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

病毒动力学和细胞多重感染：计算和实验 A

基本信息

批准号：
8309952
负责人：
DAVID N LEVY
金额：
$ 37.51万
依托单位：
UNIVERSITY OF CALIFORNIA-IRVINE
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-08-03 至 2015-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8309952
关键词：
3-Dimensional Affect Antiviral Agents Biological Biology CD4 Positive T Lymphocytes Cell Death Cell Proliferation Cells Cessation of life Clear Cell Collaborations Complement Complex Computer Simulation Data Development Disease Drug Formulations Equation Evolution Foundations Future Genetic Recombination Growth HIV HIV-1 Immune response In Vitro Individual Infection Kinetics Laws Lead Lymphoid Modeling Outcome Pathogenesis Pharmaceutical Preparations Play Population Preparation Process Production Property Proviruses Rest Role Science Structure System Target Populations Testing Therapeutic Time To specify Translating Validation Variant Viral Viral Pathogenesis Virus Virus Diseases Virus Replication Work base cell type clinically relevant data modeling design in vivo insight macrophage mathematical model monolayer novel particle reproductive research study response transmission process virology

项目摘要

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.

描述（由申请人提供）：已经在各种感染的背景下通过实验和数学模型对病毒群体和靶细胞之间的体外和体内动态进行了广泛的研究。虽然这项工作对疾病机制和抗病毒治疗的功效产生了许多重要的见解，但其中大部分都是基于单个细胞仅感染单一病毒的假设。然而，近年来，人们越来越清楚，在各种不同的感染中，细胞经常被同一病毒的多个拷贝感染。这种双重感染可能对病毒动态产生深远影响，并影响感染的建立、病毒传播、病程和抗病毒药物的反应。研究混合感染的最佳实验系统是艾滋病毒，这是本提案的重点。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了解，但迄今为止还缺乏这些信息。这将在 3 种不同靶细胞类型的背景下使用 HIV-1 来完成，以便捕获病毒复制和共感染参数的变化。随后，我们的目标是定义当病毒在其目标细胞群中传播时，这些复制动力学如何转化为病毒生长的动力学。这只能通过构建数学模型来实现，该数学模型捕获实验数据并对不同复制场景下的病毒复制动态做出可靠的预测。将考虑两种根本不同的建模方法，即常微分方程模型和基于代理的模型，并将定义它们之间的关系。这允许模型之间进行交叉验证并克服各个建模方法的固有弱点。模型结果进一步定义了为了测试模型预测而要进行的实验，这是我们提案的核心组成部分。除了体外实验外，我们还将使用离体淋巴组织培养物重复分析，以与细胞单层单一培养物进行比较，以提供我们研究的更高临床相关性。