Functional spirometric profile examinations in bronchial asthma and airways obstruction.
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Airway Obstruction↗
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Metabolic reprogramming and taxonomic drivers in bacterial vaginosis: A large-scale metagenomic meta-analysis.
OBJECTIVE: Bacterial vaginosis (BV) represents a profound ecological shift from a Lactobacillus-dominated microbiota to a diverse polymicrobial biofilm associated with adverse outcomes. While taxonomic signatures are well-documented, the functional mechanisms driving this transition remain obscured. This study elucidates the genomic potential for metabolic reprogramming and the putative "functional handover" underpinning the stability of the dysbiotic state. METHODS: A computational meta-analysis of 3557 vaginal microbiomes from diverse global cohorts was performed using the standardized MGnify pipeline. A high-resolution subset of 187 whole-genome shotgun (WGS) metagenomes was stratified to compare functional potential across demographic groups. Taxon-function interaction networks were constructed, utilizing a dual-filter statistical approach (p < 0.05 and effect size ranking), to map the shift from homeostatic maintenance to dysbiotic metabolic potential. RESULTS: BV was characterized by a fundamental shift from "maintenance" pathways to high-turnover "growth-oriented" genomic repertoires. While ABC transporter-like domains were present in healthy communities, dysbiosis was marked by a quantitative expansion and diversification of these systems alongside P-loop NTPases. Network analysis revealed a putative "functional handover": while Gardnerella serves as the adherent structural scaffold, the metabolic burden appears to be associated with secondary anaerobes, specifically BVAB1 and Sneathia, which exhibit strong genomic correlations with nutrient transport and stress response pathways. Crucially, microbiomes from women of African ancestry (Black cohort) exhibited a distinct functional profile with genomic signatures consistent with functions previously associated with resistome expansion (e.g., tetracycline/macrolide resistance), contrasting with Asian cohorts. CONCLUSION: BV is a state of metabolic reprogramming where genomic functional dominance is transferred from Lactobacillus to a cooperative network of anaerobic opportunists. Identifying BVAB1 and Sneathia as candidate metabolic engines, supported by a Gardnerella scaffold, challenges current therapeutic paradigms and highlights the potential for precision medicine targeting specific functional drivers and resistome profiles across diverse populations.
Humans↗
Imaging-Guided Omics Technologies for Resolving Rare Cancer States and Advancing Nanomedicine.
The ability to resolve rare and transient cellular states is critical for understanding metastasis, immune evasion, and therapy resistance in cancer, yet these dynamic processes often escape detection by conventional sequencing and imaging approaches. Recent advances at the interface of nanotechnology, high-resolution live-cell imaging, and single-cell/spatial multiomics methods have enabled functional profiling of cells with unprecedented precision within their native microenvironment. In this Mini-Review, we highlight emerging nanoscale platforms that couple real-time phenotypic imaging with molecular readouts, such as FUNseq and CIN-seq, to directly link functional heterogeneity to transcriptomic, proteomic, and epigenomic information. By integrating nanoscale optical imaging, microengineered perturbation tools, and AI-driven computational analysis, these technologies open up new avenues for dissecting rare metastatic, therapy-resistant, or immune-evasive subpopulations. We further discuss how these next-generation imaging-guided single-cell and spatial omics platforms not only advance fundamental cancer biology but also create opportunities to accelerate the development of nanomedicine applications.
Humans↗
[Analytical contribution to the morphological study of the normal human erythrocyte].
This note introduces a new, simple analytical function as a geometrical model for the human erythrocyte (GR). This profile function contains three shape coefficients (a1, a2, R) and shows a considerable quickness of computation.
Erythrocytes↗
Host-independent metagenomics reveal gut bacteria contribution to Delia antiqua growth by vitamin B6 provision.
Insect guts host a diverse and abundant array of microorganisms. These microbes improve host fitness by extensively involving in a range of crucial physiological processes, which have mainly been revealed by high-throughput sequencing, particularly metagenomics. However, it is almost impossible to make an accurate and complete distinction between the genetic functions of microbial symbionts and insect hosts without host genome data. By comparing metagenomic data from gut germ-free and nonaxenic larvae, we accurately identified the data belonging to the gut microbiome of the onion maggot Delia antiqua (Diptera: Anthomyiidae). Besides, a correlation between bacteria of the genus Wohlfahrtiimonas (Gammaproteobacteria: Pseudomonadaceae) and vitamin B6 metabolism was detected through collinearity analysis. Furthermore, in vitro tests confirmed that the gut bacterium Wohlfahrtiimonas larvae contributed to the growth of D. antiqua larvae via the independent synthesis of vitamin B6. This study provides a comprehensive view of the gut bacterial diversity in D. antiqua and reveals a functional profile that is strictly specific to the gut microbiota of this species. It has preliminarily revealed the functional differentiation between insect hosts and their symbiotic microorganisms. This study also offers a technical reference for the study of microbial symbiotic functions in other insect-microbe symbioses without host genomic data.
