@article{187f60b9881d4aeda9a874aaea9bd87e,
title = "In vivo screen identifies a SIK inhibitor that induces β cell proliferation through a transient UPR",
abstract = "It is known that β cell proliferation expands the β cell mass during development and under certain hyperglycemic conditions in the adult, a process that may be used for β cell regeneration in diabetes. Here, through a new high-throughput screen using a luminescence ubiquitination-based cell cycle indicator (LUCCI) in zebrafish, we identify HG-9-91-01 as a driver of proliferation and confirm this effect in mouse and human β cells. HG-9-91-01 is an inhibitor of salt-inducible kinases (SIKs), and overexpression of Sik1 specifically in β cells blocks the effect of HG-9-91-01 on β cell proliferation. Single-cell transcriptomic analyses of mouse β cells demonstrate that HG-9-91-01 induces a wave of activating transcription factor (ATF)6-dependent unfolded protein response (UPR) before cell cycle entry. Importantly, the UPR wave is not associated with an increase in insulin expression. Additional mechanistic studies indicate that HG-9-91-01 induces multiple signalling effectors downstream of SIK inhibition, including CRTC1, CRTC2, ATF6, IRE1 and mTOR, which integrate to collectively drive β cell proliferation.",
author = "J{\'e}r{\'e}mie Charbord and Lipeng Ren and Sharma, {Rohit B.} and Anna Johansson and Rasmus {\AA}gren and Lianhe Chu and Dominika Tworus and Nadja Schulz and Pierre Charbord and Stewart, {Andrew F.} and Peng Wang and Alonso, {Laura C.} and Olov Andersson",
note = "Funding Information: We thank J. Avila for assistance with flow cytometry, F. Salomons for assistance with ImageXpress and C. Karampelias and K.-C. Liu for discussions. Human islets for research were provided by the Alberta Diabetes Institute IsletCore at the University of Alberta (www.bcell.org/adi-isletcore) and the Integrated Islet Distribution Program (https://iidp.coh.org). Single-cell transcriptome data were generated at the Eukaryotic Single-Cell Genomics facility at SciLifeLab in Stockholm, Sweden. Computations and data handling were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at the UPPMAX, partially funded by the Swedish Research Council through grant agreement no. 2018-05973. This work was supported by grants from the following organisations: the Swedish Research Council, the Novo Nordisk Foundation, the Swedish Diabetes Foundation, the Ragnar S{\"o}derberg{\textquoteright}s Foundation and Strategic Research Programmes in Diabetes, Stem Cell Research & Regenerative Medicine at the Karolinska Institutet to O.A.; and NIH/ NIDDK (R01DK114686, R01DK113300) and the George F. and Sybil H. Fuller Foundation to L.C.A.; A.J. and R.{\AA}. were financially supported by the Knut and Alice Wallenberg Foundation as part of the National Bioinformatics Infrastructure Sweden at SciLifeLab. Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive licence to Springer Nature Limited.",
year = "2021",
month = may,
doi = "10.1038/s42255-021-00391-x",
language = "English",
volume = "3",
pages = "682--700",
journal = "Nature Metabolism",
issn = "2522-5812",
publisher = "Springer Berlin",
number = "5",
}