Luca Tosti1, Yan Hang2, Olivia Debnath1, Sebastian Tiesmeyer1, Timo Trefzer1, Katja Steiger3, Foo Wei Ten1, Sören Lukassen1, Simone Ballke4, Anja A Kühl5, Simone Spieckermann5, Rita Bottino6, Naveed Ishaque1, Wilko Weichert3, Seung K Kim7, Roland Eils8, Christian Conrad9. 1. Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany. 2. Department of Developmental Biology, Stanford University School of Medicine, Stanford, California; Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, California. 3. Institute of Pathology, Technische Universität München, Munich, Germany. 4. Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, California. 5. iPATH.Berlin, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, corporate member of Freie Universität, Humboldt-Universität zu Berlin, Berlin, Germany. 6. Institute of Cellular Therapeutics, Allegheny Health Network, Pittsburgh, Pennsylvania. 7. 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. 8. 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. 9. 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.
Abstract
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+ cells, a reciprocal association between macrophages and activated stellate cells, and a new potential role of tuft cells in this disease. 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.
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+ cells, a reciprocal association between macrophages and activated stellate cells, and a new potential role of tuft cells in this disease. 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.
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