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PubMed2025

Bone Adhered Sediments as a Source of Target and Environmental DNA and Proteins.

In recent years, sediments from cave environments have provided invaluable insights into ancient hominids, as well as past fauna and flora. Unfortunately, however, sediments are not always collected during excavation. In this study, we analyzed an overlooked but abundant resource in archaeological collections - sediments adhered to bone. We performed metagenomics and metaproteomics analysis on sediment from several human skeletal elements, originating from Neolithic to Medieval sites in England. We were able to reconstruct a partial human genome, the genetic profile of which matches that recovered from the original skeletal element. Additionally, aDNA sequences matching the genomes of endogenous gut microbiome bacteria were identified. We also found the presence of genetic sequences corresponding to animals and plants. In particular, we managed to retrieve the partial genome and proteome of a Black Rat (Rattus rattus), sharing close genetic affinities to other medieval Rattus rattus. Our results demonstrate that material that is usually ignored or discarded, can be used to reveal information about the individual and the environmental conditions at the time of their death.

Animals↗
PubMed2025

Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease.

INTRODUCTION: Gastrointestinal disorders (GIDs) affect nearly 40% of the global population, with gut microbiome-metabolome interactions playing a crucial role in gastric cancer (GC), colorectal cancer (CRC), and inflammatory bowel disease (IBD). This study aims to investigate how microbial and metabolic alterations contribute to disease development and assess whether biomarkers identified in one disease could potentially be used to predict another, highlighting cross-disease applicability. METHODS: Microbiome and metabolome datasets from Erawijantari et al. (GC: n = 42, Healthy: n = 54), Franzosa et al. (IBD: n = 164, Healthy: n = 56), and Yachida et al. (CRC: n = 150, Healthy: n = 127) were subjected to three machine learning algorithms, eXtreme gradient boosting (XGBoost), Random Forest, and Least Absolute Shrinkage and Selection Operator (LASSO). Feature selection identified microbial and metabolite biomarkers unique to each disease and shared across conditions. A microbial community (MICOM) model simulated gut microbial growth and metabolite fluxes, revealing metabolic differences between healthy and diseased states. Finally, network analysis uncovered metabolite clusters associated with disease traits. RESULTS: Combined machine learning models demonstrated strong predictive performance, with Random Forest achieving the highest Area Under the Curve(AUC) scores for GC(0.94[0.83-1.00]), CRC (0.75[0.62-0.86]), and IBD (0.93[0.86-0.98]). These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. CONCLUSION: These findings emphasize the potential of microbial and metabolic profiling in cross-disease characterization particularly for GIDs, advancing biomarker discovery for improved diagnostics and targeted therapies.

Humans↗
PubMed2026

Investigating mechanisms of divergent feed efficiency in dairy cows.

