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Multi-Omics Comparative Analysis Reveals Host Signaling Pathways Affected by the Gut Microbiota

Wednesday, September 13, 2017 — Poster Session I

12:00 p.m. – 1:30 p.m.
FAES Terrace


  • NP Manes
  • N Shulzhenko
  • AG Nuccio
  • S Azeem
  • A Morgun
  • A Nita-Lazar


A systems-wide understanding of the effects that the microbiota has on the host is needed, but proteomics has never before been used to compare the GI tract of conventional and germ-free mice. In this investigation, we quantitatively compared the terminal ileum of conventional and germ-free mice at both the transcriptomic and proteomic levels (female and male, and BALB/c and C57BL/10A strains; five mice per experimental condition). In addition, OMiCC was used to perform a meta-analysis using eight previously published transcriptomics datasets from analyses of conventional versus germ-free mouse whole-tissue intestinal samples. The resulting data were used to perform Ingenuity pathway analyses. We discovered significant transcriptome-proteome discordancy in the adaptation of the host to the microbiota, and we also discovered mouse strain-specific effects. The female and male mice responded similarly to the microbiota, but C57BL/10A mice responded much more strongly than BALB/c mice at both the transcriptome and proteome levels. The microbiota primarily affected two classes of pathways: immunological pathways were upregulated and metabolic pathways were downregulated in response to the microbiome. For example, the microbiota caused the interferon signaling and antigen presentation pathways to be concordantly upregulated, and the serotonin degradation and glutathione-mediated detoxification pathways to be concordantly downregulated in transcriptome and proteome. Discordantly regulated pathways were not principally involved in the immune system. Instead, they were principally involved in metabolism and protein translation and folding. This research was supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases, NIH.

Category: Systems Biology