Decoding in vivo regulatory programs of CD4+ T lymphocyte populations in inflamma

描述（由申请人提供）：在多细胞生物体中，分化的细胞表现出由不同的转录和表观遗传程序指定的专门功能。差异使用的调控元件定义了大多数以前研究的谱系特异性基因表达程序。然而，诸如应激、损伤或感染的挑战可以在分化的细胞中引发适应性或致病性反应，导致其功能状态和转录输出的变化。免疫系统的细胞提供了一个强大的实验模型，用于解剖建立不同分化和激活状态的基因组机制。 在这个提议中，我们研究了不同的CD 4 + T细胞群体，因为它们从“幼稚”（或静息）过渡到具有相反功能的激活状态：效应T细胞， - 以及抑制免疫应答和相关炎症的活化调节性T细胞（Treg）。静息Treg细胞在分化过程中作为T淋巴细胞的稳定谱系出现，不同于幼稚的CD 4 + T细胞。我们将使用复杂的遗传小鼠模型来产生短期炎症性疾病，并研究体内炎症环境中活化的Treg和T效应细胞及其静息对应物的基因组特征。我们将使用DNase-seq，TF和组蛋白修饰ChIP-seq，以及来自离体分离细胞的批量和单细胞RNA-seq图谱来分析四种细胞状态的增强子和转录景观。使用这些综合数据集，我们将：（1）解码增强子景观的变化，这些增强子景观支配不同的CD 4 + T淋巴细胞群体的激活;（2）模拟这些细胞中基因的差异转录输出作为序列的函数。 以及它们的增强子的活性;以及（3）将单个基因在细胞群体中的表达分布建模为它们的增强子的状态空间的函数。鉴于Treg细胞在抑制免疫介导的炎症中发挥的核心作用，从自身免疫，损伤和感染到妊娠和代谢疾病，以及对它们在癌症中的关键作用的新认识，我们的研究对人类健康具有广泛的相关性和重大的实际意义。

DESCRIPTION (provided by applicant): In multicellular organisms, differentiated cells exhibit specialized functions that are specified by distinct transcriptional and epigenetic programs. Differential use of regulatory elements defines most previously studied lineage specific gene expression programs. However, challenges such as stress, injury, or infection can elicit adaptive or pathogenic responses in differentiated cells leading to a change in their functional state and transcriptional output. Cells of the immune system offer a powerful experimental model for dissection of genomic mechanisms underlying establishment of distinct differentiation and activation states. In this proposal, we study distinct CD4+ T cell populations as they transition from "na�ve" (or resting) to activated states with opposing function: effector T cells that promote - and activated regulatory T cells (Treg) that suppress - immune response and associated inflammation. Resting Treg cells emerge during differentiation as a stable lineage of T lymphocytes distinct from na�ve CD4+ T cells. We will use sophisticated genetic mouse models to generate a short-term inflammatory disorder and investigate genomic features of activated Treg and T effector cells and their resting counterparts in an inflammatory context in vivo. We will profile the enhancer and transcriptional landscapes of the four cell states using DNase-seq, TF and histone modification ChIP-seq, and bulk and single-cell RNA-seq profiles from ex vivo isolated cells. Using these comprehensive data sets, we will: (1) decode the changes in the enhancer landscape that govern the activation of distinct CD4+ T lymphocyte populations; (2) model the differential transcriptional output of genes in these cells as a function of the sequence and activity of their enhancers; and (3) model the expression distribution of individual genes over a population of cells as a function of the state space of their enhancers. Given the central role that Treg cells play in suppressing immune-mediated inflammation in diverse biological contexts ranging from autoimmunity, injury, and infection to pregnancy and metabolic disease as well as emerging understanding of their pivotal role in cancer, our study has broad relevance to human health and major practical significance.