Animals↗
Comparative characterization of six teleost piscidins reveals distinct antimicrobial, antibiofilm and stability profiles.
Piscidins are cationic α-helical antimicrobial peptides (AMPs) that constitute a key component of the innate immune defense of teleost fish, yet the relationship between their genomic organization, structural properties, and functional specialization remains incompletely understood. In this study, six piscidin peptides from Epinephelus akaara, Seriola dumerili, Thunnus maccoyii, Argyrosomus regius, Dicentrarchus labrax, and Epinephelus coioides were characterized through an integrated sequence-to-function approach combining comparative genomics, structural modeling, physicochemical analysis, and in vitro validation, with the aim of identifying candidates with potential for biomedical and biotechnological applications. All genes studied exhibited the conserved four-exon, three-intron architecture characteristic of teleost piscidins. Structural modeling and circular dichroism confirmed α-helical conformations under membrane-mimetic conditions, despite measurable differences in hydrophobicity, charge distribution, and predicted membrane insertion parameters. Antimicrobial assays revealed distinct functional profiles: Sd_FI25 and Epinecidin_1 displayed broad antibacterial activity against Gram-positive and Gram-negative pathogens, whereas Dl_FI22 showed selective activity with reduced temporal persistence associated with lower peptide stability. Ea_FF25 exhibited comparatively weak antibacterial potency. Antibiofilm activity varied among peptides and did not uniformly parallel planktonic MIC values. Computational predictions further suggested antiviral and antitumoral potential for several sequences, extending their prospective relevance beyond classical antibacterial roles. Conserved genomic architecture and α-helical structure coexist with pronounced functional diversification among teleost piscidins. These findings demonstrate that integrating structural prediction with experimental validation is an effective strategy for identifying fish-derived innate immune peptides as candidates for biomedical applications.
Antimicrobial activity↗
Evaluation of linear profile scans; mathematical treatment of line-spread functions.
The profile measurement capability of a scanning multidetector whole-body counter is described using line spread functions. Measurements in air and water phantoms, as a function of energy, are discussed in relationship to the relevant physical processes. A computer program for evaluating bodyprofile scans and an attempt to improve the resolution are reported.
Evaluation Studies as Topic↗
Genome-wide identification and expression profiling of the MADS-box gene family in Lavandula angustifolia.
BACKGROUND: MADS-box genes encode transcription factors critical for plant development, particularly floral organogenesis, flowering time regulation, and adaptation to environmental stresses. Among these, the MIKCC-type genes are pivotal regulators in floral developmental processes. Although the evolutionary diversification and functional dynamics of MADS-box genes have been extensively characterized in model plants such as Arabidopsis thaliana and Oryza sativa, their evolutionary relationships and functional profiles in Lavandula angustifolia, an economically significant aromatic plant, remain poorly understood. RESULTS: Genome-wide analysis identified 173 MADS-box genes in L. angustifolia, categorized into type I (Mα: 26; Mβ: 0; Mγ: 10) and type II (MIKCC: 125; MIKC*: 12) based on phylogenetic comparisons with A. thaliana. The MIKCC subgroup was further subdivided into 12 subclasses, including genes central to the ABCDE model of floral organ specification. Structural analyses revealed distinct conserved motifs and exon-intron configurations specific to each subgroup, indicative of functional divergence. Synteny analysis demonstrated Whole Genome Duplication (WGD) and segmental duplications as major contributors to MIKCC gene family expansion, notably among genes linked to floral organ development. Expression profiling via RNA-seq and quantitative real-time PCR (qPCR) showed type II MADS-box genes exhibited higher expression levels with pronounced tissue-specific and developmental stage-specific expression patterns compared to type I genes. Many type II genes displayed significant associations with floral organogenesis, floral transition, and abiotic stress responses, underscoring their essential roles in reproductive development and environmental adaptability in L. angustifolia. CONCLUSIONS: The identification and comprehensive characterization of 173 MADS-box genes in L. angustifolia highlight the significant expansion of the MIKCC subgroup driven primarily by WGD and segmental duplications. The distinct structural features and specific expression patterns observed provide insights into the functional divergence and complexity of these genes, particularly regarding floral organogenesis and adaptation to environmental stress. This study establishes a robust molecular basis for further functional analysis and genetic improvement of aromatic plants.
