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

描述（由申请人提供）：自然杀伤（NK）细胞在防御病原性感染和肿瘤中发挥重要作用。20多年来为NK细胞耐受性提供机制框架的“自我缺失”假说已受到最近实验的直接挑战。因此，缺乏对导致NK细胞活化和耐受的来自各种刺激性和抑制性受体的信号整合的机制理解。该提案旨在通过将植根于统计物理学，非线性动力学和工程学的计算方法与湿实验室实验协同结合，产生一种新的机制框架来理解NK细胞活化。由小鼠巨细胞病毒（CMV）编码的配体刺激的基因工程人NK细胞系将用于验证计算模型和测试模型预测。这种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，用实验结果定量地测试计算模型。我们调查了提案中两个重叠的具体目标。1.确定导致NK细胞活化的相反NK受体启动的信号之间早期相互作用的潜在机制。我们将开发空间均匀的计算模型，描述随机动力学的早期信号事件在NK细胞与不同的刺激和抑制配体相互作用。将使用人NK细胞系针对湿实验室实验测试模型预测。2.确定受体和相关信号分子的空间动力学和聚集在调节导致NK细胞活化的刺激和抑制信号中的作用。将使用人NK细胞系进行空间不均匀随机和确定性模拟，结合成像和生化湿实验室实验，以确定受体-配体复合物和受体结合信号分子的微观聚类和空间动力学（扩散和转运）的影响。在成功完成拟议的项目后，我们将拥有一个具有NK细胞激活预测能力的计算模型，该模型很可能为针对病毒感染（如CMV）和肿瘤的治疗干预提供策略，并创建一个改进的机制框架来替代现有的缺失自我假设。

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.