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At least 19 recordsLinked to original sources
PubMed2025

StrainR2 accurately deconvolutes strain-level abundances in synthetic microbial communities.

MOTIVATION: Synthetic microbial communities offer an opportunity to conduct reductionist research in tractable model systems. However, deriving abundances of highly related strains within these communities is currently unreliable. 16S rRNA gene sequencing does not resolve abundance at the strain level and other methods such as quantitative polymerase chain reaction (qPCR) scale poorly and are resource prohibitive for complex communities. We present StrainR2, which utilizes shotgun metagenomic sequencing to provide high accuracy strain-level abundances for all members of a synthetic community, provided their genomes. RESULTS: Both in silico, and using sequencing data derived from gnotobiotic mice colonized with a synthetic fecal microbiota, StrainR2 resolves strain abundances with greater accuracy and efficiency than other tools utilizing shotgun metagenomic sequencing reads. We demonstrate that StrainR2's accuracy is comparable to that of qPCR on a subset of strains resolved using absolute quantification. AVAILABILITY AND IMPLEMENTATION: Software is available at GitHub and implemented in C, R, and Bash. Software is supported on Linux and MacOS, with packages available on Bioconda or as a Docker container. The source code at the time of publication is also available on figshare at the doi: 10.6084/m9.figshare.29420780.

Mice↗
PubMed2026

Synthetic community derived from the root core microbes of a desert shrub Caragana korshinskii enhances wheat drought tolerance.

BACKGROUND: Drought, intensified by climate change, poses a mounting threat to global food security by severely constraining crop productivity. While microbial inoculants offer promise for drought tolerance, their poor adaptability remains insufficient for extremely water-deficient environments. Desert plants host unique drought-adapted microbiomes that remain largely unexplored for agricultural applications. RESULTS: Here, we investigated the microbial community of the desert shrub Caragana korshinskii and identified a core set of drought-responsive strains. A synthetic microbial community (SynCom) derived from these strains significantly improved wheat growth under drought stress. Metagenomic analyses revealed that microbial functions related to biofilm formation, quorum sensing, and carbon metabolism were enriched, with Pseudomonas identified as a key functional taxon. Guided by inter-strain interactions in biofilm assembly, we streamlined the consortium into a five-member synthetic community, where quorum-sensing signals promoted community-wide biofilm formation. Community biofilm production improved strain colonization and conferred greater drought tolerance compared to monocultures. In plants, mechanistic investigations indicated that the simplified SynCom inoculation universally upregulated MAPK and jasmonic acid signaling pathways. Furthermore, carbohydrate metabolic pathways such as starch and sucrose metabolism were specifically activated, suggesting a multi-level mechanism underlying SynCom-mediated drought tolerance. CONCLUSIONS: These findings demonstrate that SynCom constructed on the endophytic flora of desert plants can significantly enhance crop drought tolerance. Our work highlights the pivotal role of community biofilm synthesis in facilitating root colonization and activating a multidimensional drought tolerance network in plants. This study not only gives an ecological perspective on desert microbiome adaptations but also offers a strategic framework for developing effective microbial inoculants for arid-region agriculture. Video Abstract.

Caragana↗
PubMed2026

Enhancing the fiber degradation efficiency in dairy cattle rumen through engineered bacterial communities.

