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

描述（由申请人提供）：在体外和体内，病毒种群和靶细胞之间的动力学已经在各种感染的背景下进行了广泛的研究，包括实验和数学模型。虽然这项工作对疾病机制和抗病毒疗法的疗效有许多重要的见解，但大多数研究都是基于单个细胞只被一种病毒感染的假设。然而，近年来，人们已经清楚地发现，在各种不同的感染中，细胞经常被同一病毒的多个副本感染。这种共同感染可能对病毒动力学产生深远影响，并影响感染的建立、病毒传播、病程和对抗病毒药物的反应。研究共同感染的最佳实验系统是HIV，这也是本提案的重点。我们寻求对病毒复制动力学和直接发病机制如何受到共感染的影响提供全面和定量的理解，这是迄今为止所缺乏的信息。这将在3种不同靶细胞类型的背景下对HIV-1进行，以捕获病毒复制和共感染参数的变化。我们随后的目标是定义这些复制动力学如何转化为病毒生长动力学，因为病毒通过其靶细胞群传播。这只能通过建立数学模型来实现，该模型可以捕获实验数据，并对不同复制场景下病毒复制的动态进行稳健的预测。将考虑两种根本不同的建模方法，常微分方程模型和基于智能体的模型，并定义它们之间的关系。这允许模型之间的交叉验证，并克服单个建模方法的固有弱点。模型结果进一步定义了要进行的实验，以测试模型预测，这是我们建议的核心组成部分。除了体外实验外，我们的分析将使用离体淋巴组织培养重复，与单层细胞单层培养进行比较，以提供更高的临床相关性。

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.