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PubMed2025

Versatile wastewater monitoring of pathogens and antimicrobial resistance enabled by metatranscriptomics and long-read metagenomics.

Widespread interest in the development of population-wide pathogen and antimicrobial resistance (AMR) monitoring has revealed wastewater's microbial footprint as a marker of public health. Near-source wastewater remains a difficult sample type for microbiome analyses but represents a closer link to human health than the downstream products of its treatment. Few studies integrate methods for non-targeted monitoring applications, and critically, current methods cannot connect AMR genes to species, nor resolve full genomes. We address these challenges by developing a pipeline that enables untargeted metagenomics, metatranscriptomics, and novel long-read metagenomics (LRG). We achieve untargeted pathogen detection, limited by highly abundant resident species, while retaining microbial information with near-source sampling. Furthermore, LRG identifies antibiotic resistance gene-containing microbes and enables assembly of culture-independent genomes with previously unreported AMR genes. We establish an integrated approach to broadly monitor pathogens in wastewater, while demonstrating the importance of LRG to illuminate microbial AMR at the species level.

Journal Article↗
PubMed2026

The Progress of Gout Prediction Models Based on Multi-source Data.

INTRODUCTION: Gout, a highly serious inflammatory disease that is caused by monosodium urate crystals, is becoming an increasingly significant health concern. Artificial Intelligence and multi-omics-based research have made significant gains for the early detection and prevention of gout based on diverse approaches. This review intends to summarize current advances in forecasting gout susceptibility and gout-related symptoms, evaluate the predictive efficacy of different features, and ascertain which clinical and omics characteristics are most effective in these prediction models. METHODS: We explored the PubMed database after 2010 using keywords such as "gout", "predictive model", "risk prediction", and "machine learning", and confined our search to Englishlanguage articles. The original peer-reviewed research articles that developed gout models were selected. Research that was not original or lacked internal validation was excluded. RESULTS: Clinical features, genomics, microbiomics, radiomics, and metabolomics have been utilized to construct models related to gout and have demonstrated excellent predictive performance. Multisource data prediction models usually exhibit better effectiveness. DISCUSSION: Gout-oriented models performed excellently in predictive performance but present limitations in certain clinical and omics domains. However, if they are to affect actual patient care, they must overcome some external confirmation roadblocks and the fiscal and practical implications they will face ahead of time. CONCLUSION: This review indicates that clinical and multi-omics models of gout are significant instruments for clinical decision-making. The models constructed in these studies may be crucial for the treatment of gout and its practical benefits.

Gout↗
PubMed2026

Research progress and application prospects of multi-omics integration strategies in precision risk stratification of type 1 diabetes mellitus.

Type 1 diabetes (T1D) is a chronic metabolic disease mediated by autoimmunity. Its pathogenesis involves complex interactions between genetic susceptibility and environmental factors. Conventional T1D risk stratification primarily relies on genetic markers, islet autoantibodies, and glycemic indicators. Although these biomarkers remain indispensable in current clinical practice, they are often insufficient when used alone to accurately identify ultra-early high-risk individuals, predict disease progression rates, or support individualized preventive strategies. Consequently, more comprehensive molecular approaches are needed to improve precision risk stratification. In recent years, the rapid development of multi-omics technologies has provided new strategies for precise risk stratification of T1D. This narrative review critically evaluates how multi-omics integration strategies can improve precision risk stratification throughout the T1D disease continuum by integrating complementary molecular information from genomics, transcriptomics, proteomics, metabolomics, epigenomics, and the microbiome. Particular emphasis is placed on stage-specific biomarker discovery, multi-omics data integration frameworks, artificial intelligence-assisted prediction models, biomarker validation, and the opportunities and challenges associated with clinical translation. Current evidence suggests that integrated multi-omics approaches have the potential to improve risk prediction accuracy, distinguish heterogeneous disease trajectories, identify individuals at imminent risk of progression, and provide biologically informed targets for precision intervention. However, important challenges remain, including data harmonization, external validation, model interpretability, cost-effectiveness, and integration into routine clinical screening programs. Future research should prioritize prospective multicenter cohorts, standardized analytical pipelines, externally validated prediction models, and clinically interpretable multi-omics frameworks to facilitate the translation of precision risk stratification into routine T1D prevention and management.

Humans↗
PubMed2026

Age and sex: dual drivers remodeling the anti-tumor immune microenvironment and shaping personalized immuno-oncology.

