Uncovering effects of antibiotics on the host and microbiota using transkingdom gene networks. Issue 11 (22nd January 2015)

• Record Type: Journal Article
• Authors: Morgun, Andrey; Dzutsev, Amiran; Dong, Xiaoxi; Greer, Renee L; Sexton, D Joseph; Ravel, Jacques; Schuster, Martin; Hsiao, William; Matzinger, Polly; Shulzhenko, Natalia
• Is Part Of: Gut. Volume 64:Issue 11(2015)
• Page Start: 1732
• Page End: 1743
• Publication Date: 2015-01-22
• Subjects: ANTIBIOTICS -- GENE EXPRESSION -- MUCOSAL IMMUNITY; Gastroenterology -- Periodicals; 616.33
• DOI: 10.1136/gutjnl-2014-308820
• Languages: English
• ISSNs: 0017-5749

Abstract

Abstract : Objective: Despite widespread use of antibiotics for the treatment of life-threatening infections and for research on the role of commensal microbiota, our understanding of their effects on the host is still very limited. Design: Using a popular mouse model of microbiota depletion by a cocktail of antibiotics, we analysed the effects of antibiotics by combining intestinal transcriptome together with metagenomic analysis of the gut microbiota. In order to identify specific microbes and microbial genes that influence the host phenotype in antibiotic-treated mice, we developed and applied analysis of the transkingdom network. Results: We found that most antibiotic-induced alterations in the gut can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues and the effects of remaining antibiotic-resistant microbes. Normal microbiota depletion mostly led to downregulation of different aspects of immunity. The two other factors (antibiotic direct effects on host tissues and antibiotic-resistant microbes) primarily inhibited mitochondrial gene expression and amounts of active mitochondria, increasing epithelial cell death. By reconstructing and analysing the transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria, a finding further validated using in vitro experiments. Conclusions: In addition to revealing mechanisms of antibiotic-induced alterations, this study also describes a new bioinformatics approach that predicts microbial components that regulate host functions and establishes a comprehensive resource on what, why and how antibiotics affect the gut in a widely used mouse model of microbiota depletion by antibiotics.