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Stochastic modelling of cellular immune responses: crossing the theoretical-experimental divide

细胞免疫反应的随机建模：跨越理论与实验的鸿沟

基本信息

批准号：
BB/G023395/1
负责人：
Carmen Molina-Paris
金额：
$ 19.81万
依托单位：
University of Leeds
依托单位国家：
英国
项目类别：
Fellowship
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FG023395%2F1
关键词：
Stochastic modelling cellular immune responses

项目摘要

The adaptive cellular immune system recognises pathogenic antigens by means of the T~cell antigen receptor (TCR), which interacts with peptide antigens displayed on the surface of antigen presenting cells (APCs) by major histocompatibility complex (MHC) proteins. The immune system contains millions of distinct TCR molecules, formed by random rearrangement of the gene segments encoding the region of the TCR molecule that interacts with the peptide-MHC (pMHC) complex. Each T~cell expresses one specific TCR species or clonotype, unique to the T~cell and the clone to which it belongs. The interaction of T~cells with APCs is a key event in the control of both self-tolerance and effector function. Understanding TCR-pMHC interactions and TCR triggering is the pre-requisite to finding suitable targets that control T~cell activation. This proposal aims to provide a systems biology approach to T~cell immunology by making use of both current mathematical and experimental models to: (1) understand T~cell receptor (TCR-CD3) triggering, TCR clustering and conformational changes at the cytoplasmic tails of the CD3 subunits, (2) understand how the T~cell repertoire structure induced by central tolerance is related to thymic self-antigen presentation statistics, and (3) understand how T~cell numbers are homeostatically regulated to maintain both the size and diversity of the T~cell repertoire. The overall goal of this proposal is to provide adaptive immunology with a quantitative and systems biology perspective. This will be achieved by making use of both current mathematical models and experimental data, in order to (i) test existing mathematical models with preliminary experimental data, (ii) refine those mathematical models, (iii) suggest new experiments and (iv) generate new experimentally testable hypothesis. Dr. Molina-Paris aims to model adaptive immune responses using stochastic methods and working closely with experimental immunologists. The proposed research project falls within the priorities and mission of BBSRC: systems biology and mathematical tools for biology. Thus, the BBSRC Research Development Fellowship is both timely to the applicant and to the BBSRC remit and UK science, in general. This Fellowship will not only open up significant new directions in the fellow's research but will also give an inter-disciplinary dimension and bring new experimental techniques and methodologies to her research, the members of her group and the members of the I2M network. Furthermore, it is also timely that this work should be carried out now as 'immunology remains crassly empirical'.

适应性细胞免疫系统通过T细胞抗原受体（TCR）识别病原性抗原，TCR通过与抗原呈递细胞（APC）表面的主要组织相容性复合体（MHC）蛋白结合而识别抗原。免疫系统包含数百万个不同的TCR分子，其通过编码与肽-MHC（pMHC）复合物相互作用的TCR分子区域的基因片段的随机重排形成。每个T细胞表达一种特定的TCR种类或克隆型，这对于T细胞及其所属的克隆是独特的。T细胞与APC的相互作用是调节自身耐受和效应功能的关键。了解TCR-pMHC相互作用和TCR触发是找到控制T细胞活化的合适靶标的先决条件。本研究的目的是利用现有的数学模型和实验模型，为T细胞免疫学提供一种系统生物学方法：（1）了解T细胞受体（TCR-CD 3）触发、TCR聚集和CD 3亚基胞质尾部的构象变化，（2）了解中枢耐受诱导的T细胞谱系结构如何与胸腺自身相关抗原递呈统计数据，（3）了解T细胞数量是如何被稳态调节以维持T细胞库的大小和多样性的。该提案的总体目标是提供具有定量和系统生物学视角的适应性免疫学。这将通过利用现有的数学模型和实验数据来实现，以便（i）用初步实验数据测试现有的数学模型，（ii）改进这些数学模型，（iii）提出新的实验，以及（iv）产生新的实验可检验的假设。Molina-Paris博士的目标是使用随机方法模拟适应性免疫反应，并与实验免疫学家密切合作。拟议的研究项目福尔斯属于优先事项和使命的BBSRC：系统生物学和生物学的数学工具。因此，BBSRC研究发展奖学金对申请人和BBSRC的职权范围和英国科学来说都是及时的。该奖学金不仅将在研究员的研究中开辟重要的新方向，而且还将提供跨学科的维度，并为她的研究，她的团队成员和I2 M网络的成员带来新的实验技术和方法。此外，现在开展这项工作也是及时的，因为“免疫学仍然是一门粗糙的学科”。