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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

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2026

Cross-domain cooperation drives nutrient acquisition and metabolism in the bark beetle holobiont.

Microbial symbiosis underpins host adaptation, yet mechanisms of metabolic integration in holobionts remain unclear. Using metatranscriptomics, genomics, and metabolic assays, we investigated gut microbiome interactions in the European spruce bark beetle (Ips typographus). We observed metabolic complementarity among symbionts and host, forming cross-domain networks that support nutrient acquisition. Nitrogen recycling revealed strong interdependence: no single partner possessed a complete uric acid degradation pathway, but combined evidence supports a distributed pathway spanning beetle, Bacteria, and fungi. Additionally, bacterial nitrate reduction to ammonia indicates a potential nitrogen influx, making otherwise inaccessible inorganic nitrogen available to the host. Shaped by microbial interactions, symbionts also likely supply specific amino acids, while vitamin metabolism showed cross-domain co-metabolism, with Bacteria as main producers of B vitamins, while host and fungi modulated interconversion. Carbohydrate degradation was highly partitioned; bacteria target xylan and pectin, while fungi contribute to glucan breakdown. Crucially, our data provide indirect evidence that the beetle may contribute to complete cellulose degradation, highlighting an underappreciated host role in lignocellulose processing. In terms of enzymatic functional diversity, the bacteriome emerged as the most important microbiome component-an observation that contrasts with the traditional focus on fungi and underscores the need to consider bacterial contributions in insect symbioses. Despite life-stage variation, core metabolic functions remained stable. Overall, metabolic interdependence, rather than microbial composition alone, structures holobiont function. These results highlight functional redundancy and ecological resilience, emphasizing the importance of microbial cooperation and host-microbe metabolic evolution.

Bark beetle↗

PubMed2026

Metabolic niche differentiation and napA evolution stabilize partial denitrification in wastewater ecosystems.

Although partial denitrification (PD) is increasingly applied as a nitrite-supplying strategy for anammox-based nitrogen removal, the ecological distribution, metabolic specialization, and genomic determinants of stable nitrite accumulation remain poorly understood at the ecosystem scale. Here, we reconstructed 516 high-quality metagenome-assembled genomes (MAGs) using high-depth metagenomic sequencing of 107 wastewater treatment plants and classified denitrifiers according to their nitrite production or consumption capacities. Of these genomes, 23% (120 MAGs) were classified as partial denitrifiers, 41% (211 MAGs) as complete denitrifiers, and 36% (185 MAGs) as nitrite-reducing denitrifiers, revealing pronounced functional partitioning rather than dominance by complete denitrification pathways. Comparative genomics showed that partial denitrifiers possess metabolic architectures favoring rapid carbon oxidation and NADH generation while exhibiting constrained NADPH production and biosynthetic investment, thereby promoting nitrate-to-nitrite conversion but limiting subsequent nitrite reduction. Nitrite accumulation does not result from incomplete denitrification pathways but from metabolic niche differentiation. These metabolic trade-offs were further associated with the evolutionary divergence of the periplasmic nitrate reductase gene, napA, which displayed distinct sequence characteristics and genomic contexts between partial and complete denitrifiers. Integration of carbohydrate-active enzyme repertoires further revealed metabolic complementarity between partial denitrifiers and anammox bacteria, supporting efficient carbon handoff without direct substrate competition. From an engineering perspective, operating conditions that impose moderate electron limitation, such as low or fluctuating C/N ratios and intermittent carbon feeding, may selectively enrich partial denitrifiers and enhance a stable nitrite supply for PD-anammox systems. Together, these findings identify PD as a predictable ecological state shaped by genome-encoded metabolic specialization and provide a mechanistic basis for designing robust, low-carbon nitrogen-removal processes.

Anammox↗

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↗

PubMed2026

Comprehensive quality profiling and comparative metabolic characterization of seven dominant fresh-eating Chinese olive (Canarium album Lour.) cultivars in Southern China.

Fresh-eating Chinese olive (Canarium album Lour.) is a subtropical fruit endemic to southern China with considerable commercial value, yet systematic quality characterization of dominant cultivars remains scarce. This study established a multi-dimensional quality dataset for seven dominant cultivars from Fujian and Guangdong provinces, integrating nutritional components, soluble sugars, organic acids, mineral elements, volatile profiles, and non-targeted metabolomics. Significant cultivar-specific differences were observed across all evaluated dimensions: "Lingfeng" exhibited a sugar-dominant low-acid profile, whereas "Sanleng" showed elevated phenolic constituents accumulation. Volatile profiling identified terpenoid-based candidate discriminatory biomarkers, and metabolomic analysis revealed phenylpropanoid biosynthesis, tryptophan metabolism, and starch and sucrose metabolism as the most variable pathways. Correlations between untargeted profiling and targeted absolute quantification validated untargeted result reliability and revealed their complementarity in nutritional evaluation. These findings provide baseline data for FECO germplasm evaluation and targeted industrial utilization.

