Evidence map›Paper›PMID 40195537›Full record

ArticleNature microbiology2025

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

Jingjing Li, Yunlong Ma, Yue Cao, Gongwei Zheng, Qing Ren, Cheng Chen, Qunyan Zhu, Yijun Zhou, Yu Lu, Yaru Zhang and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. A Brief Review of Microbial Omics: Methods and Perspectives.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jingjing Li *Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.ORCID http://orcid.org/0000-0002-9882-7377
Yunlong Ma *Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Yue Cao *Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Gongwei ZhengOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Qing RenOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Cheng ChenOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Qunyan ZhuOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Yijun ZhouOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Yu LuThe Second School of Clinical Medicine, Institution of Medical Artificial Intelligence, Binzhou Medical University, Yantai, China.
Yaru ZhangOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Chunyu DengOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Wei-Hua ChenKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. weihuachen@hust.edu.cn.ORCID http://orcid.org/0000-0003-2168-6147
Jianzhong SuOujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Eye Hospital, Wenzhou Medical University, Wenzhou, China. sujz@wmu.edu.cn.ORCID http://orcid.org/0000-0003-1054-6042

Funding

China Postdoctoral Science Foundation 2023M732679National Natural Science Foundation of China (National Science Foundation of China) 32200535Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) 2025C02153
6 · The paper itself

Abstract

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.

Indexed as

Gastrointestinal MicrobiomeGenome-Wide Association StudyHost Microbial InteractionsSingle-Cell AnalysisTranscriptomeAnimalsBacteriaCholesterolGene Expression ProfilingHepatocytesHumansLiverMiceMice, Inbred C57BLCholesterol

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.