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Snail immunity to schistosomes: insights from omics studies.

Schistosomiasis is a serious public health concern, with transmission facilitated by a small number of freshwater snail intermediate host species. Infection outcomes vary greatly across the primary vector genera, Biomphalaria (for Schistosoma mansoni), Bulinus (for S. haematobium), and Oncomelania (for S. japonicum), even within species, ranging from full resistance to high compatibility. Omics methods have altered this field by correlating host genotype, baseline immunological status, and time-resolved responses to whether invading miracidia are eliminated or develop sporocysts. Evidence from genomes, transcriptomics, proteomics, and epigenomics suggests that resistance is frequently primed prior to exposure. However, the clearest divergence between resistant and susceptible trajectories occurs during a small early window (<12-48&#x202f;h) after penetration. During this time, recognition, hemocyte recruitment, and soluble effector deployment either come together quickly or are delayed and guided by parasite-derived modulators. Established infections cause the host to adapt to chronic conditions through immune regulation, metabolic reprogramming, tissue and neuroendocrine remodeling, microbiome modification, and parasite castration. Comparative genomics reveals that each vector genus has evolved its own immunogenomic profile, which includes lineage-specific expansions of recognition and effector gene families. Together, these findings can help with field surveillance and intervention by providing molecular compatibility markers, functional tools for testing candidate genes, and tactics that target parasite-derived immune modulators. Integrated multi-omics approaches are a top priority, yet they are still limited in snail vectors compared to other disease vector systems.

Animals↗

The current and future perspective of ChickenGTEx project and its applications in precision breeding.

The Chicken Genotype-Tissue Expression (ChickenGTEx) project was established to systematically characterize the regulatory landscape of the chicken genome and to accelerate the translation of functional genomics into precision breeding. By integrating whole-genome sequencing with multi-tissue transcriptomic profiling, ChickenGTEx provides a comprehensive atlas of gene expression regulation across diverse tissues and physiological systems. Current findings demonstrate that complex production traits are governed by coordinated regulatory networks rather than isolated loci, with substantial contributions from tissue-specific gene expression, structural variation, and genotype-by-sex interactions. Sex-dependent regulatory effects further refine the genetic architecture of metabolic, immune, and reproductive traits, highlighting the importance of incorporating sex as a biological variable in genomic analyses. Application of integrative omics frameworks within elite layer populations has revealed multilayer regulatory mechanisms underlying extended laying performance, feed efficiency, metabolic health, and eggshell quality. By partitioning phenotypic variance into genetic, regulatory, and host-microbiome components, these approaches move beyond association-based mapping toward causal inference and biological interpretation. Importantly, validated regulatory loci identified through ChickenGTEx and related analyses provide actionable markers for genomic selection and rational targets for precision genome modification. Looking forward, continued expansion of regulatory atlases, incorporation of single-cell and longitudinal data in diverse environmental conditions, and integration of functional annotation into breeding pipelines will further enhance prediction accuracy and sustainable genetic improvement. The ChickenGTEx project thus represents a foundational platform bridging functional genomics and practical poultry breeding.

Animals↗

Comprehensive analyses of a large human gut Bacteroidales culture collection reveal species and strain level diversity and evolution.

Species of the Bacteroidales order are among the most abundant and stable bacterial members of the human gut microbiome with diverse impacts on human health. While Bacteroidales strains and species are genomically and functionally diverse, order-wide comparative analyses are lacking. We cultured and sequenced the genomes of 408 Bacteroidales isolates from healthy human donors representing nine genera and 35 species and performed comparative genomic, gene-specific, mobile gene, and metabolomic analyses. Families, genera, and species could be grouped based on many distinctive features. However, we also show extensive DNA transfer between diverse families, allowing for shared traits and strain evolution. Inter- and intra-specific diversity is also apparent in the metabolomic profiling studies. This highly characterized and diverse Bacteroidales culture collection with strain-resolved genomic and metabolomic analyses can serve as a resource to facilitate informed selection of strains for microbiome reconstitution.

Preprint↗

Meta-CD: a metagenomic sequencing coverage and depth calculator for target species.

