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PubMed2026

Metabolic reprogramming and taxonomic drivers in bacterial vaginosis: A large-scale metagenomic meta-analysis.

OBJECTIVE: Bacterial vaginosis (BV) represents a profound ecological shift from a Lactobacillus-dominated microbiota to a diverse polymicrobial biofilm associated with adverse outcomes. While taxonomic signatures are well-documented, the functional mechanisms driving this transition remain obscured. This study elucidates the genomic potential for metabolic reprogramming and the putative "functional handover" underpinning the stability of the dysbiotic state. METHODS: A computational meta-analysis of 3557 vaginal microbiomes from diverse global cohorts was performed using the standardized MGnify pipeline. A high-resolution subset of 187 whole-genome shotgun (WGS) metagenomes was stratified to compare functional potential across demographic groups. Taxon-function interaction networks were constructed, utilizing a dual-filter statistical approach (p < 0.05 and effect size ranking), to map the shift from homeostatic maintenance to dysbiotic metabolic potential. RESULTS: BV was characterized by a fundamental shift from "maintenance" pathways to high-turnover "growth-oriented" genomic repertoires. While ABC transporter-like domains were present in healthy communities, dysbiosis was marked by a quantitative expansion and diversification of these systems alongside P-loop NTPases. Network analysis revealed a putative "functional handover": while Gardnerella serves as the adherent structural scaffold, the metabolic burden appears to be associated with secondary anaerobes, specifically BVAB1 and Sneathia, which exhibit strong genomic correlations with nutrient transport and stress response pathways. Crucially, microbiomes from women of African ancestry (Black cohort) exhibited a distinct functional profile with genomic signatures consistent with functions previously associated with resistome expansion (e.g., tetracycline/macrolide resistance), contrasting with Asian cohorts. CONCLUSION: BV is a state of metabolic reprogramming where genomic functional dominance is transferred from Lactobacillus to a cooperative network of anaerobic opportunists. Identifying BVAB1 and Sneathia as candidate metabolic engines, supported by a Gardnerella scaffold, challenges current therapeutic paradigms and highlights the potential for precision medicine targeting specific functional drivers and resistome profiles across diverse populations.

Humans↗

PubMed2026

Intratumoral Mycobacterium abscessus promotes cytidine deaminase mutagenesis in non-small cell lung cancer.

The intratumoral microbiota is increasingly recognized as an active component of the tumor microenvironment, yet whether it directly drives tumor mutagenesis remains unclear. Here, integrated multi-omics analysis of human non-small cell lung cancer (NSCLC) identifies Mycobacterium abscessus as a microbial determinant of APOBEC3A-associated mutagenesis. Mechanistically, the bacterial effector nucleoside diphosphate kinase (NDK) directly targets the host transcription factor IRF3 and installs a non-canonical 1-phosphohistidine modification at H263, thereby amplifying type I interferon signaling and sustaining APOBEC3A expression. This inter-kingdom phosphotransfer event links intratumoral microbial colonization to an endogenous mutational process that promotes genomic diversification. Genetic inactivation of NDK, or pharmacologic elimination using an engineered NDK-PROTAC, suppresses APOBEC3A activation and attenuates microbe driven mutagenesis. Together, these findings establish a direct microbial effector mechanism that promotes APOBEC3A-associated mutagenesis and provide a therapeutic framework to intercept microbiome driven mutagenesis in NSCLC.

Humans↗

PubMed2026

Hormone priming and metabolic engineering of phytohormone crosstalk in rice under combined biotic and abiotic stresses: a multi-omics perspective for climate-resilient crop development.

Rice (Oryza sativa L.) is the caloric backbone for more than half of humanity, yet it remains one of the most vulnerable crops to the simultaneous biotic and abiotic stresses exacerbated by climate change. Phytohormone priming and the complex crosstalk networks governed by transcription factor hubs like WRKY, MYB, and NAC serve as the central adaptive mechanism for stress resilience. This review synthesizes how multi-omics integration, including spatial and single-cell transcriptomics, is resolving the molecular architecture of hormonal priming and epigenetic stress memory. We critically evaluate advanced metabolic engineering and genome-editing strategies such as CRISPR-Cas9, base/prime editing, and synthetic gene circuits that enable precision modifications to decouple stress tolerance from historical yield penalties. Furthermore, we discuss the emerging roles of microbiome-assisted priming via synthetic consortia and the application of artificial intelligence and digital twins (continuously updated computational models of crop physiology) for predictive stress management. By integrating these diverse technological pillars, we propose a systems-level roadmap for developing climate-resilient rice cultivars capable of maintaining yield stability across a volatile combinatorial stress landscape. This synthesis provides a framework for translating mechanistic hormonal insights into field-applicable cultivars to ensure global food security.