BACKGROUND: The rumen functions as an anaerobic fermentation chamber, housing microorganisms with cellulolytic and proteolytic capabilities that facilitate feed utilization. Fiber-degrading bacteria possess the capability to enhance the productivity of cellulolytic feed. The application of omics technologies has greatly improved our understanding of the rumen microbiome. Determining microbial composition and functional patterns in the rumen does not equate to a comprehensive exploration of rumen microbial resources and their mechanisms of action. This study seeks to integrate high throughput 16S rRNA data with information on culturomics, cellulolytic activities, nutrition, and synthetic microbial communities (SynCom) engineering. The objective is to evaluate the relationship between rumen microbial activity and fiber utilization efficiency in cattle, ultimately aiming to develop a more powerful intervention strategy for the ruminant industry. RESULTS: The enrichment culture with various carbon sources led to significant alterations in the composition and structure of rumen microbiota, particularly enhancing those associated with carbohydrate metabolism. Employing the culturomics methodology, 896 strains from 78 species (including 8 novel species) were isolated, resulting in a 10.1% isolation rate relative to the rumen bacterial community. Among them, 35 strains demonstrated boosted cellulose-degrading capability on plates, while 25 exhibited the ability to degrade hemicellulose as well. SynComs of these candidates were prepared based on the ratio observed in rumen microbiota exhibiting high cellulolytic performance. SynCom 3 improved the neutral detergent fiber degradation (NDFD) by 20.39% averagely. Additionally, both in vitro and in situ assessments indicated that the optimization of dose/strain in SynCom 3 significantly improved the in vitro NDFD by 20.56% and increased the in situ NDFD by 7.81%, along with the acidic detergent fiber (ADF, + 11.47%). Genomic analysis revealed that the SynCom 3 functioned well in fiber degradation through the synergistic action of key carbohydrate-active enzymes. CONCLUSIONS: This study strengthens rumen microbiome research by integrating omics and SynCom engineering within a microbiota-bacteria-enzymes-genes framework, revealing the significance of enzymatic synergy in carbohydrate metabolism. The findings establish a framework for utilizing low-abundance microbes and engineering functional consortia, which are crucial for improving ruminant feed utilization and biomass conversion. Future research should investigate the transcriptomic profiles and the metabolic cross-feeding mechanisms of fiber-degrading strains in the rumen. Video Abstract.

Animals↗
PubMed2026

Precisely designed keystone metabolites boost shrimp disease resistance by recruiting symbionts via the lipoxin A4-AP-1 pathway.

BACKGROUND: Gut metabolites and symbionts are indispensable for host health, yet the precise identification of keystone metabolites and construction of synthetic microbial communities (SynComs) to enhance disease resistance remains limited. RESULTS: Using Litopenaeus vannamei as a model, we identified pyruvic acid and DL-glutamine (1:2) as keystone metabolites by borrowing the microbial ecology principles of bio-indicators and driver taxa. Dietary supplementation with these metabolites sufficiently protected shrimp from white feces syndrome (WFS). Multi-omics analyses demonstrated that keystone metabolites exerted positive effects by enriching beneficial Ruegeria lacuscaerulensis, Bacillus subtilis and Nioella nitratireducens, strengthening the gut network stability, and enhancing shrimp immunity, which collectively potentiated WFS resistance. The recruited three strains were consumers and producers of the two keystone metabolites, and discriminative strains between healthy and diseased shrimp across global datasets. A SynCom constructed from the three strains (4:3:2) replicated the efficacy of keystone metabolites. Both keystone metabolites and SynCom elevated shrimp gut and hepatopancreas lipoxin A4 (LXA4) levels, which suppressed the pro-inflammatory transcription factor AP-1, as validated by in vivo inhibition assay. CONCLUSIONS: Our findings demonstrate that precisely designed keystone metabolites enhance shrimp disease resistance through the recruitment of key symbionts-LXA4-AP-1 axis. The rationally designed keystone metabolites and SynCom are compelling biocontrol solutions in improving host disease resistance. Video Abstract.

Animals↗
PubMed2026

Rhizosphere Dialogue: Microorganisms Mediated by Root Exudates Alleviate Drought Stress in Grasses.

Drought stress threatens the ecological functions and economic value of grasses, posing a major challenge to their sustainable production. Plants co-evolve with rhizosphere microbial communities, sometimes described as the plant's second genome, that can contribute to drought adaptation. Drought alters root architecture, hormonal and redox regulation and belowground carbon allocation, thereby modifying the quantity and composition of root exudation and reshaping the rhizosphere environment. This review uses the rhizosphere dialogue as an integrative framework to link these plant responses with microbial recruitment and subsequent feedback to the host. We summarise three linked stages of this dialogue: drought-induced changes in root exudation; microbial recruitment and colonisation through chemotaxis, attachment, biofilm formation, and root colonisation; and microbiome-mediated feedback that improves plant water relations, hormonal and redox homoeostasis, nutrient acquisition, and root function. We highlight microbial extracellular polymeric substances, 1-aminocyclopropane-1-carboxylate deaminase, and microbial volatile organic compounds as key mediators of drought alleviation. We then discuss how this framework may inform rational synthetic microbial community (SynCom) design, microbiome-informed breeding, artificial intelligence and machine-learning assisted strain prioritisation, rhizosphere legacy effects, and real-time monitoring. Future work should distinguish active exudate-mediated recruitment from drought-driven environmental filtering and integrate multi-omics, plant genetics, functional validation, and multi-location field trials to determine whether rhizosphere dialogue can become a predictive framework for climate-resilient grass production.

