and apply our results to show how the apparent difficulty in culturing the microbial diversity emerges as an inherent property of their cross-feeding networks.

Microbial consortium involving Pseudomonas and Bacillus: strain selection and the effect of co-cultivation on biocontrol activity against phytopathogens and the composition of metabolic extracts

Agricultural sustainability is vital to meet the growing global demand for food; therefore, the search for more sustainable options to replace traditional chemical products has gained attention due to their benefits. The sector has applied innovative microbial consortium approaches as a niche for exploring new bioproducts and metabolic pathways through microbial interactions. Thus, this study sought to select two endophytic bacterial strains with biocontrol activity to study their metabolic interactions in culture. For this, co-cultivation and axenic culture assays were carried out to evaluate the inhibition of Corynespora cassiicola, Sclerotinia sclerotiorum, Moniliophthora perniciosa, and Colletotrichum truncatum. After the production of antiphytopathogenic compound tests, two strains were selected: P. putida MG36 and B. amyloliquefaciens SS14. These bacteria were cultivated under three distinct conditions: axenic cultivation of SS14, axenic cultivation of MG36, and co-cultivation. The metabolites were extracted and analyzed by liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS). The results showed that both strains exhibited significant antifungal activity. B. amyloliquefaciens SS14 demonstrated 65% inhibition against C. truncatum, while P. putida MG36 showed 58% inhibition against S. sclerotiorum. Analysis of the chemical profiles revealed the presence of exclusive and shared metabolites, such as iturin A4 (antifungal lipopeptide) and macrolactin A (bioactive polyketide), under different culture conditions. In conclusion, P. putida MG36 and B. amyloliquefaciens SS14 show promise as biocontrol agents against phytopathogens, contributing to more sustainable agricultural practices.

Exploring the function of key species in different composting stages for effective waste biotransformation

Composting is a microbial-driven process that plays a vital role in recycling waste and promoting sustainable production. To develop more effective bioaugmentation strategies, this study examined three successive stages in an aerobic composting system, focusing on microbial community adaptation to high-temperature stress (mode_2) and nutrient-poor conditions (mode_3). The results revealed a shift from an r-strategy (rapid growth) to a K-strategy (thriving under resource-limited conditions). Community succession was predominantly driven by deterministic processes (>90 %) and exhibited strong cooperative interactions. Using multiple statistical approaches, key species were identified for each condition. These species enhanced microbial network connectivity under environmental stresses, increasing network edges by 29 %-35 %. Under high-temperature stress, Bacillus and Ureibacillus maintained core functions, while Chelativorans and Aeribacillus contributed to key metabolic pathways, including amino acid metabolism. In nutrient-poor conditions, Saccharomonospora and Pseudoxanthomonas enhanced overall system functionality, and Novibacillus played a key role in carbon and nitrogen cycling, particularly nitrogen fixation. Predictive models for microbial community stability (R2 = 0.68-0.97) were developed based on these key species to enable rapid assessment of system stability. Overall, this study identifies essential microbes involved in composting across different environmental conditions and clarifies their functional roles, providing valuable insights for optimizing aerobic composting efficiency and advancing waste resource management.

Microbial Biotic Associations Dominated Adaptability Differences of Dioecious Poplar Under Salt Stress

How different stress responses by male and female plants are influenced by interactions with rhizosphere microbes remains unclear. In this study, we employed poplar as a dioecious model plant and quantified biotic associations between microorganisms to explore the relationship between microbial associations and plant adaptation. We propose a health index (HI) to comprehensively characterize the physiological characteristics and adaptive capacity of plants under stress. It was found that male poplars demonstrated higher salt stress tolerance than females, and root-secreted citric acid was significantly higher in the rhizospheres of male poplars. Positive biotic association among bacteria increased poplar HI significantly under salt stress, while fungal and cross-domain biotic association (bacteria-fungi) did not. We further identified a keystone bacterial taxon regulating bacterial biotic association, ASV_22706, which was itself regulated by citric acid and significantly positively correlated with host HI. The abundance of keystone fungal taxa was positively correlated with HI of male poplars and negatively correlated with HI of female poplars. Compared with female poplars, male poplars enriched more prebiotics and probiotics under stress. This work primarily reveals the relationship between adaptation differences and microbial interactions in dioecious plants, which suggests a microbial approach to improve plant adaptability to stress conditions.

The impact of ecological pressure caused by toxic lignin metabolites on microbial function transformation during composting

Environmental stress coexists with microbial interactions during composting, temperature was thought to be the main stress, the toxic stress caused by aromatic compounds was often overlooked. Herein, lignin and lignin degradation products (LDP) were used alone or in combination to culture the compost microbial community, which manually delineated 32 niches to explore the effects of toxic stress on microbe and their responses. Results showed that the toxicity of LDP significantly changed the distribution of microbial community. Then, microorganisms were divided into three groups: specialist showed high diversity and low abundance, responsible for the metabolism of toxic macromolecules, with detoxification effect. Generalist exhibited high abundance and diversity, which mainly changed metabolic byproducts to cellular energy and sustaining the survival of microorganisms. Accordingly, these characteristics were the survival strategies of microbial communities to harmonize the toxic stress in different ecological niche. While the results of the lignin metabolic catalog have confirmed the metabolic tendency of different microorganism in the metabolic module. Finally, this study help to further understand microbe survival strategies in aromatic pollutants composting, which may be possible to accelerate or alter the composting process by manipulating the microbial community.

Automated adjustment of metabolic niches enables the control of natural and engineered microbial co-cultures

Much attention has focused on understanding microbial interactions leading to stable co-cultures. In this work, substrate pulsing was performed to promote better control of the metabolic niches (MNs) corresponding to each species, leading to the continuous co-cultivation of diverse microbial organisms. We used a cell-machine interface, which allows adjustment of the temporal profile of two MNs according to a rhythm, ensuring the successive growth of two species, in our case, a yeast and a bacterium. The resulting approach, called 'automated adjustment of metabolic niches' (AAMN), was effective for stabilizing both cooperative and competitive co-cultures. AAMN can be considered an enabling technology for the deployment of co-cultures in bioprocesses, demonstrated here based on the continuous bioproduction of p-coumaric acid. The data accumulated suggest that AAMN could be used not only for a wider range of biological systems, but also to gain fundamental insights into microbial interaction mechanisms.

Unveiling the latitudinal dependency of global patterns in soil prokaryotic gene content

Prokaryotic genomic traits offer insights into their functional roles, evolutionary processes, and ecological interactions, but global patterns in soil microbial genomes remain poorly understood. In this study, we examined 6436 metagenome-assembled genomes (MAGs) from global soil environments to explore the driving factors of prokaryotic gene content. Through random forest analysis, we found that, among numerous potential influencing factors such as climate, soil physicochemical properties, and human activities, geographic latitude was the primary factor affecting prokaryotic gene content. Our results showed a marked decrease in gene content from the tropics to the poles, with polar MAGs containing 10.4 % and 13.3 % fewer genes than those in tropical and temperate zones, respectively. This decline correlates with shifts in key metabolic processes, such as nitrogen fixation and energy conversion. Furthermore, we assessed interspecies metabolic interactions using Metabolic Resource Overlap (MRO) and Metabolic Interaction Potential (MIP) metrics. Our analysis revealed significantly lower MRO in high-latitude microbial communities, yet comparable MIP values to those in lower latitudes, indicating that reduced competition may contribute to genomic streamlining. These findings highlight the significant influence of latitude and interspecies interactions on microbial genomic characteristics, advancing our comprehension of microbial ecological adaptations.

