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Idiopathic inflammatory myopathies (IIMs) are systemic autoimmune disorders with unknown etiology. Despite the established link between gut microbes and immunity, the roles of gut bacteriome, mycobiome, and virome in IIM are unexplored. We performed shotgun metagenomic sequencing on fecal samples from 34 IIM patients and 37 healthy controls to profile gut microbiota. Taxonomic, functional, network, and machine-learning analyses revealed microbial dysbiosis and its potential for discriminating IIM. All three microbial kingdoms were significantly altered in IIM. Several inflammation-associated bacterial taxa (e.g., Rothia mucilaginosa , Streptococcus parasanguinis , Trueperella pyogenes ) and opportunistic fungi (e.g., Aspergillus spp.) were enriched in IIM, while SCFA-producing bacteria and fungi were depleted. Virome analysis revealed substantial shifts, with higher abundance of Siphoviridae in IIM. Altered viral functional gene profiles suggesting enhanced phage-mediated genome integration, recombination, and bacterial stress adaptation. Multi-kingdom network analysis showed extensive rewiring in IIM, characterized by increased network connectivity and a shift toward fungi-centered ecological hubs, contrasting with bacteria/virus-dominated networks in controls. In machine-learning models, the virome demonstrated the strongest discriminatory power, and viral signatures dominated the combined multi-kingdom classifier (AUC = 0.997). This first comprehensive multi-kingdom gut microbiota analysis in IIM provides a foundation for developing diagnostic and therapeutic strategies.

Background Systemic lupus erythematosus (SLE) is a complex autoimmune disorder shaped by host genetics and environmental exposures, including the gut microbiota. While bacterial dysbiosis in SLE is well characterized, the role of the gut mycobiome and its cross-kingdom interactions remains largely unexplored. Methods Using fecal metagenomic sequencing from 117 SLE patients and 115 healthy controls (HCs), we established a non-redundant fungal genome catalog and revealed significant alterations in fungal composition, function, and cross-kingdom ecology. Results Fungal diversity was increased in SLE, with enrichment of potentially pathogenic taxa such as Candida , Malassezia , and Trichophyton , and depletion of commensal genera such as Pichia . Functional analysis showed expanded biosynthetic and redox capacities in SLE-associated fungi, including enrichment of RiPP- and terpene-related biosynthetic gene clusters and oxidative stress–related Pfam domains. Several predicted metabolites—such as kynurenine, phenylacetic acid, secondary bile acids, and acylcarnitines—were linked to immune activation and inflammation, suggesting that fungal metabolism may contribute to immune dysregulation. Network analysis revealed sparser and less centralized fungal–bacterial interactions in SLE, indicating disrupted ecological stability and the emergence of fungal taxa as key structural drivers. Integrating fungal and bacterial profiles markedly improved diagnostic performance (AUC = 0.934), underscoring the complementary predictive value of the gut mycobiome. In contrast, post-treatment samples showed reduced fungal richness but no major compositional shifts. Conclusions This study provides a comprehensive, multi-dimensional view of the gut mycobiome in SLE, demonstrating its taxonomic, functional, and ecological remodeling. Our findings highlight the potential contribution of fungal metabolic and redox activities to SLE pathogenesis and support the inclusion of fungi in multi-kingdom microbiome frameworks for disease diagnosis and therapeutic development.

Background The gut microbiota is a key modulator of immune checkpoint inhibitor (ICI) efficacy, yet the contribution of the gut virome remains poorly defined, particularly in advanced non–small cell lung cancer (NSCLC). Here, we characterized the gut virome and explored its potential role in shaping response to PD-1 blockade. Methods We performed metagenomic virome profiling of fecal samples from 338 advanced NSCLC patients treated with PD-1 inhibitors and evaluated model generalizability in an independent external cohort ( n  = 30). Viral diversity, taxonomic composition, and functional potential were analyzed. Virus–bacteria co-occurrence networks were constructed, and random forest classifiers were developed to predict treatment response. Results Viral Shannon diversity decreased progressively with poorer clinical response, and β-diversity analyses revealed distinct virome community structures between responders ( R ) and non-responders ( NR ). Differential abundance analysis identified 194 NR -enriched vOTUs, predominantly assigned to Peduoviridae and Inoviridae , and 594 R -enriched vOTUs, mainly from Herelleviridae and Microviridae. Host prediction indicated that NR -enriched vOTUs frequently targeted bacterial genera such as Clostridium_M , Bacteroides , and Escherichia , whereas R -enriched vOTUs targeted beneficial genera such as Faecalibacterium and Roseburia . Network analyses further revealed response-specific virus–bacteria interaction modules. Functional profiling showed that NR -enriched vOTUs were associated with metabolic functions, including K01689 ( eno ; enolase). A virus-only random forest model outperformed a bacterium-only model in predicting response (area under the curve [AUC] = 0.768 vs. 0.664) and maintained superior performance in the external cohort (AUC = 0.742). In addition, Akkermansia muciniphi la positivity was associated with a higher-diversity, responder-favorable virome configuration. Conclusions The gut virome undergoes marked remodeling during anti–PD-1 therapy in advanced NSCLC and displays distinct taxonomic, ecological, and functional signatures associated with clinical outcome. These findings support the gut virome as a strong predictor of ICI response and highlight its potential as both a biomarker and a therapeutic target.

