Gene co-expression network analysis of the human gut commensal bacterium Faecalibacterium prausnitzii based on WGCNA in R-Shiny

Abstract

AbstractFaecalibacterium prausnitzii is abundant in the healthy human intestinal microbiota, and the absence or scarcity of this bacterium has been linked with inflammatory diseases and metabolic disorders. F. prausnitzii thus shows promise as a next-generation probiotic for use in restoring the balance of the gut microbial flora and, due to its strong anti-inflammatory properties, for the treatment of certain pathological conditions. However, very little information is available about gene function and regulation in this species. Here, we utilized a systems biology approach - weighted gene co-expression network analysis (WGCNA) – to analyze gene expression in three publicly available RNAseq datasets from F. prausnitzii strain A2-165, all obtained in different laboratory conditions. The co-expression network was then subdivided into 24 co-expression gene modules. A subsequent enrichment analysis revealed that these modules are associated with different kinds of biological processes, such as arginine, histidine, cobalamin, or fatty acid metabolism as well as bacteriophage function, molecular chaperones, stress response, or SOS response. Some genes appeared to be associated with mechanisms of protection against oxidative stress and could be essential for F. prausnitzii’s adaptation and survival under anaerobic laboratory conditions. Hub and bottleneck genes were identified by analyses of intramodular connectivity and betweenness, respectively; this highlighted the high connectivity of genes located on mobile genetic elements, which could promote the genetic evolution of F. prausnitzii within its ecological niche. This study provides the first exploration of the complex regulatory networks in F. prausnitzii, and all of the “omics” data are available online for exploration through a graphical interface at https://feaprau.omics.ovh/.