Genome-scale metabolic modeling reveals specific vaginal Lactobacillus strains and their metabolites as key inhibitors of Candida albicans

As the predominant constituents of the vaginal microbiome in healthy women, Lactobacillus species are considered essential in maintaining a homeostatic vaginal microbiome. Specific Lactobacillus species can produce beneficial metabolites to support their persistence within the host environment and inhibit Candida albicans colonization. Due to the extensive diversity of Lactobacillus species and their metabolites, comprehensively investigating all possible interactions remains challenging. This study employed an integrative approach combining genome-scale metabolic modeling, metagenomic sequencing, and in vitro validation to explore Lactobacillus and C. albicans interactions. Pairwise simulations of 159 Lactobacillus strains with C. albicans revealed that most strains exhibit inhibitory effects, altering fungal amino acid and carbohydrate metabolism. Key inhibitory metabolites identified included formate, L-lactate, and L-malate. Metagenomic analysis of vaginal swabs from 20 vulvovaginal candidiasis (VVC) patients and 20 healthy women showed a correlation between Lactobacillus species abundance and reduced C. albicans colonization. In vitro experiments confirmed the inhibitory effects of these metabolites and the selected Lactobacillus strains on C. albicans growth, thereby validating our computational predictions. These findings provide insights into the metabolic interactions within the vaginal microbiome and pave the way for targeted microbial or metabolite-based therapeutic strategies to manage VVC.IMPORTANCEVulvovaginal candidiasis is a prevalent fungal infection with significant implications for women's health, caused primarily by Candida albicans. Although the protective role of a Lactobacillus-dominated vaginal microbiome is well established, the metabolic mechanisms underlying the interactions between Lactobacillus species and C. albicans remain inadequately understood. Specifically, the Lactobacillus species that effectively inhibit C. albicans and the metabolic pathways involved warrant further investigation. This study offers novel insights into the metabolic mechanisms underlying Lactobacillus antagonism against C. albicans. By identifying critical metabolic pathways and inhibitory metabolites, this study enhances our understanding of vaginal microbiome dynamics and host-microbe interactions. The findings suggest that key Lactobacillus strains and their metabolites could significantly reduce harmful levels of C. albicans, paving the way for future therapeutic strategies that leverage these microbial characteristics to promote vaginal health.

Harnessing plant-microbe interactions: strategies for enhancing resilience and nutrient acquisition for sustainable agriculture

The rhizosphere, a biologically active zone where plant roots interface with soil, plays a crucial role in enhancing plant health, resilience, and stress tolerance. As a key component in achieving Sustainable Development Goal 2, the rhizosphere is increasingly recognized for its potential to promote sustainable agricultural productivity. Engineering the rhizosphere microbiome is emerging as an innovative strategy to foster plant growth, improve stress adaptation, and restore soil health while mitigating the detrimental effects of conventional farming practices. This review synthesizes recent advancements in omics technologies, sequencing tools, and synthetic microbial communities (SynComs), which have provided insights into the complex interactions between plants and microbes. We examine the role of root exudates, composed of organic acids, amino acids, sugars, and secondary metabolites, as biochemical cues that shape beneficial microbial communities in the rhizosphere. The review further explores how advanced omics techniques like metagenomics and metabolomics are employed to elucidate the mechanisms by which root exudates influence microbial communities and plant health. Tailored SynComs have shown promising potential in enhancing plant resilience against both abiotic stresses (e.g., drought and salinity) and biotic challenges (e.g., pathogens and pests). Integration of these microbiomes with optimized root exudate profiles has been shown to improve nutrient cycling, suppress diseases, and alleviate environmental stresses, thus contributing to more sustainable agricultural practices. By leveraging multi-disciplinary approaches and optimizing root exudate profiles, ecological engineering of plant-microbiome interactions presents a sustainable pathway for boosting crop productivity. This approach also aids in managing soil-borne diseases, reducing chemical input dependency, and aligning with Sustainable Development Goals aimed at global food security and ecological sustainability. The ongoing research into rhizosphere microbiome engineering offers significant promise for ensuring long-term agricultural productivity while preserving soil and plant health for future generations.

Agricultural soil microbiomes at the climate frontier: Nutrient-mediated adaptation strategies for sustainable farming

The equilibrium transformation of soil microbial community dynamics and succession across various temporal and spatial dimensions plays a critical role in maintaining plant adaptability. Intensive agricultural practices accelerate the succession of plant microbial communities, rendering their restoration function more vulnerable. Climate change, with its variable impacts, affects the resilience of plant microbial communities through regulatory and mediating effects. Investigating the spatiotemporal dynamics of soil microbial communities in the context of climate change offers valuable insights into developing robust and resilient microbial ecosystems. This review examines the regulatory role of soil resources in plant microbial communities, the interactive effects of climate change on soil resource regulation, and the prediction of microbial community structures through resource allocation. Additionally, it explores the mechanisms that sustain ecological resilience in plant microbial community systems, emphasizing the application of the profit-averaging law.

New Insights into a Conceptual Bionic Colonic Bioreactor: A Model, 'Probiotics in Human Colon', Showing How Probiotics Alleviate Constipation from a Bioprocess Engineering Perspective

Constipation is a common problem which often causes negative impacts on the patient's quality of life. Apart from the pharmacologic and diet approaches, the use of probiotics has gradually shown promising efficacy to alleviate constipation. However, an exact understanding of the underlying mechanisms of probiotic actions on alleviating constipation is still unclear and need to be explored. In this review, we propose a model, 'probiotics in human colon', from a bioprocess engineering perspective. This model can be interpreted as a new concept of bionic colonic bioreactor design of a human colon in vitro, in which the transport phenomena during the fermentation of chyme by probiotics can be detected. By reviewing the anatomy structure and peristalsis mode of the human colon, we have focused on the influence by probiotics on the physical properties of colonic contents during the fermentation process. We relate physical properties such as shape, water content, density, hardness, viscosity, and elasticity to constipation symptoms directly. The influences on the physical properties of colon contents triggered by probiotics can be a potential key to understand the mechanisms for alleviating constipation.

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.

Paradox of the Sub-Plankton: Plausible Mechanisms and Open Problems Underlying Strain-Level Diversity in Microbial Communities

Microbial communities are often complex and highly diverse, typically with dozens of species sharing spatially-restricted environments. Within these species, genetic and ecological variation often exists at a much finer scale, with closely related strains coexisting and competing. While the coexistence of strains in communities has been heavily explored over the past two decades, we have no self-consistent theory of how this diversity is maintained. This question challenges our conventional understanding of ecological coexistence, typically framed around species with clear phenotypic and ecological differences. In this review, we synthesise plausible mechanisms underlying strain-level diversity (termed microdiversity), focusing on niche-based mechanisms such as nutrient competition, neutral mechanisms such as migration, and evolutionary mechanisms such as horizontal gene transfer. We critically assess the strengths and caveats of these mechanisms, acknowledging key gaps that persist in linking genetic similarity to ecological divergence. Finally, we highlight how the origin and maintenance of microdiversity could pose a major challenge to conventional ecological thinking. We articulate a call-to-arms for a dialogue between well-designed experiments and new theoretical frameworks to address this grand conceptual challenge in understanding microbial biodiversity.