Objectives were to investigate the associations between residual DMI (RFI), calculated as the difference between observed minus predicted DMI, with rumen microbiome, digestion, behavior, and metabolism that might explain the differences in RFI in lactating cows. One hundred 50 genotyped Holstein cows in 3 cohorts were used in this cohort study in which exposure was RFI. Rumen microbiota from 114 cows were sequenced, and a subset of 30 cows was used for hepatic mitochondrial respiration analysis. Cows were ranked by RFI and grouped into quartiles (Q1, most efficient, to Q4, least efficient) according to phenotypic (pQ) or genomic (gQ) quartiles of RFI for data presentation. Statistical models fitted the linear and quadratic RFI as continuous explanatory variables. Increasing efficiency, i.e., from larger to smaller RFI values, whether phenotypic or genomic, were associated with reduced DMI, a 3.0 kg/d difference between Q4 and Q1 according to phenotypic RFI (pRFI) and 1.9 kg/d according to genomic RFI (gRFI) without compromising ECM or body tissue reserves. These differences between Q4 and Q1 of pRFI and gRFI resulted in increased feed conversion ratio by an additional 200 and 100 g of ECM/kg DMI, respectively. Both pRFI and gRFI were associated with FA profiles in milk fat, with decreasing proportions of de novo and mixed FA and increasing proportions of pre-formed FA, particularly monounsaturated FA, as efficiency improved. Additionally, pRFI and gRFI were moderately correlated (r = 0.48) and ranking of cows was consistent across the 2 grouping methods (ρ = 0.44). Reducing RFI was associated with less total rumination time, but greater rumination time per kg of DMI by 2.0 and 1.7 min/kg between the extreme quartiles of pRFI and gRFI, respectively. Phenotypically and genomically more efficient cows were associated with less microbial α diversity based on inverse Simpson index. A total of 57 amplicon sequence variant groups were differentially abundant between Q1 and Q4 classified based on pRFI and gRFI, with Prevotella and Succinivibrionaceae shared between phenotypic and genomic RFI classifications. Increasing phenotypic and genomic efficiency was associated with an increased concentration of ruminal NH3-N. Genomically more efficient cows tended to have reduced ruminal pH (gQ1 to gQ4; 6.42 vs. 6.47 vs. 6.43 vs. 6.53) despite eating less. Decreasing pRFI was associated with reduced microbial N yield whereas, it tended to increase microbial N yield relative to the amount of N intake. Collectively, phenotypic and genomic RFI have a moderate degree of agreement matching the estimated heritability of the trait, and mechanisms underlying improved feed efficiency were linked with differences in ruminal microbiota and fermentation, and with increased rumination per kg of DM rather than total-tract digestibility or hepatic mitochondrial respiration.

dairy cow↗
PubMed2025

PLSKO: a robust knockoff generator to control false discovery rate in omics variable selection.

MOTIVATION: Integrating the knockoff framework with any variable-selection method delivers stringent false discovery rate (FDR) control without recourse to p-values, offering a powerful alternative for differential expression analysis of high-throughput omics datasets. However, existing knockoff generators rely on restrictive modelling assumptions or coarse approximations that often inflate the FDR when applied to real-world data. RESULTS: We introduce Partial Least Squares Knockoff (PLSKO), an efficient, assumption-free generator that remains robust across diverse omics platforms. Our extensive simulations show that PLSKO is the only method to maintain FDR control with sufficient power in complex non-linear settings. Our semi-simulation studies drawn from RNA-seq, proteomics, metabolomics, and microbiome experiments confirm PLSKO generates valid knockoff variables. In pre-eclampsia multi-omics case studies, we combine PLSKO with Aggregation Knockoff to address the randomness of knockoffs and improve power, and demonstrate the method's ability to recover biologically meaningful features. AVAILABILITY AND IMPLEMENTATION: Our proposed algorithm is available on Github (https://github.com/guannan-yang/PLSKO) and Zenodo (https://doi.org/10.5281/zenodo.16879594).

Algorithms↗
PubMed2026

Evaluation of metabolic, reproductive, and gut microbiota alterations in a comparative study of different preclinical models of polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a multifaceted, complex metabolic and endocrine disease where gut flora is considered an important factor in causing PCOS. This study aimed to identify a suitable PCOS model that contributes to gut microbial dysbiosis and metabolic and hormonal disturbances. Prepubertal SD rats were administered with normal control (NC), dihydrotestosterone (DHT), DHT with fructose (F), DHT+ high fat diet (HFD) for 91 days, dehydroepiandrosterone (DHEA), DHEA with fructose, DHEA with HFD for 30 days, sodium valproate (SV), sodium valproate with fructose, and sodium valproate with HFD for 21 days. The estrous cycles were assessed over this timeframe. At the end of the experiment, superoxide dismutase and uterine and ovarian morphology were evaluated, along with hormone levels, lipid profiles, and 16S rRNA genomic sequencing. All models exhibited PCOS characteristics, including hormonal imbalances, insulin resistance (p ≤ .001), multiple follicular cysts on ultrasonography, and histological alterations. Gut microbial dysbiosis was observed across all PCOS-induced groups; however, the DHT alone group showed more pronounced alterations in microbial composition than the other experimental groups. Specifically, the DHT alone group exhibited reduced abundance of Firmicutes and increased abundance of Proteobacteria. Among the evaluated models, the DHT-only model showed more pronounced metabolic, hormonal, reproductive, and gut microbial alterations and may serve as a suitable model for PCOS research.