Metagenomic Coverage and Depth Calculator (Meta-CD) is a convenient, biologist-friendly tool for determining coverage and depth to enhance taxonomic detection, functional profiling, and metagenome-assembled genome (MAG) recovery in metagenomics. It supports experimental design and post-sequencing analysis, modeling how genome size, relative abundance, sequencing depth, and DNA quantity influence detection of target species.

metagenomics↗

Enrichment of root-associated Streptomyces strains in response to drought is driven by diverse functional traits and does not predict beneficial effects on plant growth.

The genus Streptomyces has consistently been found enriched in drought-stressed plant root microbiomes, yet the ecological basis and functional variation underlying this enrichment at the strain and isolate level remain unclear. Using two 16S rRNA sequencing methods with different levels of taxonomic resolution, we confirmed drought-associated enrichment (DE) of Streptomyces in field-grown sorghum roots and identified five closely related but distinct amplicon sequence variants (ASVs) belonging to the genus with variable drought enrichment patterns. From a culture collection of sorghum root endophytes, we selected 12 Streptomyces isolates representing these ASVs for phenotypic and genomic characterization. Whole-genome sequencing revealed substantial variation in gene content, even among closely related isolates, and exometabolomic profiling showed distinct metabolic responses to media supplemented with drought- versus well-watered root tissue. Traits linked to drought survival, including osmotic stress tolerance, siderophore production, and carbon utilization, varied widely among isolates and were not phylogenetically conserved. Using a broader panel of 48 Streptomyces, we demonstrate that DE scores, determined through mono-association experiments in gnotobiotic sorghum systems, showed high variability and lacked correlation with plant growth promotion. Pangenome-wide association identified orthogroups involved in osmolyte transport (e.g., proP) and membrane biosynthesis (e.g., fabG) as positively associated with DE, though most associations lacked phylogenetic signal. Collectively, these results demonstrate that Streptomyces DE is not a conserved genus-level trait but is instead strain-specific and functionally heterogeneous. Furthermore, DE in the root microbiome was shown not to predict beneficial effects on plant growth. This work underscores the need to resolve functional traits at the strain level and highlights the complexity of microbe-host-environment interactions under abiotic stress.

Streptomyces↗

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↗

Desert-derived Ensifer sp. SA403 enhances potato salt tolerance by reshaping rhizosphere microbiome functions and host responses.

Soil salinization increasingly threatens global food security, and potato (Solanum tuberosum L.), a moderately salt-sensitive crop, is particularly vulnerable to saline soils. Plant growth-promoting rhizobacteria (PGPR) offer a promising strategy to improve crop performance, yet how PGPR interact with native microorganisms to enhance potato salt tolerance remains poorly understood. In this study, we identified a desert-derived PGPR strain, Ensifer sp. SA403, which substantially enhanced potato performance under high salinity across sterile, non-sterile and field conditions. Physiologically, inoculation with SA403 reduced shoot Na&#x207a; accumulation and increased the K&#x207a;/Na&#x207a; ratio; notably, these effects were markedly stronger in non-sterile substrates than under sterile conditions, indicating that SA403-mediated ion homeostasis relies on cooperation with the resident microbiota rather than on the strain acting alone. Metagenomic profiling indicated that SA403 strain reshaped rhizosphere communities, significantly enriching beneficial taxa such as Priestia and Bradyrhizobium, and upregulated functional pathways involved in glutathione and sulfur metabolism. Furthermore, host transcriptomic analyses showed that SA403 modulated plant responses to salt stress, with differentially expressed genes enriched in jasmonic acid signaling, ethanolamine metabolism and amino-acid biosynthesis pathways. Field trials on saline soils confirmed that SA403 significantly increased seedling emergence and tuber weight. Together, our results demonstrate that SA403 functions as a biological mediator that optimizes rhizosphere microecology and coordinates ion balance and host signaling to enhance potato salt tolerance. These findings support the potential of SA403 as a robust PGPR-based tool for sustainable potato production on saline soils.

Rhizosphere↗

Synthesis and Application of a Suite of 2,5-Aryl Tetrazole Photoaffinity-Based Probes for Profiling Microbial Carbohydrate and Mucin Metabolism in Gut Microbiota.