drought stress↗
PubMed2026

From dysbiosis to resilience: Microbiome engineering for sustainable shrimp aquaculture.

The intensification of shrimp aquaculture has increased exposure to disease, environmental perturbations, and antimicrobial pressure, making microbial stability increasingly relevant to sustainable production. Microbiome stability-encompassing resistance to disturbance and resilience of functional recovery-provides an ecological framework for understanding how shrimp and culture-environment microbial communities respond to intensive farming. This review examines the transition from microbial homeostasis to dysbiosis and evaluates how microbiome engineering could redirect disrupted communities towards resilient states. Evidence is integrated across the intestine, hepatopancreas, rearing water, sediment and biofloc to assess how host genetics, ontogeny, diet, culture conditions, antibiotics and pollutants shape microbiome assembly and destabilization. Disease-associated changes in acute hepatopancreatic necrosis disease, white faeces syndrome, Enterocytozoon hepatopenaei infection, and white spot syndrome virus infection are critically evaluated, with explicit separation of associations, pathogen-induced dysbiosis, and community-level causality. Established and emerging interventions-including probiotics, prebiotics, synbiotics, functional diets, biofloc management, phages, postbiotics, microbiota transplantation and synthetic microbial communities-are assessed according to their capacity to modify microbial function, persistence and recovery rather than taxonomic change alone. We further examine how multi-omics, microbiome-informed breeding, and environmental monitoring could support biomarker development, predictive decision support and context-specific intervention. We argue that progress requires a shift from taxonomic description to function-guided engineering, from endpoint comparisons to direct measurement of resilience, and from laboratory efficacy to reproducible farm-scale validation. Overall, microbiome management may contribute to more disease-resilient and sustainable shrimp production, provided that its effectiveness can be validated under commercial farming conditions.

Dysbiosis↗
PubMed2026

Decoding microbial metabolic complementarity from individual traits to community structuring.

A fundamental challenge in microbiome research lies in elucidating the functional capacity of microbial communities through community membership and genomic data. As community structuring and emergent functional traits are determined by bacterial community metabolic networks, it is important to gain insights into the principles that govern bacteria-bacteria interactions. Here, we applied an integrative framework linking individual strain-level traits to community structuring in a simplified synthetic bacterial community (SSC8) that promotes the growth of ungrafted watermelon. By combining mono- and coculture assays with genome-scale metabolic modeling and metabolomic profiling of spent media, we characterized directional interactions and resource dependencies among community members. Our findings show that positive interactions dominated the community network, accounting for 55% of all pairwise combinations, indicating a high prevalence of growth-promoting effects among strains. Genome-scale metabolic modeling showed that functional divergence among strains enhanced the potential for metabolic complementarity as phylogenetic distance increased. Integrating metabolic modeling with metabolomics further suggested that Pseudomonas azotifigens Q6 not only benefited from all other community members, but also exhibited mutualistic interactions with the other three strains, with metabolite exchange involving compounds such as L-lysine and L-cysteine. Pseudomonas azotifigens Q6 acted as an important driver of community composition by affecting the abundance of several other consortium members in vitro. These findings highlight the role of metabolic complementarity in driving community structuring by promoting selective persistence of specific strains. Our work provides mechanistic insights into microbial interaction networks in vitro and offers a conceptual foundation for the rational design of functionally robust and plant-beneficial microbiomes.

Bacteria↗
PubMed2026

PGPR inoculation and growth enhancement of crops cultivated in hydroponic systems.