Despite breakthrough advancements in cancer immunotherapy, significant inter-individual heterogeneity in clinical outcomes persists, bringing the regulatory roles of intrinsic host biological variables into sharp focus. Accumulating fundamental and clinical evidence indicates that age and sex play crucial roles in determining tumor susceptibility, disease progression, and the remodeling of the anti-tumor immune microenvironment. This review systematically delineates the profound impacts of the dual dimensions of age and sex on anti-tumor immune responses and immune evasion mechanisms. In the dimension of age, this article outlines the progressive functional decline of T/B lymphocytes and innate immune subsets driven by immunosenescence, and emphatically reveals how inflammaging and its associated senescence-associated secretory phenotype (SASP) orchestrate the formation of an immunosuppressive tumor microenvironment. In the dimension of sex, we deeply explore four core mechanisms comprising sex chromosome genomics (e.g., escape from X-chromosome inactivation and loss of Y chromosome), sex hormone networks, microenvironmental metabolic reprogramming, and the host gut microbiome, elucidating the molecular basis driving the disparities in innate and adaptive immunity between males and females. In summary, thoroughly deciphering the complex immune regulatory networks driven by age and sex not only helps elucidate the disparities in efficacy and toxicity observed in patients undergoing immune checkpoint inhibitors, but also provides crucial theoretical foundations and translational insights for the future development of "age-tailored" and "sex-specific" strategies in personalized immuno-oncology.

Humans↗
PubMed2026

Metagenomic profiling of blood-associated microbial DNA signatures in leukemia-associated febrile neutropenia.

Febrile neutropenia (FN) is a life-threatening complication of chemotherapy, but the low microbial biomass of blood makes shotgun metagenomic profiles highly sensitive to technical background. We reanalyzed 47 publicly available patient sequencing runs representing 43 unique patient-timepoint samples from 19 SRA-labeled patients, together with 23 no-template-control (NTC) runs spanning 21 sequencing batches. To distinguish reference-catalogue content from progressively stronger evidence of patient-associated signal, we applied batch-matched NTC correction together with nested abundance thresholds and a feature-specific global NTC envelope. CheckM2 evaluated 1,013 bins; 13 met completeness &#x2265;50% and contamination <10%, and dereplication yielded 11 draft MAG representatives. Ten representatives showed positive patient-to-control abundance excess, but only four showed recurrent support above both threefold matched-control abundance and the global NTC envelope. Functional annotations were therefore interpreted as reference-genome homologs rather than evidence of expression, phenotype, viability or bloodstream origin. Matched-control correction retained 19 read-level ARG types, but only seven subjects contributed complete longitudinal ARG-profile contrasts, limiting reliable temporal inference. The resulting run-resolved, nested evidence framework identified a subset of microbial DNA and ARG signals that remained detectable under increasingly stringent control criteria while distinguishing them from catalogue-level or background-sensitive signals. These findings support cautious reporting of patient-enriched microbial DNA and ARG signals rather than inference of a resident blood microbiome or clinical resistance phenotype.

antimicrobial resistance genes↗
PubMed2026

Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with limited therapeutic options and marked molecular heterogeneity. Despite available antifibrotic therapies, disease progression remains poorly predictable, highlighting the need for improved mechanistic understanding and therapeutic targeting. This review summarizes recent advances in multi-omics research to elucidate the molecular mechanisms underlying IPF and to identify potential biomarkers and pharmacological targets. Multi-omics studies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and single-cell sequencing, have revealed key pathogenic mechanisms in IPF. Genetic susceptibility factors such as MUC5B promoter variants and telomere-related genes contribute to disease risk. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNAs, plays a central role in fibrotic remodeling. Transcriptomic and proteomic analyses have identified dysregulated signaling pathways, including TGF-&#x3b2;, mTOR, cellular senescence, and extracellular matrix remodeling. Metabolomic alterations indicate disrupted lipid and amino acid metabolism. Importantly, integration of multi-omics datasets enables the identification of molecular endotypes, candidate biomarkers, and potential therapeutic targets. However, challenges including data integration, tissue heterogeneity, limited cohort size, and the need for functional validation remain important barriers to clinical translation. Continued development of multi-omics approaches may facilitate more accurate disease classification and support the development of personalized therapeutic strategies for IPF.

biomarkers↗
PubMed2026

Virome metatranscriptomic profiling of birch pollen reveals a diverse viral community.