CRISPR↗

PubMed2026

Bridging Organ-on-a-Chip and Omics: A Multi-Dimensional Frontier in Biomedical Research.

Organ-on-a-Chip (OOC) technology offers a powerful platform for replicating human tissue-specific microenvironments, thereby narrowing the translational gap between conventional biomedical models and actual human physiology. Concurrently, omics technologies deliver comprehensive molecular-level insights into biological systems. This review highlights the transformative potential of integrating OOC platforms with high-throughput omics methodologies. We systematically examine the classification, structural configurations, and engineering principles underlying OOC systems, alongside the defining attributes of key omics domains-genomics, transcriptomics, proteomics, and metabolomics. The convergence of dynamic OOC models with advanced omics technologies enables high-resolution, multi-dimensional analyses across numerous biomedical applications, including drug metabolism, disease mechanisms, environmental toxicity assessments, and host-microbiome interactions. This interdisciplinary integration is driving a paradigm shift in precision and translational medicine. However, several challenges remain to be addressed, such as the development of whole-organ mimetics, adaptation of sample collection techniques, and real-time artificial intelligence-based integration of biosensor data with multi-omics datasets. Addressing these hurdles will be vital for unlocking the full potential of this technological synergy in biomedical science.

Multiomics↗

PubMed2025

Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.

Tumor-specific antigens, also known as neoantigens, have potential utility in anti-cancer immunotherapy, including immune checkpoint blockade (ICB), neoantigen-specific T cell receptor-engineered T (TCR-T), chimeric antigen receptor T (CAR-T), and therapeutic cancer vaccines (TCVs). After recognizing presented neoantigens, the immune system becomes activated and triggers the death of tumor cells. Neoantigens may be derived from multiple origins, including somatic mutations (single nucleotide variants, insertions/deletions, and gene fusions), circular RNAs, alternative splicing, RNA editing, and polymorphic microbiomes. An increasing amount of bioinformatics tools and algorithms are being developed to predict tumor neoantigens derived from different sources, which may require inputs from different multi-omics data. In addition, calculating the peptide-major histocompatibility complex (MHC) affinity can aid in selecting putative neoantigens, as high binding affinities facilitate antigen presentation. Based on these approaches and previous experiments, many resources have been developed to reveal the landscape of tumor neoantigens across multiple cancer types. Herein, we summarize these tools, algorithms, and resources to provide an overview of computational analysis for neoantigen discovery and prioritization, as well as the future development of potential clinical utilities in this field.

Humans↗

PubMed2026

Precision Engineering of Evolution-Resilient Rice against Bacterial Blight.

The persistent conflict between rice and Xanthomonas oryzae pv. oryzae (Xoo), the causal agent of bacterial blight, exemplifies a dynamic genetic arms race in agriculture. The cyclical deployment and erosion of major resistance (R) genes highlight the high adaptive potential of Xoo and the need for strategies that are durable rather than absolute. This review synthesizes a paradigm shift from reactive, single R-gene deployment toward proactive engineering of evolution-resilient resistance. We explore the molecular-genetic basis of Xoo adaptability, including TAL effector diversification, non-TAL virulence functions, genome variation, and immune suppression mechanisms. In response, we propose a framework for durable disease management with three connected components: precision disarmament through editing of susceptibility-gene effector-binding elements and executor/decoy designs; smart induction through targeted delivery and immune priming; and ecological fortification through protective microbiomes. We also discuss the limits, trade-offs, and field-validation requirements of these approaches. Integrating frontier technologies with evolutionary genetics, predictive genomics, and pathogen population dynamics can help develop rice varieties and deployment systems that are more difficult for Xoo populations to overcome.

CRISPR↗

PubMed2025

Biosynthetic potential of the culturable foliar fungi associated with field-grown lettuce.