Plant growth-promoting rhizobacteria (PGPR) are ubiquitous rhizosphere microorganisms that promote plant health through various mechanisms. Although the study of PGPR inoculants in soil has been done for ages, their application in hydroponic systems has received relatively limited attention. This review identifies PGPR inoculants that are commonly used in hydroponics, methods of application, and their effects on plant growth and nutrient use efficiency. Literature shows that PGPR inoculants improve plant performance in controlled hydroponic systems through the production of growth-stimulating substances, nitrogen fixation, and improved nutrient acquisition. However, the plant growth responses are highly variable depending on the composition of nutrient solutions, environmental factors, crop and microbe species, and the type of hydroponic system. The review identifies various challenges of PGPR inoculation in hydroponic systems and future research directions to address the current gaps. Generally, the productivity of hydroponic systems can be enhanced through advanced inoculation strategies and the development of suitable carrier materials to improve inoculant survival, viability, and functions. Emphasis should also be placed on designing system-specific microbial consortia and Synthetic communities that are tailored to the unique ecological conditions of hydroponic systems.

Hydroponics↗
PubMed2025

In silico encounters: harnessing metabolic modelling to understand plant-microbe interactions.

Understanding plant-microbe interactions is vital for developing sustainable agricultural practices and mitigating the consequences of climate change on food security. Plant-microbe interactions can improve nutrient acquisition, reduce dependency on chemical fertilizers, affect plant health, growth, and yield, and impact plants' resistance to biotic and abiotic stresses. These interactions are largely driven by metabolic exchanges and can thus be understood through metabolic network modelling. Recent developments in genomics, metagenomics, phenotyping, and synthetic biology now enable researchers to harness the potential of metabolic modelling at the genome scale. Here, we review studies that utilize genome-scale metabolic modelling to study plant-microbe interactions in symbiotic, pathogenic, and microbial community systems. This review catalogues how metabolic modelling has advanced our understanding of the plant host and its associated microorganisms as a holobiont. We showcase how these models can contextualize heterogeneous datasets and serve as valuable tools to dissect and quantify underlying mechanisms. Finally, we consider studies that employ metabolic models as a testbed for in silico design of synthetic microbial communities with predefined traits. We conclude by discussing broader implications of the presented studies, future perspectives, and outstanding challenges.

Plants↗
PubMed2025

Coarse-grained model of serial dilution dynamics in synthetic human gut microbiome.

Many microbial communities in nature are complex, with hundreds of coexisting strains and the resources they consume. We currently lack the ability to assemble and manipulate such communities in a predictable manner in the lab. Here, we take a first step in this direction by introducing and studying a simplified consumer resource model of such complex communities in serial dilution experiments. The main assumption of our model is that during the growth phase of the cycle, strains share resources and produce metabolic byproducts in proportion to their average abundances and strain-specific consumption/production fluxes. We fit the model to describe serial dilution experiments in hCom2, a defined synthetic human gut microbiome with a steady-state diversity of 63 species growing on a rich media, using consumption and production fluxes inferred from metabolomics experiments. The model predicts serial dilution dynamics reasonably well, with a correlation coefficient between predicted and observed strain abundances as high as 0.8. We applied our model to: (i) calculate steady-state abundances of leave-one-out communities and use these results to infer the interaction network between strains; (ii) explore direct and indirect interactions between strains and resources by increasing concentrations of individual resources and monitoring changes in strain abundances; (iii) construct a resource supplementation protocol to maximally equalize steady-state strain abundances.

Gastrointestinal Microbiome↗
PubMed2026

Unveiling phthalate esters biodegradation from microbial community to Pseudarthrobacter scleromae HL-1: Kinetics, genomic insights, pathways, toxicity assessment and environmental remediation.

