A computational model to uncover basic signaling mechanisms of NK cell activation

揭示 NK 细胞激活基本信号机制的计算模型

基本信息

批准号：
8434574
负责人：
Jayajit Das
金额：
$ 18.56万
依托单位：
RESEARCH INST NATIONWIDE CHILDREN'S HOSP
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-04-10 至 2014-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8434574
关键词：
Affinity B-Lymphocytes Binding Biochemical Cell Line Cells Communicable Diseases Complex Computer Simulation Computing Methodologies Conflict (Psychology)Cytomegalovirus Development Diffusion Engineering Event Feedback Goals Guidelines Herpesviridae Infections Human Human Engineering Image Immune Immune response Immunity Infection Kinetics Lead Life Ligands Major Histocompatibility Complex Malignant Neoplasms Mediating Membrane Microscopic Modeling Murid herpesvirus 1 Mus NK Cell Activation Natural Killer Cells Nonlinear Dynamics Outcome PTPN6 gene Patients Phosphoric Monoester Hydrolases Phosphotransferases Physics Plant Roots Play Population Process Proteins Resistance Role Signal Pathway Signal Transduction Signaling Molecule Stimulus System T-Lymphocyte Testing Therapeutic Therapeutic Intervention Time Virus Diseases adapter protein base cell killing cytokine design fluorescence imaging human disease improved inhibitor/antagonist model design neoplastic cell pathogen protein activation protein function receptor receptor binding research study response simulation success tumor

项目摘要

DESCRIPTION (provided by applicant): Natural Killer (NK) cells play a major role in defense against pathogenic infections and tumors. The "missing- self" hypothesis that provided a mechanistic framework for NK cell tolerance for more than 20 years has been challenged directly by recent experiments. Thus, a mechanistic understanding of signal integration from a variety of stimulatory and inhibitory receptors leading to NK cell activation and tolerance is lacking. This proposal seeks to produce a new mechanistic framework for understanding NK cell activation by synergistically combining computational approaches rooted in statistical physics, nonlinear dynamics and engineering with wet lab experiments. Genetically engineered human NK cell lines stimulated by mouse cytomegalovirus (CMV) encoded ligands will be used to validate the computational model and test model predictions. This unique experimental system allows us to quantitatively test the computational model with experimental outcomes by precisely controlling the numbers and types of the ligands and receptors. We investigate two overlapping specific aims in the proposal. 1. Determine mechanisms underlying the early time interplay between signals initiated by opposing NK receptors that lead to NK cell activation. We will develop spatially homogeneous computational model describing stochastic kinetics of early time signaling events in NK cells interacting with diverse stimulatory and inhibitory ligands. Model predictions will be tested against wet lab experiments using human NK cell lines. 2. Determine the role of spatial kinetics and clustering of receptors and associated signaling molecules in modulating stimulatory and inhibitory signals leading to NK cell activation. Spatially inhomogeneous stochastic and deterministic simulations combined with imaging and biochemical wet lab experiments using human NK cell lines will be carried out to determine the effect of microscopic clustering and spatial kinetics (diffusion and transport) of receptor-ligand complexes and receptor-bound signaling molecules. At successful completion of the proposed projects, we will have a computational model with predictive capabilities for NK cell activation that will very likely provide strategies for therapeutic interventions against viral infections (such as CMV) and tumors, as well as, create an improved mechanistic framework alternate to the existing missing-self hypothesis.

描述（由申请人提供）：自然杀手（NK）细胞在防御致病感染和肿瘤中起着重要作用。最近实验直接挑战了20多年的NK细胞耐受性机械框架的“缺失自我”假设。因此，缺乏对导致NK细胞激活和耐受性的多种刺激和抑制受体对信号整合的机械理解。该提案旨在通过协同结合基于统计物理，非线性动力学和工程技术的计算方法来生成一个新的机械框架，以了解NK细胞的激活。由小鼠巨细胞病毒（CMV）编码的配体刺激的基因设计的人NK细胞系将用于验证计算模型和测试模型预测。这个独特的实验系统使我们能够通过精确控制配体和受体的数量和类型来定量测试通过实验结果测试计算模型。我们调查了该提案中的两个重叠特定目标。 1。确定由导致NK细胞激活的NK受体引发的信号之间的早期相互作用的机制。我们将开发出空间均匀的计算模型，描述NK细胞中早期信号事件的随机动力学与各种刺激性和抑制性配体相互作用。模型预测将对使用人NK细胞系进行湿实验室实验进行测试。 2。确定空间动力学以及受体的聚类以及相关的信号分子在调节刺激和抑制信号中导致NK细胞激活的作用。将在空间上进行不均匀的随机和确定性模拟，并使用人NK细胞系结合成像和生化湿实验室实验，以确定显微镜聚类和空间动力学（扩散和运输）受体 - 辅助配合物和受体结合物和受体结合信号分子的影响。在成功完成拟议项目的过程中，我们将拥有一个具有NK细胞激活能力的计算模型，很可能很可能为针对病毒感染（例如CMV）和肿瘤的治疗干预提供策略，并为现有缺失的假设提供了改进的机械框架。