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<p>Microbial genome-wide association studies (GWAS) have uncovered numerous host genetic variants associated with gut microbiota. However, links between host genetics, the gut microbiome and specific cellular contexts remain unclear. Here we use a computational framework, scBPS (single-cell Bacteria Polygenic Score), to integrate existing microbial GWAS and single-cell RNA-sequencing profiles of 24 human organs, including the liver, pancreas, lung and intestine, to identify host tissues and cell types relevant to gut microbes. Analysing 207 microbial taxa and 254 host cell types, scBPS-inferred cellular enrichments confirmed known biology such as dominant communications between gut microbes and the digestive tissue module and liver epithelial cell compartment. scBPS also identified a robust association between <i>Collinsella</i> and the central-veinal hepatocyte subpopulation. We experimentally validated the causal effects of <i>Collinsella</i> on cholesterol metabolism in mice through single-nuclei RNA sequencing on liver tissue to identify relevant cell subpopulations. Mechanistically, oral gavage of <i>Collinsella</i> modulated cholesterol pathway gene expression in central-veinal hepatocytes. We further validated our approach using independent microbial GWAS data, alongside single-cell and bulk transcriptomic analyses, demonstrating its robustness and reproducibility. Together, scBPS enables a systematic mapping of the host–microbe crosstalk by linking cell populations to their interacting gut microbes.</p>

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Integrating microbial GWAS and single-cell transcriptomics reveals associations between host cell populations and the gut microbiome

  • 期刊论文

  • 发表日期：

    2025年4月7日

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  • Jingjing Li,
  • Yunlong Ma,
  • Yue Cao,
  • Gongwei Zheng,
  • Qing Ren,
  • Cheng Chen,
  • Qunyan Zhu,
  • Yijun Zhou,
  • Yu Lu,
  • Yaru Zhang,
  • Chunyu Deng,
  • Wei-Hua Chen,
  • Jianzhong Su

摘要

Microbial genome-wide association studies (GWAS) have uncovered numerous host genetic variants associated with gut microbiota. However, links between host genetics, the gut microbiome and specific cellular contexts remain unclear. Here we use a computational framework, scBPS (single-cell Bacteria Polygenic Score), to integrate existing microbial GWAS and single-cell RNA-sequencing profiles of 24 human organs, including the liver, pancreas, lung and intestine, to identify host tissues and cell types relevant to gut microbes. Analysing 207 microbial taxa and 254 host cell types, scBPS-inferred cellular enrichments confirmed known biology such as dominant communications between gut microbes and the digestive tissue module and liver epithelial cell compartment. scBPS also identified a robust association between Collinsella and the central-veinal hepatocyte subpopulation. We experimentally validated the causal effects of Collinsella on cholesterol metabolism in mice through single-nuclei RNA sequencing on liver tissue to identify relevant cell subpopulations. Mechanistically, oral gavage of Collinsella modulated cholesterol pathway gene expression in central-veinal hepatocytes. We further validated our approach using independent microbial GWAS data, alongside single-cell and bulk transcriptomic analyses, demonstrating its robustness and reproducibility. Together, scBPS enables a systematic mapping of the host–microbe crosstalk by linking cell populations to their interacting gut microbes.