Fungal endophytes and epiphytes associated with plant leaves can play important ecological roles through the production of specialized metabolites encoded by biosynthetic gene clusters (BGCs). However, their functional capacity, especially in crops like lettuce (Lactuca sativa L.), remains poorly understood. We sequenced the genomes of nine fungal isolates, representing Fusarium sp., Fulvia sp., Alternaria alternata, and Alternaria postmessia, from leaves of lettuce grown under field conditions in Arizona, USA. We used antibiotics and secondary metabolite analysis shell (antiSMASH) and the database for automated carbohydrate-active enzyme annotation (dbCAN3), to predict BGCs and carbohydrate-active enzymes (CAZymes) for each strain, and then compared them to conspecific strains from other environments and substrates. Foliar lettuce-associated fungi featured 39-95 BGCs per genome, with substantial overlap between isolates occurring in association with lettuce leaves vs. from other substrates. Species identity was a significant determinant of BGC count, while host type, isolation source, and lifestyle were not. Several BGCs, including those for alternariol and 1,3,6,8-Tetrahydroxynaphthalene (T4HN), showed 100% similarity to characterized minimum information about a biosynthetic gene cluster (MIBiG) clusters based on antiSMASH predictions. Although analysis by biosynthetic gene similarity clustering and prospecting engine (BiG-SCAPE) identified gene cluster families (GCFs) across the dataset, these reference-matching clusters were not always grouped, reflecting methodological differences in how the tools assess similarity. Comparative CAZyme analysis in a focal species (Fulvia sp.) revealed higher gene counts in a foliar lettuce-derived isolate than in tomato (Solanum lycopersicum)-associated strains, challenging assumptions about host chemical complexity. These results highlight the importance of phylogenetic context in shaping fungal functional potential and suggest that selection on microbial traits in edible leafy crops may be more subtle and species-specific than previously assumed. KEY POINTS: • Lettuce-associated fungi feature diverse biosynthetic potential • Phylogeny predicts fungal BGC content more strongly than ecological lifestyle • Findings support genome-informed microbiome strategies for leafy crops.

Lactuca↗

PubMed2026

Probiotic-derived extracellular vesicles as food-based nanocarriers: Mechanisms, functional applications, and future perspectives in food systems.

Probiotic-derived extracellular vesicles (PDEVs) are a promising type of postbiotic nanoparticle derived by fermentation of probiotics, and have gained growing interest as a potential application in food science and nutrition. These are lipid bilayer vesicles of nanoscale, which are naturally released by probiotic cells and contain a wide variety of bioactive molecules, such as proteins, nucleic acids, and metabolites. Moreover, PDEVs are highly stable, biocompatible, and can be easily engineered to have surfaces with high functionality, which makes them good candidates in functional engineering. In contrast to traditional live probiotics, PDEVs overcome the difficulties of preserving microbial viability during processing and storage, thus providing superior safety, stability, and predictable biological performance. This is a systematic review of the various functions of PDEVs in food systems. We conclude on the processes through which PDEVs control intestinal barrier integrity, alter gut microbiota composition, and alter host immune responses, and their potential to enhance gut health when added to functional foods. In addition to their health-promoting effects, PDEVs have shown significant potential as natural antimicrobial agents to preserve food and as effective nanocarriers of hydrophobic bioactive compounds, including fucoxanthin, to improve their stability, bioavailability, and targeted delivery. Moreover, PDEVs can be used as new regulators of microbial fermentation. However, it should be noted that a lot of the evidence that is available is still preliminary and the effectiveness of these applications in real food-processing and storage conditions has not been fully proven. Although they have potential, there are a number of challenges that still hinder the widespread use of PDEVs in the food industry. These involve the creation of scalable and cost-effective production processes, batch-to-batch consistency, vesicle stability in a variety of food matrices, and regulatory and safety considerations. Other emerging engineering approaches, such as surface functionalization and cargo loading, are also discussed in this review and could further increase the specificity, functionality, and application versatility of PDEVs in food systems. Moving forward, the incorporation of PDEVs into the next generation functional foods, novel food preservation methods, and customized nutrition plans should be prioritized in future studies. Further developments in these fields can make PDEVs useful platforms at the interface of food microbiology, nanotechnology, and human health.

Probiotics↗

PubMed2024

Stool Protein Mass Spectrometry Identifies Biomarkers for Early Detection of Diffuse-type Gastric Cancer.