Animals↗
PubMed2025

Oral Lachnoanaerobaculum Levels and Survival in Patients With Head and Neck Cancer.

IMPORTANCE: The oral microbiome plays a critical role in cancer treatment responses, yet its influence on outcomes in patients with head and neck squamous cell carcinoma (HNSCC) undergoing (chemo)radiotherapy remains poorly understood. Identifying specific microbiome signatures associated with treatment effectiveness could provide novel prognostic biomarkers and therapeutic targets. OBJECTIVE: To investigate the association between salivary Lachnoanaerobaculum spp abundance and treatment outcomes in patients with HNSCC undergoing (chemo)radiotherapy and to explore potential mechanisms. DESIGN, SETTING, AND PARTICIPANTS: This prognostic study analyzed saliva samples from patients with HNSCC who were enrolled in 2 independent prospective biomarker studies (SALIVA and ZissTrans) and underwent definitive (chemo)radiotherapy. Oral microbiome composition was assessed using 16S rRNA gene sequencing. Tumor-infiltrating lymphocytes (TILs) were evaluated via immunohistochemistry in patients with available data. Findings were further assessed using data from The Cancer Microbiome Atlas and The Cancer Genome Atlas. Sample collection occurred from 2008 to 2011 (SALIVA) and from 2017 to 2022 (ZissTrans), and the data for this study were analyzed from July to December 2024. EXPOSURE: Definitive (chemo)radiotherapy. MAIN OUTCOMES AND MEASURES: The primary outcome was locoregional recurrence-free survival (LRFS) and a secondary outcome was overall survival (OS). Additional secondary analyses evaluated the association between Lachnoanaerobaculum spp levels and TIL levels, and the incidence of severe radiation-induced oral mucositis. RESULTS: The analysis included 92 patients with HNSCC (mean [SD] age, 61.1 [7.9] years; 15 female [16.3%] 77 male [83.7%] individuals) and found that higher Lachnoanaerobaculum spp abundance was associated with substantially improved LRFS (median, 69 vs 11 months; hazard ratio [HR], 0.50; 95% CI, 0.29-0.86) and OS (median, 75 vs 27 months; HR, 0.54; 95% CI, 0.30-0.98). This finding was confirmed by multivariable Cox regression (LRFS: HR, 0.50; 95% CI, 0.25-1.00; OS: HR, 0.37; 95% CI, 0.16-0.85). TILs were evaluated in 76 patients (82.2%) and showed that increased Lachnoanaerobaculum spp levels were associated with higher CD4-positive and CD8-positive TIL counts. Lachnoanaerobaculum spp abundance showed no meaningful association with severe radiation-induced oral mucositis. Data from The Cancer Microbiome Atlas (n = 157) indicated that higher intratumoral Lachnoanaerobaculum spp levels were associated with improved OS (HR, 0.62; 95% CI, 0.39-0.98). Transcriptomic analyses in The Cancer Genome Atlas cohort further supported an immune-stimulated tumor microenvironment in Lachnoanaerobaculum-high tumors. CONCLUSIONS AND RELEVANCE: This prognostic study found that higher salivary Lachnoanaerobaculum spp abundance was associated with improved tumor control and survival in patients with HNSCC undergoing (chemo)radiotherapy. These findings support further investigation into microbiome-targeted interventions to improve HNSCC treatment effectiveness.

Humans↗
PubMed2026

Whole metagenome sequencing: not deep enough for complete microbial function recovery.

