Background Gut dysbacteriosis has been reported as one of the etiologies for irritable bowel syndrome (IBS). However, the association between gut microbiota and IBS is still inconclusive. Method A paired-sample study was designed by retrieving original multicenter 16 s-rRNA data of IBS patients and healthy controls from the GMrepo database. The propensity score matching (PSM) algorithm was applied to reduce confounding bias. The differential analysis of microbiota composition was performed at different taxonomic levels. The co-occurrence network was established. Subgroup analysis was performed to identify specific microbial compositions in different IBS subtypes. Results A total of 1522 amplicon samples were initially enrolled. After PSM, 708 individuals (354 IBS and 354 healthy controls) were eligible for further analysis. A total of 1,160 genera were identified. We identified significantly changed taxa in IBS groups (IBS-enriched: the families Enterobacteriaceae, Moraxellaceae and Sphingobacteriaceae; the genera Streptococcus, Bacillus, Enterocloster, Sphingobacterium, Holdemania and Acinetobacter. IBS-depleted: the phyla Firmicutes, Euryarchaeota, Cyanobacteria, Acidobacteria and Lentisphaerae; the families Bifidobacteriaceae, Ruminococcaceae, Methanobacteriaceae and the other 25 families; the genera Faecalibacterium, Bifidobacterium and other 68 genera). The co-occurrence network identified three hub genera and six hub species (including Faecalibacterium prausnitzii) that may be involved in IBS pathophysiology. Strong positive interactions were identified among the Bifidobacterium longum, Bifidobacterium breve and Bifidobacterium adolescentis in the Bifidobacterium community. Conclusion This study provides quantitative analysis and visualization of the interaction between the gut microbiota and IBS. The identification of key species should be further validated to evaluate their causal relationships with the pathogenesis of IBS.

Growing evidence has shown that altered gut microbiota is associated with the pathogenesis of COVID‐19, but their causal effects are still unclear. We conducted a bidirectional Mendelian randomization (MR) study to assess the causal effects of gut microbiota on COVID‐19 susceptibility or severity, and vice versa. The microbiome genome‐wide association studies (GWAS) data of 18 340 individuals and GWAS statistics from the COVID‐19 host genetics initiative (38 984 European patients and 1 644 784 controls) were used as exposure and outcomes. The inverse variance weighted (IVW) was used as the primary MR analysis. Sensitivity analyses were performed to validate the robustness, pleiotropy, and heterogeneity of results. In the forward MR, we identified several microbial genera with causal effects on COVID‐19 susceptibility (p < 0.05 and FDR < 0.1): Alloprevotella (odds ratio [OR]: 1.088, 95% confidence interval [CI]: 1.021–1.160), Coprococcus (OR: 1.159, 95% CI: 1.030–1.304), Parasutterella (OR: 0.902, 95% CI: 0.836–0.973), and Ruminococcaceae UCG014 (OR: 0.878, 95% CI: 0.777–0.992). The Reverse MR identified that exposure to COVID‐19 had causal effects on the depletion of the families Lactobacillaceae (Beta [SE]: −0.220 [0.101]) and Lachnospiraceae (−0.129 [0.062]), the genera Flavonifractor (−0.180 [0.081]) and Lachnoclostridium [−0.181 [0.063]). Our findings supported the causal effect of gut microbiota on the pathogenesis of COVID‐19, and infection of COVID‐19 might further causally induce gut microbiota dysbiosis.

Background Gut dysbacteriosis has been reported as one of the etiologies for irritable bowel syndrome (IBS). However, the association between gut microbiota and IBS is still inconclusive. The study aims to provide new evidence of the interaction between the gut Microbiota and IBS. Method A paired-sample study was designed by retrieving original multicenter 16s-rRNA data of IBS patients and healthy controls from the GMrepo database. The propensity score matching (PSM) algorithm was applied to reduce confounding bias. The differential analysis of microbiota composition was performed at different taxonomic levels. The co-occurrence network was established. Subgroup analysis was performed to identify specific microbial compositions in different IBS subtypes. Results A total of 1522 amplicon samples were initially enrolled. After PSM, 708 samples (354 IBS and 354 healthy individuals) were eligible for further analysis. A total of 1,160 genera were identified. We identified significantly changed taxa in IBS groups (IBS-enriched: the families Enterobacteriaceae, Moraxellaceae, and Sphingobacteriaceae; the genera Streptococcus, Bacillus, Enterocloster, Sphingobacterium, Holdemania, and Acinetobacter. IBS-depleted: the phyla Firmicutes, Euryarchaeota, Cyanobacteria, Acidobacteria, and Lentisphaerae; the families Bifidobacteriaceae, Ruminococcaceae, Methanobacteriaceae, and the other 25 families; the genera Faecalibacterium, Bifidobacterium, and other 68 genera). In subgroup analysis, we profiled microbial compositions in IBS with predominant diarrhea and constipation. We further identified the genera Bilophila and Enterocloster that may be involved in linking IBS with psychiatric disorders. The co-occurrence network identified three hub genera and six hub species (including Faecalibacterium prausnitzii) that may be important in IBS pathophysiology. Strong positive interactions were identified among the Bifidobacterium longum, Bifidobacterium breve, and Bifidobacterium adolescentis in the Bifidobacterium community. Conclusion This study provides updated evidence in identifying specific microbes that may involve in IBS pathogenesis. Future modalities may be further validated by targeting these microorganisms.