Phthalate esters (PAEs) are ubiquitous synthetic plasticizer pollutants posing severe ecological and human health risks. This study compared microbial community structures and dibutyl phthalate (DBP) degradation kinetics of two consortia: 7-day enriched MC1 (50 mg/L DBP) and 6-cycle acclimated MC7 (50-1000 mg/L DBP), demonstrating directional DBP stress selection generated a low-diversity, highly specialized degradative community with a 25.4 mg/L/h maximum degradation rate (Vmax), 1.68-fold higher than MC1. Four dominant DBP-degrading strains were isolated from MC7; Pseudarthrobacter scleromae HL-1 showed the highest efficiency with 17.1 mg/L/h Vmax and complete 500 mg/L DBP removal within 72 h, broad substrate spectrum, and strong adaptability after optimization. Whole-genome sequencing and GC-MS/MS elucidated a dual-parallel DBP mineralization pathway, first reported in Pseudarthrobacter, integrating ester hydrolysis and side-chain β-oxidation. ECOSAR and Chlorella vulgaris bioassays confirmed progressive toxicity attenuation, with > 99% relative toxicity reduction after 72 h and no toxic intermediate accumulation. Natural lake water trials with trace background PAEs showed HL-1 successfully colonized aquatic environments, reshaped indigenous communities into synergistic degradative consortia, and achieved 99.2% DBP removal in 84 h. This work provides comprehensive insights into PAE biodegradation mechanisms from community to single strain and highlights HL-1 as a promising candidate for remediating PAE-polluted aquatic ecosystems.

Genomic analysis↗
PubMed2026

In silico analysis and comparison of the metabolic capabilities of different organisms by reducing metabolic complexity.

BACKGROUND: Understanding how metabolic capabilities diverge across microbial species is essential for deciphering community function, ecological interactions, and the design of synthetic microbiomes. Despite shared core pathways, microbial phenotypes can differ markedly due to evolutionary adaptations and metabolic specialization. Genome-scale metabolic models (GEMs) provide a systems-level framework to explore these differences; however, their complexity hinders direct comparison. RESULTS: We introduce NIS (Neidhardt-Ingraham-Schaechter), a computational workflow that integrates the redGEM, lumpGEM, and redGEMX algorithms to systematically reduce genome-scale models into biologically interpretable modules. This approach enables direct, quantitative comparison of fueling pathways, biomass biosynthetic routes, and environmental exchange processes while retaining essential metabolic information. We first demonstrate the utility of NIS by analyzing Escherichia coli and Saccharomyces cerevisiae, which revealed both conserved and divergent strategies in central metabolism, biosynthetic cost, and substrate utilization. We then applied NIS to the core honeybee gut microbiome, uncovering distinct metabolic traits, functional redundancy, and complementarity that help explain auxotrophy, cross-feeding interactions, and microbial coexistence. CONCLUSIONS: NIS provides an automated, scalable, and reproducible framework for dissecting microbial metabolic networks beyond gene content or taxonomy. By linking metabolism to ecological function, NIS offers new opportunities to interpret microbial community dynamics and to support the rational design of microbiomes in health, agriculture, and environmental applications. Video Abstract.

Metabolic Networks and Pathways↗
PubMed2025

Roles of microbial interactions in determining the establishment and function of synthetic consortium inoculants for soil applications.

Synthetic microbial consortium inoculants are emerging nature-based solutions for promoting sustainable agriculture and mitigating environmental challenges. However, despite promising results in simpler lab-scale trials, many inoculants fail to establish or perform satisfactorily in field conditions. One most critical yet least understood factor influencing inoculant effectiveness is the complex microbial interactions, both within consortium inoculants ("within-community" interactions) and between consortium inoculants and native soil communities ("cross-community" interactions). Here, we first discuss major negative and positive "within-community" interactions and highlight the importance to design consortium inoculants with positive interactions for improved stability and functionality. We then examine the bidirectional "cross-community" interactions once introducing consortium inoculants to soils. Soil native communities often create strong resistance to the invasion of inoculants. We discuss major drivers controlling the invasibility of native communities and various strategies increasing the invasiveness of consortium inoculants. We then discuss how consortium inoculants can reshape native communities, with implications for long-term ecosystem resilience and functioning. We propose future research efforts including advancing strategies for harnessing natural species from relatively untapped soil reservoirs and using high-throughput interaction profiling with multi-omics and computational tools to build compatible synthetic consortia with desirable functions; leveraging positive interactions and prebiotics to facilitate inoculant establishment; and assessing fully soil functional resilience over longer terms, including recognizing the importance of rare keystone taxa. By integrating with ecological theory, this review provides a comprehensive insight into microbial interactions to advance the design, application, and monitoring of synthetic consortium inoculants for enhancing soil health and ecosystem sustainability.

establishment↗
PubMed2026

Bacterial motility in rhizosphere colonization: mechanisms, constraints, and implications for microbial inoculants.