BACKGROUND: Whole metagenome shotgun sequencing (WMS) is widely used to profile microbial function. However, technical variability in sequencing and analysis often obscures true biological patterns. Large-scale studies are particularly susceptible to batch effects, such as differences in sequencing depth and platform and annotation strategies, as well as sample-to-flow-cell assignments. However, the relative effects of these factors on functional inference in such studies have yet to be systematically evaluated. We analyzed oral-rinse WMS data from 671 Nigerian youths aged 9-18, sequenced on two Illumina platforms. Microbial molecular functionality encoded in these data was annotated using the mi-faser/Fusion pipeline, to capture the broad functional repertoire, and HUMAnN 3/EC numbers pipeline to characterize curated enzymatic activities. We then quantified how technical factors and batch effects shaped the recovery of microbial functionality. RESULTS: Three findings of our work were most salient. First, we observed that the choice of annotation strategy traded off between breadth and specificity of functional coverage. Second, we found that low-prevalence functions were disproportionately lost at shallow sequencing depths, indicating that in, e.g., case-control studies with few representatives of the minor class, sequencing depth could critically impact study resolution. Finally, using our newly developed model relating sequencing depth to functional recovery, we demonstrated that increasing sequencing depth does not directly or proportionally improve functional recall. That is, at as little as 10% of this study's sequencing depth, 30% of the estimated complete microbiome functional repertoire was detectable. However, even at the full depth used in this study, we were only able to recover an estimated 60% of that complete functional repertoire. We further showed that despite biomes differences in functional diversity and host contamination levels (e.g., soil, fecal), incomplete functional recovery at commonly used sequencing depths was consistently observed. CONCLUSIONS: Together, these findings and our depth-to-function mapping framework provide practical guidelines for the design and interpretation of WMS studies. Coordinating sequencing depth planning with annotation strategy, experimental design, and rigorous batch control is thus essential for robust detection of microbial functions and for ensuring reproducible microbiome insights. Video Abstract.

Humans↗
PubMed2025

A comprehensive reference catalog of human skin DNA virome reveals novel viral diversity and microenvironmental influences.

UNLABELLED: Human skin serves as a dynamic habitat for a diverse microbiome, including a complex array of viruses whose diversity and roles are not fully understood. A total of 2,760 skin metagenomes from 6 published skin studies were collected. A skin virome catalog was constructed using standard methods in the viromics field. Viral characteristics were identified through cross-cohort meta-analysis and used to characterize viral features across different skin environments. We identified 20,927 viral sequences, which clustered into 2,873 viral operational taxonomic units (vOTUs), uncovering a substantial breadth of viral diversity on human skin. The results also highlight significant differences in viral communities that are associated with varying skin microenvironments. The oily skin is enriched in Papillomaviridae, the dry skin area is enriched in Autographiviridae and Inoviridae, and the moist skin is enriched in Herelleviridae. We also investigated the relationship between bacteriophages and bacteria on the skin surface. We found that skin bacteria such as Pseudomonas, Klebsiella, and Staphylococcus are predicted to be infected by phages from the class Caudoviricetes. This comprehensive skin DNA viral catalog significantly advances our understanding of the virome's role within the skin ecosystem. IMPORTANCE: This study presents a comprehensive reference catalog of the human skin DNA virome, constructed from 2,760 metagenomic datasets collected globally. It identified 20,927 viral sequences, with 90.85% representing previously unknown viruses, greatly expanding our understanding of skin viral diversity. The findings reveal significant differences in viral communities between distinct skin microenvironments (oily, dry, and moist) and highlight close interactions between bacteriophages and their bacterial hosts, suggesting a potential role for the virome in maintaining microbial balance and skin health. This extensive skin viral catalog constitutes a crucial resource for future epidemiological and therapeutic research, potentially facilitating the development of novel phage therapies and diagnostic markers for skin disorders.

Humans↗
PubMed2026

Transcriptomic changes in the gut mucosa of fasting northern elephant seal pups reveal immune modulation during early microbiome establishment.

