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Organization of the human intestine at single-cell resolution

Author

Listed:
  • John W. Hickey

    (Stanford School of Medicine)

  • Winston R. Becker

    (Stanford School of Medicine)

  • Stephanie A. Nevins

    (Stanford School of Medicine)

  • Aaron Horning

    (Stanford School of Medicine)

  • Almudena Espin Perez

    (Stanford School of Medicine)

  • Chenchen Zhu

    (Stanford School of Medicine)

  • Bokai Zhu

    (Stanford School of Medicine)

  • Bei Wei

    (Stanford School of Medicine)

  • Roxanne Chiu

    (Stanford School of Medicine)

  • Derek C. Chen

    (Stanford School of Medicine)

  • Daniel L. Cotter

    (Stanford School of Medicine)

  • Edward D. Esplin

    (Stanford School of Medicine)

  • Annika K. Weimer

    (Stanford School of Medicine)

  • Chiara Caraccio

    (Stanford School of Medicine)

  • Vishal Venkataraaman

    (Stanford School of Medicine)

  • Christian M. Schürch

    (Stanford School of Medicine
    University Hospital and Comprehensive Cancer Center Tübingen)

  • Sarah Black

    (Stanford School of Medicine)

  • Maria Brbić

    (Stanford University
    École Polytechnique Fédérale de Lausanne)

  • Kaidi Cao

    (Stanford University)

  • Shuxiao Chen

    (University of Pennsylvania)

  • Weiruo Zhang

    (Stanford School of Medicine)

  • Emma Monte

    (Stanford School of Medicine)

  • Nancy R. Zhang

    (University of Pennsylvania)

  • Zongming Ma

    (University of Pennsylvania)

  • Jure Leskovec

    (Stanford University)

  • Zhengyan Zhang

    (Washington University)

  • Shin Lin

    (University of Washington)

  • Teri Longacre

    (Stanford School of Medicine)

  • Sylvia K. Plevritis

    (Stanford School of Medicine)

  • Yiing Lin

    (Washington University)

  • Garry P. Nolan

    (Stanford School of Medicine)

  • William J. Greenleaf

    (Stanford School of Medicine)

  • Michael Snyder

    (Stanford School of Medicine)

Abstract

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health1. The intesting has a length of over nine metres, along which there are differences in structure and function2. The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function. Here, to better understand these differences, we evaluated the organization of single cells using multiplexed imaging and single-nucleus RNA and open chromatin assays across eight different intestinal sites from nine donors. Through systematic analyses, we find cell compositions that differ substantially across regions of the intestine and demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighbourhoods and communities, highlighting distinct immunological niches that are present in the intestine. We also map gene regulatory differences in these cells that are suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation and organization for this organ, and serve as an important reference map for understanding human biology and disease.

Suggested Citation

  • John W. Hickey & Winston R. Becker & Stephanie A. Nevins & Aaron Horning & Almudena Espin Perez & Chenchen Zhu & Bokai Zhu & Bei Wei & Roxanne Chiu & Derek C. Chen & Daniel L. Cotter & Edward D. Espli, 2023. "Organization of the human intestine at single-cell resolution," Nature, Nature, vol. 619(7970), pages 572-584, July.
  • Handle: RePEc:nat:nature:v:619:y:2023:i:7970:d:10.1038_s41586-023-05915-x
    DOI: 10.1038/s41586-023-05915-x
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    Cited by:

    1. Yashvardhan Jain & Leah L. Godwin & Sripad Joshi & Shriya Mandarapu & Trang Le & Cecilia Lindskog & Emma Lundberg & Katy Börner, 2023. "Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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