Systematic Mining of gut microbiota biomarkers for IBD

Abstract Background Inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn’s disease (CD), represents a chronic inflammatory condition with an incompletely understood etiology. Emerging evidence suggests that alterations in gut microbiota composition play a pivotal role in disease development. Here, we leveraged gut fecal metagenomic data (3044 samples: 2248 IBD and 796 healthy) from publicly available sources to explore microbiome biomarkers related to IBD to provide new ideas for clinical treatment. Results Our analyses revealed marked disparities in microbial species abundance and composition between IBD and healthy samples in both male and female subjects from the United States, whereas such distinctions were absent in subjects from Spain. Hierarchical and systematic investigations uncovered microbial phyla, such as Verrucomicrobia and Firmicutes, associated with IBD in US cohorts. Furthermore, we identified 127 highly correlated pathways with these differential microbes, covering functions such as peptidoglycan biosynthesis III, dTDP-L-rhamnose biosynthesis I, starch degradation, and glucose-1-phosphate degradation. Gut microbial metabolites were predicted based on metagenomic data using the MelonnPan workflow and 16 metabolites with significant differences were identified that collectively contribute to energy metabolism, digestion, skin integrity and general bodily function. Conclusions This study identified differences in microbial species and metabolic pathways related to Inflammatory Bowel Disease (IBD) through hierarchical and systematic analysis, which can aid in the clinical diagnosis of IBD. Pathways such as Peptidoglycan Biosynthesis III and dTDP-L-Rhamnose Biosynthesis I are associated with the generation of bacterial cell walls, and disruptions in these pathways affect bacterial activity, leading to an imbalance in the host’s gut microbiota. Based on the hypotheses regarding the pathogenesis of IBD derived from the above mining results, it provides a theoretical basis for selecting precise treatment options.