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）：该项目代表了T细胞响应建模和分析的独特协作机会。对CD和IL-2R信号输入如何结合以设置二元生长/死亡开关的定量理解对于优化癌症，病毒感染和自身免疫性疾病的免疫治疗策略至关重要。我们建议在培养的原代人T细胞中构建静止，激活，反感和凋亡的离散状态之间的过渡状态的预测动态模型。这些研究的系统透视图是提示/信号/响应。从实验和计算领域中应用最先进的合成和分析方法，将通过应用最新的合成和分析方法来解析，细胞外提示，细胞内信号以及人类T细胞对CD和IL-2R刺激的总体反应。提示将由抗CD抗体模拟物和高亲和力IL-2突变体组成，该突变体由指向进化设计，以提供定量控制的系统输入。信号将以几个详细的级别跟踪：在单细胞水平上，通过关键信号分子的多维流式细胞仪测量值；在人口水平上，通过蛋白质印迹和激酶测定；并在磷蛋白体水平上通过质谱法。贝叶斯推论将用于从多元流式细胞术和质谱法获得的磷光蛋白质组数据中构建影响网络，将使用部分最小二乘分析来进行状态识别，并将使用信号通路的动力学建模来描述和预测线索之间的动态关系和信号。该协作项目将在蛋白质工程（KDW），理论和系统生物学（DAL），磷蛋白酶质谱法（FW）以及细胞免疫学和流式细胞仪（GPN）中整合专业知识。这些研究将提供有关T细胞调节的见解，并发展具有潜在治疗价值的CD和IL-2刺激分子。