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Beta-cell dependence to alpja-cell signals for proper insulin secretion in mouse pancreatic islets

GSE292158 Mus musculus Expression profiling by high throughput sequencing 6 samples Submitted 2025/05/01 Platform GPL19057
Summary
The islets of Langerhans play a central role in detecting and regulating blood glucose levels. While insulin-producing beta-cells are well-characterized, much remains to be studied about the other cell types in pancreatic islets (alpha-, delta-, PPY-, and epsilon-cells). In this context, we have developed chimeric organoids that we use to understand the interactions between the different cell populations present in pancreatic islets. We previously developed an efficient approach to purify the major cell populations present in pancreatic islets (alpha, beta, and delta) using flow cytometry. We have now developed a technique to re-aggregate these sorted cell populations, enabling the production of clusters (pseudo-islets) in which we can modulate the proportion of each cell population on demand. We generated clusters devoid of delta cells or both alpha and delta cells and confirmed this depletion at the gene and protein levels. We then evaluated the function of these pseudo-islets by measuring glucose-stimulated insulin secretion. The absence of delta-cells did not affect insulin secretion. However, the insulin secretory capacity of pseudo-islets lacking both alpha- and delta-cells was significantly reduced. Transcriptomic analysis of these pseudo-islets did not reveal a loss of beta-cell identity as the cause of the observed functional impairment but highlighted potential new signaling pathways influenced by alpha- and delta-cells. This demonstrates the importance of interactions among different endocrine cell types within the islet for the function of pancreatic beta-cells. It represents a new and effective tool for identifying signaling pathways and compounds that directly or indirectly (via other endocrine cell types) modulate the identity and function of pancreatic endocrine cells.
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Direct links to NCBI, no account and no request form: the whole study as GSE292158_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1237303 and SRA study SRP570915. Searching any of these in the dataset finder brings you back here.

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