Background Emerging evidence suggests that the gut microbiome plays a key role in metabolic diseases such as non-alcoholic fatty liver disease, yet the contribution of the gut mycobiome remains largely overlooked. Methods We performed a comprehensive analysis of publicly available fecal metagenomic sequencing data and matched serum metabolomic profiles from 90 non-alcoholic fatty liver disease patients and 90 healthy controls. A curated fungal genome database was constructed for taxonomic profiling. We integrated fungal, bacterial, and metabolomic data to assess taxon-specific associations, cross-kingdom interactions, and predictive potential. Results Although overall fungal diversity showed no significant differences between groups, four fungal species— Pseudopithomyces sp. c174, Mucor sp. c176, Aspergillus sp. c25, and Ascochyta c213—were significantly enriched in non-alcoholic fatty liver disease patients. The gut mycobiome explained 38.2% of the variance in serum metabolomic profiles, with several species displaying strong correlations with non-alcoholic fatty liver disease relevant metabolites. For instance, Pseudopithomyces sp. c174 was positively associated with protective metabolites such as glycoursodeoxycholic acid and alpha-linolenic acid, while Aureobasidium c170 and Basipetospora c193 were linked to phenylacetic acid, a metabolite implicated in hepatic lipid accumulation. Network analysis revealed altered fungal–bacterial co-abundance patterns in non-alcoholic fatty liver disease, with fungal taxa such as Alternaria alternata c42 and Malassezia c303 emerging as key hubs. A random forest classifier integrating 42 bacterial and fungal features achieved an AUC of 0.772 for distinguishing non-alcoholic fatty liver disease from controls, highlighting the predictive value of the mycobiome. Conclusions Our findings reveal that gut fungal communities are functionally and ecologically altered in non-alcoholic fatty liver disease and contribute to shaping the host metabolic environment. These results underscore the need to incorporate the gut mycobiome into future microbiome-based strategies for non-alcoholic fatty liver disease diagnosis and treatment.

Background Nonalcoholic fatty liver disease (NAFLD) is a prevalent metabolic disorder with complex gut microbiome involvement. While bacterial dysbiosis in NAFLD has been widely studied, the role of the gut virome remains largely unexplored. Methods We profiled gut viral communities from 90 NAFLD patients and 90 non-NAFLD controls using whole-metagenome shotgun sequencing. Viral taxonomic composition, host associations, and functional gene repertoires were analyzed. Serum metabolomic data were integrated to assess virus–metabolite interactions, and random forest models were constructed to evaluate the diagnostic potential of viral signatures. Results Overall viral diversity showed no significant differences between NAFLD and controls, but subtle compositional shifts were detected at the vOTU level, with 105 viruses enriched in NAFLD and 185 in non-NAFLD individuals. NAFLD-enriched phages primarily targeted Bacteroides, whereas non-NAFLD-enriched phages were associated with beneficial genera such as Faecalibacterium, Oscillibacter, and Prevotella. Functional annotation revealed a reorganization of viral gene repertoires: genes involved in DNA recombination and horizontal transfer (e.g. int, recD) were depleted, while those related to host interaction and stress response (e.g. xerD, dnaK, hipB) were enriched in NAFLD, indicating enhanced viral persistence and host communication. Serum metabolomic profiling identified 8 differential metabolites, and correlation analysis linked specific vOTUs with altered metabolic pathways. A random forest model based on viral features achieved an AUC of 0.758, outperforming the bacterial model, while integration of viral and bacterial features further improved prediction (AUC = 0.837). Conclusion The gut virome in NAFLD undergoes compositional and functional remodeling characterized by a shift toward host-adaptive, metabolically interactive viral communities. These viral alterations are closely associated with host metabolic changes and demonstrate strong diagnostic potential. Our findings highlight the virome as an overlooked yet critical component of the gut ecosystem in NAFLD pathogenesis and as a promising source of noninvasive biomarkers for disease prediction and monitoring.

This study highlights the gut virome as a previously underappreciated component of acute pancreatitis (AP)-associated dysbiosis and suggests that viral communities may influence disease severity and metabolic disturbances beyond bacterial effects alone. By demonstrating the diagnostic potential of virome-based signatures, our findings support expanding microbiome research in AP to include viral components, with implications for improved disease stratification and future therapeutic development.

