Modeling of Lung HIV Cytokine/Chemokine Networks

描述(由申请人提供)：宿主肺内先天免疫功能的改变可能容易发生机会性感染，从而在艾滋病毒感染期间导致极大的发病率和死亡率。需要数学模型来帮助理解细胞因子、细胞因子拮抗剂和趋化因子之间的复杂相互作用，这些因素在HIV感染期间影响肺内的固有宿主免疫反应。到目前为止，分析仅限于描述艾滋病毒如何影响单个或小部分这些分子，而不是以协调方式影响宿主免疫的更大网络。我们团队开发了“反向工程”方法来模拟相互作用的蛋白质和信使核糖核酸的网络。我们将使用这些反向工程方法来确定肺部细胞因子/趋化因子网络结构，这些网络结构在HIV感染期间以及在高效抗逆转录病毒疗法(HAART)治疗后如何改变。逆向工程算法提出了通过迭代过程解析网络结构的最有效方法，在迭代过程中，对一个实验的数据进行分析，为下一个实验的设计提供信息。具体地说，我们将使用反向工程方法，在细胞系(U1和U937)以及来自HIV受试者(有或没有HAART)和HIV受试者的AM中创建细胞因子/趋化因子网络的数学模型。这将通过执行一系列实验来实现，在这些实验中，我们扰乱细胞因子/趋化因子网络的不同组件，测量网络组件的变化，并应用反向工程算法来确定下一个最具信息量的扰动以解析网络结构。将被测量和扰动的网络组件包括选定的细胞因子和趋化因子、信号通路分子、转录因子和这些部分的mRNA。识别这些关联系统中最核心的分子可能会提出新的治疗或疫苗方法，以增强宿主对艾滋病毒的免疫反应。

DESCRIPTION (provided by applicant): Alterations in host innate immune function within the lung may predispose to opportunistic infections that cause great morbidity and mortality during HIV infection. Mathematical models are needed to help understand the complex interactions of cytokines, cytokine antagonists, and chemokines that affect the innate host immune response within the lung during HIV infection. To date, analyses have been limited to descriptions of how HIV affects single or small sets of these molecules, instead of the larger network that acts in a coordinated manner to affect host immunity. Our group has developed "reverse engineering" methods to model networks of interacting proteins and mRNA. We will use these reverse engineering methods to determine the structure of the cytokine/chemokine networks in the lung, how these are altered during HIV infection, and after treatment with highly active antiretroviral therapy (HAART). The reverse engineering algorithms suggest the most efficient way to resolve the network structure through an iterative process in which analysis of data from one experiment informs the design of the next experiment. Specifically, we will create mathematical models of cytokine/chemokine networks, using reverse engineering methods, in cell lines (U1 and U937) and in AMs from HIV+ subjects (with or without HAART) and HIV- subjects. This will be accomplished by performing a series of experiments in which we perturb different components of the cytokine/chemokine networks, measure changes in the components of the network, and apply the reverse engineering algorithms to determine the next most informative perturbations to resolve the network structure. The components of the network that will be both measured and perturbed include selected cytokines and chemokines, signaling pathway molecules, transcription factors, and mRNA for these moieties. Identification of the most central molecules in these linked systems may suggest new therapeutic or vaccine approaches to bolster the host immune response to HIV.