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

描述(申请人提供)：在多细胞生物体中，分化的细胞表现出特殊的功能，这些功能由不同的转录和表观遗传程序指定。调控元件的不同使用定义了大多数先前研究的谱系特异性基因表达程序。然而，应激、损伤或感染等挑战可以在分化的细胞中引发适应性或致病反应，导致其功能状态和转录输出的变化。免疫系统的细胞为剖析建立不同分化和激活状态的基因组机制提供了一个强大的实验模型。在这项研究中，我们研究了不同的CD_4~+T细胞群，当它们从“NA�ve”(或静止状态)转变到具有相反功能的激活状态时：促进 -和激活的调节T细胞(Treg)，抑制免疫反应和相关的炎症。静息的Treg细胞在分化过程中形成稳定的T淋巴细胞谱系，有别于NA�ve CD4+T细胞。我们将使用复杂的遗传小鼠模型来产生短期的炎症障碍，并在体内研究激活的Treg和T效应细胞以及它们在炎症环境中的静止对应细胞的基因组特征。我们将使用DNase-seq、Tf和组蛋白修饰芯片-seq以及来自体外分离细胞的散装和单细胞RNA-seq图谱来描述四种细胞状态的增强子和转录情况。使用这些全面的数据集，我们将：(1)解码控制不同的CD4+T淋巴细胞群激活的增强子格局的变化；(2)将这些细胞中基因的差异转录输出模拟为序列的函数 和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细胞在从自身免疫、损伤和感染到妊娠和代谢性疾病等多种生物学环境中在抑制免疫介导的炎症中发挥的核心作用，以及对其在癌症中的关键作用的逐渐认识，我们的研究对人类健康具有广泛的相关性和重大的现实意义。

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.