MADS Domain Proteins↗
Effects of Fecal Microbiota Transplantation on Intestinal Microbial Characteristics and Clinical Phenotypes in Patients with Parkinson's Disease.
Alterations in the gut microbiota have been associated with Parkinson's disease (PD), but longitudinal microbial changes after fecal microbiota transplantation (FMT) and their clinical associations remain poorly understood. This single-center retrospective observational study included 6 patients with PD, stratified into high- and low-severity subgroups based on disease duration (>6 years vs ≤6 years). Thirty-six fecal samples were collected before FMT and monthly for five months afterward. Microbial diversity, community structure, taxonomic composition, and predicted functional profiles were assessed using 16S ribosomal RNA gene sequencing. Analyses included alpha and beta diversity, taxonomic abundance, linear discriminant analysis effect size, Tax4Fun2-based functional prediction, and Spearman rank correlations between microbial features and clinical indicators. Descriptive analyses indicated differences in microbial richness, diversity, community structure, and predicted functions between severity subgroups and across post-FMT time points. At baseline, the low-severity subgroup had greater microbial richness and diversity than the high-severity subgroup, with relatively higher abundances of taxa including Bifidobacterium and Lactobacillus. One month after FMT, richness and diversity increased from baseline in the high-severity subgroup, accompanied by changes in taxonomic composition. Both subgroups showed time-associated variation in microbial diversity and predicted Kyoto Encyclopedia of Genes and Genomes pathway enrichment after FMT. Predicted functions included carbohydrate and amino acid metabolism, secondary metabolite biosynthesis, membrane transport, and signal transduction. Several operational taxonomic units correlated with indicators of motor impairment, constipation, sleep quality, functional status, and neuropsychiatric symptoms. FMT was therefore associated with longitudinal changes in gut microbial diversity, composition, and predicted functions, and specific microbial features were associated with motor and non-motor indicators. Given the small retrospective cohort, these findings are preliminary and warrant confirmation in larger controlled studies. Future studies should determine whether these microbial alterations are reproducible, persist beyond five months, reflect donor engraftment, and correspond to measurable clinical improvement after transplantation in PD.
Humans↗
ScGOclust: leveraging gene ontology to find functionally analogous cell types between distant species.
MOTIVATION: Basic biological processes are shared across animal species, yet their cellular mechanisms are profoundly diverse. Comparing cell-type gene expression between species reveals conserved and divergent cellular functions. However, as phylogenetic distance increases, gene-based comparisons become less informative. The gene ontology (GO) knowledgebase offers a solution by serving as the most comprehensive resource of gene functions across a vast diversity of species, providing a bridge for distant species comparisons. RESULTS: Here, we present scGOclust, a computational tool that constructs de novo cellular functional profiles using GO terms, facilitating systematic and robust comparisons within and across species. We applied scGOclust to analyse and compare the heart, gut, and kidney between mouse and fly, and whole-body data from Caenorhabditis elegans and Hydra vulgaris. We show that scGOclust effectively recapitulates the function spectrum of different cell types, characterizes functional similarities between homologous cell types, and reveals functional convergence between unrelated cell types. Additionally, we identified subpopulations within the fly crop that show circadian rhythm-regulated secretory properties and hypothesize an analogy between fly principal cells from different segments and distinct mouse kidney tubules. We envision scGOclust as an effective tool for uncovering functionally analogous cell types or organs across distant species, offering fresh perspectives on evolutionary and functional biology. AVAILABILITY AND IMPLEMENTATION: ScGOclust is publicly available on CRAN: https://cran.r-project.org/web/packages/scGOclust/index.html and development versions are available on GitHub: github.com/Papatheodorou-Group/scGOclust/.
Animals↗
Evaluation of the gastric microbiota based on body mass index using 16S rRNA gene sequencing.
