Abstract
The gut microbiome affects the health status of the host through complex interactions with the host’s intestinal wall. These host-microbiome interactions may spatially vary along the physical and chemical environment of the intestine, but these changes remain unknown. This study investigated these intricate relationships through a gene co-expression network analysis based on dual transcriptome profiling of different intestinal sites—cecum, transverse colon, and rectum—of the primate common marmoset. We proposed a gene module extraction algorithm based on the graph theory to find tightly interacting gene modules of the host and the microbiome from a vast co-expression network. The 27 gene modules identified by this method, which include both host and microbiome genes, not only produced results consistent with previous studies regarding the host-microbiome relationships, but also provided new insights into microbiome genes acting as potential mediators in host-microbiome interplays. Specifically, we discovered associations between the host gene FBP1, a cancer marker, and polysaccharide degradation-related genes (pfkA and fucI) coded by Bacteroides vulgatus, as well as relationships between host B cell-specific genes (CD19, CD22, CD79B, and PTPN6) and a tryptophan synthesis gene (trpB) coded by Parabacteroides distasonis. Furthermore, our proposed module extraction algorithm surpassed existing approaches by successfully defining more functionally related gene modules, providing insights for understanding the complex relationship between the host and the microbiome.
| Original language | English |
|---|---|
| Journal | mSystems |
| Volume | 9 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2024 May |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- common marmoset
- gut microbiome
- host-microbiome interaction
- metatranscriptome
- network analysis
- non-human primate
- transcriptome
ASJC Scopus subject areas
- Microbiology
- Ecology, Evolution, Behavior and Systematics
- Physiology
- Biochemistry
- Modelling and Simulation
- Molecular Biology
- Genetics
- Computer Science Applications
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