Postlarval Shrimp-Associated Microbiota and Underlying Ecological Processes over AHPND Progression

Postlarval shrimp frequently face threats from acute hepatopancreatic necrosis disease (AHPND). Although AHPND affects both postlarval and adult shrimp, abiotic and biotic factors are distinct between life stages, such as rearing water nutrient levels and host life stage-dependent microbiota. The response of postlarvae-associated microbiota to AHPND, however, remains largely unexplored compared with its effects on juvenile and adult shrimp. To address this knowledge gap, a comparative analysis of postlarvae-associated microbiota and the ecological processes underlying AHPND progression was performed by sequencing the bacterial V3-V4 hypervariable region of the 16S rRNA gene. AHPND infection was validated by high copies of pirAB genes (Toxin 1) in diseased shrimp hepatopancreas. Advanced AHPND significantly altered the structure of the postlarvae-associated microbiota, with significant enrichment of Bacilli and Bdellovibrionia species in healthy larvae compared with matched AHPND-infected cohorts, although gut microbiota recovery was observed at the late disease stage, corresponding with the cessation of postlarval mortality. AHPND infection explained 11.0% (p < 0.001) of the variance in community structures, whereas postlarvae days post hatching also significantly influenced bacterial communities (7.1% variance, p < 0.001). AHPND-infected shrimp exhibited reduced homogeneous selection and increased dispersal limitation and drift governing their microbiota. These changes were primarily driven by specific microbial lineages, including enriched Bin36 Rhodobacteraceae and Bin11 Flavobacteriaceae, and suppressed Bin63 Vibrio and Bin9 Bacillus in AHPND-infected shrimp. After excluding shrimp age effect, 13 AHPND-discriminatory taxa were identified, accurately distinguishing infected shrimp from healthy individuals with 100% precision. Furthermore, AHPND outbreak weakened the network complexity and stability, which was driven by the suppressed keystone taxa that were positively associated with network robustness. Collectively, our findings deepen the understanding of the inextricable interplay between postlarval shrimp health, microbiota dynamics, and survival, as well as the underlying ecological mechanisms over AHPND progression.

Age matters: exploring differential effects of antimicrobial treatment on gut microbiota of adult and juvenile brown trout (Salmo trutta)

BACKGROUND

Antibiotics and antiparasitics are essential tools in controlling infectious disease outbreaks in commercial aquaculture. While the negative effects of antimicrobials on the gut microbiome of various farmed fish species are well documented, the influence of underlying host factors, such as age, on microbiome responses remains poorly understood. This is especially evident for peracetic acid, whose impact on the gut microbiome has not yet been studied. Understanding how microbiome dynamics vary by host age is critical to improving antibiotic stewardship in aquaculture. In this study, juvenile and sexually mature brown trout (Salmo trutta) were used as a model to investigate the age-dependent effects of florfenicol and peracetic acid on the gut microbiome using a 16S rRNA metabarcoding approach.

RESULTS

Fish age significantly shaped taxonomic composition and microbial co-occurrence network structure of the gut microbiome, regardless of treatment. Juvenile trout exhibited greater microbiome volatility and a stronger response to both florfenicol and peracetic acid compared to adult fish, with disruptions persisting up to 11 days post-treatment. Temporal dynamics were also evident, with microbial shifts characterized by a decline in beneficial commensals like Cetobacterium and Lactococcus. Although overall abundance recovered by 18 days post-treatment, network positions of key microbial community members remained altered, particularly in juvenile fish. Opportunistic pathogens, including Aeromonas and Streptococcus, were enriched and assumed more central roles within the microbial networks in treated fish.

CONCLUSION

The initial composition of the gut microbiome in brown trout is strongly influenced by fish age, which in turn affects the microbiome's response to antibiotic disruption. Juveniles displayed higher susceptibility to microbiome perturbation, and although recovery was observed at the community level, network properties remained altered. This study also provides the first evidence that external peracetic acid application can disrupt gut microbial communities. Since compositional shifts are often linked to functional alterations, even short-term disruptions may have important consequences for host health in developing fish. These findings emphasize the importance of considering gut microbial community structure in relation to fish age in aquaculture management practices.

Collective dynamical regimes predict invasion success and impacts in microbial communities

The outcomes of ecological invasions may depend on either characteristics of the invading species or attributes of the resident community. Here we use a combination of experiments and theory to show that the interplay between dynamics, interaction strength and diversity determine the invasion outcome in microbial communities. We find that the communities with fluctuating species abundances are more invasible and diverse than stable communities, leading to a positive diversity-invasibility relationship among communities assembled in the same environment. As predicted by theory, increasing interspecies interaction strength and species pool size leads to a decrease of invasion probability in our experiment. Our results show a positive correspondence between invasibility and survival fraction of resident species across all conditions. Communities composed of strongly interacting species can exhibit an emergent priority effect in which invader species are less likely to colonize than species in the original pool. However, if an invasion is successful, its ecological effects on the resident community are greater when interspecies interactions are strong. Our findings provide a unified perspective on the diversity-invasibility debate by showing that invasibility and invasion effect are emergent properties of interacting species, which can be predicted by simple community-level features.

Harnessing microbial division of labor for biomanufacturing: a review of laboratory and formal modeling approaches

Bioprocess industries aim to meet the increasing demand for product complexity by designing enhanced cellular and metabolic capabilities for the host. Monocultures, standard biomanufacturing workhorses, are often restricted in their capability to meet these demands, and the solution often involves the genetic modification of the host. Synthetic microbial communities are a promising alternative to monocultures because they exhibit division of labor, enabling efficient resource utilization and pathway modularity. This specialization minimizes metabolic burden and enhances robustness to perturbations, providing a competitive advantage. Despite this potential, their utilization in biotechnological or bioprocessing applications remains limited. The recent emergence of new and innovative community design tools and strategies, particularly those harnessing the division of labor, holds promise to change this outlook. Understanding the microbial interactions governing natural microbial communities can be used to identify complementary partners, informing synthetic community design. Therefore, we particularly consider engineering division of labor in synthetic microbial communities as a viable solution to accelerate progress in the field. This review presents the current understanding of how microbial interactions enable division of labor and how this information can be used to design synthetic microbial communities to perform tasks otherwise unfeasible to individual organisms. We then evaluate laboratory and formal modeling approaches specifically developed to: elucidate microbial community physiology, guide experimental design, and improve our understanding of complex community interactions assisting synthetic community design. By synthesizing these insights, we aim to present a comprehensive framework that advances the use of microbial communities in biomanufacturing applications.

