Quantitative-Proteomic Comparison of Alpha and Beta Cells to Uncover Novel Targets for Lineage Reprogramming
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Choudhary-2014-Quantitative-proteom.pdf
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Author(s) • • • • • • • • •
Choudhary, Amit
Hu He, Kaihui
Mertins, Philipp
Udeshi, Namrata D.
Dancik, Vlado
Fomina-Yadlin, Dina
Kubicek, Stefan
Clemons, Paul A.
Schreiber, Stuart L.
Wagner, Bridget K.
Date Issued
April 2014
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Choudhary, Amit, Kaihui Hu He, Philipp Mertins, Namrata D. Udeshi, Vlado Dancik, Dina Fomina-Yadlin, Stefan Kubicek, et al. “Quantitative-Proteomic Comparison of Alpha and Beta Cells to Uncover Novel Targets for Lineage Reprogramming.” Edited by Amar Abderrahmani. PLoS ONE 9, no. 4 (April 23, 2014): e95194.
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Final published version
Abstract
Type-1 diabetes (T1D) is an autoimmune disease in which insulin-secreting pancreatic beta cells are destroyed by the immune system. An emerging strategy to regenerate beta-cell mass is through transdifferentiation of pancreatic alpha cells to beta cells. We previously reported two small molecules, BRD7389 and GW8510, that induce insulin expression in a mouse alpha cell line and provide a glimpse into potential intermediate cell states in beta-cell reprogramming from alpha cells. These small-molecule studies suggested that inhibition of kinases in particular may induce the expression of several beta-cell markers in alpha cells. To identify potential lineage reprogramming protein targets, we compared the transcriptome, proteome, and phosphoproteome of alpha cells, beta cells, and compound-treated alpha cells. Our phosphoproteomic analysis indicated that two kinases, BRSK1 and CAMKK2, exhibit decreased phosphorylation in beta cells compared to alpha cells, and in compound-treated alpha cells compared to DMSO-treated alpha cells. Knock-down of these kinases in alpha cells resulted in expression of key beta-cell markers. These results provide evidence that perturbation of the kinome may be important for lineage reprogramming of alpha cells to beta cells.
MIT Department
Koch Institute for Integrative Cancer Research at MIT
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0095194