Single nucleus and in situ RNA sequencing reveals cell topographies in the human pancreas.

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Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been yet established, due to 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-FISH, in situ sequencing and computational approaches.We created the first comprehensive atlas of human pancreas cells, including epithelial and non-epithelial constituents and uncovered three distinct acinar cell types, with possible implications for homeostatic and inflammatory processes of the pancreas. The comparison with neonatal sNuc-seq data revealed a different cellular composition of the endocrine tissue, highlighting 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 morphological organization of the organ. Furthermore, similar analyses in chronic pancreatitis biopsies revealed 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.Interactive exploration tool and data download: http://singlecell.charite.de/pancreas. Raw sequencing access-protected data on European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home): EGAS00001004653. In Situ Sequencing raw data: 10.6084/m9.figshare.12173232.


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