Photoaffinity-based chemoproteomics provides a strategy for interrogating protein engagement and networks within complex biological systems. In the context of carbohydrate metabolism, however, linking the probe structure to glycan-processing networks remains challenging due to the diversity and redundancy of carbohydrate-active enzymes (CAZymes). Here, we employ 2,5-tetrazoles as photoreactive groups to develop a suite of monosaccharide-bearing probes designed to capture carbohydrate-associated protein environments in gut microorganisms. Across defined bacterial cultures and human fecal lysates, tetrazole probes enriched glycoside hydrolases (GHs) and additional carbohydrate-associated proteins, including transporters and regulatory elements. Notably, enrichment profiles were functionally biased toward glycan-processing modules, despite minimal shifts in global protein abundance under different growth conditions. These findings demonstrate that tetrazole chemoproteomics complements abundance-based proteomics by reporting on glycan-associated protein engagement and organization. Together, this probe suite provides a substrate-centric approach to studying carbohydrate-processing networks in defined microbes and complex microbiomes.

Tetrazoles↗

Potential contribution of the microbiota-gut-brain axis to doxorubicin-associated cognitive impairment: Mechanisms, evidence, and therapeutic opportunities.

Chemotherapy-induced cognitive impairment (CICI), often termed chemobrain, is a clinically important complication of cancer treatment that can affect memory, attention, executive function, and processing speed during and after therapy. Doxorubicin is of particular mechanistic interest because brain parenchymal exposure is limited, yet preclinical studies consistently identify neuroinflammatory, oxidative, vascular, and synaptic abnormalities after treatment. This critical narrative review evaluates whether intestinal injury and disruption of the microbiota-gut-brain axis may contribute to these central effects. Preclinical evidence indicates that doxorubicin can alter microbial community structure, injure the intestinal barrier, modify SCFA-associated taxa or predicted functions, alter selected metabolite profiles, and promote systemic inflammatory and metabolic signaling. These peripheral changes could interact with brain endothelial cells, glia, mitochondria, hippocampal neurogenesis, and synaptic-plasticity pathways. However, the proposed doxorubicin-gut-brain pathway remains a predominantly preclinical and incompletely tested framework. No longitudinal human study has yet established, within the same patients, the temporal sequence linking doxorubicin exposure, microbiome or metabolome changes, systemic inflammation, and objective cognitive outcomes. Existing animal studies also vary in dose, regimen, tumor context, sampling time, microbiome methodology, and control of behavioral or microbiological confounders, while causal rescue experiments remain limited. Key priorities are therefore longitudinal human cohorts with pretreatment baselines and repeated multi-omics and cognitive assessments; animal studies that test temporal precedence and causal rescue or pathway blockade in the same model; mediation analyses that determine whether microbial or metabolic changes lie between treatment and cognitive dysfunction; and mechanism-informed clinical trials that demonstrate target engagement, cognitive benefit, oncology safety, and preservation of antitumor efficacy. Microbiome-directed interventions are promising but remain investigational for doxorubicin-associated CICI.

blood&#x2013;brain barrier↗

Two worlds beneath: Distinct microbial strategies of the rock-attached and planktonic subsurface biosphere.

BACKGROUND: Microorganisms in groundwater ecosystems exist either as planktonic cells or as attached communities on aquifer rock surfaces. Attached cells outnumber planktonic ones by at least three orders of magnitude, suggesting a critical role in aquifer ecosystem function. However, particularly in consolidated carbonate aquifers, where research has predominantly focused on planktonic microbes, the metabolic potential and ecological roles of attached communities remain poorly understood. RESULTS: To investigate the differences between attached and planktonic communities, we sampled the attached microbiome from passive samplers filled with crushed carbonate rock exposed to oxic and anoxic groundwater in the Hainich Critical Zone Exploratory and compared it to a previously published, extensive dataset of planktonic communities from the same aquifer ecosystem. Microbial lifestyle (attached vs. planktonic) explained more variance in community composition than redox conditions, prompting us to further investigate its role in shaping functional and activity profiles. Metagenomic analysis revealed a striking taxonomic and functional segregation: the 605 metagenome-assembled genomes (MAGs) from attached communities were dominated by Proteobacteria (358 MAGs) and were enriched in genes for biofilm formation, chemolithoautotrophy, and redox cycling (e.g., iron and sulfur metabolism). In contrast, the 891 MAGs from planktonic communities were dominated by Cand. Patescibacteria (464 MAGs) and Nitrospirota (60 MAGs) and showed lower functional versatility. Only a few genera were shared, and even closely related MAGs (>&#x2009;90% average nucleotide identity) differed in assembly size and metabolic traits, demonstrating lifestyle-specific functional adaptation. Analysis of active replication indicated that the active fraction of the attached community was primarily represented by the most abundant MAGs. Planktonic communities featured a higher fraction of active MAGs compared to attached communities, but overall with lower relative abundances. CONCLUSIONS: The high abundance, metabolic specialization, and carbon fixation potential of attached microbes suggest that they are key drivers of subsurface biogeochemical processes. Carbonate aquifers may act as much larger inorganic carbon sinks than previously estimated based on CO2 fixation rates of the planktonic communities alone. Our findings underscore the need to incorporate attached microbial communities into models of subsurface ecosystem function. Video Abstract.