Fasting is an integral component of the life-history of many species. Following abrupt weaning, northern elephant seal pups (Mirounga angustirostris) undergo an extended post-weaning fast of approximately 60 days. During this period, enteric bacterial diversity increases, suggesting that host immune regulation may facilitate the establishment of microbial communities. However, the molecular processes occurring within the intestinal mucosa during this transition remain poorly understood. To investigate these mechanisms, we characterized transcriptional changes in the enteric mucosa of male and female northern elephant seal pups sampled at weaning and after one month of fasting. Total RNA isolated from rectal swabs was sequenced and aligned to the Mirounga angustirostris reference genome. Differential gene expression and gene set enrichment analyses were used to identify genes and pathways associated with fasting and sex-specific responses. Fasting was accompanied primarily by transcriptional downregulation, including genes involved in antimicrobial defense, inflammation, protein turnover, and epithelial remodeling. In contrast, several genes associated with B-cell activity and immune recognition were upregulated. Gene Set Enrichment Analysis revealed coordinated activation of immune-regulatory pathways indicating dynamic modulation of intestinal immunity rather than generalized immune suppression. Pronounced sex-specific differences were also observed. Male pups exhibited transcriptional patterns consistent with enhanced immune tolerance, whereas females showed broader immune-pathway activation, including enrichment of pro-inflammatory and stress-response pathways. Several non-coding RNAs also displayed sex-specific changes in expression. Together, these findings suggest that fasting induces transcriptional remodeling of the gut and may contribute to immune regulation during a critical period of microbiome establishment in northern elephant seal pups.

Animals↗
PubMed2025

Duration of Hospitalization is Associated with the Gut Microbiome in Patients Undergoing Hematopoietic Stem Cell Transplantation: Early Results from a Randomized Trial of Home Versus Hospital Transplantation.

Home-based hematopoietic stem cell transplantation (HCT) is an innovative care model with growing interest, but its impact on the gut microbiome remains unexplored in a randomized setting. We present interim results from the first randomized controlled trials (RCT) evaluating the effect of HCT location-home versus hospital-on gut microbial diversity and antimicrobial resistance (AMR) gene carriage. We hypothesize that patients randomized to undergo home HCT would have higher gut taxonomic diversity and lower AMR gene abundance compared to those undergoing standard hospital HCT. We analyzed stool samples from the first 28 patients enrolled in ongoing Phase II RCTs comparing home (n = 16) and hospital (n = 12) HCT at Duke University using shotgun metagenomic sequencing to compare taxa and AMR gene composition between groups. We also performed a secondary analysis comparing patients who received transplants at outpatient infusion clinics versus inpatient standard HCT to evaluate the influence of hospitalization duration. In the primary RCT analysis, taxonomic and AMR gene α- and β-diversity were comparable between home and hospital groups, reflecting similar durations of hospitalization despite group allocation. In contrast, secondary analyses demonstrated that patients transplanted in outpatient infusion clinics who experienced significantly reduced hospitalization had higher gut taxonomic α-diversity and differential β-diversity, although AMR gene diversity remained unchanged. In summary, randomization by transplant location did not impact the gut microbiota to the same extent as the duration of hospitalization, although secondary analyses were heavily confounded. Even when taxonomic differences were observed, AMR genes were similar between groups. This RCT represents a novel investigation into how care setting influences the gut microbiome during HCT. Our findings suggest that hospital duration, rather than randomization allocation alone, is the primary driver of microbial disruption. These results underscore the potential for reducing hospital duration to mitigate microbiome injury, thereby informing future interventions to reduce infection risk and improve patient outcomes.

Microbiome↗
PubMed2006

Community structure of actively growing bacterial populations in plant pathogen suppressive soil.

The bacterial community in soil was screened by using various molecular approaches for bacterial populations that were activated upon addition of different supplements. Plasmodiophora brassicae spores, chitin, sodium acetate, and cabbage plants were added to activate specific bacterial populations as an aid in screening for novel antagonists to plant pathogens. DNA from growing bacteria was specifically extracted from the soil by bromodeoxyuridine immunocapture. The captured DNA was fingerprinted by terminal restriction fragment length polymorphism (T-RFLP). The composition of the dominant bacterial community was also analyzed directly by T-RFLP and by denaturing gradient gel electrophoresis (DGGE). After chitin addition to the soil, some bacterial populations increased dramatically and became dominant both in the total and in the actively growing community. Some of the emerging bands on DGGE gels from chitin-amended soil were sequenced and found to be similar to known chitin-degrading genera such as Oerskovia, Kitasatospora, and Streptomyces species. Some of these sequences could be matched to specific terminal restriction fragments on the T-RFLP output. After addition of Plasmodiophora spores, an increase in specific Pseudomonads could be observed with Pseudomonas-specific primers for DGGE. These results demonstrate the utility of microbiomics, or a combination of molecular approaches, for investigating the composition of complex microbial communities in soil.

