Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas
Multiple single-cell RNA sequencing (scRNA-seq) datasets have been generated to study pancreatic islet cells during development, homeostasis, and diabetes progression. However, despite the time and resources invested into the past scRNA-seq studies, there is still no consensus on islet cell states and associated pathways in health and dysfunction as well as the value of frequently used preclinical mouse diabetes models. Since these challenges can be only resolved with a joint analysis of multiple datasets, we present a scRNA-seq cross-condition mouse islet atlas (MIA). We integrated over 300,000 cells from nine datasets with 56 samples, varying in age, sex, and diabetes models, including autoimmune type 1 diabetes (T1D) model (NOD), gluco-/lipotoxicity T2D model (db/db), and chemical streptozotocin (STZ) β-cell ablation model. MIA is a curated resource that enables interactive exploration of gene expression and transfer of cell types and states. We use MIA to obtain new insights into islet cells in health and disease that cannot be reached from individual datasets. Based on the MIA β-cell landscape we report cross-publication differences between previously suggested marker genes of individual phenotypes. We further show that in the STZ model β-cells transcriptionally correlate to human T2D and mouse db/db model β-cells, but are less similar to human T1D and mouse NOD model β-cells. We define new cell states involved in disease progression across diabetes models. We also observe different pathways shared between immature, aged, and diabetes model β-cell states. In conclusion, our work presents the first comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation, and demise.
Citation
@misc{hrovatin2022,
author = {Karin Hrovatin and Aimée Bastidas-Ponce and Mostafa Bakhti
and Luke Zappia and Maren Büttner and Ciro Sallino and Michael Sterr
and Anika Böttcher and Adriana Migliorini and Heiko Lickert and
Fabian J Theis},
title = {Delineating Mouse β-Cell Identity During Lifetime and in
Diabetes with a Single Cell Atlas},
date = {2022-12-22},
url = {https://lazappi.id.au/publications/2022-hrovatin-MIA},
doi = {10.1101/2022.12.22.521557},
langid = {en},
abstract = {Multiple single-cell RNA sequencing (scRNA-seq) datasets
have been generated to study pancreatic islet cells during
development, homeostasis, and diabetes progression. However, despite
the time and resources invested into the past scRNA-seq studies,
there is still no consensus on islet cell states and associated
pathways in health and dysfunction as well as the value of
frequently used preclinical mouse diabetes models. Since these
challenges can be only resolved with a joint analysis of multiple
datasets, we present a scRNA-seq cross-condition mouse islet atlas
(MIA). We integrated over 300,000 cells from nine datasets with 56
samples, varying in age, sex, and diabetes models, including
autoimmune type 1 diabetes (T1D) model (NOD), gluco-/lipotoxicity
T2D model (db/db), and chemical streptozotocin (STZ) β-cell ablation
model. MIA is a curated resource that enables interactive
exploration of gene expression and transfer of cell types and
states. We use MIA to obtain new insights into islet cells in health
and disease that cannot be reached from individual datasets. Based
on the MIA β-cell landscape we report cross-publication differences
between previously suggested marker genes of individual phenotypes.
We further show that in the STZ model β-cells transcriptionally
correlate to human T2D and mouse db/db model β-cells, but are less
similar to human T1D and mouse NOD model β-cells. We define new cell
states involved in disease progression across diabetes models. We
also observe different pathways shared between immature, aged, and
diabetes model β-cell states. In conclusion, our work presents the
first comprehensive analysis of β-cell responses to different
stressors, providing a roadmap for the understanding of β-cell
plasticity, compensation, and demise.}
}