China↗

PubMed2026

Genome-resolved analysis reveals disruption of gut microbial vitamin B and K2 biosynthesis during Toxoplasma gondii infection in mice.

UNLABELLED: Toxoplasma gondii infection remodels the gut microbiome, yet its impact on microbial vitamin biosynthetic potential and host redox metabolism remains unclear. Here, we integrated mouse gut metagenomes with publicly available metagenome-assembled genomes (MAGs) to construct a genome-resolved atlas of B-vitamin and vitamin K2 biosynthesis. From 45,697 MAGs, we curated 4,771 representative genomes, of which 2,682 met high-quality criteria (completeness ≥90%, contamination <5%). Functional annotation identified 229,717 vitamin-related genes corresponding to 177 Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologs across de novo pathways for eight B vitamins, thiamine (B1), riboflavin (B2), niacin (B3), pantothenate (B5), pyridoxine (B6), biotin (B7), folate (B9), cobalamin (B12), and vitamin K2. Among the high-quality genomes, 1,665 encoded complete de novo pathways for at least one vitamin, highlighting functional specialization and community-level complementarity. Transcripts per million-normalized metagenomic read counts revealed significant differences in KEGG ortholog abundances across six of the nine vitamin pathways. Reanalysis of metagenomic data from infected mice (acute, chronic, and control; n = 10 per group) revealed a stage-dependent reduction in α-diversity of vitamin biosynthesis pathways during acute infection, and a clear β-diversity separation from chronic and control groups. Core niacin biosynthesis genes (nadB, nadA, nadC) displayed phylum-specific redistribution, indicating selective remodeling of microbial NAD+ precursor production under infection-induced metabolic stress. These results suggest that T. gondii infection disrupts cooperative vitamin biosynthetic networks while specifically modulating niacin pathways linked to host NAD+ metabolism. IMPORTANCE: Gut microbes can synthesize essential vitamins, but how infection alters this function is poorly understood. By integrating mouse gut metagenomes with genome-resolved microbial data, we show that Toxoplasma gondii infection reshapes the vitamin biosynthetic potential of the gut microbiome in a stage-dependent manner. Acute infection reduces the diversity of vitamin biosynthesis pathways and shifts the taxonomic distribution of key niacin biosynthesis genes involved in microbial NAD+ precursor production. These findings identify vitamin metabolism, especially niacin-related pathways, as a sensitive functional axis of microbiome remodeling during infection. Our work links microbial taxonomic changes to functional metabolic consequences and suggests that microbiome-mediated regulation of NAD+-related metabolism may contribute to host redox adaptation during T. gondii infection.

B vitamins↗

PubMed2026

Dual recognition drives site-directed G-quadruplex stabilization: Oligonucleotide design in G4 ligand-oligonucleotide conjugates.

G-quadruplex (G4) DNA structures are increasingly recognized for their roles in transcriptional regulation and genome stability, making them attractive therapeutic targets. Selective recognition of individual G4s remains challenging due to the high structural similarity among G4 motifs. G4 Ligand-Oligonucleotides conjugates (GL-Os) address this challenge by combining small-molecule G4 ligands with the sequence specificity of oligonucleotides, targeting sequences flanking the intended G4 target. Here, we systematically investigate how oligonucleotide length, backbone composition, and sequence complementarity govern GL-O binding, selectivity, and G4 stabilization. We show that effective G4 recognition depends on the interdependence between oligonucleotide hybridization and G4 ligand binding, such that both elements cooperatively reinforce complex stability and site specificity. Longer oligonucleotides promote more stable complexes and stronger G4 stabilization, whereas central mismatches disrupt this dual-recognition mechanism. Replacement of DNA with peptide nucleic acids (PNAs) enhances binding strength, thermal stability, and metabolic stability. Importantly, ligand conjugation redirects PNA oligonucleotides from nonspecific polymerase stalling toward selective G4 stabilization. Finally, we demonstrate receptor-mediated cellular uptake of modified GL-Os, supporting the feasibility of cellular delivery while highlighting remaining delivery barriers. Together, these findings show the molecular design principles governing GL-O behavior and provide a foundation for the future development and evaluation of selective G4-targeting therapeutics.

G-quadruplex DNA↗