Bacteria↗
PubMed2026

Species-specific structuring of gut bacterial and fungal communities in honey bees Apis cerana and Apis mellifera.

Honey bee gut microbiome studies have primarily emphasized bacteria, leaving fungal communities comparatively overlooked despite their ecological and functional importance. Whole-genome shotgun metagenomics of Apis cerana and Apis mellifera revealed fungal assemblages dominated by Ascomycota, with Basidiomycota and Microsporidia in minor proportions, alongside gut bacterial communities composed mainly of Pseudomonadota, Bacillota, and Actinomycetota. The bacterial diversity was markedly higher in A. mellifera (Shannon = 5.90; Simpson = 0.98) than in A. cerana (Shannon = 4.01; Simpson = 0.94; p > 0.05), while fungal diversity remained comparable between species (p > 0.05). Beta-diversity analyses revealed strong host-specific clustering for both bacterial (PERMANOVA R2 = 0.7989, p > 0.05) and fungal communities (R2 = 0.7218, p > 0.05), indicating distinct microbial organization driven by host species. Bacterial-fungal co-occurrence patterns exhibited host-specific structuring, suggesting differential inter-kingdom community organization between A. cerana and A. mellifera. Linear Discriminant Analysis Effect Size (LEfSe) identified 93 discriminatory fungal taxa (45 enriched in A. cerana, 48 in A. mellifera), highlighting yeast-dominated signatures in A. mellifera and Basidiomycota-affiliated enrichments in A. cerana. KEGG and CAZy profiling revealed host- and kingdom-specific functional differences, with bacterial communities of A. mellifera showing distinct representation of carbohydrate metabolism and nutrient-cycling functions, while fungal communities exhibited a comparatively narrower functional repertoire. Together, these findings provide a high-resolution view of honey bee bacterial and fungal microbiomes, highlighting strong host-driven divergence in taxonomy, function, and cross-kingdom interactions.

Animals↗
PubMed2026

Metagenomic profiling of gut microbiome in post-cholecystectomy patients with diarrhea: a nested case-control study.

BACKGROUND: Cholecystectomy can cause diarrhea, with an incidence as high as 57.2%, seriously impacting patient prognosis. To investigate the gut dysbiosis following cholecystectomy and identify microbial biomarkers and functional genomics associated with post-cholecystectomy diarrhea (PCD), we conducted a nested case-control study within a prospective cohort. METHODS: We enrolled a cohort of 160 patients. At follow-up completion, 30 patients who developed PCD were matched with 30 non-PCD (NPCD) controls. 16 S rRNA sequencing was used to analyze gut microbiota structure and diversity (mainly at genus level). Representative fecal samples underwent metagenomic sequencing for species level and genetic differential analysis. RESULTS: The potentially pathogenic bacterial species Coprococcus comes and Blautia sp. were significantly enriched in the gut microbiota of PCD patients, with their abundance positively correlated with the degree of intestinal inflammation. In contrast, the potentially beneficial bacterial species Bacteroides intestinalis and Prevotella copri, known to contribute to lipid metabolism and play a role in modulating gut immunity and suppressing inflammatory responses, were found to be significantly depleted in PCD patients. Further metagenomic functional analysis revealed significant enrichment of pathways related to cell motility, membrane transport, and sulfur metabolism in PCD patients. CONCLUSIONS: This work identified potential beneficial and pathogenic bacterial species associated with the onset of PCD, as well as significantly enriched functional pathways within the intestinal microbiota. These findings provide a scientific basis for elucidating the relationship between PCD and gut microbiota, and provide candidate microbial signatures and functional pathways that may inform future microbiota-targeted strategies, pending external and mechanistic validation.

Humans↗
PubMed2026

A Mobile Glycosylation Locus Modulates Cell Wall Architecture in Lactobacillus crispatus.

