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A study of miR-15/16 in T cell biology

Abstract

Coordinate control of T cell proliferation, survival, and differentiation are essential for host protection from pathogens and cancer. Long-lived memory cells, whose precursors are formed during the initial immunological insult, provide protection from future encounters and their generation is the goal of many vaccination strategies. On the other hand, regulatory T cells play a critical role in the resolution of immune responses through an arsenal of anti-inflammatory molecules.

microRNAs are key nodes in regulatory networks that shape effective T cell responses through the fine-tuning of thousands of genes. Here, using new compound conditional mutant mice to eliminate miR-15/16 family miRNAs in T cells, I demonstrated that miR-15/16 restrict T cell cycle, survival, and memory T cell differentiation. High throughput sequencing of RNA isolated by cross-linking immunoprecipitation of AGO2 combined with gene expression analysis in miR-15/16 deficient T cells indicate that these effects are mediated through the direct inhibition of an extensive network of known and novel target genes within pathways critical to cell cycle, survival, and memory. Stability and miR-15/16 occupancy of the long non-coding RNA, Malat1, suggest that it may act as a sponge for miR-15/16, thus aiding in memory cell differentiation.

Regulatory T cells (Tregs) aid in the resolution of immune responses as well as protection from autoimmune disease. Through the characterization of miR-15/16 deficient CD4+ T cells I uncovered a role for these microRNAs in the thymic development and peripheral maintenance of Treg cells. Tregs deficient in miR-15/16 displayed reduced expression of markers associated with stability and suppressive capacity.

This body of work highlights the important role that miRNAs play in shaping the global gene expression program that is required for T cell cycle, survival, and the proper formation of memory cells as well as the development of appropriate populations of regulatory T cells. Additionally, I have developed an application, plotGrouper, for the graphing and statistical analysis of raw data; especially those associated with flow cytometry.

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