Gut microbiota rewires host mRNA m6A epitranscriptomic landscape via bile acid metabolism
收藏NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP408045
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Gut microbiota and their metabolites influence host gene expression and physiological status through diverse mechanisms. Here we investigate how gut microbiota and their metabolites impact host's mRNA m6A epitranscriptome in various antibiotic-induced microbiota dysbiosis models. With multi-omics analysis, we find that the imbalance of gut microbiota can rewire host mRNA m6A epitranscriptomic profiles in brain, liver and intestine. We further explore the underlying mechanisms regulating host mRNA m6A methylome by depleting the microbiota with ampicillin. Metabolomic profiling shows that cholic acids are the main down-regulated metabolites with Firmicutes as the most significantly reduced genus in ampicillin-treated mice comparing to untreated mice. Fecal microbiota transplantations in germ-free mice and metabolites supplementations in cells verify that cholic acids are associated with host mRNA m6A epitranscriptomic rewiring. Collectively, this study employs an integrative multi-omics analysis to demonstrate the impact of gut microbiota dysbiosis on host mRNA m6A epitranscriptomic landscape via cholic acid metabolism. Overall design: To investigate the influence of gut microbiota on host mRNA m6A epitranscriptome and explore the underlying mechanisms following our previous work, we constructed various gut microbiota dysbiosis mouse models in this study. We treated SPF mice with single antibiotic (ampicillin, gentamicin, metronidazole, neomycin and vancomycin, respectively) via drinking water for 40 days. SPF mice were also treated with an antibiotic cocktail (a mix of the above five antibiotics), and mice treated with distilled water were included in parallel for comparisons. After the model constructions, we collected tissue samples and fecal samples for multi-omics profiling (microbiome, metabolome, m6A epitranscriptome, and proteome) followed by comprehensive data analysis.
创建时间:
2024-07-23



