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MECHANISMS UNDERLYING THE DIRECT PROGRAMMING OF MOUSE EMBRYONIC FIBROBLASTS TO THYMIC EPITHELIAL CELLS BY FOXN1 [scRNA-seq]

GSE264266 Mus musculus Expression profiling by high throughput sequencing 9 samples Submitted 2024/04/22 Platform GPL30172
Summary
Thymic epithelial cells (TECs) are a critical functional component of the thymus’s ability to generate T cells for the adaptive immune system in vertebrates. However, no in vitro system for studying TEC function exists. Overexpressing the transcription factor FOXN1 initiates transdifferentiation of fibroblasts into TEC-like cells (iTECs) that support T cell differentiation in culture or after transplant. In this study, we characterized iTEC programming at the cellular and molecular level to determine how it proceeds and identified mechanisms that can be targeted for improving this process. These data showed that iTEC programming consisted of discrete gene expression changes that differed early and late in the process, and that iTECs upregulated markers of both cortical and medullary TEC (cTEC and mTEC) lineages. We demonstrated that promoting proliferation enhanced iTEC generation, and that Notch inhibition allowed induction of mTEC differentiation. Finally, we showed that MHCII expression was the major difference between iTECs and fetal TECs. MHCII expression was improved by co-culturing iTECs with fetal double-positive T-cells. This study supports future efforts to improve iTEC generation for both research and translational uses.
Published in
Mechanisms underlying the direct programming of mouse embryonic fibroblasts to thymic epithelial cells by FOXN1
Ma Z, Kang S, Condie BG et al. · Development (Cambridge, England) 2024 · PMID 38958026 · doi:10.1242/dev.202730
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Direct links to NCBI, no account and no request form: the whole study as GSE264266_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 9 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1101567 and SRA study SRP502460. Searching any of these in the dataset finder brings you back here.

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