Mechanisms of ligand discrimination by the T cell signaling machinery

摘要 T细胞可以区分疾病状态和非疾病状态。为了做出这种区分，这些信息 由细胞外受体提供的信号必须由T细胞内的信号网络解释。最值得注意的是T 细胞抗原受体(TCR)信号网络，因为它结合了扫描人类表面的受体 细胞寻找威胁和信号蛋白，以确保高度敏感和特异的反应。该TCR信令 机器可以检测到少量的抗原激动剂，并将其与结构背景区分开来 相似的内源性配体。我的研究小组的首要目标是阐明TCR信号是如何 机械通过产生不同的信号结果来区分TCR配体。过去几十年 已经揭示了TCR是如何与T细胞内的信号蛋白连接的，但关于TCR是如何连接到T细胞内的，我们还知之甚少 这些信号蛋白被协调以产生不同的细胞反应，例如TCR配体是否 应被忽略，或导致T细胞被激活。用于产生上下文的基本机制- 必须确定特定的TCR信号，以充分实现T细胞作为治疗实体的潜力 人类疾病的治疗。调节机制可以通过控制信号的活性来使信号多样化。 信号蛋白，如激酶，以及它们组装成蛋白质复合体。我们建议确定如何 TCR信号多样化可能源于(1)负反馈环路，(2)信号的差分组装 复合体，以及(3)TCR信号的适应性脱敏。来询问这些信号的机制 多样化及其对T细胞反应的影响，我们将结合化学工具和免疫学 接近了。我们将使用邻近标记和质谱分析来确定成分 信号复合体的数量被激酶反应的负反馈和TCR-配体结合特性所改变。 我们还将评估适应性转录导致受体脱敏的更多长期机制。 通过RNA测序的变化。这些数据集将与我们的合作者一起在 密歇根大学医学院，其中包括蛋白质组学资源设施和高级 基因组学核心。

SUMMARY T cells can discriminate between diseased and non-diseased states. To make this distinction, the information provided by extracellular receptors must be interpreted by signaling networks within the T cell. Most notable is T cell antigen receptor (TCR) signaling network because it combines a receptor that scans the surface of human cells for threats and signaling proteins that ensure a highly sensitive and specific response. This TCR signaling machinery can detect small quantities of an antigenic agonist and discriminate it from a background of structurally similar endogenous ligands. The overarching goal of my research group is to elucidate how the TCR signaling machinery discriminates between TCR ligands by producing distinct signaling outcomes. The past few decades have revealed how the TCR is coupled to signaling proteins within the T cell, but much less is known about how these signaling proteins are coordinated to produce different cellular responses, such as whether a TCR ligand should be ignored, or cause the T cell to become activated. The underlying mechanisms used to produce context- specific TCR signals must be determined to fully realize the potential of T cells as therapeutic entities for the treatment of human disease. Regulatory mechanisms can diversify signaling by controlling the activity of signaling proteins, such as kinases, and their assembly into protein complexes. We propose to determine how TCR signal diversification can arise from (1) negative feedback loops, (2) differential assembly of signaling complexes, and (3) adaptive desensitization of TCR signaling. To interrogate these mechanisms of signal diversification and their effect on a T cell response, we will combine chemical tools with immunological approaches. We will use proximity labeling and mass spectrometry analyses to determine how the composition of signaling complexes is altered by kinase-responsive negative feedback and TCR-ligand binding properties. We will also evaluate more long-term mechanisms of receptor desensitization caused by adaptive transcriptional changes by RNA sequencing. These datasets will be generated and analyzed with our collaborators at the University of Michigan Medical School, which includes the Proteomics Resource Facility and Advanced Genomics Core.