Engineering and Analysis of T cell CD3 and IL2R Signals

T 细胞 CD3 和 IL2R 信号的工程和分析

• 批准号: 7074737
• 负责人: Karl Dane Wittrup
• 金额: $ 56.89万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-15 至 2009-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7074737
• 关键词: CD3 molecule; T lymphocyte; anergy; antireceptor antibody; apoptosis; cell population study; cytokine receptors; directed evolution; flow cytometry; human genetic material tag; interleukin 2; leukocyte activation /transformation; mathematical model; model design /development; protein engineering; proteomics; tissue /cell culture; western blottings

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.

描述（由申请人提供）：该项目为 T 细胞反应建模和分析提供了独特的合作机会。定量了解 CDS 和 IL-2R 信号输入如何结合起来设置二元生长/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治疗策略至关重要。我们建议构建培养的原代人类 T 细胞的静息、激活、无反应和凋亡离散状态之间转变的预测动态模型。这些研究的系统视角是提示/信号/响应。细胞外线索、细胞内信号以及人类 T 细胞对 CDS 和 IL-2R 刺激的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 抗体模拟物和通过定向进化设计的高亲和力 IL-2 突变体组成，以提供定量控制的系统输入。信号将在几个细节层面进行跟踪：在单细胞层面，通过关键信号分子的多维流式细胞仪测量；通过蛋白质印迹和激酶测定在群体水平上进行；并通过质谱法在磷酸化蛋白质组水平上进行分析。贝叶斯推理将用于从多元流式细胞术和质谱获得的磷酸化蛋白质组数据构建影响网络，偏最小二乘分析将用于状态识别，信号通路的动力学模型将用于描述和预测线索和信号之间的动态关系。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）方面的专业知识。这些研究将深入了解 T 细胞调节，并开发具有潜在治疗价值的 CDS 和 IL-2 刺激分子。