Comparative analysis of amino acid auxotrophies and peptidase profiles in non-dysbiotic and dysbiotic small intestinal microbiomes

Small Intestinal Bacterial Overgrowth (SIBO) is linked to various diseases and has been associated with altered serum amino acid levels. However, the direct role of the gut microbiome in these changes remains unconfirmed. This study employs genome-scale metabolic modeling to predict amino acid auxotrophy and peptidase gene profiles in the small intestinal microbiomes of SIBO and non-SIBO subjects. Auxotrophy and peptidase gene profiles were further examined in the large intestinal microbiome under non-dysbiotic conditions to assess their similarity to the microbial SIBO profile. Our analysis revealed that the abundance of auxotrophic bacteria is higher in the microbiota of the small intestine than in the large intestine in non-dysbiotic controls. In patients with SIBO, the abundance of auxotrophies in the small intestine decreased compared to non-SIBO subjects. Peptidase gene profiles in non-dysbiotic individuals were distinct between small and large intestinal microbiomes, with fewer extracellular peptidase genes in small intestine microbiomes. In SIBO, extracellular peptidase genes increased compared to non-SIBO subjects. Further, there were more significant associations between the abundance of auxotrophies and peptidase genes in microbiomes of the small intestine compared to the large intestine. In conclusion, the auxotrophy and peptidase gene profiles of the small and large intestinal microbiomes were distinct. In SIBO, the small intestinal microbiome shifts towards a metabolic state resembling that of the large intestine, particularly in its increased abundance of extracellular peptidase genes. This highlights the potential of genome-scale metabolic modeling in identifying metabolic disruptions associated with SIBO, which could inform the development of targeted interventions.

A novel decomposer-exploiter interaction framework of plant residue microbial decomposition

BACKGROUND

Plant residue microbial decomposition, subject to significant environmental regulation, represents a crucial ecological process shaping and cycling the largest terrestrial soil organic carbon pool. However, the fundamental understanding of the functional dynamics and interactions between the principal participants, fungi and bacteria, in natural habitats remains limited.

RESULTS

In this study, the evolution of fungal and bacterial communities and their functional interactions were elucidated during the degradation of complexity-gradient plant residues. The results reveal that with increasing residue complexity, fungi exhibit heightened adaptability, while bacterial richness declines sharply. The differential functional evolution of fungi and bacteria is driven by residue complexity but follows distinct trajectories. Fundamentally, fungi evolve towards promoting plant residue degradation and so consistently act as the dominant decomposers. Conversely, bacteria predominantly increase expression of genes of glycosidases to exploit fungal degradation products, thereby consistently acting as exploiters. The presence of fungi enables and endures bacterial exploitation.

CONCLUSIONS

This study introduces a novel framework of fungal decomposers and bacterial exploiters during plant residue microbial decomposition, advancing our comprehensive understanding of microbial processes governing the organic carbon cycling.

Stochastic and deterministic processes shape microbial communities and flavor characteristics of strong-flavor daqu during storage

Daqu is a wheat-based fermentation starter essential for Chinese Baijiu production. The storage of daqu critically influences its quality. However, the assembly mechanisms of microbial communities in daqu during the storage phase and their impact on volatile flavor compounds remain unclear. This study investigated the microbial community assembly process and volatile compound profiles of daqu from three major regions of strong-flavor Baijiu production, Luzhou (LZ), Chengdu (CD), and Deyang (DY), during the storage phase. Fifteen biomarkers were identified across the regions using the random forest algorithm. Co-occurrence network analysis indicated that the LZ network was the most stable, while the CD network had the lowest complexity and stability, revealing 14 keystone species. Additionally, 42 differential volatile flavor compounds were identified. The analysis of microbial assembly mechanisms revealed that both stochastic and deterministic processes influenced the assembly of microbial communities in daqu during storage, as indicated by the modified stochasticity ratio (MST) and the neutral community model. Stochastic processes predominantly shaped the community of samples DY, while deterministic processes were more influential in the communities of samples LZ and CD. Notably, the important taxa (dominant microorganisms, keystone species, and biomarkers) were mainly influenced by deterministic processes, including temperature, dewpoint temperature, and surface air pressure, showing significant correlations with volatile flavor compounds. In conclusion, these findings highlight the effects of regional differences and storage processes on microbial community assembly and volatile flavor compounds in daqu, offering insights to regulate the daqu storage process and thereby optimize production.

Microbial functional diversity and redundancy: moving forward

Microbial functional ecology is expanding as we can now measure the traits of wild microbes that affect ecosystem functioning. Here, we review techniques and advances that could be the bedrock for a unified framework to study microbial functions. These include our newfound access to environmental microbial genomes, collections of microbial traits, but also our ability to study microbes' distribution and expression. We then explore the technical, ecological, and evolutionary processes that could explain environmental patterns of microbial functional diversity and redundancy. Next, we suggest reconciling microbiology with biodiversity-ecosystem functioning studies by experimentally testing the significance of microbial functional diversity and redundancy for the efficiency, resistance, and resilience of ecosystem processes. Such advances will aid in identifying state shifts and tipping points in microbiomes, enhancing our understanding of how and where will microbes guide Earth's biomes in the context of a changing planet.

Adaptive survival strategies of rumen microbiota with solid diet deficiency in early life cause epithelial mitochondrial dysfunction

With extreme nutritional substrate deficiency, the adaptive responses of the gastrointestinal microbiota and host metabolism are largely unknown. Here, we successfully established a microbial substrate deficiency model in the rumen without solid diet introduction in neonatal lambs. In the absence of solid diet, we observed a reduction in the Simpson Index of rumen bacteria, along with a marked decline in the abundance of keystone microorganisms such as Prevotella, Selenomonas, Megasphaera, and Succiniclasticum, indicating a simplified microbial interaction network. Additionally, more urea and NH3-N production facilitated microbial efficient nitrogen utilization to prioritize ammonia as a nitrogen source for survival, reallocating energy to overcome nutritional limitations and sustain their viability. In addition, enriched archaea (Methanosarcina, Methanomicrobium, Methanobrevibacter, and Methanobacterium) promoted hydrogen removal and the growth of nitrogen-producing microorganisms (Pecoramyces, Piromyces, Caecomyces, and Orpinomyces). It also reinforced the glutamate-glutamine pathway, as evidenced by the higher expression of glnA, GLUL, gdhA, and ureAB, suggesting enhanced internal cycling of nitrogen for microbial survival. This selfish microbial survival strategy deprived the host of adequate volatile fatty acids for energy metabolism, resulting in the downregulation of rumen epithelial cell cycle proteins (CCNB1, CCNE), abnormal mitochondrial morphology, and reduced mitochondrial deoxyribonucleic acid copy number and adenosine triphosphate production. Overall, these findings revealed the adaptive survival strategies of rumen microbiota with solid diet deficiency in early life, which caused alterations in epithelial cell mitochondrial function.