INTRODUCTION: Obesity is a multifactorial condition influenced by various factors, including the gut microbiota. However, the relationship between the gastric microbiota and obesity remains poorly understood. This study aimed to investigate the composition of gastric microbiota, excluding Helicobacter pylori, in relation to body mass index (BMI) and metabolic indicators. METHODS: Thirty participants undergoing health checkups were classified into three groups-normal weight (BMI 18.5-22.9), overweight (BMI 23.0-24.9), and obese (BMI ≥25.0)-with ten individuals per group. Those with H. pylori infection, atrophic gastritis, or intestinal metaplasia were excluded. Gastric microbiota from four antral biopsies per subject were analyzed using 16S rRNA sequencing and functional profiling by metagenomic prediction. RESULTS AND DISCUSSION: Alpha diversity (Gini-Simpson index) was significantly lower in the combined overweight/obese group than that in the normal group (P=0.049). Beta diversity analysis revealed clear group separation (Bray-Curtis, P=0.005; unweighted UniFrac, P=0.004). Significant species differences between the groups were observed; specifically, the abundances of Muribaculum gordoncarteri, Turicibacter bilis, and Duncaniella dubosii, were significantly reduced in the overweight/obese group. Functional predictions showed differential enrichment of pathways related to fatty acid, amino acid, vitamin, and carbohydrate metabolism across BMI categories. These findings suggest that alterations in the gastric microbiota may be linked to obesity and metabolic dysregulation.
Humans↗
Characteristics and assembly mechanisms of tobacco-associated bacteria in typical tobacco-planting regions across China.
INTRODUCTION: Plant-associated microbiota critically modulates host growth and environmental adaptation, yet assembly mechanisms, niche differentiation, and ecological strategies of bacterial communities inhabiting tobacco microhabitats remain poorly elucidated across geographical gradients. METHODS: Here, we systematically characterized bacterial microbiome assembly across five tobacco-associated niches (bulk soil, rhizosphere soil, root, stem, and leaf) from seven typical tobacco-planting regions using 16S rRNA amplicon sequencing, genome annotation, and niche breadth analysis. The independent and interactive effects of geographical location and host compartment on community structure, and further compared genomic traits, functional profiles, and life-history strategies between specialist and generalist bacterial populations were quantified. RESULTS: The results revealed a deterministic soil-plant continuum stratification of bacterial communities and diversity, with progressively simplified communities and decreasing alpha diversity from bulk soil to above-ground tissues, accompanied by progressive dominance of Proteobacteria. Geographical factors predominantly structured soil microbial communities via divergent edaphic properties, while host filtering acted as a universal dominant driver shaping endophytic microbiome assembly. Niche differentiation analysis demonstrated that niche-specialized bacterial ASVs overwhelmingly dominated all microhabitats and geographical sites, whereas generalist taxa only constituted auxiliary populations. Although specialist and generalist microbes exhibited highly conserved core genomic architectures and overall functional repertoires, they displayed distinct niche-specific functional divergence in metabolic pathways, stress resistance, and secondary metabolism across host compartments. Life-history strategy analysis further revealed that Y-strategist represented the core adaptive bacterial population, especially enriched in above-ground tobacco tissues. DISCUSSION: Our study establishes a hierarchical dual-filtering assembly model for tobacco microbiota, clarifies the ecological differentiation and functional adaptation of specialist and generalist bacteria, and provides fundamental insights into the assembly rules and adaptive mechanisms of crop-associated microbiomes for future microbial resource utilization and agricultural microbiome regulation.
biogeography↗
Mapping cell-type- and age-dependent neuronal vulnerability through genome-wide in vivo CRISPRi screens in the mouse brain.
Current brain atlases are largely descriptive, cataloging correlative molecular snapshots such as gene expression signatures yet offering limited functional insight. Here, we develop a scalable, cell-type-resolved in vivo CRISPR interference (CRISPRi) platform enabling systematic gene function profiling in the mouse brain. Through genome-wide screens across four neuronal populations at three time points spanning youth to aging, we identify neuronal essential genes missed in vitro and define a consensus set of 269 neuronal core essential genes. The data reveal cell-type-specific genetic vulnerabilities, including divergent dependencies validated for exosome component 9 (Exosc9) and osteopetrosis-associated transmembrane protein 1 (Ostm1) between excitatory and inhibitory neurons. We uncover aging-specific dependencies enriched in mitochondrial and translational pathways, aligning with transcriptional changes in the aging human brain. Finally, we establish the CRISPRinvivo data portal as a community resource for in vivo screening. Altogether, this work provides a broadly applicable platform for in vivo functional genomics and a framework for building comprehensive gene-function brain atlases.
brain aging↗
Data-driven approaches in green microbiology: strategies for plant growth-promoting bacteria.