INTRODUCTION: Viruses are increasingly recognized as integral components of plant-associated biological systems. However, their occurrence and diversity in the reproductive tissues of woody plants remain poorly understood. Birch (Betula spp.) produces large quantities of wind-dispersed pollen that can travel over long distances and may harbour viruses or virus-derived nucleic acids originating from the host plant and/or its associated microbiota. METHODS: We investigated the virome of birch pollen collected from trees growing in central and suburban Berlin, Germany. Metatranscriptomic analyses were performed on pooled pollen samples collected in 2020. These analyses were complemented by RT-PCR screening of individually processed pollen samples collected in 2025 from resampled trees. Primer walking was additionally used to recover an extended genome sequence of a pollen-associated birch toti-like virus. RESULTS: Multiple virus-associated contigs were identified in both pooled metatranscriptomic datasets. These included sequences corresponding to the cherry leaf roll virus (CLRV), the birch idaeovirus (BIV) and the birch toti-like virus (BTLV), as well as additional virus-like contigs provisionally assigned to lineages related to the Orthototiviridae, Botourmiaviridae, Endornaviridae, and Chrysoviridae families. RT-PCR analysis of individually processed pollen samples confirmed the continued detection of CLRV, BIV, and BTLV within the Berlin sampling framework. A near-complete genome sequence was recovered from a pollen-derived BTLV isolate from Berlin, showing high amino acid sequence identity to a recently described leaf-derived BTLV isolate from the United States. DISCUSSION: These findings demonstrate that birch pollen harbours a diverse assemblage of plant- and/or microbiome-associated viruses and expand the known tissue distribution and geographic range of BTLV. More broadly, they establish pollen as an underexplored ecological niche for virome research and provide a foundation for future studies on the ecology, transmission dynamics, and epidemiological significance of pollen-associated and pollen-transmitted viruses.

Betula↗
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↗
PubMed2025

A Graph Contrastive Learning Method for Enhancing Genome Recovery in Complex Microbial Communities.

Accurate genome binning is essential for resolving microbial community structure and functional potential from metagenomic data. However, existing approaches-primarily reliant on tetranucleotide frequency (TNF) and abundance profiles-often perform sub-optimally in the face of complex community compositions, low-abundance taxa, and long-read sequencing datasets. To address these limitations, we present MBGCCA, a novel metagenomic binning framework that synergistically integrates graph neural networks (GNNs), contrastive learning, and information-theoretic regularization to enhance binning accuracy, robustness, and biological coherence. MBGCCA operates in two stages: (1) multimodal information integration, where TNF and abundance profiles are fused via a deep neural network trained using a multi-view contrastive loss, and (2) self-supervised graph representation learning, which leverages assembly graph topology to refine contig embeddings. The contrastive learning objective follows the InfoMax principle by maximizing mutual information across augmented views and modalities, encouraging the model to extract globally consistent and high-information representations. By aligning perturbed graph views while preserving topological structure, MBGCCA effectively captures both global genomic characteristics and local contig relationships. Comprehensive evaluations using both synthetic and real-world datasets-including wastewater and soil microbiomes-demonstrate that MBGCCA consistently outperforms state-of-the-art binning methods, particularly in challenging scenarios marked by sparse data and high community complexity. These results highlight the value of entropy-aware, topology-preserving learning for advancing metagenomic genome reconstruction.

canonical correlation analysis↗
PubMed2026

Beyond Earth: Recent Advancements in Microgravity Biomedical and Genetic Research in Saudi Arabia.

Microgravity research has emerged as a rapidly evolving field at the intersection of space medicine, genomics, biotechnology, and precision medicine. Exposure to the space environment induces complex physiological and molecular adaptations that affect multiple biological systems, including immune regulation, metabolism, musculoskeletal function, and gene expression. Recent advances in genomics, multi-omics technologies, artificial intelligence, and bioengineering have substantially improved our understanding of biological adaptation to spaceflight and expanded opportunities for translational biomedical research. This review summarizes recent advances in genetic and biomedical research under microgravity conditions, with particular emphasis on molecular mechanisms, omics technologies, genome editing, microbiome research, regenerative medicine, and personalized healthcare approaches. Major experimental platforms, landmark spaceflight studies, and translational applications in infectious diseases, cancer biology, aging, tissue engineering, and pharmaceutical development are discussed. The review also highlights Saudi Arabia's emerging contributions to genomic medicine and space biosciences through initiatives such as the Saudi Human Genome Program, the Saudi Pangenome Project, the Saudi Space Agency, and the BioGravity Initiative. Recent Saudi participation in human spaceflight and microgravity-associated biomedical research is discussed within the context of Vision 2030 and national investments in biotechnology and precision medicine. Collectively, advances in microgravity research are expected to contribute to the advancement of precision medicine and facilitate the development of innovative diagnostic and therapeutic strategies with significant implications for both human space exploration and terrestrial healthcare.

