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pmid:37581620
IFNɣ but not IFNα increases recognition of insulin defective ribosomal product-derived antigen to amplify islet autoimmunity.
Sofia Thomaidou · Amadeo Munoz Garcia · Sabine de Lange · Jin Gan · Arno R van der Slik · Rob C Hoeben · Bart O Roep · Françoise Carlotti · Arnaud Zaldumbide
Diabetologia · 2023 doi:10.1007/s00125-023-05991-8
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Complete file
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Here, we studied the role of early innate cytokines (IFNα) and late immune adaptive events (IFNɣ) in insulin DRiP-derived peptide presentation to diabetogenic CD8+ T cells.\nMETHODS: Single-cell transcriptomics of human pancreatic islets was used to study the composition of the (immuno)proteasome. Specific inhibition of the immunoproteasome catalytic subunits was achieved using siRNA, and antigenic peptide presentation at the cell surface of the human beta cell line EndoC-βH1 was monitored using peptide-specific CD8 T cells.\nRESULTS: We found that IFNγ induces the expression of the PSMB10 transcript encoding the β2i catalytic subunit of the immunoproteasome in endocrine beta cells, revealing a critical role in insulin DRiP-derived peptide presentation to T cells. Moreover, we showed that PSMB10 is upregulated in a beta cell subset that is preferentially destroyed in the pancreases of individuals with type 1 diabetes.\nCONCLUSIONS/INTERPRETATION: Our data highlight the role of the degradation machinery in beta cell immunogenicity and emphasise the need for evaluation of targeted immunoproteasome inhibitors to limit beta cell destruction in type 1 diabetes.\nDATA AVAILABILITY: The single-cell RNA-seq dataset is available from the Gene Expression Omnibus (GEO) using the accession number GSE218316 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE218316 ).", "claims": [{"id": "claim-method", "statement": "Differential gene expression analysis was performed using the Wilcoxon rank sum test to analyse gene expression differences between treated and untreated cell groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37581620", "locator": "sections[9] \"RNA-seq data processing and analysis\" paragraph 2", "quote": "Differential gene expression analysis was performed using the Wilcoxon rank sum test to analyse gene expression differences between treated and untreated cell groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The single-cell RNA-seq dataset is available from the Gene Expression Omnibus (GEO) using the accession number GSE218316 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE218316). 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