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The role of the intracellular complement system - the complosome - in Th1 biology

The role of the intracellular complement system - the complosome - in Th1 biology
细胞内补体系统(复合体)在 Th1 生物学中的作用
批准号:
10699737
负责人:
Claudia Kemper
金额:
$212.26万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
未结题
起止时间:
至

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中文摘要
翻译
A.我们在理解C3基因表达如何在T细胞和其他免疫细胞中调节方面取得了重大进展。我们发现由整合素LFA-1介导的信号(在免疫细胞渗出到组织中期间参与)是C3的主要诱导物。因此,LFA-1缺乏的患者不能上调免疫细胞中的C3,因此缺乏正常的Th 1、CTL和IL-1b产生巨噬细胞(Kolev和West,Immunity,2020)。 B。我们现在也已经能够理清确切的分子机制,其中CD 46的胞内结构域诱导Th 1相关的基因和活动的人CD 4 + T细胞。这是通过与细胞核中的特定转录因子直接相互作用而发生的(手稿正在准备中)。 C.我们在理解补体如何在Th 1细胞中共同诱导IL-10并启动其关闭程序方面取得了同样的进展。复杂体的这些新功能涉及调节脂质和氨基酸使用的代谢酶的受控表达诱导(手稿已提交并正在编写中)。 D.为了以前所未有的深度理解幼稚和记忆CD 4+和CD 8 + T细胞活化的信号传导事件,我们对人类分选的T细胞进行了首次比较scRNA-seq分析,并与宾夕法尼亚大学的Zhang实验室合作,利用整合多个未知多变量概率分布的新算法分析了数据。
英文摘要
A. We have made major progress in understanding how C3 gene expression is regulated in T and other immune cells. We found that signals mediated by the integrin LFA-1 (engaged during diapedesis of immune cells into tissues) is a master inducer of C3. In consequence, patients with deficiency in LFA-1 cannot upregulate C3 in immune cells and, thus, lack normal Th1, CTL and IL-1b producing macrophages (Kolev and West, Immunity, 2020). B. We have now also been able to detangle the exact molecular mechanisms by which the intracellular domain of CD46 induces Th1-related genes and activities in human CD4+ T cells. This occurs via direct interaction with specific transcription factors in the nucleus (manuscript in preparation). C. We have made equal progress in understanding how the complosome co-induces IL-10 in Th1 cells and initiates their shutdown program. These novel functions of the complosome involve the controlled expression induction of metabolic enzymes regulating lipid and amino acid usage (manuscript submitted and in preparation). D. In an attempt to understand the signaling event underlying naive and memory CD4+ and CD8+ T cell activation in unprecedented depth, we have performed the first comparative scRNA-seq analysis of human sorted T cells over time and analyzed the data utilizing a novel algorithm integrating multiple unknown multivariate probability distributions in collaboration with the Zhang laboratory at U-Penn (manuscript under final revision).
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