Plankton↗

Interkingdom remodeling of the intestinal bacteriome and virome during Toxoplasma gondii infection in rats.

Toxoplasma gondii infection is associated with intestinal microbiome disruption, but its effects on genome-resolved bacterial populations, the gut virome, and bacteriome-virome relationships remain poorly understood. Using previously generated shotgun metagenomic datasets from 36 intestinal samples collected from 18 Sprague-Dawley rats across control, acute, and chronic infection groups, we reconstructed 294 quality-filtered, non-redundant bacterial metagenome-assembled genomes (MAGs) and identified 899 medium-to-high-quality viral operational taxonomic units (vOTUs) from assembled metagenomic contigs. Infection was associated with reduced bacterial richness in the small intestine during both acute and chronic stages and lower Shannon diversity during chronic infection. In contrast, large-intestinal &#x3b1;-diversity remained stable despite significant compositional reorganization. Taxonomic changes included increased Lactobacillus intestinalis, Limosilactobacillus reuteri, and Prevotella sp900547005, together with decreased Rothia sp002492045 and Akkermansia muciniphila. Functional profiling revealed region- and stage-specific changes in predicted bacterial metabolic potential, including reduced energy-related pathways and carbohydrate-active enzyme abundance. The virome also showed significant compositional changes in both intestinal regions. Quimbyviridae and Podoviridae_crAss-like viruses decreased in the small intestine during chronic infection, while Quimbyviridae, Flandersviridae, and Podoviridae_crAss-like viruses showed stage-specific decreases in the large intestine. Predicted bacterial hosts were assigned to 48.39% of vOTUs, with Lachnospiraceae and Ruminococcaceae being the most frequently linked families. Trans-kingdom networks further revealed region-specific positive and negative abundance correlations between bacterial and viral taxa. These findings extend previous microbiota-metabolome observations by integrating genome-resolved bacteriome analysis with contig-based virome profiling, providing a foundation for future mechanistic studies of toxoplasmosis-associated microbiome remodeling.

Gut virome↗

GRUMB: a genome-resolved metagenomic framework for monitoring urban microbiomes and diagnosing pathogen risk.

SUMMARY: Urban infrastructure hosts dynamic microbial communities that complicate biosurveillance and AMR monitoring. Existing tools rarely combine genome-resolved reconstruction with ecological modeling and batch-aware analytics tailored to infrastructure-scale studies. We present GRUMB (Genome-Resolved Urban Microbiome Biosurveillance), an open-source, SLURM-compatible pipeline that reconstructs high-quality metagenome-assembled genomes (MAGs) from shotgun sequencing reads and integrates taxonomic/functional annotation (CARD, VFDB), batch-aware normalization, ecological diagnostics and machine learning classification of environment types with uncertainty and risk scoring. GRUMB accepts either SRA project accessions or paired-end FASTQ files with metadata, and produces assemblies, MAGs, taxonomic and functional profiles, ecological outputs and risk-informed classification. Its modular design enables reproducible, infrastructure-scale biosurveillance across diverse environments. AVAILABILITY AND IMPLEMENTATION: GRUMB is freely available under the MIT License at: https://github.com/SuleimanAminu/genome-resolved-urban-microbiome-biosurveillance; Zenodo DOI: https://doi.org/10.5281/zenodo.15505402. Requirements: Linux (Ubuntu 20.04+), Python 3.11, R 4.2+, SLURM. Issues and feature requests are tracked on GitHub.

Microbiota↗

Multi-level aggregation analysis of microbiome composition and host gene expression reveals associations with systemic and local immunity.

