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）细胞在防御致病性感染和肿瘤中发挥重要作用。最近的实验直接挑战了20多年来为NK细胞耐受提供机制框架的“缺失自我”假说。因此，缺乏对来自各种刺激和抑制受体的信号整合导致NK细胞活化和耐受的机制理解。本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的计算方法与湿实验室实验，为理解NK细胞激活提供一个新的机制框架。由小鼠巨细胞病毒（CMV）编码配体刺激的基因工程人类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来定量地测试计算模型和实验结果。我们在提案中研究两个重叠的具体目标。1. 确定由对立NK受体引发的导致NK细胞活化的信号之间早期相互作用的机制。我们将开发空间均匀的计算模型，描述NK细胞与各种刺激和抑制配体相互作用的早期信号事件的随机动力学。模型预测将在使用人类NK细胞系的湿实验室实验中进行测试。2. 确定空间动力学和受体聚集以及相关信号分子在调节导致NK细胞活化的刺激和抑制信号中的作用。空间非均匀随机和确定性模拟结合成像和生化湿实验室实验，使用人类NK细胞系进行，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（扩散和运输）的影响。在成功完成提议的项目后，我们将有一个具有预测NK细胞激活能力的计算模型，这将很可能为针对病毒感染（如巨细胞病毒）和肿瘤的治疗干预提供策略，以及创建一个改进的机制框架，替代现有的自我缺失假说。

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.