Engineering and Analysis of T cell CD3 and IL2R Signals

描述（由申请人提供）：该项目代表了T细胞反应建模和分析的独特合作机会。定量了解CDS和IL-2 R信号输入如何结合联合收割机以设置二元生长/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策略至关重要。我们建议构建预测的动态模型之间的离散状态的休息，激活，无能，和细胞凋亡培养的原代人T细胞的过渡。这些研究的系统视角框架是线索/信号/反应。细胞外信号，细胞内信号，和人T细胞的CDS和IL-2 R刺激的整体反应将解析的应用程序的最先进的合成和分析方法，从实验和计算领域。线索将由抗CDS抗体模拟物和通过定向进化工程化的高亲和力IL-2突变体组成，以提供定量控制的系统输入。信号将在几个层次的细节跟踪：在单细胞水平的多维流式细胞术测量的关键信号分子;在人口水平的蛋白质印迹和激酶测定;和在磷酸化蛋白质组水平的质谱。贝叶斯推理将被应用于构建影响网络从磷酸化蛋白质组数据获得的多变量流式细胞术和质谱，偏最小二乘分析将被用于状态识别，和信号传导通路的动力学建模将被用于描述和预测之间的动态关系的线索和信号。该合作项目将整合蛋白质工程（KDW），理论和系统生物学（DAL），磷酸化蛋白质组质谱（FW）以及细胞免疫学和流式细胞术（GPN）的专业知识。这些研究将提供对T细胞调节的见解，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.