P928 Identification of mucosal microbiome-host gene interactions in ulcerative colitis patients
Namjoo, K.(1)*;Beom Jae Prof. Dr., L.(2);Jeong-An , G.(3);Seung Han, K.(1);Moon Kyung , J.(1);Jong-Jae , P.(1);
(1)Korea University Medical Center- Seoul- Korea- Republic Of., Department of Gastroenterology-, Seoul, Korea- Republic Of;(2)Korea University Medical Center, Department of Gastroenterology, Seoul, Korea- Republic Of;(3)Korea University Guro Hospital- Seoul- Republic of Korea, Medical Science Research Center, Seoul, Korea- Republic Of;
Background
With the development of NGS analysis, many studies have been performed on the role of gut microbiota in the pathogenesis of inflammatory bowel disease and the possibility of gut bacteria as a diagnosis and treatment modality for IBD. However, the role of gut microbiota in clinical applications such as markers for diagnosis, prognosis prediction and the therapeutic agents is still unclear, and further studies on host-microbe interactions are still needed. In this study, we tried to detect mucosal bacterial species which can discriminate between ulcerative colitis and normal control and the correlations between the microbiome and gene expression through integrated analysis of metagenomic sequencing and RNA-sequencing in the colonic mucosa of UC patients and normal controls.
Methods
Colonic tissues obtained from UC patients (n = 7) and normal control (n = 13) were subjected to 16S rRNA sequencing of the microbiome and next-generation sequencing (NGS) RNA-seq. The differentially expressed genes (DEGs) and DEGs-based enrichment terms were obtained. Gene set enrichment analysis (GSEA) and PathfindR were also used to reveal significant differences of meaningful gene sets. The datasets were analyzed individually and integrated including sociomedical factors for combined analysis using bioinformatics approaches. Correlation analyses were performed between microbiome and gene expression and network analysis were presented.
Results
From DEG results, 28 and 18 genes were higher expressed in the UC and normal groups, respectively. GSEA provided total 1,857 gene sets enriched in the UC group. We identified that patients with UC show decreased species such as Bacteroides coprocola, Bacteroides phlebeius, Parabacteroides merdae and increased abundance of other species, such as Eubacterium._eligens, Clostridium_clostridioforme, Faecalibacterium_prausnitzii. An integrative analysis identified immunomodulatory genes including HLA-G, PSMA4 for which gene expression is negatively correlated with Bacteroides species.
Conclusion
In addition to identifying mucosal microbiome and host-genes expression patterns in the UC patients, we showed the potential role of host-microbe interactions in the development of UC. These findings provided the integrated analysis of microbe- host gene can be served as a biomarker for diagnosis and treatment target in patients with UC.