Lactobacillus crispatus dominance in the vaginal microbiome is associated with beneficial health outcomes, yet strain-level variation and its implications remain poorly understood. Here, we resolve the genomic context of three glycosyltransferase gene fragments (GT1-3) previously linked with dysbiotic states. Long-read resequencing revealed that GT1-3 are part of a ~18.7 kb Wzx/Wzy-dependent cell wall polysaccharide (CWPS) locus, containing several IS256-family transposases. Serial propagation in vitro produced isolates with 4.1 kb excised via a composite transposon encompassing the GT3, UDP-galactopyranose mutase, flippase, and hypothetical protein, demonstrating structural plasticity. Transmission electron microscopy showed a ~20%-25% thinner peptidoglycan layer in the derived strains, while FT-IR and monosaccharide analysis indicated no gross changes. Molecular dynamics simulations suggest that GT3 contributes to the structural stability of the glycosyltransferase complex, without compromising catalytic function. Together, these findings establish the CWPS locus as a mobile, structurally plastic element that directly influences cell wall architecture in L. crispatus.

Lactobacillus crispatus↗
PubMed2026

Pan-genomics and multi-omics for deciphering genetic variation and accelerating genetic improvement in ruminant livestock.

Livestock reference genomes have transformed the discovery of variants associated with production, reproduction, health, and environmental adaptation. Nevertheless, a single linear reference represents only one mosaic haplotype and incompletely captures sequence diversity within a species, particularly structural variants, copy-number changes, repeat-rich regions, and breed-specific sequences. Pangenomes address this limitation by integrating multiple high-quality assemblies or population-scale variants into a unified sequence or graph representation. Concurrently, multi-omics approaches connect genomic variation with transcriptomic, epigenomic, manuscriptproteomic, metabolomic, and microbiome responses, thereby improving biological interpretation of genotype-phenotype relationships. This review synthesizes recent progress in livestock pangenomics and multi-omics, with emphasis on cattle, goats, sheep, water buffalo, and chickens. It describes advances in long-read and haplotype-resolved sequencing, graph construction, structural-variant discovery and genotyping, functional annotation, and integrative analysis. Recent pangenome studies have uncovered substantial non-reference sequence, reduced reference bias, identified breed- and population-specific structural variants, and resolved candidate variants underlying pigmentation, body size, tail morphology, cashmere production, altitude adaptation, and other economically relevant traits. However, translation into routine breeding remains constrained by uneven population representation, inconsistent structural-variant definitions, limited functional annotation, computational demands, and insufficient validation across environments. Future progress will depend on diverse near-complete assemblies, graph-aware imputation and genomic prediction, long-read transcriptomics, single-cell and spatial omics, rigorous causal validation, and open, interoperable resources. Together, these developments can support more accurate, resilient, and biologically informed livestock improvement. Importantly, current dairy-cattle evidence indicates that pangenome-derived structural variants can substantially improve variant discovery and functional interpretation while yielding only marginal average gains in routine genomic prediction, favoring targeted augmentation rather than wholesale replacement of established SNP-based evaluations.

Animals↗
PubMed2025

Metagenome-Based Characterization of the Gut Virome Signatures in Patients With Gout.

The gut microbiome has been implicated in the development of autoimmune diseases, including gout. However, the role of the gut virome in gout pathogenesis remains underexplored. We employed a reference-dependent virome approach to analyze fecal metagenomic data from 102 gout patients (77 in the discovery cohort and 25 in the validation cohort) and 86 healthy controls (HCs) (63 and 23 in each cohort). A subset of gout patients in the discovery cohort provided longitudinal samples at Weeks 2, 4, and 24. Our analysis revealed significant alterations in the gut virome of gout patients, including reduced viral richness and shifts in viral family composition. Notably, Siphoviridae, Myoviridae, and Podoviridae were depleted, while Quimbyviridae, Retroviridae, and Schitoviridae were enriched in gout patients. We identified 359 viral operational taxonomic units (vOTUs) associated with gout. Enriched vOTUs in gout patients predominantly consisted of Fusobacteriaceae, Bacteroidaceae, and Selenomonadaceae phages, while control-enriched vOTUs included Ruminococcaceae, Oscillospiraceae, and Enterobacteriaceae phages. Longitudinal analysis revealed that a substantial proportion of these virome signatures remained stable over 6 months. Functional profiling highlighted the enrichment of viral auxiliary metabolic genes, suggesting potential metabolic interactions between viruses and host bacteria. Notably, gut virome signatures effectively discriminated gout patients from HCs, with high classification performance in the validation cohort. This study provides the first comprehensive characterization of the gut virome in gout, revealing its potential role in disease pathogenesis and highlighting virome-based signatures as promising biomarkers for gout diagnosis and future therapeutic strategies.

