Viruis Dynamics and Multiple Infection of Cells: Computational and Experimental A

描述（由申请方提供）：在各种感染的背景下，已通过实验和数学模型广泛研究了体外和体内病毒群与靶细胞之间的动力学。虽然这项工作导致了对疾病机制和抗病毒治疗效果的许多重要见解，但大多数都是基于单个细胞仅被单一病毒感染的假设。然而，近年来，已经清楚的是，细胞在各种不同的感染中经常被同一病毒的多个拷贝感染。这种合并感染可能会对病毒动力学产生深远影响，并影响感染的建立、病毒传播、疾病进程和对抗病毒药物的反应。研究合并感染的最佳实验系统是艾滋病毒，这是本提案的重点。我们试图提供一个全面的和定量的了解病毒复制动力学和直接发病机制是如何影响的共同感染，迄今为止一直缺乏的信息。这将在3种不同靶细胞类型的背景下使用HIV-1进行，以捕获病毒复制和共感染参数的变化。随后，我们的目标是确定这些复制动力学如何转化为病毒生长的动力学，因为病毒通过其靶细胞群传播。这只能通过构建数学模型来实现，该模型捕获实验数据并对不同复制情况下的病毒复制动态进行稳健的预测。两个根本上不同的建模方法将被认为是，一个常微分方程模型和基于代理的模型，它们之间的关系将被定义。这允许模型之间的交叉验证，并克服个别建模方法的固有弱点。模型结果进一步定义了要执行的实验，以测试模型预测，这是我们提案的核心组成部分。除了体外实验，我们的分析将使用离体淋巴组织培养与细胞单层单一培养进行比较，以提供我们研究的更高临床相关性。

DESCRIPTION (provided by applicant): The dynamics between virus populations and target cells in vitro and in vivo have been investigated extensively in the context of a variety of infections, both experimentally and with mathematical models. While this work has lead to many important insights into disease mechanisms and the efficacies of antiviral therapeutics, most of it has been based upon the assumption that individual cells are only infected with a single virus. In recent years, however, it has become clear that cells are frequently infected with multiple copies of the same virus in a variety of different infections. Such coinfection is likely to have a profound influence on viral dynamics and to influence the establishment of infection, viral spread, the course of disease and the response to antiviral drugs. The best experimental system to study coinfection is HIV, which is the focus of this proposal. We seek to provide a thorough and quantitative understanding of how virus replication kinetics and direct pathogenesis are influenced by coinfection, information which so far has been lacking. This will be done with HIV-1 in the context of 3 different target cell types in order to capture variation in viral replication and coinfection parameters. We subsequently aim to define how these replication kinetics translate into the dynamics of virus growth, as the virus spreads through its target cell population. This can only be achieved with the construction of mathematical models which capture the experimental data and make robust predictions regarding the dynamics of viral replication under different replication scenarios. Two fundamentally different modeling approaches will be considered, an ordinary differential equation model and an agent based model, and the relationship between them will be defined. This allows cross-validation between models and to overcome inherent weaknesses of individual modeling approaches. The model outcomes further define the experiments to be performed in order to test model predictions, which is a central component of our proposal. In addition to in vitro experiments, our analysis will be repeated using ex vivo lymphoid histoculture for comparison with cell monolayer monocultures, to provide higher clinical relevance of our studies.