A novel computational model of B cell signaling and activation

B 细胞信号传导和激活的新型计算模型

• 批准号: 8120735
• 负责人: CRAIG J. BENHAM
• 金额: $ 28.05万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-05 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8120735
• 关键词: Address; Affinity; Antigens; B-Cell Activation; B-Lymphocytes; Binding; Biological; Cell membrane; Cell surface; Cells; Complex; Computer Simulation; Coupling; Crowding; Data; Diffusion; Discrimination; Disease; Functional disorder; Future; Goals; Image; Immune; Immune response; Immunologist; In Vitro; Investigation; Laboratories; Maps; Measurable; Mediating; Membrane; Methods; Modeling; Other Genetics; Pattern Formation; Physiological; Positioning Attribute; Process; Reaction; Receptors, Antigen, B-Cell; Regulation; Research; Running; Scheme; Signal Pathway; Signal Transduction; Synapses; System; Techniques; Work; computer program; in vivo; insight; novel; predictive modeling; public health relevance; receptor; research study; response; simulation; single molecule; synaptogenesis; tool; Address; Affinity; Antigens; B-Cell Activation; B-Lymphocytes; Binding; Biological; Cell membrane; Cell surface; Cells; Complex; Computer Simulation; Coupling; Crowding; Data; Diffusion; Discrimination; Disease; Functional disorder; Future; Goals; Image; Immune; Immune response; Immunologist; In Vitro; Investigation; Laboratories; Maps; Measurable; Mediating; Membrane; Methods; Modeling; Other Genetics; Pattern Formation; Physiological; Positioning Attribute; Process; Reaction; Receptors, Antigen, B-Cell; Regulation; Research; Running; Scheme; Signal Pathway; Signal Transduction; Synapses; System; Techniques; Work; computer program; in vivo; insight; novel; predictive modeling; public health relevance; receptor; research study; response; simulation; single molecule; synaptogenesis; tool

DESCRIPTION (provided by applicant): One of the long-term goals of our laboratory is to develop and combine different analytical and computer simulation techniques into a unified computational modeling scheme to investigate B cell responses. We are developing this proposed in silico model specifically to investigate the mechanism of B cell immune recognition, signaling, and activation. Computational modeling will be carried out synergistically with biological experiments in an iterative manner. The stochastic character of our model enables us to capture any cell-to-cell stochastic fluctuations present in the system. We rigorously map the probabilistic parameters of our model to the reaction and diffusion rate constants that are measurable in biological experiments. This proposed work is going to deliver the following: (i) computational and theoretical approaches to investigate B cell receptor clustering in the form of immune synapses and caps for the cases of membrane-bound and soluble antigens respectively, (ii) a computer model of receptor diffusion in a heterogeneous B cell membrane in parallel with single molecules tracking studies, (iii) a computational model of B cell signaling that can be used by B cell immunologists to study B cell antigen recognition, signaling, and activation under a plethora of different physiological conditions by running controlled in silico experiments. Our approach will also be able to address the question of how B cells generate a graded response by recognizing antigens of widely varying affinities. PUBLIC HEALTH RELEVANCE: The B cell immune response is a complex process and a precise mechanism of B cell signaling and activation is not easy to investigate from in vivo and in vitro experiments alone. In the proposed research, we plan to develop computer models of B cell antigen recognition, signaling, and activation. Our computer model will help elucidate the fundamental regulation mechanisms underlying the B cell immune response and could potentially be applied to investigate B cell mediated diseases.

描述（由申请人提供）：我们实验室的长期目标之一是将不同的分析和计算机仿真技术开发和结合到研究B细胞响应的统一计算建模方案中。我们正在在计算机模型中开发这种提出的，以研究B细胞免疫识别，信号传导和激活的机制。计算建模将以迭代方式与生物学实验协同进行。我们模型的随机特征使我们能够捕获系统中存在的任何细胞间随机波动。我们将模型的概率参数严格映射到生物学实验中可测量的反应和扩散速率常数。这项提出的工作将提供以下内容：（i）计算和理论方法，以免疫突触和帽的形式研究B细胞受体聚类，分别以膜结合和可溶性抗原的形式进行（ii）一种在异构B细胞中的受体扩散的计算机模型，该模型与单个分解相似的B细胞相似，以实现BB细胞的使用（II II II II），（III）（II II II II II），（III）（II II II II II），（细胞免疫学家通过在有机硅实验中控制的多种不同生理条件下研究B细胞抗原识别，信号传导和激活。我们的方法还将能够解决B细胞如何通过识别较大亲和力的抗原产生分级反应的问题。 公共卫生相关性：B细胞免疫反应是一个复杂的过程，B细胞信号传导和激活的精确机制并不容易从体内和仅凭体外实验进行研究。在拟议的研究中，我们计划开发B细胞抗原识别，信号传导和激活的计算机模型。我们的计算机模型将有助于阐明B细胞免疫反应背后的基本调节机制，并有可能应用于研究B细胞介导的疾病。