Single-Nucleus and In Situ RNA-Sequencing Reveal Cell Topographies in the Human Pancreas.


Journal

Gastroenterology
ISSN: 1528-0012
Titre abrégé: Gastroenterology
Pays: United States
ID NLM: 0374630

Informations de publication

Date de publication:
03 2021
Historique:
received: 25 05 2020
revised: 30 10 2020
accepted: 03 11 2020
pubmed: 20 11 2020
medline: 6 8 2021
entrez: 19 11 2020
Statut: ppublish

Résumé

Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been yet established because of the local concentration and cascade of hydrolytic enzymes that can rapidly degrade cells and RNA upon pancreatic resection. We sought to better understand the heterogeneity and cellular composition of the pancreas in neonates and adults in healthy and diseased conditions using single-cell sequencing approaches. We innovated single-nucleus RNA-sequencing protocols and profiled more than 120,000 cells from pancreata of adult and neonatal human donors. We validated the single-nucleus findings using RNA fluorescence in situ hybridization, in situ sequencing, and computational approaches. We created the first comprehensive atlas of human pancreas cells including epithelial and nonepithelial constituents, and uncovered 3 distinct acinar cell types, with possible implications for homeostatic and inflammatory processes of the pancreas. The comparison with neonatal single-nucleus sequencing data showed a different cellular composition of the endocrine tissue, highlighting the tissue dynamics occurring during development. By applying spatial cartography, involving cell proximity mapping through in situ sequencing, we found evidence of specific cell type neighborhoods, dynamic topographies in the endocrine and exocrine pancreas, and principles of morphologic organization of the organ. Furthermore, similar analyses in chronic pancreatitis biopsy samples showed the presence of acinar-REG Our human pancreas cell atlas can be interrogated to understand pancreatic cell biology and provides a crucial reference set for comparisons with diseased tissue samples to map the cellular foundations of pancreatic diseases.

Sections du résumé

BACKGROUND & AIMS
Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been yet established because of the local concentration and cascade of hydrolytic enzymes that can rapidly degrade cells and RNA upon pancreatic resection. We sought to better understand the heterogeneity and cellular composition of the pancreas in neonates and adults in healthy and diseased conditions using single-cell sequencing approaches.
METHODS
We innovated single-nucleus RNA-sequencing protocols and profiled more than 120,000 cells from pancreata of adult and neonatal human donors. We validated the single-nucleus findings using RNA fluorescence in situ hybridization, in situ sequencing, and computational approaches.
RESULTS
We created the first comprehensive atlas of human pancreas cells including epithelial and nonepithelial constituents, and uncovered 3 distinct acinar cell types, with possible implications for homeostatic and inflammatory processes of the pancreas. The comparison with neonatal single-nucleus sequencing data showed a different cellular composition of the endocrine tissue, highlighting the tissue dynamics occurring during development. By applying spatial cartography, involving cell proximity mapping through in situ sequencing, we found evidence of specific cell type neighborhoods, dynamic topographies in the endocrine and exocrine pancreas, and principles of morphologic organization of the organ. Furthermore, similar analyses in chronic pancreatitis biopsy samples showed the presence of acinar-REG
CONCLUSIONS
Our human pancreas cell atlas can be interrogated to understand pancreatic cell biology and provides a crucial reference set for comparisons with diseased tissue samples to map the cellular foundations of pancreatic diseases.

Identifiants

pubmed: 33212097
pii: S0016-5085(20)35399-3
doi: 10.1053/j.gastro.2020.11.010
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1330-1344.e11

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Luca Tosti (L)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Yan Hang (Y)

Department of Developmental Biology, Stanford University School of Medicine, Stanford, California; Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, California.

Olivia Debnath (O)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Sebastian Tiesmeyer (S)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Timo Trefzer (T)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Katja Steiger (K)

Institute of Pathology, Technische Universität München, Munich, Germany.

Foo Wei Ten (FW)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Sören Lukassen (S)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Simone Ballke (S)

Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, California.

Anja A Kühl (AA)

iPATH.Berlin, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität, Humboldt-Universität zu Berlin, Berlin, Germany.

Simone Spieckermann (S)

iPATH.Berlin, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität, Humboldt-Universität zu Berlin, Berlin, Germany.

Rita Bottino (R)

Institute of Cellular Therapeutics, Allegheny Health Network, Pittsburgh, Pennsylvania.

Naveed Ishaque (N)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Wilko Weichert (W)

Institute of Pathology, Technische Universität München, Munich, Germany.

Seung K Kim (SK)

Department of Developmental Biology, Stanford University School of Medicine, Stanford, California; Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, California; Department of Medicine, Endocrinology Division, Stanford University School of Medicine, Stanford, California. Electronic address: seungkim@stanford.edu.

Roland Eils (R)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany; Health Data Science Unit, Medical Faculty and BioQuant, University of Heidelberg, Heidelberg, Germany. Electronic address: roland.eils@charite.de.

Christian Conrad (C)

Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany. Electronic address: christian.conrad@charite.de.

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Classifications MeSH