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Hrovatin, K. ; Bastidas-Ponce, A. ; Bakhti, M. ; Zappia, L. ; Büttner, M. ; Salinno, C. ; Sterr, M. ; Böttcher, A. ; Migliorini, A. ; Lickert, H. ; Theis, F.J.

Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas.

Nat. Metab. 5, 1615-1637 (2023)
DOI PMC
Creative Commons Lizenzvertrag
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Although multiple pancreatic islet single-cell RNA-sequencing (scRNA-seq) datasets have been generated, a consensus on pancreatic cell states in development, homeostasis and diabetes as well as the value of preclinical animal models is missing. Here, we present an scRNA-seq cross-condition mouse islet atlas (MIA), a curated resource for interactive exploration and computational querying. We integrate over 300,000 cells from nine scRNA-seq datasets consisting of 56 samples, varying in age, sex and diabetes models, including an autoimmune type 1 diabetes model (NOD), a glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a chemical streptozotocin β-cell ablation model. The β-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that β-cells in the streptozotocin model transcriptionally correlate with those in human type 2 diabetes and mouse db/db models, but are less similar to human type 1 diabetes and mouse NOD β-cells. We also report pathways that are shared between β-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation and demise.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Unfolded Protein Response; Gene-expression; Pancreatic-islets; Delta Cells; Reveals; Dedifferentiation; Mechanisms; Transcriptomes; Heterogeneity; Dysfunction
ISSN (print) / ISBN 2522-5812
e-ISSN 2522-5812
Zeitschrift Nature metabolism
Quellenangaben Band: 5, Heft: 9, Seiten: 1615-1637 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort London
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Institute of Diabetes and Regeneration Research (IDR)
Förderungen Helmholtz Zentrum Munchen Deutsches Forschungszentrum fur Gesundheit und Umwelt (GmbH)