Working Models of HIV Persistence & Evolution

HIV 持久性的工作模型

• 批准号: 7132169
• 负责人: IGOR M ROUZINE
• 金额: $ 32.7万
• 依托单位: TUFTS UNIVERSITY BOSTON
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7132169
• 关键词: HIV infections; evolution; mathematical model; model; virus replication

DESCRIPTION (provided by applicant): HIV infection involves many different cell types (infected cells, uninfected cells permissive for virus replication, HIV specific immune cells, and others) which interact with each other and whose numbers, in general, depend on time. Because of interaction among its parts, the system automatically arrives at an approximate steady state coincident with the asymptomatic phase of an HIV infection. The replicating virus population remains quite constant but exhibits considerable genetic variation in time (and among sampled sequences). Our long-term goal is to use mathematical modeling to aid in understanding how such a system can work. Our approach is to (i) select mathematical models of HIV infection based on the criterion that all their predictions agree with the known features of HIV pathogenesis in representative individuals and (ii) formulate predictions for new experiments to test the models. This strategy of "multiple match" has been successfully used in the physical sciences for dealing with complex systems of unknown structure, but it is only being implemented in HIV research. We will apply this strategy to develop models of virus-immune cell interaction in .vivo and explain the mechanism of steady state, and to understand the principal factors of evolution of drug resistance and antigenic escape. At this stage of our research, we will put emphasis on follow-up tests of our models in collaborating groups and design of new tests of updated models.

描述（由申请人提供）：HIV感染涉及许多不同的细胞类型（感染细胞、允许病毒复制的未感染细胞、HIV特异性免疫细胞等），这些细胞相互作用，其数量通常取决于时间。由于其各部分之间的相互作用，系统自动达到与HIV感染的无症状阶段一致的近似稳定状态。复制的病毒群体保持相当恒定，但在时间上（以及在采样序列中）表现出相当大的遗传变异。我们的长期目标是使用数学建模来帮助理解这样一个系统如何工作。我们的方法是（i）选择数学模型的基础上的标准，所有的预测同意在代表性的个人和（ii）制定新的实验来测试模型的预测HIV感染的发病机制的已知特征。这种“多重匹配”的策略已经成功地用于物理科学中处理未知结构的复杂系统，但它只在艾滋病毒研究中实施。我们将应用这一策略来开发体内病毒-免疫细胞相互作用的模型，并解释稳态的机制，并了解耐药性和抗原逃逸进化的主要因素。在我们的研究的这个阶段，我们将把重点放在我们的模型在合作小组的后续测试和设计更新的模型的新的测试。