Large-Scale Functional Genomics Screen to Identify Modulators of Human β-Cell Insulin Secretion.
EndoC-βH1
EndoC-βH5
GSIS
T2D
glucose-stimulated insulin secretion
large-scale
siRNA screen
text mining
β-cell
Journal
Biomedicines
ISSN: 2227-9059
Titre abrégé: Biomedicines
Pays: Switzerland
ID NLM: 101691304
Informations de publication
Date de publication:
04 Jan 2022
04 Jan 2022
Historique:
received:
29
11
2021
revised:
24
12
2021
accepted:
27
12
2021
entrez:
21
1
2022
pubmed:
22
1
2022
medline:
22
1
2022
Statut:
epublish
Résumé
Type 2 diabetes (T2D) is a chronic metabolic disorder affecting almost half a billion people worldwide. Impaired function of pancreatic β-cells is both a hallmark of T2D and an underlying factor in the pathophysiology of the disease. Understanding the cellular mechanisms regulating appropriate insulin secretion has been of long-standing interest in the scientific and clinical communities. To identify novel genes regulating insulin secretion we developed a robust arrayed siRNA screen measuring basal, glucose-stimulated, and augmented insulin secretion by EndoC-βH1 cells, a human β-cell line, in a 384-well plate format. We screened 521 candidate genes selected by text mining for relevance to T2D biology and identified 23 positive and 68 negative regulators of insulin secretion. Among these, we validated ghrelin receptor (
Identifiants
pubmed: 35052782
pii: biomedicines10010103
doi: 10.3390/biomedicines10010103
pmc: PMC8773179
pii:
doi:
Types de publication
Journal Article
Langues
eng
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