Chronic functional constipation (CFC) is a common gastrointestinal disorder increasingly linked to gut microbiome dysbiosis. However, multi-kingdom metagenomic characterization of bacterial, fungal, and viral communities in CFC remains limited. Fecal samples from 53 CFC patients and 48 healthy controls were analyzed using whole-metagenome shotgun sequencing. Microbial composition, function, cross-kingdom interactions, and diagnostic potential were evaluated using diversity analyses, KEGG annotation, network analysis, and random forest modeling. Compared with healthy controls, CFC patients exhibited marked alterations across multiple microbial kingdoms. The gut bacteriome showed significant community-structure shifts despite comparable α-diversity, characterized by depletion of health-associated Firmicutes (e.g., and ) and enrichment of Proteobacteria (e.g., ). The mycobiome displayed selective changes in diversity and composition, with several potentially pathogenic fungal taxa enriched in CFC (e.g., sp. ). In the virome, community composition differed significantly between groups, with higher viral richness in CFC and widespread depletion of diverse bacteriophages in CFC patients. Functional profiling suggested feature-level functional differences without a clear global shift, including reduced carbohydrate transport and utilization pathways and relatively higher abundance of stress-response and metabolic adaptation modules in CFC. Cross-kingdom network analysis demonstrated substantially denser microbial interactions in CFC, dominated by viral associations, with and _SGB15346 acting as central hubs. Machine-learning models showed strong discriminatory power for CFC classification based on bacterial and viral features, whereas fungal features contributed less. CFC is associated with coordinated multi-kingdom gut microbiome dysbiosis involving bacteria, fungi, and viruses, accompanied by functional shifts and intensified cross-kingdom interactions. Bacterial and viral signatures show strong potential as microbiome-based biomarkers for CFC, highlighting the importance of integrating multi-kingdom analyses to better understand disease-associated gut ecosystem alterations.

Diabetes mellitus (DM), a globally prevalent chronic metabolic disorder characterized by persistent hyperglycemia, has been increasingly linked to dysbiosis of the oral microbiome. However, the relationship between the virome, a crucial component of the oral microbiome, and DM remains poorly understood. To explore the characteristics of the oral virome in DM patients, we analyze the oral viral communities of 45 DM patients and 40 healthy controls (HC) using a publicly available metagenomic dataset. Our analysis revealed no significant differences in a-diversity between DM patients and HC. However, was enriched in DM patients, whereas was more prevalent in HC. A total of 1,131 virus signal was identified, primarily belonging to the and taxa. Notably, HC-enriched vOTUs exhibited broader host tropism, predominantly infecting , , and , whereas DM-enriched vOTUs showed narrower specificity for and . Cross-kingdom network analysis suggested that certain viruses (HMP_1157.k81_309051) may have potential links to the development of DM, and the bacteria genus F0040 might play a significant role in maintaining oral health. Additionally, the random forest model based on viral markers effectively distinguished between HC and DM patients (AUC =90.8%), significantly outperforming the bacterial model. This indicates that these unique viral markers could serve as potential targets for DM intervention. Taken together, our findings reveal distinct alterations in the oral virome of DM patients and highlight its promise as a novel diagnostic and therapeutic target in metabolic disease research.

Hypertension (HTN) represents a global health burden affecting billions of individuals worldwide; however, the relationship between HTN and gut microbial ecosystems remains inadequately characterized. This study presents the first cross-cohort microbiome analysis revealing significant alterations in the gut bacteriome of HTN patients, with limited changes observed in the mycobiome. These findings highlight the critical role of the gut bacteriome in the pathogenesis of HTN and provide new microbial biomarkers for early diagnosis. Furthermore, the identification of bacterial species establishes a foundation for future intervention approaches, enhancing the applicability of microbiome research in cardiovascular health and opening new avenues for related studies in this field.

Precise outcome prediction for fecal microbiota transplantation (FMT) in irritable bowel syndrome (IBS) remains a clinical challenge. The roles of the gut virome and its interplay with bacteria in FMT efficacy are particularly underexplored. This secondary analysis aimed to conduct an exploratory, hypothesis-generating investigation into these cross-kingdom dynamics. We conducted a secondary, integrative analysis of a published cohort, performing longitudinal, cross-kingdom metagenomic profiling on 83 samples from 22 IBS patients and healthy donors. We integrative approach combined microbial diversity, species-specific biomarker identification, bacterial-viral associated networks, and exploratory random forest modeling to identify microbial features associated with FMT outcomes. IBS patients showed higher bacterial and viral alpha diversity than donors. Cross-kingdom profiling identified 223 bacterial and 724 viral biomarkers. Donor-enriched biomarkers were predominantly health-associated Bacteroidetes (e.g., B. ovatus, B. faecis), whereas pre-FMT-enriched biomarkers were largely Firmicutes (e.g., B. obeum) with potential pathobiont roles. The Effect and No effect groups displayed different microbial trajectories. Although both groups shifted toward a donor-like composition initially, only responders maintained a stable donor-like ecology throughout the 12-month follow-up, supported by more resilient bacterial-viral association networks. Exploratory random forest modeling highlighted microbial features, such as R. pickettii, with high relative importance for outcome discrimination. However, permutation testing (p = 0.548-0.616) confirmed that model performance on this small cohort did not exceed chance level, underscoring the risk of overfitting and the exploratory nature of these computational findings. This integrative re-analysis provides preliminary evidence that cross-kingdom gut microbiome profiles are strongly associated with FMT outcomes in IBS. Successful outcomes appear linked to sustained donor-like remodeling and stable bacterial-viral networks. Our findings are primarily hypothesis-generating and offer a framework of candidate biomarkers for future validation in larger cohorts. This work underscores the necessity of external validation to develop robust, microbiome-based tools for personalized FMT therapy.