HCA Data Explorer

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

Updated September 16, 2024

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+ cells, a reciprocal association between macrophages and activated stellate cells, and a new potential role of tuft cells in this disease. 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.

Seung K KimStanford University School of Medicineseungkim@stanford.edu
Roland EilsUniversity of Heidelbergroland.eils@charite.de
Christian ConradBerlin Institute of Health and Charité - Universitätsmedizin Berlinchristian.conrad@charite.de
Luca Tosti1
Yan Hang2
Olivia Debnath1
Sebastian Tiesmeyer1
Timo Trefzer1
Katja Steiger3
Foo Wei Ten1
Sören Lukassen1
Simone Ballke2
Anja A Kühl1
Simone Spieckermann1
Rita Bottino4
Naveed Ishaque1
Wilko Weichert3
Seung K Kim2
Roland Eils5
Christian Conrad1
1Berlin Institute of Health and Charité - Universitätsmedizin Berlin
2Stanford University School of Medicine
3Institute of Pathology, Technische Universität München
4Institute of Cellular Therapeutics, Allegheny Health Network
5University of Heidelberg
Arsenios Chatzigeorgiou

To reference this project, please use the following link:

https://explore.data.humancellatlas.dev.clevercanary.com/projects/b3938158-4e8d-4fdb-9e13-9e94270dde16

Supplementary links are provided by contributors and represent items such as additional data which can’t be hosted here; code that was used to analyze this data; or tools and visualizations associated with this specific dataset.

1.http://singlecell.charite.de/pancreas
EGA Accessions:

Atlas

None

Analysis Portals

None

Project Label

PancreasTopographiesTosti10x

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

pancreas

Organ Part

3 organ parts

Selected Cell Types

Unspecified

Disease Status (Specimen)

5 disease statuses

Disease Status (Donor)

5 disease statuses

Development Stage

3 development stages

Library Construction Method

2 library construction methods

Nucleic Acid Source

single nucleus

Paired End

false

Analysis Protocol

analysis_protocol

File Format

5 file formats

Cell Count Estimate

120.0k

Donor Count

10
coord.tsv.gz3 file(s)rds3 file(s)tsv3 file(s)tsv.gz3 file(s)xlsx1 file(s)