Affiliation:
1. Department of Gastroenterology Qilu Hospital of Shandong University Jinan 250012 China
2. Shandong Provincial Clinical Research Center for digestive disease Jinan Shandong 250012 China
3. Laboratory of Translational Gastroenterology Qilu Hospital of Shandong University Jinan Shandong 250012 China
4. Robot engineering laboratory for precise diagnosis and therapy of GI tumor Qilu Hospital of Shandong University Jinan Shandong 250012 China
Abstract
AbstractA compelling correlation method linking microbial communities and host gene expression in tissues is currently absent. A novel pipeline is proposed, dubbed Transcriptome Analysis of Host‐Microbiome Crosstalk (TAHMC), designed to concurrently restore both host gene expression and microbial quantification from bulk RNA‐seq data. Employing this approach, it discerned associations between the tissue microbiome and host immunity in the context of Crohn's disease (CD). Further, machine learning is utilized to separately construct networks of associations among host mRNA, long non‐coding RNA, and tissue microbes. Unique host genes and tissue microbes are extracted from these networks for potential utility in CD diagnosis. Experimental validation of the predicted host gene regulation by microbes from the association network is achieved through the co‐culturing of Faecalibacterium prausnitzii with Caco‐2 cells. Collectively, the TAHMC pipeline accurately recovers both host gene expression and microbial quantification from CD RNA‐seq data, thereby illuminating potential causal links between shifts in microbial composition as well as diversity within CD mucosal tissues and aberrant host gene expression.
Funder
National Natural Science Foundation of China