Metagenomic symphony of the intestinal ecosystem: How the composition affects the mind

Mental health disorders and neurodegenerative diseases place a heavy burden on patients and societies, and, although great strides have been made to understand the pathophysiology of these conditions, advancement in drug development is lagging. The importance of gastrointestinal health in maintaining overall health and preventing disease is not a new concept. Hundreds of years ago, healers from various cultures and civilizations recognized the crucial role of the gut in sustaining health. More than a century ago, scientists began exploring the restorative effects of probiotics, marking the early recognition of the importance of gut microbes. The omics era brought more enlightenment and enabled researchers to identify the complexity of the microbial ecosystems we harbour, encompassing bacteria, eukaryotes (including fungi), archaea, viruses, and other microorganisms. The extensive genetic capacity of the microbiota is dynamic and influenced by the environment. The microbiota therefore serves as a significant entity within us, with evolutionarily preserved functions in host metabolism, immunity, development, and behavior. The significant role of the bacterial gut microbiome in mental health and neurodegenerative disorders has been realized and described within the framework of the microbiota-gut-brain axis. However, the bacterial members do not function unaccompanied, but rather in concert, and there is a substantial knowledge gap regarding the involvement of non-bacterial microbiome members in these disorders. In this review, we will explore the current literature that implicates a role for the entire metagenomic ensemble, and how their complex interkingdom relationships could influence CNS functioning in mental health disorders and neurodegenerative diseases.

Sowing success: ecological insights into seedling microbial colonisation for robust plant microbiota engineering

Manipulating the seedling microbiota through seed or soil inoculations has the potential to improve plant health. Mixed in-field results have been attributed to a lack of consideration for ecological processes taking place during seedling microbiota assembly. In this opinion article, we (i) assess the contribution of ecological processes at play during seedling microbiota assembly (e.g., propagule pressure and priority effects); (ii) investigate how life history theory can help us identify microbial traits involved in successful seedling colonisation; and (iii) suggest how different plant microbiota engineering methods could benefit from a greater understanding of seedling microbiota assembly processes. Finally, we propose several research hypotheses and identify outstanding questions for the plant microbiota engineering community.

Co-evolutionary dynamics of microbial communities and flavor profiles during natural fermentation of Cabernet Sauvignon and Merlot: A comparative study within a single vineyard

Indigenous microorganisms play a crucial role in determining the quality of naturally fermented wines. However, the impact of grape cultivar specificity on microbial composition is often overshadowed by the geographical location of the vineyard, leading to underestimation of its role in natural wine fermentation. Therefore, this study focuses on different grape cultivars within a single vineyard. The physicochemical results revealed that during fermentation of Merlot and Cabernet Sauvignon wines, ethanol content significantly increased, while residual sugar, pH, malic acid, citric acid, and yeast assimilable nitrogen notably decreased. High-throughput sequencing (HTS) results showed that fungal diversity and richness in Merlot were significantly higher than in Cabernet Sauvignon, whereas bacterial diversity exhibited the opposite trend. The predominant fungal genera in Merlot were Hanseniaspora, followed by Lachancea, whereas the opposite was observed in Cabernet Sauvignon. Erysiphe and Pantoea were exclusively present in Merlot, whereas Erwinia was detected only in Cabernet Sauvignon. A total of 106 flavor compounds were quantified using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS), identifying 22 core volatile compounds in Merlot and 19 in Cabernet Sauvignon. Moreover, at the end of fermentation, the total ester content in Cabernet Sauvignon was significantly higher than in Merlot, imparting a more pronounced fruity and floral aroma, which was further confirmed using sensory analysis. Correlation analysis indicated that Saccharomyces was positively correlated with alcohol content, total acidity, and 16 core volatile compounds, while Hanseniaspora and Lachancea showed opposite correlations. These insights provide a data reference for producing high-quality wines with regional characteristics.

A framework for understanding collective microbiome metabolism

Microbiome metabolism underlies numerous vital ecosystem functions. Individual microbiome members often perform partial catabolism of substrates or do not express all of the metabolic functions required for growth. Microbiome members can complement each other by exchanging metabolic intermediates and cellular building blocks to achieve a collective metabolism. We currently lack a mechanistic framework to explain why microbiome members adopt partial metabolism and how metabolic functions are distributed among them. Here we argue that natural selection for proteome efficiency-that is, performing essential metabolic fluxes at a minimal protein investment-explains partial metabolism of microbiome members, which underpins the collective metabolism of microbiomes. Using the carbon cycle as an example, we discuss motifs of collective metabolism, the conditions under which these motifs increase the proteome efficiency of individuals and the metabolic interactions they result in. In summary, we propose a mechanistic framework for how collective metabolic functions emerge from selection on individuals.

Enhanced Fermentation of Pu-Erh Tea with Aspergillus niger: Quality and Microbial Community Analysis

Post-fermented Pu-erh tea (PFPT) is a microbial fermented tea characterized by unique sensory attributes and multiple health benefits. Aspergillus niger is the dominant fungus involved in the fermentation process and plays a significant role in imparting the distinct characteristics of PFPT. To investigate the role of Aspergillus niger in the fermentation of Pu-erh tea, this study inoculated unsterilized sun-dried green tea with Aspergillus niger isolated from Pu-erh tea to enhance the fermentation process. Metabolites and microbial communities in sun-dried green tea (CK), fortified fermented tea (TF), and naturally fermented tea (NF) were analyzed using non-targeted metabolomics, 16S rDNA, and internal transcribed spacer sequencing. Non-targeted metabolomics revealed that Aspergillus niger significantly altered the metabolite profile of the tea samples, identifying a total of 200 different metabolites, with 95 showing significant increases and 105 significant decreases, predominantly enriched in metabolic pathways associated with amino acid biosynthesis and degradation. High-throughput sequencing revealed that although the relative abundance of the fungal community remained largely unchanged, the inoculation of Aspergillus niger significantly increased the abundance of Bacillales and Pseudomonas within the bacterial community, thereby influencing the dynamic balance of the microbial ecosystem. Collectively, the inoculation of Aspergillus niger altered the composition of the microbial community and metabolic activities, resulting in changes to the content of amino acid-dominated metabolites, thereby enhancing the flavor profile and overall quality of Pu-erh tea. These findings provide important insights for optimizing the production processes of Pu-erh tea and the application of microorganisms in other fermented foods.

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.

Initial soil condition, stand age, and aridity alter the pathways for modifying the soil carbon under afforestation

Afforestation is a crucial pathway for ecological restoration and has the potential to modify soil microbial community, thereby impacting the cycling and accumulation of carbon in soil across diverse patterns. However, the overall patterns of how afforestation impacts below-ground carbon cycling processes remain uncertain. In this comprehensive meta-analysis, we systematically evaluated 7045 observations from 210 studies worldwide to evaluate the influence of afforestation on microbial communities, enzyme activities, microbial functions, and associated physicochemical properties of soils. Afforestation increases microbial biomass, carbon and nitrogen hydrolase activities, and microbial respiration, but not carbon oxidase activity and nitrogen decomposition rate. Conversely, afforestation leads to a reduction in the metabolic quotient, with significant alteration of bacterial and fungal community structures and positive effects on the fungi: bacteria ratio rather than alpha and beta diversity metrics. We found a total 77 % increase in soil organic carbon (SOC) content after afforestation, which varied depending on initial SOC content before afforestation, afforestation stand age, and aridity index of afforestation sites. The modified SOC is associated with bacterial community composition along with intracellular metabolic quotient and extracellular carbon degrading enzyme activity playing a role. These findings provide insights into the pathways through which afforestation affects carbon cycling via microorganisms, thus improving our knowledge of soil carbon reservoir's responses to afforestation under global climate change.