Plant growth-promoting bacteria (PGPB) are gaining attention as scalable biological solutions to enhance crop productivity and resilience. However, accurately identifying and characterizing PGPB remains challenging, particularly under variable environmental conditions where microbial functions are context-dependent and shaped by complex plant-microbe interactions. Advances in high-throughput sequencing have shifted the field from culture-dependent approaches to genome-informed strategies, enabling large-scale taxonomic and functional profiling. Although trait-based databases support the prediction of plant-beneficial genes, they capture only a fraction of the underlying biological complexity and often require labor-intensive analyses. Machine learning (ML) and deep learning (DL) have emerged as powerful tools to integrate genomic, physiological, and ecological data, enabling the prioritization of candidate strains with plant growth-promoting potential. To evaluate advances in the field, we conducted a systematic review of studies integrating ML and DL with PGPB characterization, assessing algorithm selection, performance, and target plant systems. Across 248 observations, only 6.0% of studies directly addressed PGPB screening, whereas the majority (77.4%) focused on plant disease detection, revealing a substantial gap in the application of AI to beneficial microorganisms for plant growth. Convolutional neural networks (CNNs) were the most frequently applied algorithms, largely driven by image-based phenotyping tasks. Overall, the field is constrained by limited datasets, high computational demands, and challenges in modeling multispecies and host-associated interactions. We highlight the need for integrative and interpretable ML and DL frameworks that bridge genomic data and functional validation. Such approaches represent a promising path toward scalable, data-driven discovery and deployment of bioinoculants in sustainable agriculture.
Agriculture↗
Resistant starch types 2 and 4 induce distinct and reversible changes in the human gut microbiome.
Resistant starch (RS) can confer benefits for the gut microbiome and host cardiometabolic health. However, different types of resistant starch can differentially affect gut microbiome composition and functional capacity, especially given interindividual variability in responses, thus limiting the application of resistant starch in dietary strategies. We used shotgun metagenomics to perform a secondary analysis of samples collected during a previously reported randomized clinical trial to determine the effects of dietary supplementation with two types of resistant starch (RS2 and RS4) and a digestible starch (control) on the gut microbiome. Both resistant starch types induced distinct but transient alterations in the gut microbial community. RS2 enriched the keystone degrader, Ruminococcus bromii, and Blautia glucerasea, whereas RS4 favored Parabacteroides distasonis and known but uncharacterized microbial species such as a Lachnospiraceae bacterium. Moreover, we detected strain-level differences in the response of Bifidobacterium adolescentis to resistant starch. Microbial functional profiling revealed an enhanced capacity for complex carbohydrate utilization following resistant starch intake, including increased abundance of specific α-amylases, glycoside hydrolases, starch utilization systems, and other currently uncharacterized genes. Identifying the bacterial strains and genes that respond to different RS types will help to more accurately predict who will benefit from a given RS type. Our findings demonstrate that RS2 and RS4 differentially shape microbial ecology and metabolic capacity and provide a foundation for microbiome-informed personalization of resistant starch-based dietary interventions.IMPORTANCEDietary intake influences human health by modulating metabolism, partly by shaping the microbiota inhabiting the gut. Resistant starch (RS), a dietary fiber, is associated with metabolic improvements. While previous research has explored how RS alters the gut microbiome, RS comprises five types with differing physical and chemical characteristics, and the distinct impacts of each type on the microbiome and host health have not been fully characterized, particularly using high-resolution approaches such as shotgun metagenomics. In this secondary analysis of samples from a longitudinal crossover intervention study, we link dietary supplementation with RS2 and RS4 with distinct and transient changes in the composition and functional potential of the human gut microbiome. Specifically, we identify species that increase in abundance with each RS type, accompanied by increases in genes and pathways involved in complex carbohydrate utilization. The findings support the development of precision nutrition strategies utilizing RS supplementation to improve metabolic health.This study is registered with ClinicalTrials.gov as NCT05743790.
Humans↗
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↗
Clinical sequelae of gut microbiome development and disruption in hospitalized preterm infants.
Aberrant preterm infant gut microbiota assembly predisposes to early-life disorders and persistent health problems. Here, we characterize gut microbiome dynamics over the first 3 months of life in 236 preterm infants hospitalized in three neonatal intensive care units using shotgun metagenomics of 2,512 stools and metatranscriptomics of 1,381 stools. Strain tracking, taxonomic and functional profiling, and comprehensive clinical metadata identify Enterobacteriaceae, enterococci, and staphylococci as primarily exploiting available niches to populate the gut microbiome. Clostridioides difficile lineages persist between individuals in single centers, and Staphylococcus epidermidis lineages persist within and, unexpectedly, between centers. Collectively, antibiotic and non-antibiotic medications influence gut microbiome composition to greater extents than maternal or baseline variables. Finally, we identify a persistent low-diversity gut microbiome in neonates who develop necrotizing enterocolitis after day of life 40. Overall, we comprehensively describe gut microbiome dynamics in response to medical interventions in preterm, hospitalized neonates.
Humans↗
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 α-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↗