RAPID: Multiscale Modeling Of SARS-CoV-2 Viral Intracellular and Intercellular Dynamics

________________________________________________________________________________________________________________ 最近出现的SARS-CoV-2病毒COVID-19病因代理人,在短短几个星期已引起了世界范围内的影响。在相当长的一段时间内，全球将感受到巨大的负面社会、经济和健康影响。必须采取许多补充性战略来处理这一问题并减轻其后果。显然需要的一种策略是更好地了解SARS-CoV-2的基本生物学。该项目的目标是创建SARS-CoV-2病毒细胞内和细胞间病毒动力学的多尺度模型。采用了系统病毒学方法。该项目将使人们了解这种病毒是如何工作的，并将为许多基础研究和开发有效药物和疗法的应用工作提供必要的框架。开发的模型将在开源许可下发布，并在GitHub网站上免费提供。该项目将在计算系统病毒学领域培养一名研究生。本项目基于目前对SARS-2019-CoV-2病毒反应网络的认识，建立了细胞内和细胞间模型。利用反应动力学理论，将反应网络拓扑结构转化为数学模型。一组描述病毒在感染细胞内复制动力学的常微分方程是用质量作用动力学范式制定的。通过对模型参数空间的蒙特卡罗采样，以及灵敏度分析和稳定性分析，确定了数学和生物约束条件。进行随机模拟以确定感染细胞亚群是否存在潜在的不同表型。最后，利用基本微积分原理，将细胞内模型与病毒复制动力学的标准细胞间模型耦合起来。多尺度模型与细胞内模型经过相同的分析，并且也是随机实施的，以确定纳入更高尺度信息是否会影响亚种群分布的预测。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

________________________________________________________________________________________________________________The recent emergence of the SARS-CoV-2 virus, the etiological agent of COVID-19, has caused worldwide repercussions in just a few short weeks. The tremendous negative social, economic and health impact will be felt for a considerable time around the globe. Numerous complementary strategies must be taken to address this issue and to ameliorate the consequences. One such strategy that is clearly required is a better understanding of the fundamental biology of SARS-CoV-2. The objective of this project is to create a multiscale model of the intracellular and intercellular viral dynamics of the SARS-CoV-2 virus. A systems virology approach is used. This project would deliver an understanding of how the virus works and will provide the framework necessary for numerous fundamental studies and applied efforts for developing effective drugs and therapies. The developed model would be released under an open source license and made freely available from the GitHub website. The project would train one graduate student in the area of computational systems virology. This project creates intracellular and intercellular models of the SARS-2019-CoV-2 virus based on the current understanding of the virus reaction network. The reaction network topology is translated into a mathematical model with the use of the theory of reaction kinetics. A set of ordinary differential equations describing the dynamics of viral replication within an infected cell is formulated with the use of the mass action kinetics paradigm. With the use of Monte Carlo sampling of the model’s parameter space, as well as sensitivity analysis and stability analysis, mathematical and biological constraints are identified. Stochastic simulation is carried out to determine whether subpopulations of infected cells exist with potentially different phenotypes. Finally, with the use of principles grounded in basic calculus, the intracellular model is coupled to a standard intercellular model of viral replication dynamics. The multiscale models undergo the same analyses as the intracellular model and is also implemented stochastically to determine if incorporating higher scale information influences prediction of subpopulation distribution.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.