Deciphering microbial metabolic interactions and their implications for community dynamics in acid mine drainage sediments

The microbially-mediated reduction processes have potential for the bioremediation of acid mine drainage (AMD), which represents a worldwide environment problem. However, we know little about the microbial interactions in anaerobic AMD sediments. Here we utilized genome-resolved metagenomics to uncover the nature of cooperative and competitive metabolic interactions in 90 AMD sediments across Southern China. Our analyses recovered well-represented prokaryotic communities through the reconstruction of 2625 population genomes. Functional analyses of these genomes revealed extensive metabolic handoffs which occurred more frequently in nitrogen metabolism than in sulfur metabolism, as well as stable functional redundancy across sediments resulting from populations with low genomic relatedness. Genome-scale metabolic modeling showed that metabolic competition promoted microbial co-occurrence relationships, suggesting that community assembly was dominated by habitat filtering in sediments. Notably, communities colonizing more extreme conditions tended to be highly competitive, which was typically accompanied with increased network complexity but decreased stability of the microbiome. Finally, our results demonstrated that heterotrophic Thermoplasmatota associated with ferric iron and sulfate reduction contributed most to the elevated levels of competition. Our study shed light on the cooperative and competitive metabolisms of microbiome in the hazardous AMD sediments, which may provide preliminary clues for the AMD bioremediation in the future.

iNAP 2.0: Harnessing metabolic complementarity in microbial network analysis

With the widespread adoption of metagenomic sequencing, new perspectives have emerged for studying microbial ecological networks, yielding metabolic evidence of interspecies interactions that traditional co-occurrence networks cannot infer. This protocol introduces the integrated Network Analysis Pipeline 2.0 (iNAP 2.0), which features an innovative metabolic complementarity network for microbial studies from metagenomics sequencing data. iNAP 2.0 sets up a four-module process for metabolic interaction analysis, namely: (I) Prepare genome-scale metabolic models; (II) Infer pairwise interactions of genome-scale metabolic models; (III) Construct metabolic interaction networks; and (IV) Analyze metabolic interaction networks. Starting from metagenome-assembled or complete genomes, iNAP 2.0 offers a variety of methods to quantify the potential and trends of metabolic complementarity between models, including the PhyloMint pipeline based on phylogenetic distance-adjusted metabolic complementarity, the SMETANA (species metabolic interaction analysis) approach based on cross-feeding substrate exchange prediction, and metabolic distance calculation based on parsimonious flux balance analysis (pFBA). Notably, iNAP 2.0 integrates the random matrix theory (RMT) approach to find the suitable threshold for metabolic interaction network construction. Finally, the metabolic interaction networks can proceed to analysis using topological feature analysis such as hub node determination. In addition, a key feature of iNAP 2.0 is the identification of potentially transferable metabolites between species, presented as intermediate nodes that connect microbial nodes in the metabolic complementarity network. To illustrate these new features, we use a set of metagenome-assembled genomes as an example to comprehensively document the usage of the tools. iNAP 2.0 is available at https://inap.denglab.org.cn for all users to register and use for free.

Metabolic cross-feeding interactions modulate the dynamic community structure in microbial fuel cell under variable organic loading wastewaters

The efficiency of microbial fuel cells (MFCs) in industrial wastewater treatment is profoundly influenced by the microbial community, which can be disrupted by variable industrial operations. Although microbial guilds linked to MFC performance under specific conditions have been identified, comprehensive knowledge of the convergent community structure and pathways of adaptation is lacking. Here, we developed a microbe-microbe interaction genome-scale metabolic model (mmGEM) based on metabolic cross-feeding to study the adaptation of microbial communities in MFCs treating sulfide-containing wastewater from a canned-pineapple factory. The metabolic model encompassed three major microbial guilds: sulfate-reducing bacteria (SRB), methanogens (MET), and sulfide-oxidizing bacteria (SOB). Our findings revealed a shift from an SOB-dominant to MET-dominant community as organic loading rates (OLRs) increased, along with a decline in MFC performance. The mmGEM accurately predicted microbial relative abundance at low OLRs (L-OLRs) and adaptation to high OLRs (H-OLRs). The simulations revealed constraints on SOB growth under H-OLRs due to reduced sulfate-sulfide (S) cycling and acetate cross-feeding with SRB. More cross-fed metabolites from SRB were diverted to MET, facilitating their competitive dominance. Assessing cross-feeding dynamics under varying OLRs enabled the execution of practical scenario-based simulations to explore the potential impact of elevated acidity levels on SOB growth and MFC performance. This work highlights the role of metabolic cross-feeding in shaping microbial community structure in response to high OLRs. The insights gained will inform the development of effective strategies for implementing MFC technology in real-world industrial environments.

Metabolic interdependencies in thermophilic communities are revealed using co-occurrence and complementarity networks

Microbial communities exhibit intricate interactions underpinned by metabolic dependencies. To elucidate these dependencies, we present a workflow utilizing random matrix theory on metagenome-assembled genomes to construct co-occurrence and metabolic complementarity networks. We apply this approach to a temperature gradient hot spring, unraveling the interplay between thermal stress and metabolic cooperation. Our analysis reveals an increase in the frequency of metabolic interactions with rising temperatures. Amino acids, coenzyme A derivatives, and carbohydrates emerge as key exchange metabolites, forming the foundation for syntrophic dependencies, in which commensalistic interactions take a greater proportion than mutualistic ones. These metabolic exchanges are most prevalent between phylogenetically distant species, especially archaea-bacteria collaborations, as a crucial adaptation to harsh environments. Furthermore, we identify a significant positive correlation between basal metabolite exchange and genome size disparity, potentially signifying a means for streamlined genomes to leverage cooperation with metabolically richer partners. This phenomenon is also confirmed by another composting system which has a similar wide range of temperature fluctuations. Our workflow provides a feasible way to decipher the metabolic complementarity mechanisms underlying microbial interactions, and our findings suggested environmental stress regulates the cooperative strategies of thermophiles, while these dependencies have been potentially hardwired into their genomes during co-evolutions.

DyMMM-LEAPS: An ML-based framework for modulating evenness and stability in synthetic microbial communities

There have been a growing number of computational strategies to aid in the design of synthetic microbial consortia. A framework to identify regions in parametric space to maximize two essential properties, evenness and stability, is critical. In this study, we introduce DyMMM-LEAPS (dynamic multispecies metabolic modeling-locating evenness and stability in large parametric space), an extension of the DyMMM framework. Our method explores the large parametric space of genetic circuits in synthetic microbial communities to identify regions of evenness and stability. Due to the high computational costs of exhaustive sampling, we utilize adaptive sampling and surrogate modeling to reduce the number of simulations required to map the vast space. Our framework predicts engineering targets and computes their operating ranges to maximize the probability of the engineered community to have high evenness and stability. We demonstrate our approach by simulating five cocultures and one three-strain culture with different social interactions (cooperation, competition, and predation) employing quorum-sensing-based genetic circuits. In addition to guiding circuit tuning, our pipeline gives an opportunity for a detailed analysis of pockets of evenness and stability for the circuit under investigation, which can further help dissect the relationship between the two properties. DyMMM-LEAPS is easily customizable and can be expanded to a larger community with more complex interactions.

