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Gene circuits programming IL-17 production in innate lymphocytes

Gene circuits programming IL-17 production in innate lymphocytes
基因电路编程先天淋巴细胞中 IL-17 的产生
批准号:
9194376
负责人:
Joonsoo Kang
金额:
$41.88万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-01-01 至 2017-12-31

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中文摘要
翻译
描述(由申请人提供):与细胞谱系分化相关的基因转录动力学可以通过三个连续的过程来建模:首先,负责开启与分化状态相关的基因的转录因子(TFs)活性的快速和短暂的开始;第二,抑制与直接前体状态或交替细胞命运选择相关的基因;第三,分化状态相关基因的长期诱导。与免疫基因组计划(ImmGen)联合制作的成熟先天γδTCR+胸腺细胞亚群转录组的初稿与该模型相匹配,并预测其他具有共享功能但在独特解剖位置起作用的先天淋巴样细胞(ILCs)受具有主题共性的调节网络控制。为了揭示指定关键先天免疫功能的基因调控网络,我们建议测试γδT细胞(Tγδ17)控制先天IL-17产生的预测调控模块。IL-17细胞因子家族已成为人类自身免疫性疾病炎症反应的中心效应因子。虽然适应性T细胞产生IL-17的规则被广泛研究,但如何调节来自特定ILC亚群的IL-17的产生尚不清楚。在细菌感染期间,Tγδ17细胞是IL-17的主要来源,其生产IL-17的能力在胸腺中被编程。控制编程的基因调控网络是未知的。负责Tγδ17分化的架构蓝图一旦被发现,就可以作为理解所有效应ILC发展的指南。对先天T效应谱系分化的全面理解可以通过三种相互关联的方法来完成:首先,识别定义分化Tγδ17状态的tf的初始波和初始编程明显的祖细胞;第二,系统定位TF调控因子占用目标t - γδ17基因;第三,来自基因调控网络顶端的网络扰动(基因KO小鼠和病原体攻击),随后进行影响分析,以确定网络内基因模块的功能互联性。通过对Tγδ17细胞命运调控网络中主要基因节点的功能表征,迄今为止发现了5个必需转录因子(TFs): SOX13、SOX4、RORγt、TCF1和LEF1,其中只有一个RORγt是之前发现的。缺乏Sox13或Sox4的小鼠t - γδ17分化受损。缺乏TCF1的小鼠产生IL-17过量产生的T细胞,而LEF1的表达是双相的,被排除在IL-17先天效应物之外。因此,这五种tf构成了先天IL-17产生的核心调节因子,它们被嵌入到其他ILC效应程序中,支持了一个共同的基因网络蓝图产生ILC效应物的预测,并了解它们相互关联的功能将是炎症疾病潜在靶向免疫治疗的核心。
英文摘要
DESCRIPTION (provided by applicant): Gene transcription dynamics associated with cell lineage differentiation can be modeled on three sequential processes: First, a rapid and transient onset of activities of transcription factors (TFs) responsible for turning on genes associated with differentiated states; second, suppression of genes associated with the immediate precursor state or alternate cell fate choice; and third, long lasting induction of gene associated with differentiated states. The first draft of a compendium of transcriptomes of maturing innate γδTCR+ thymocyte subsets produced in conjunction with the Immunological Genome Project (ImmGen) matches the model and predicts that other innate lymphoid cells (ILCs) with shared function, but acting at unique anatomical locations, are controlled by regulatory networks with thematic commonality. To uncover the gene regulatory networks that specify critical innate immune function we propose to test the predicted regulatory modules controlling innate IL-17 production from γδT cells (Tγδ17). IL-17 family of cytokines has emerged as the central effectors of inflammatory responses contributing to autoimmune disorders in humans. While the rules for IL-17 production by adaptive T cells are extensively studied how IL-17 production from specialized ILC subsets is regulated is unknown. Tγδ17 cells are the primary source of IL-17 during bacterial infection and its capacity for IL-17 production is programmed in the thymus. The gene regulatory network controlling the programming was unknown. The architectural blueprint responsible for Tγδ17 differentiation, once discovered, can be used as a guide to understand all effector ILC development. A comprehensive understanding of innate T effector lineage differentiation can be accomplished by three interconnected approaches: First, identification of the initial wave of TFs that define differentiated Tγδ17 state and the progenitors in which the initial programming is evident; second, a systematic mapping of TF regulator occupancy of target Tγδ17 genes; and third, perturbation of the network (gene KO mice and pathogen challenge) from the apex of the gene regulatory network followed by impact analyses to determine functional interconnectivity of gene modules within the network. Functional characterization of the primary gene nodes in the regulatory network specifying Tγδ17 cell fate has so far revealed five essential transcription factors (TFs): SOX13, SOX4, RORγt, TCF1 and LEF1, of which only one, RORγt, was previously identified. Mice deficient in Sox13 or Sox4 have impaired Tγδ17 differentiation. Mice lacking TCF1 generate T cells with hyper-production of IL-17 while LEF1 expression is biphasic, excluded from IL-17 innate effectors. The five TFs therefore constitute the core regulators of innate IL-17 production and they are embedded in other ILC effector programs, supporting the prediction that a common gene network blueprint generates ILC effectors and understanding their interconnected function will be central to potential targeted immunotherapies of inflammatory disorders.
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