There is a high unmet need for early detection approaches for diffuse gastric cancer (DGC). We examined whether the stool proteome of mouse models of gastric cancer (GC) and individuals with hereditary diffuse gastric cancer (HDGC) have utility as biomarkers for early detection. Proteomic mass spectrometry of the stool of a genetically engineered mouse model driven by oncogenic KrasG12D and loss of p53 and Cdh1 in gastric parietal cells [known as Triple Conditional (TCON) mice] identified differentially abundant proteins compared with littermate controls. Immunoblot assays validated a panel of proteins, including actinin alpha 4 (ACTN4), N-acylsphingosine amidohydrolase 2 (ASAH2), dipeptidyl peptidase 4 (DPP4), and valosin-containing protein (VCP), as enriched in TCON stool compared with littermate control stool. Immunofluorescence analysis of these proteins in TCON stomach sections revealed increased protein expression compared with littermate controls. Proteomic mass spectrometry of stool obtained from patients with HDGC with CDH1 mutations identified increased expression of ASAH2, DPP4, VCP, lactotransferrin (LTF), and tropomyosin-2 relative to stool from healthy sex- and age-matched donors. Chemical inhibition of ASAH2 using C6 urea ceramide was toxic to GC cell lines and GC patient-derived organoids. This toxicity was reversed by adding downstream products of the S1P synthesis pathway, which suggested a dependency on ASAH2 activity in GC. An exploratory analysis of the HDGC stool microbiome identified features that correlated with patient tumors. Herein, we provide evidence supporting the potential of analyzing stool biomarkers for the early detection of DGC. Prevention Relevance: This study highlights a novel panel of stool protein biomarkers that correlate with the presence of DGC and has potential use as early detection to improve clinical outcomes.

Feces↗

PubMed2026

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome↗

PubMed2026

Increasing gut short-chain fatty acids protects intestinal barrier function but does not spare muscle glycogen or impact aerobic performance.

Animal studies suggest gut microbiota-derived short-chain fatty acids (SCFA) provide an intestinal barrier-protecting, glycogen-sparing energy source that increases aerobic endurance performance, but confirmation in humans is needed. This study aimed to determine whether increasing colonic SCFA availability impacts intestinal barrier function, substrate metabolism, muscle glycogen and aerobic performance in healthy adults. Using a randomized, double-blind, crossover design 12 active men (age 18-30 years;40.0 ± 7.1 mL/kg/min) performed prescribed exercise and consumed a provided diet supplemented with acetylated and butyrylated high-amylose maize starch engineered to deliver SCFA to the colon (HAMS-A/B) or low-amylose maize starch (LAMS) for 7 days, separated by a 2 week washout. Indirect calorimetry, stable isotopes and blood, muscle and urine biomarkers were measured on intervention day 8 while participants completed 90 min of steady-state cycle ergometry (ExSS; 60 ± 5%) followed by a 5 km treadmill time trial. HAMS-A/B, relative to LAMS, increased faecal and serum SCFA. Multiple markers of intestinal barrier damage and permeability were lower, and the respiratory exchange ratio during ExSS was higher (0.02 [95% confidence interval (CI): 0.01, 0.03], Ptreatment < 0.001) following HAMS-A/B versus LAMS. However no between-treatment difference in glucose turnover, muscle glycogen depletion (14 µmol/kg/g dry wt. [95% CI: -116, 143], Pinteractio n = 0.613) or TT performance (5 s [95%CI: -44, 54], Ptreatment = 0.816) was observed. Increasing colonic and circulating SCFA modestly altered substrate oxidation and preserved intestinal barrier function during endurance exercise. However effects were not sufficient to spare muscle glycogen or increase aerobic endurance performance, leaving the practical relevance unclear and underscoring challenges inherent in translating promising preclinical findings to humans. KEY POINTS: Animal studies suggest gut microbiota-derived short-chain fatty acids (SCFA) provide an intestinal barrier-protecting, glycogen-sparing energy source that increases aerobic endurance performance, but confirmation in humans is lacking. A gut microbiota-targeted dietary supplementation strategy was used to deliver SCFA to the colon and successfully increased colonic and systemic SCFA concentrations in healthy, physically active adults before and during an endurance exercise bout and aerobic performance test. Increasing colonic and systemic SCFA availability preserved intestinal barrier function but did not impact glucose turnover, alter protein expression in muscle or spare muscle glycogen during endurance exercise. Increasing colonic and systemic SCFA availability did not impact aerobic endurance performance.

Humans↗