The human gut microbiome plays a critical role in immune regulation, yet the molecular links between microbiome composition and host gene expression remain incompletely understood. We analyzed associations between host gene expression and microbiome composition in a cohort of 315 healthy individuals, integrating microarray-based gene expression data from three intestinal sites (ileum, transverse colon, and rectum) and six immune cell types with microbiome sequencing data. Using a hierarchical feature aggregation strategy combining principal component analysis, clustering, and covariate correction, we discovered significant associations primarily related to immunity. While microbial profiles were similar across the three intestinal sites, the transverse colon yielded the most "microbiome-host gene expression" associations. Among the immune cell types, CD8+ cells showed the highest number of associations. The first principal component of microbiome composition, reflecting a gradient from commensals (e.g., Ruminococcaceae and Christensenellaceae) to proinflammatory taxa ([Ruminococcus] gnavus and Lachnoclostridium), correlated with the expression of TNF-&#x3b1;-linked genes (HMOX1, CPI17, HSD3B2, and SLC5A1). Among individual genera, Catenibacterium abundance was associated with gene expression in both intestinal and immune cells, including negative associations with MRPS21 (related to mitochondrial function) in the transverse colon and with CD8+ gene programs related to T cell differentiation. These findings align with emerging evidence implicating mitochondrial dysfunction in intestinal inflammation. Our results identify multi-level associations between the gut microbiome and host gene expression, suggesting potential mechanisms by which microbiota shape local and systemic immunity and vice versa. The implicated genes and taxa represent candidates for experimental validation to improve understanding of host-microbiome homeostasis and its disruption in disease.IMPORTANCEThe gut microbiome and immune system are engaged in a complex interplay throughout human life. While most associative studies focus on case-control comparisons-typically examining patients with conditions such as inflammatory bowel disease or metabolic diseases-less is known about the molecular links between the microbiome and immune system in healthy individuals. In this study of a large cohort of healthy individuals, we addressed this gap by applying multiscale modeling to tackle the high dimensionality of host-microbiome data. We identified multi-level associations between microbiome composition and host gene expression in both intestinal tissues and immune cells. These findings offer a valuable reference for understanding baseline host-microbiome communication and highlight molecular candidates-such as TNF-&#x3b1;-related genes and mitochondrial pathways-for future experimental validation.

Humans↗

Linking visceral fat accumulation to gut microbiota: key bacterial taxa and their roles in the glycogen synthesis pathway.

Obesity, marked by visceral fat accumulation, has a complex relationship with the gut microbiome that impacts body weight and fat accumulation. However, previous studies did not account for fat distribution, reflecting only overall fat mass, leaving specifics of this relationship partially understood. Here we analyzed the mechanistic links between visceral fat and the microbiome in a large cohort of healthy Koreans. Using permutational multivariate analysis of variance and prediction modeling, we examined associations between microbial profiles and metabolic variables including insulin, triglycerides, waist circumference and visceral fat. The strongest correlations were noted with specific enterotypes. Shotgun sequencing revealed that visceral fat is linked to the glycogen synthesis pathway influenced by Dorea longicatena and Bifidobacterium adolescentis. This suggests that these specific microbial signatures and their associated functional potential play a role in visceral fat-related obesity. To validate these findings, we conducted an in vivo study using diet-induced obesity mouse model. Oral administration of D. longicatena or B. adolescentis significantly promoted body weight gain and fat mass expansion and induced hepatic lipogenic gene upregulation. The prevalence of these strains in Korean and American populations highlights their global relevance, contributing to the development of personalized treatments and advanced health strategies.

Journal Article↗

Exploring the associations between preen oil bacterial, chemical and proteomic profiles of passerines.

