Engineering and Analysis of T cell CD3 and IL2R Signals

描述(由申请人提供)：该项目为T细胞反应的建模和分析提供了一个独特的合作机会。定量了解CDS和IL-2R信号输入如何结合来设定二元生长/死亡开关，对于优化癌症、病毒感染和自身免疫性疾病的免疫治疗策略至关重要。我们建议在原代培养的人T细胞中构建静息、激活、无能和凋亡这四种离散状态之间转换的预测性动力学模型。构成这些研究的系统视角是提示/信号/响应。人类T细胞对CDS和IL-2R刺激的细胞外信号、细胞内信号和总体反应将通过应用来自实验和计算领域的最先进的合成和分析方法来解析。这些线索将由抗CDS抗体模拟物和高亲和力IL-2突变体组成，这些突变体通过定向进化来提供定量控制的系统输入。信号将在几个细节水平上进行跟踪：在单细胞水平上，通过对关键信号分子的多维流式细胞术测量；在群体水平上，通过Western印迹和激酶分析；以及在磷酸蛋白质组水平上，通过质谱学。应用贝叶斯推理从多变量流式细胞仪和质谱仪获得的磷蛋白质组数据构建影响网络，利用偏最小二乘分析进行状态识别，利用信号通路的动力学建模来描述和预测线索和信号之间的动态关系。这个合作项目将整合蛋白质工程(KDW)、理论和系统生物学(DAL)、磷酸蛋白质组质谱(FW)以及细胞免疫学和流式细胞术(GPN)方面的专业知识。这些研究将为T细胞调节提供洞察力，并开发具有潜在治疗价值的CDS和IL-2刺激分子。

DESCRIPTION (provided by applicant): This project represents a unique collaborative opportunity for the modeling and analysis of T cell responses. A quantitative understanding of how CDS and IL-2R signal inputs combine to set the binary growth/death switch is critical for optimizing immunotherapeutic strategies in cancer, viral infection, and autoimmune diseases. We propose to construct predictive dynamic models of transitions between the discrete states of resting, activation, anergy, and apoptosis in cultured primary human T cells. The systems perspective framing these studies is cue/signal/response. The extracellular cues, intracellular signals, and overall responses of human T cells to CDS and IL-2R stimulation will be parsed by the application of state-of-the-art synthetic and analytical methodologies from both the experimental and computational realms. The cues will consist of anti-CDS antibody mimics and high affinity IL-2 mutants engineered by directed evolution to provide quantitatively controlled system inputs. Signals will be tracked at several levels of detail: at the single-cell level by multidimensional flow cytometric measurements of the key signaling molecules; at the population level by Western blot and kinase assay; and at the phosphoproteome level by mass spectrometry. Bayesian inference will be applied to construct influence networks from phosphoproteome data obtained with multivariate flow cytometry and mass spectrometry, partial least squares analysis will be utilized for state identification, and kinetic modeling of signaling pathways will be used to describe and predict the dynamic relationships between cues and signals. This collaborative project will integrate expertise in protein engineering (KDW), theoretical and systems biology (DAL), phosphoproteome mass spectrometry (FW), and cellular immunology and flow cytometry (GPN). These studies will provide insights into T cell regulation as well as develop CDS and IL-2 stimulatory molecules of potential therapeutic value.