Unveiling the Links Between Microbial Alteration and Host Gene Disarray in Crohn's Disease Via TAHMC

Huijun Chang,Yongshuai Liu,Yue Wang,Lixiang Li,Yijun Mu,Mengqi Zheng, Junfei Liu,Jinghui Zhang, Runze Bai,Yanqing Li,Xiuli Zuo

Advanced Biology（2024）

Shandong Univ

Cited 0|Views19

Abstract

A 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.

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Key words

Crohn's disease,host-microbiome crosstalk,immune infiltration subtypes,machine learning,tissue-resident microbes

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