Humans↗
PubMed2025

Cardiovascular Complications Are Increased in Inflammatory Bowel Disease: A Path Toward Achievement of a Personalized Risk Estimation.

Background/Objectives: The global burden of inflammatory bowel diseases (IBDs) continues to rise, with up to 50% of patients experiencing extraintestinal manifestations. Cardiovascular diseases (CVDs) are of particular concern, ranking as the second leading cause of mortality in this population. Despite a comparatively lower prevalence of traditional cardiovascular (CV) risk factors, the persistent inflammatory milieu and immune dysregulation inherent to IBD may contribute to heightened CVD risk. In this study, following a review of the current literature, an ongoing prospective trial designed to clarify CV risk profiles in IBD patients is detailed. Methods: A cohort of patients with IBD is being enrolled for comprehensive baseline evaluation of CV risk factors, lifestyle metrics, and disease characteristics. The incidence of major adverse cardiovascular events (MACEs) will be tracked and contrasted with a gender- and age-matched non-IBD cohort over a 2-year follow-up period. In cases of MACE occurrence, a multi-omics analysis-including genomic, proteomic, transcriptomic, and microbiome profiling-will be performed, along with a parallel evaluation in matched IBD controls without MACE. An artificial intelligence (AI) framework will support the analysis of this complex dataset. Results: To date, over 150 patients with IBD have been enrolled, and detailed phenotypic data and biological samples have been collected. Conclusions: We aim to introduce an IBD-specific correction factor for existing CV risk scores upon study completion. This is particularly relevant for individuals under 40 years of age, who are often inadequately assessed by current risk stratification models.

Crohn&#x2019;s disease↗
PubMed2019

Dietary iron variably modulates assembly of the intestinal microbiota in colitis-resistant and colitis-susceptible mice.

Iron deficiency, a common comorbidity of gastrointestinal inflammatory disorders such as inflammatory bowel diseases (IBD), is often treated with oral iron supplementation. However, the safety of oral iron supplementation remains controversial because of its association with exacerbated disease activity in a subset of IBD patients. Because iron modulates bacterial growth and function, one possible mechanism by which iron may exacerbate inflammation in susceptible hosts is by modulating the intestinal microbiota. We, therefore, investigated the impact of dietary iron on the intestinal microbiota, utilizing the conventionalization of germ-free mice as a model of a microbial community in compositional flux to recapitulate the instability of the IBD-associated intestinal microbiota. Our findings demonstrate that altering intestinal iron availability during community assembly modulated the microbiota in non-inflamed wild type (WT) and colitis-susceptible interleukin-10-deficient (Il10-/-) mice. Depletion of luminal iron availability promoted luminal compositional changes associated with dysbiotic states irrespective of host genotype, including an expansion of Enterobacteriaceae such as Escherichia coli. Mechanistic in vitro growth competitions confirmed that high-affinity iron acquisition systems in E. coli enhance its abundance over other bacteria in iron-restricted conditions, thereby enabling pathobiont iron scavenging during dietary iron restriction. In contrast, distinct luminal community assembly was observed with dietary iron supplementation in WT versus Il10-/- mice, suggesting that the effects of increased iron on the microbiota differ with host inflammation status. Taken together, shifts in dietary iron intake during community assembly modulate the ecological structure of the intestinal microbiota and is dependent on host genotype and inflammation status.

Animals↗
PubMed2025

Bacterial metabolite patterns of infants receiving multi-strain probiotics and risk of late-onset sepsis.

The effect of multi-strain probiotics containing Bifidobacterium longum (B. longum) on late-onset sepsis (LOS) risk in very-low-birth-weight infants (VLBWIs; birth weight < 1,500 g) remains uncertain. In a single-center study, we analyzed intestinal metagenome and metabolome data in VLBWIs during the period of highest vulnerability of LOS. Using a unit's policy change to routinely administer B. longum subspecies infantis plus Lactobacillus acidophilus as natural experiment, we compared 97 infants (including 38 LOS cases) after change with 78 infants (including 32 LOS cases) before. Probiotic supplementation was associated with more beneficial bacteria and reduced abundance of nosocomial pathobionts, such as Klebsiella spp. Infants in the probiotic group had significantly lower concentrations of B. longum fermentation products prior to sepsis diagnosis than matched non-LOS cases (acetate: padj = 0.0049; lactate: padj = 0.048). Modulation of the gut metabolic milieu is an interesting target for LOS prevention.