Although the potential of microbial inoculants for sustainable agriculture and environmental restoration has been widely recognized, their field performance remains highly variable and often unpredictable. Current research and development frameworks for microbial inoculants primarily focus on their plant growth-promoting functions and metabolic traits, often overlooking the ecological processes that determine whether introduced strains can successfully disperse, access, and establish within the rhizosphere. Increasing evidence suggests that successful dispersal and establishment cannot be assumed in the highly heterogeneous conditions of soil systems. Here, we summarize the key mechanisms underlying bacterial motility and discuss its role within the broader framework of microbial dispersal, highlighting how motility-mediated processes contribute to rhizosphere colonization. We propose that bacterial motility represents a key mechanistic determinant of biofertilizer efficacy. Its role extends beyond the ability of inoculant strains to physically reach the rhizosphere, encompassing competitive colonization on the root surface, long-term persistence, and the ability to respond to dynamic root-derived chemical gradients associated with newly developing root tissues. We argue that inoculant motility should be elevated from a passive descriptive trait to a core design parameter that can be systematically incorporated and regulated during the development and optimization of microbial inoculants. We outline a multi-tiered strategic framework for next-generation biofertilizer engineering that integrates strain selection, community design, motility regulation, and deployment strategies, thereby unlocking the full potential of synthetic microbial consortia for sustainable agriculture, ecosystem restoration, and climate change mitigation.

Biofertilizer↗
PubMed2026

Deciphering the effects of sulfonamide antibiotics on denitrification from a metagenomic perspective: Inhibition of nitrite reduction and succession patterns of functional microorganisms.

Limited research has thoroughly elucidated the impact mechanisms of antibiotics on the denitrification process at the genomic and gene levels, which has hindered the optimization and development of nitrogen removal technology for antibiotic-containing swine wastewater. Lab-scale sequencing batch reactors were constructed in this study to treat synthetic wastewater containing different sulfonamides and nitrate. Investigations were carried out on denitrification performance, microbial community diversity, denitrifier succession patterns, and functional gene distribution. The stress of sulfonamides inhibited the nitrite reduction process, transforming complete denitrification into partial denitrification and causing significant nitrite accumulation. The average nitrogen removal efficiency in the treatment groups decreased from 81.0% ± 2.2-40.1% ± 6.1%. Alicycliphilus and Thauera were identified as the key taxa, accounting for 32.2% and 16.9% of all potential denitrifying bacteria, respectively. Although metagenome-assembled genomes (MAGs) from Thauera were enriched with genes encoding nitrate reductases (nap, nar) and nitrite reductases (nir), this genus preferentially utilized nitrate as an electron acceptor, resulting in the preferential nitrate reduction and subsequent nitrite accumulation. In contrast, Alicycliphilus MAGs developed tolerance to the sulfonamides stress during later stages, with concomitant enrichment of associated functional genes. They replaced Thauera to reemerge as the dominant group, thereby restoring complete denitrification. This study provides new insights into the regulatory mechanisms governing complete versus partial denitrification in nitrogen removal from antibiotic-containing wastewater.

Denitrifier succession↗
PubMed2026

Ecological Restoration of the Soil-Like Function in the Bauxite Residue: Natural Microbiomes Mediated Molecular Transformation of Dissolved Organic Matter.

