KAUST DepartmentBiological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955–6900, Saudi Arabia
Biological and Environmental Sciences and Engineering (BESE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/660340
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AbstractGM-CSF produced by autoreactive CD4-positive T helper cells is involved in the pathogenesis of autoimmune diseases, such as multiple sclerosis. However, the molecular regulators that establish and maintain the features of GM-CSF-positive CD4 T cells are unknown. In order to identify these regulators, we isolated human GM-CSF-producing CD4 T cells from human peripheral blood by using a cytokine capture assay. We compared these cells to the corresponding GM-CSF-negative fraction, and furthermore, we studied naïve CD4 T cells, memory CD4 T cells, and bulk CD4 T cells from the same individuals as additional control cell populations. As a result, we provide a rich resource of integrated chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from these primary human CD4 T cell subsets and we show that the identified signatures are associated with human autoimmune diseases, especially multiple sclerosis. By combining information about mRNA expression, DNA accessibility, and predicted transcription factor binding, we reconstructed directed gene regulatory networks connecting transcription factors to their targets, which comprise putative key regulators of human GM-CSF-positive CD4 T cells as well as memory CD4 T cells. Our results suggest potential therapeutic targets to be investigated in the future in human autoimmune disease.
CitationÉliás, S., Schmidt, A., Gomez-Cabrero, D., & Tegnér, J. (2021). Gene Regulatory Network of Human GM-CSF-Secreting T Helper Cells. Journal of Immunology Research, 2021, 1–24. doi:10.1155/2021/8880585
SponsorsThe authors thank Matilda Eriksson and Peri Noori for performing RNA extractions, library preparation, and quality control for RNA-seq and next-generation sequencing, as well as for their excellent general lab management, Sunjay JudeFernandes for the reagents and advice for the ATAC-seq protocol, and Gilad Silberberg for the helpful discussions about footprinting and motif scanning (all from Computational Medicine Unit, Karolinska Institute). We thank John Andersson (Translational Immunology Unit, Karolinska Institute) for the helpful suggestions and discussions. This work was supported by Karolinska Institutet’s faculty funds for doctoral education (KID funding to S.E.), the Center of Excellence for Research on Inflammation and Cardiovascular Disease (CERIC to A.S. and J.T.), the 7th European Community Framework Programme (FP7-PEOPLE project 326930 to A.S.; FP7-IDEAS-ERC project 617393 to S.E., A.S., J.T., and D.G.C.; and FP7-HEALTH project 306000 to J.T. and D.G.C.), Vetenskapsrådet Medicine and Health (2011-3264 to J.T.), and Torsten Söderberg Foundation (to J.T.)
JournalJournal of Immunology Research
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