Humans↗
PubMed2026

Do Multi-Omics Approaches Improve the Diagnosis of Microbial Overgrowth Syndromes?

PURPOSE OF REVIEW: This review investigates how advances in breath testing (BT), small bowel (SB) culture, metagenomics, metatranscriptomics, transcriptomics and proteomics are reshaping the definition and diagnosis of small intestinal bacterial overgrowth (SIBO). It also discusses whether SIBO should be redefined as part of a larger group of microbial overgrowth syndromes. RECENT FINDINGS: Recent studies identify distinct hydrogen-, methane-, and hydrogen sulfide-associated overgrowth phenotypes, termed SIBO, intestinal methanogen overgrowth (IMO), and intestinal sulfide overproduction (ISO). SB sampling shows that these conditions involve different microbial patterns and functional activity, symptoms, and host responses. Quantitative shotgun metagenomics provides greater taxonomic and functional resolution than culture, while metatranscriptomics reveals active microbial pathways. On top of that, host transcriptomics and proteomics contribute to the better understanding of the predominant microbial effects in host cellular mechanisms in each of the distinct small bowel overgrowth types. SIBO has been increasingly identified as a disorder of microbial ecology and function rather than bacterial quantity alone. Integrating BT with SB sampling and multi-omics approaches may improve classification, clarify symptom mechanisms, and support a more individualized treatment, although standardized methods and further clinical validation remain necessary.

Humans↗
PubMed2026

Multi-omics insights into the physiological mechanisms of bile acid accumulation in the gallbladder in brumation-like snakes.

Hibernation/brumation represents an important physiological adaptation for animals to cope with seasonal environmental changes. Field observations suggested increased gallbladder weight in the Five-pacer viper (Deinagkistrodon acutus) during brumation, and our quantitative measurements confirmed this increase together with bile acid accumulation. By integrating a multi-omic approach, this study elucidates the regulatory mechanisms of bile acid accumulation in the gallbladder during brumation. Results showed that taurocholic acid (TCA) and taurodeoxycholic acid (TDCA) were the major components in the gallbladder of the brumation-like group, with significantly elevated concentrations of bile acids, whereas bile acid concentrations in serum and intestinal contents were markedly reduced, indicating suppression of the enterohepatic circulation and consequent accumulation of bile acids in the gallbladder. Hepatic transcriptomic analysis revealed significant downregulation of bile acid synthesis and regulatory genes in brumation-like snakes. In contrast, the alternative synthesis pathway gene sterol 27-hydroxylase (CYP27A1) and some transporter genes were slightly upregulated. Further, some modification genes and regulatory genes showed no significant differences between active and brumation-like states. Gut microbiota analysis demonstrated Akkermansia muciniphila, Bacteroides fragilis, and Citrobacter freundii were more enriched in the active group, which were common microbes related to bile acid metabolism, and the correlation analysis confirmed this relationship. Taken together, these findings indicate that the "physiological bile acid accumulation" observed in snakes during brumation-like state is jointly driven by suppressed hepatic synthesis, reduced enterohepatic circulation, and remodeled microbial community structure. The study provides novel comparative physiological insights into extreme metabolic homeostasis in animals.

Animals↗
PubMed2025

Health-associated key gut microbiota drives the variation in community metabolic interactions in non-human primates.

Gut microbiota often undergo metabolic cross-feeding and resource competition. However, our understanding of global variations in these interactions and their implications for host health remain elusive. By analyzing a microbial genome catalog from 841 fecal metagenomes across 53 primate species worldwide, we identified key microbiota assigned to two taxa, i.e., Bacillota_A and Pseudomonadota, which well predicted the trade-off of community-level interaction types between metabolic competition and cooperation. Specifically, Bacillota_A species were inherently competitive and amino acid auxotrophic and typically found in anaerobic habitats. In contrast, members of Pseudomonadota were inherently cooperative, siderophore producers, and more abundant in aerobic conditions. Random forest models successfully distinguished unhealthy gut samples from healthy samples through the key competitive and cooperative microbiota, suggesting potential links between community metabolic interactions and host health. Together, this study enhances our mechanistic understanding of microbial interaction dynamism within complex gut ecosystems, offering new targets for understanding host health.

Animals↗
PubMed2024

Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption.

Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in&#xa0;vitro and in&#xa0;vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M.&#xa0;rupellensis or E.&#xa0;coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M.&#xa0;rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.

Inositol↗