Soilization of bauxite residues offers a scalable route for long-term carbon management and ecological restoration. However, the microbial processes that transform exogenous organic inputs into stable soil-like carbon pools remain poorly resolved. Here, we combined cross-ecosystem meta-analysis, machine-learning prediction, native synthetic community (SynCom) construction, 13C-labeled straw microcosms, field validation, Fourier transform ion cyclotron resonance mass spectrometry, and genome-resolved metagenomics to unravel microbiome-mediated carbon transformation at the dissolved organic matter (DOM) molecular scale. Our meta-analysis revealed that alkaline industrial wastes retained soil-like DOM signatures but were enriched in microbial humic- and protein-like components, indicating active yet incomplete carbon processing. Guided by these patterns, native SynCom inoculation increased 13C incorporation into total organic carbon (TOC) and dissolved organic carbon (DOC), enlarged biodegradable and adsorbable DOC fractions, and shifted DOM from recalcitrant aromatic pools toward oxygenated carbohydrate-, tannin-, and phenolic-like molecular classes. Genome-resolved analyses linked this transformation to complementary polymer degradation and nutrient-cycling functions across fungal and bacterial guilds, including enriched carbohydrate-active enzymes in straw-carbon-utilizing metagenome-assembled genomes. Null model and thermodynamic analyses further showed that microbial communities were constrained by homogeneous selection, whereas DOM molecules were diversified through variable selection and redox-dependent transformation. Field-scale validation confirmed that SynCom promoted TOC and DOC accumulation and humic-like, high-density DOM fractions under alkaline conditions. Together, these findings establish a mechanistic framework in which functional microbiomes couple plant carbon depolymerization, DOM molecular diversification, and mineral-interactive carbon stabilization, providing a microbiome-guided strategy for carbon sequestration and soilization in the bauxite residue.

Soil↗
PubMed2025

Function-based selection of synthetic communities enables mechanistic microbiome studies.

Understanding the complex interactions between microbes and their environment requires robust model systems such as synthetic communities (SynComs). We developed a functionally directed approach to generate SynComs by selecting strains that encode key functions identified in metagenomes. This approach enables the rapid construction of SynComs tailored to any ecosystem. To optimize community design, we implemented genome-scale metabolic models, providing in silico evidence for cooperative strain coexistence prior to experimental validation. Using this strategy, we designed multiple host-specific SynComs, including those for the rumen, mouse, and human microbiomes. By weighting functions differentially enriched in diseased versus healthy individuals, we constructed SynComs that capture complex host-microbe interactions. We designed an inflammatory bowel disease SynCom of 10 members that successfully induced colitis in gnotobiotic IL10-/- mice, demonstrating the potential of this method to model disease-associated microbiomes. Our study establishes a framework for designing functionally representative SynComs of any microbial ecosystem, facilitating mechanistic study.

Animals↗
PubMed2025

Reducing redundancy and enhancing accuracy through a phylogenetically-informed microbial community metabolic modeling approach.

MOTIVATION: Metabolic modeling has emerged as a powerful tool for predicting community functions. However, current modeling approaches face significant challenges in balancing the metabolic trade-offs between individual and community-level growth. In this study, we investigated the effect of metabolic relatedness among taxa on growth rate calculations by merging related taxa based on their metabolic similarity, introducing this approach as PhyloCOBRA. RESULTS: This approach enhanced the accuracy and efficiency of microbial community simulations by combining genome-scale metabolic models (GEMs) of closely related organisms, aligning with the concepts of niche differentiation and nestedness theory. To validate our approach, we implemented PhyloCOBRA within the MICOM and OptCom package (creating PhyloMICOM and PhyloOptCom, respectively), and applied it to metagenomic data from 186 individuals and four-species synthetic community (SynCom). Our results demonstrated significant improvement in the accuracy and reliability of growth rate predictions compared to the standard methods. Sensitivity analysis revealed that PhyloMICOM models were more robust to random noise, while Jaccard index calculations showed a reduction in redundancy, highlighting the enhanced specificity of the generated community models. Furthermore, PhyloMICOM reduced the computational complexity, addressing a key concern in microbial community simulations. This approach marks a significant advancement in community-scale metabolic modeling, offering a more stable, efficient, and ecologically relevant tool for simulating and understanding the intricate dynamics of microbial ecosystems. AVAILABILITY AND IMPLEMENTATION: PhyloCOBRA implementations are available as extensions to the MICOM packages and can be accessed at https://github.com/sepideh-mofidifar/PhyloCOBRA.

Phylogeny↗