Humans↗
PubMed2026

Differentiating hemorrhagic shock and organophosphate poisoning through integrated skin microbiome-metabolome signatures.

Accurate determination of cause of death and estimation of postmortem interval (PMI) are critical yet challenging tasks in forensic science, particularly in cases with rapid demise and absence of obvious morphological abnormalities. We employed an integrative multi-omics approach to characterize postmortem microbial succession and metabolic alterations on facial skin in mouse models of hemorrhagic shock (HS) and organophosphorus poisoning (OP) across three decomposition stages: bloating (2 days), active decay (8 days), and advanced decay (16 days). Metagenomic profiling revealed significantly reduced &#x3b1;-diversity in HS compared with OP throughout all stages (p&#x2009;<&#x2009;0.001), accompanied by stage-dependent compositional shifts, including early enrichment of Firmicutes in HS and Proteobacteria in OP. A total of 237 differential taxa were identified, with Providencia and Morganella predominating in OP, whereas Staphylococcus and Corynebacterium dominated bloating stage of HS. Untargeted metabolomics uncovered distinct cause-of-death-linked metabolites, notably elevated 2'-deoxycytidine-5'-diphosphate in early OP and persistent cholic acid/cholate accumulation in HS at later PMI. Functional analysis highlighted histidine and phosphate/phosphonate metabolism as key discriminatory pathways, exhibiting stage-specific oscillations and strong correlations with characteristic taxa. These findings demonstrate that skin-based metagenomic-metabolomic integration provides robust, mechanistically informed biomarkers for both PMI estimation and cause-of-death differentiation, offering a minimally invasive and temporally dynamic tool for forensic investigations.

Animals↗
PubMed2026

Perseus: Lineage-Aware Refinement of Kraken2 Taxonomic Classification for Long Read Metagenomes.

MOTIVATION: Long-read metagenomic sequencing improves assembly contiguity and enables genome-resolved analysis of complex microbial communities, but accurate taxonomic classification of long reads and assembled contigs remains challenging. Highly scalable k-mer-based classifiers such as Kraken2 frequently over-assign fine-rank taxonomic labels when applied to long-read data, producing high false positive classification rates driven by sparse or localized k-mer matches, particularly in microbiomes with extensive taxonomic novelty. RESULTS: We present Perseus, a lineage-aware confidence estimation framework for taxonomic classification that models the spatial distribution and hierarchical consistency of k-mer evidence along sequences. This formulation reframes taxonomic classification as a hierarchical confidence estimation problem rather than a single-rank prediction task. Perseus refines k-mer-level taxonomic signals from Kraken2 using a multi-headed convolutional neural network that estimates calibrated confidence scores for taxonomic correctness at each canonical rank. Using these estimates, Perseus confirms assignments, backs off to higher taxonomic ranks, or abstains when evidence is insufficient, prioritizing correctness and lineage consistency over overly specific assignments. Across simulations of taxonomic novelty and real-world metagenomic datasets, Perseus consistently and substantially reduces the false assignment rate while improving precision and lineage-consistent accuracy. These improvements are most pronounced for long reads and assembled contigs, where spatial context enables reliable discrimination between consistent taxonomic signal and spurious matches. AVAILABILITY AND IMPLEMENTATION: Perseus integrates with existing Kraken2 workflows and is available at https://github.com/matnguyen/perseus.

Journal Article↗