Description
Stem cell-derived islet cell therapy can effectively treat type 1 diabetes, but its efficacy is hindered by low oxygen supply post-transplantation, particularly in subcutaneous spaces and encapsulation devices, leading to cell dysfunction. The response to hypoxia and effective strategies to alleviate its detrimental effects remain poorly understood. Here, we show that beta cells within stem cell-derived islets gradually undergo a decline in cell identity and metabolic function in hypoxia. This is linked to reduced expression of immediate early genes (EGR1, FOS, and JUN), which downregulates key beta cell transcription factors. We further identified genes important for maintaining beta cell fitness in hypoxia, with EDN3 as a potent player. Elevated EDN3 expression preserves beta cell identity and function in hypoxia by modulating genes involved in beta cell maturation, glucose sensing and regulation. These insights improve the understanding of hypoxias impact on stem cell-derived islets, offering a potential intervention for clinical applications.
[doi:10.25345/C5VD6PH53]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: hypoxia beta cells pancreas sc-islets ; DatasetType:Proteomics
Contact
Principal Investigators:
(in alphabetical order)
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Doug Melton, Harvard University, United States
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sbrielle
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Number of distinct conditions across all analyses (original submission and reanalyses)
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Distinct condition labels are counted across all files submitted in the "Metadata" category
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Number of distinct biological replicates across all analyses (original submission and reanalyses)
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Originally identified proteins that were automatically
remapped by MassIVE to proteins in the
SwissProt
human reference database.
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Number of distinct protein accessions reported across all analyses (original submission and
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Number of distinct unmodified peptide sequences reported across all analyses (original
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Number of distinct peptide sequences (including modified variants or peptidoforms) reported
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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all
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Number of distinct proteins quantified across all analyses (original submission and reanalyses)
associated with this dataset.
Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
of Quantified Analytes" category having a "Protein" column in this dataset.
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Number of distinct proteins found to be differentially abundant in at least one comparison
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A protein is differentially abundant if its change in abundance across conditions is found
to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated
with statistical tests for differential abundance.
Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
of Quantified Analytes" category having a "Protein" column in this dataset.
"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE.
It has been imported to MassIVE for reanalysis purposes, so its spectra data here may
consist solely of processed peak lists suitable for reanalysis with most software.