Ecological associations distribution modelling of marine plankton at a global scale

Marine plankton communities form intricate networks of interacting organisms at the base of the food chain, and play a central role in regulating ocean biogeochemical cycles and climate. However, predicting plankton community shifts in response to climate change remains challenging. While species distribution models are valuable tools for predicting changes in species biogeography under climate change scenarios, they generally overlook the key role of biotic interactions, which can significantly shape ecological processes and ecosystem responses. Here, we introduce a novel statistical framework, association distribution modelling (ADM), designed to model and predict ecological associations distribution in space and time. Applied on a Tara Oceans genome-resolved metagenomics dataset, the present-day biogeography of ADM-inferred marine plankton associations revealed four major biogeographic biomes organized along a latitudinal gradient. We predicted the evolution of these biome-specific communities in response to a climate change scenario, highlighting differential responses to environmental change. Finally, we explored the functional potential of impacted plankton communities, focusing on carbon fixation, outlining the predicted evolution of its geographical distribution and implications for ecosystem function.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Engineering agricultural soil microbiomes and predicting plant phenotypes

Plant growth-promoting rhizobacteria (PGPR) can improve crop yields, nutrient use efficiency, plant tolerance to stressors, and confer benefits to future generations of crops grown in the same soil. Unlocking the potential of microbial communities in the rhizosphere and endosphere is therefore of great interest for sustainable agriculture advancements. Before plant microbiomes can be engineered to confer desirable phenotypic effects on their plant hosts, a deeper understanding of the interacting factors influencing rhizosphere community structure and function is needed. Dealing with this complexity is becoming more feasible using computational approaches. In this review, we discuss recent advances at the intersection of experimental and computational strategies for the investigation of plant-microbiome interactions and the engineering of desirable soil microbiomes.

Host control and species interactions jointly determine microbiome community structure

The host microbiome can be considered an ecological community of microbes present inside a complex and dynamic host environment. The host is under selective pressure to ensure that its microbiome remains beneficial. The host can impose a range of ecological filters including the immune response that can influence the assembly and composition of the microbial community. How the host immune response interacts with the within-microbiome community dynamics to affect the assembly of the microbiome has been largely unexplored. We present here a mathematical framework to elucidate the role of host immune response and its interaction with the balance of ecological interactions types within the microbiome community. We find that highly mutualistic microbial communities characteristic of high community density are most susceptible to changes in immune control and become invasion prone as host immune control strength is increased. Whereas highly competitive communities remain relatively stable in resisting invasion to changing host immune control. Our model reveals that the host immune control can interact in unexpected ways with a microbial community depending on the prevalent ecological interactions types for that community. We stress the need to incorporate the role of host-control mechanisms to better understand microbiome community assembly and stability.

Investigation of the toxicity of Cr (VI) against cyanobacteria and the mechanism of tolerance of the cyanobacterial consortia: a quantum mechanical approach

Hexavalent chromium (Cr (VI)) is a heavy metal that is distributed globally and poses a significant threat to the environment through various mechanisms. It can react with soil and water, leading to severe environmental damage. In this study, the toxicity of Cr (VI) was investigated by analyzing two major cyanobacteria species, Nostoc commune and Anabaena variabilis, commonly found in soil along with their consortia. The findings revealed that the toxicity mechanisms of Cr (VI) differed in individual monocultures, with Cr (VI) competing with various components. However, when the cyanobacteria species were combined, i.e., in consortia, they demonstrated an impressive retention of their functioning even in Cr (VI) concentration at 10 ppm. The study also concluded that non-photochemical quenching played a critical role in minimizing Cr (VI) toxicity. Furthermore, the research examined the role of the S-cycle in the process. The quantum yield of electron flux revealed that the Cr (VI) was competing with Qa in A. variabilis and with Qb in N. commune, albeit the photosystem dysfunction is only visible in the latter. The mechanism seemed to be quantum tunneling alteration because of the Cr (VI) having different energized quantum wells. The consortia proved to be behaving in a better manner as compared to the control. Overall, this study reveals the mode of toxicity of Cr (VI) in these two important cyanobacterial strains as well as it also discusses the mechanism of tolerance of consortia against Cr (VI) toxicity.

Reducing Application of Nitrogen Fertilizer Increases Soil Bacterial Diversity and Drives Co-Occurrence Networks

Reducing nitrogen fertilizer application highlights its role in optimizing soil bacterial communities to achieve sustainable agriculture. However, the specific mechanisms of bacterial community change under these conditions are not yet clear. In this study, we employed long-term field experiments and high-throughput sequencing to analyze how varying levels of nitrogen application influence the soil bacterial community structure and co-occurrence networks. The results show that reducing the nitrogen inputs significantly enhances the diversity and evenness of the soil bacterial communities, possibly due to the diminished dominance of nitrogen-sensitive taxa, which in turn liberates the ecological niches for less competitive species. Furthermore, changes in the complexity and stability of the bacterial co-occurrence networks suggest increased community resilience and a shift toward more mutualistic interactions. These findings underline the potential of reduced nitrogen application to alleviate competitive pressures among bacterial species, thereby promoting a more diverse and stable microbial ecosystem, highlighting the role of competitive release in fostering microbial diversity. This research contributes to our understanding of how nitrogen management can influence soil health and offers insights into sustainable agricultural practices.

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

BACKGROUND

Microbiomes are generally characterized by high diversity of coexisting microbial species and strains, and microbiome composition typically remains stable across a broad range of conditions. However, under fixed conditions, microbial ecology conforms with the exclusion principle under which two populations competing for the same resource within the same niche cannot coexist because the less fit population inevitably goes extinct. Therefore, the long-term persistence of microbiome diversity calls for an explanation.

RESULTS

To explore the conditions for stabilization of microbial diversity, we developed a simple mathematical model consisting of two competing populations that could exchange a single gene allele via horizontal gene transfer (HGT). We found that, although in a fixed environment, with unbiased HGT, the system obeyed the exclusion principle, in an oscillating environment, within large regions of the phase space bounded by the rates of reproduction and HGT, the two populations coexist. Moreover, depending on the parameter combination, all three major types of symbiosis were obtained, namely, pure competition, host-parasite relationship, and mutualism. In each of these regimes, certain parameter combinations provided for synergy, that is, a greater total abundance of both populations compared to the abundance of the winning population in the fixed environment.

CONCLUSIONS

The results of this modeling study show that basic phenomena that are universal in microbial communities, namely, environmental variation and HGT, provide for stabilization and persistence of microbial diversity, and emergence of ecological complexity.

Microbiome modeling: a beginner's guide

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

Bacterial dispersal enhances the elimination of active fecal coliforms during vermicomposting of fruit and vegetable wastes: The overlooked role of earthworm mucus

Earthworms play a pivotal role in the elimination of fecal coliforms during vermicomposting of fruit and vegetable waste (FVWs). However, the specific mechanisms underlying the action of earthworm mucus remain unclear. This study investigated the mechanisms of fecal coliform reduction related to earthworm mucus during FVWs vermicomposting by comparing treatments with and without earthworms. The results show that the secretion of earthworm mucus decreased by 13.93 % during the startup phase, but significantly (P < 0.001) increased by 57.80 % during the degradation phase. Compared to the control without earthworms, vermicomposting led to a significant (P < 0.05) 1.22 -fold increase in the population of active bacteria, with a strong positive correlation between mucus characteristics and dominant bacterial phyla. As the dominant fecal coliforms, Escherichia coli and Klebsiella pneumoniae significantly (P < 0.05) declined by 86.20 % and 93.38 %, respectively, in the vermi-reactor relative to the control. Bacterial dispersal limitation served as a key factor constraining the elimination of E. coli (r = 0.73, P < 0.01) and K. pneumoniae (r = 0.77, P < 0.001) during vermicomposting. This study suggests that earthworm mucus increases the active bacterial abundance and cooperation by weakening the bacterial dispersal limitation, thus intensifying competition and antagonism between fecal coliforms and other bacteria.