Preen gland bacteria are thought to be the key producers of preen oil components such as chemosignalling molecules including volatile organic compounds (VOCs) and antimicrobial compounds including peptides and antimicrobial VOCs. However, data on the preen oil bacteriome and chemical composition are limited to a small subset of bird species, and the presence of antimicrobial peptides is largely unexplored. Here, we performed an exploratory study to characterize, for the first time, the preen oil chemical and proteomic profiles and to explore the possible contribution of the bacteriome to the production of preen oil VOCs and antimicrobial peptides (bacteriocins) in eight passerine species, each represented by a single individual. Preen oil bacteriome, chemical and proteomic profiles varied among birds. The bacterial profiles were dominated by the genera Streptococcus, Lactococcus, Corynebacterium and Cutibacterium. The chemical profiles mainly consisted of alcohols, ketones and carboxylic acids. The biological functions primarily associated with the proteomic profiles were proteolysis and response to oxidative stress. Although we were unable to explore a direct association between the bacteriome and chemical profiles, the preen oil contained bacteriocin- and VOC-producing bacterial genera capable of producing detected microbially-derived VOCs (mVOCs), the relative abundance of which varied between birds. Riparian species showed the highest chemical diversity and high abundances of putative preen oil mVOC-producing bacteria, which could suggest habitat-specific adaptations. This exploratory study may significantly contribute to the formulation of hypotheses on the potential role of host ecological factors in the variation of preen oil bacterial, chemical and proteomic profiles in passerines.

Animals↗

Dual-transcriptomic analysis of human nasal transcriptome and microbiome reveals host-bacteria associations in symptomatic respiratory infection.

BACKGROUND: The human nasopharynx is colonized by a diverse community of commensal microbiota linked to many respiratory diseases, yet their associations with the host remain unclear. RESULTS: In this study, we introduced a dual-transcriptomics analysis strategy, which can characterize the host transcriptome and microbiome from nasal samples simultaneously. We applied this workflow to a local SARS-CoV-2 cohort with 76 asymptomatic infected patients, among whom 52 (68.42%) developed symptomatic infection during a 1-week follow-up period. Nasal swabs were collected from all 76 patients at enrollment and from 73 patients at one-week later follow-up. We detected a median of 8.94% reads that did not map to the human genome across all 149 samples, among which around half (median 49.68%) were successfully mapped to microbiome genome. Meta-transcriptomic analysis detected significantly higher SARS-related coronavirus loads in samples from the symptomatic group at enrollment (P&#x2009;=&#x2009;0.004), and both groups showed decreased loads one week later (symptomatic, P&#x2009;=&#x2009;0.001; asymptomatic, P&#x2009;=&#x2009;0.035). Compared with benchmarking 16&#xa0;S rRNA sequencing on 53 samples, our computational strategy showed high correlation of relative abundance in all top 20 genera (median Rho&#x2009;=&#x2009;0.90, Pmax < 0.001). A total of 670 bacteria species were identified to show a relative abundance&#x2009;&#x2265;&#x2009;0.01% in at least 10% samples. Differential abundance analysis identified 76 species (DASs) from six phyla with significantly decreased abundance in samples from the symptomatic group (log2(fold change or FC) < -1 and adjusted P&#x2009;<&#x2009;0.05) compared to the asymptomatic group at enrollment. Integrating these symptom-associated DASs with host's gene expression using an expression quantitative trait bacteria (eQTB) model, we found 45 symptom-associated DASs identified at enrollment were significantly associated with one to 14 genes (adjusted P&#x2009;<&#x2009;0.05). GSEA showed a series of symptom-associated DASs were significantly correlated with pathways related to olfactory function, keratinocyte differentiation, and DNA methylation. CONCLUSIONS: In summary, our dual-transcriptomic analysis strategy effectively characterized host-microbiome associations, offering insights into microbial contributions to respiratory diseases.

Humans↗

kMermaid: Ultrafast metagenomic read assignment to protein clusters by hashing of amino acid k-mer frequencies.

Shotgun metagenomic sequencing can determine both the taxonomic and functional content of microbiomes. However, functional classification for metagenomic reads remains highly challenging as protein mapping tools require substantial computational resources and yield ambiguous classifications when short reads map to homologous proteins originating from different bacteria. Here we introduce kMermaid for the purpose of uniquely mapping bacterial short reads to taxa-agnostic clusters of homologous proteins, which can then be used for downstream analysis tasks such as read quantification and pathway or global functional analysis. Using a nested hash map containing amino acid k-mer profiles as a model for protein assignment, kMermaid achieves the sensitivity of popular existing protein mapping tools while remaining highly resource efficient. We evaluate kMermaid on simulated data and data from human fecal samples as well as demonstrate the utility of kMermaid for classifying reads originating from new, unseen proteins. kMermaid allows for highly accurate, unambiguous and ultrafast metagenomic read assignment into protein clusters, with a fixed memory usage, and can easily be employed on a typical computer.

Metagenomics↗

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↗