Oral bacteria relative abundance in faeces increases due to gut microbiota depletion and is linked with patient outcomes

The detection of oral bacteria in faecal samples has been associated with inflammation and intestinal diseases. The increased relative abundance of oral bacteria in faeces has two competing explanations: either oral bacteria invade the gut ecosystem and expand (the 'expansion' hypothesis), or oral bacteria transit through the gut and their relative increase marks the depletion of other gut bacteria (the 'marker' hypothesis). Here we collected oral and faecal samples from mouse models of gut dysbiosis (antibiotic treatment and DSS-induced colitis) and used 16S ribosomal RNA sequencing to determine the abundance dynamics of oral bacteria. We found that the relative, but not absolute, abundance of oral bacteria increases, reflecting the 'marker' hypothesis. Faecal microbiome datasets from diverse patient cohorts, including healthy individuals and patients with allogeneic haematopoietic cell transplantation or inflammatory bowel disease, consistently support the 'marker' hypothesis and explain associations between oral bacterial abundance and patient outcomes consistent with depleted gut microbiota. By distinguishing between the two hypotheses, our study guides the interpretation of microbiome compositional data and could potentially identify cases where therapies are needed to rebuild the resident microbiome rather than protect against invading oral bacteria.

Dual stressors of infection and warming can destabilize host microbiomes

Climate change is causing extreme heating events and intensifying infectious disease outbreaks. Animals harbour microbial communities, which are vital for their survival and fitness under stressful conditions. Understanding how microbiome structures change in response to infection and warming may be important for forecasting host performance under global change. Here, we evaluated alterations in the microbiomes of several wild Caenorhabditis elegans isolates spanning a range of latitudes, upon warming temperatures and infection by the parasite Leucobacter musarum. Using 16S rRNA sequencing, we found that microbiome diversity decreased, and dispersion increased over time, with the former being more prominent in uninfected adults and the latter aggravated by infection. Infection reduced dominance of specific microbial taxa, and increased microbiome dispersion, indicating destabilizing effects on host microbial communities. Exposing infected hosts to warming did not have an additive destabilizing effect on their microbiomes. Moreover, warming during pre-adult development alleviated the destabilizing effects of infection on host microbiomes. These results revealed an opposing interaction between biotic and abiotic factors on microbiome structure. Lastly, we showed that increased microbiome dispersion might be associated with decreased variability in microbial species interaction strength. Overall, these findings improve our understanding of animal microbiome dynamics amidst concurrent climate change and epidemics. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

Designing function-specific minimal microbiomes from large microbial communities

Microorganisms exist in large communities of diverse species, exhibiting various functionalities. The mammalian gut microbiome, for instance, has the functionality of digesting dietary fibre and producing different short-chain fatty acids. Not all microbes present in a community contribute to a given functionality; it is possible to find a minimal microbiome, which is a subset of the large microbiome, that is capable of performing the functionality while maintaining other community properties such as growth rate and metabolite production. Such a minimal microbiome will also contain keystone species for SCFA production in that community. In this work, we present a systematic constraint-based approach to identify a minimal microbiome from a large community for a user-proposed function. We employ a top-down approach with sequential deletion followed by solving a mixed-integer linear programming problem with the objective of minimising the L1-norm of the membership vector. Notably, we consider quantitative measures of community growth rate and metabolite production rates. We demonstrate the utility of our algorithm by identifying the minimal microbiomes corresponding to three model communities of the gut, and discuss their validity based on the presence of the keystone species in the community. Our approach is generic, flexible and finds application in studying a variety of microbial communities. The algorithm is available from https://github.com/RamanLab/minMicrobiome .

Carbon starvation raises capacities in bacterial antibiotic resistance and viral auxiliary carbon metabolism in soils

Organic carbon availability in soil is crucial for shaping microbial communities, yet, uncertainties persist concerning microbial adaptations to carbon levels and the ensuing ecological and evolutionary consequences. We investigated organic carbon metabolism, antibiotic resistance, and virus-host interactions in soils subjected to 40 y of chemical and organic fertilization that led to contrasting carbon availability: carbon-poor and carbon-rich soils, respectively. Carbon-poor soils drove the enrichment of putative genes involved in organic matter decomposition and exhibited specialization in utilizing complex organic compounds, reflecting scramble competition. This specialization confers a competitive advantage of microbial communities in carbon-poor soils but reduces their buffering capacity in terms of organic carbon metabolisms, making them more vulnerable to environmental fluctuations. Additionally, in carbon-poor soils, viral auxiliary metabolic genes linked to organic carbon metabolism increased host competitiveness and environmental adaptability through a strategy akin to "piggyback the winner." Furthermore, putative antibiotic resistance genes, particularly in low-abundance drug categories, were enriched in carbon-poor soils as an evolutionary consequence of chemical warfare (i.e., interference competition). This raises concerns about the potential dissemination of antibiotic resistance from conventional agriculture that relies on chemical-only fertilization. Consequently, carbon starvation resulting from long-term chemical-only fertilization increases microbial adaptations to competition, underscoring the importance of implementing sustainable agricultural practices to mitigate the emergence and spread of antimicrobial resistance and to increase soil carbon storage.

Modeling Dynamics of Human Gut Microbiota Derived from Gluten Metabolism: Obtention, Maintenance and Characterization of Complex Microbial Communities

Western diets are rich in gluten-containing products, which are frequently poorly digested. The human large intestine harbors microorganisms able to metabolize undigested gluten fragments that have escaped digestion by human enzymatic activities. The aim of this work was obtaining and culturing complex human gut microbial communities derived from gluten metabolism to model the dynamics of healthy human large intestine microbiota associated with different gluten forms. For this purpose, stool samples from six healthy volunteers were inoculated in media containing predigested gluten or predigested gluten plus non-digested gluten. Passages were carried out every 24 h for 15 days in the same medium and community composition along time was studied via V3-V4 16S rDNA sequencing. Diverse microbial communities were successfully obtained. Moreover, communities were shown to be maintained in culture with stable composition for 14 days. Under non-digested gluten presence, communities were enriched in members of Bacillota, such as Lachnospiraceae, Clostridiaceae, Streptococcaceae, Peptoniphilaceae, Selenomonadaceae or Erysipelotrichaceae, and members of Actinomycetota, such as Bifidobacteriaceae and Eggerthellaceae. Contrarily, communities exposed to digested gluten were enriched in Pseudomonadota. Hence, this study shows a method for culture and stable maintenance of gut communities derived from gluten metabolism. This method enables the analysis of microbial metabolism of gluten in the gut from a community perspective.