Mathematically Modeling the regulation of immune responses to HIV-infection

该项目将在项目1-5产生的大量重要数据的基础上开发一个 HIV感染和宿主反应相互作用的计算模型以研究有效性 宿主免疫反应，并开发基于以下方面的治疗和预防性治疗策略 先天免疫力。PIS在两个相关的领域率先进行了迭代建模和实验研究 互补主题：宿主炎症和先天免疫反应(霍夫曼)和艾滋病毒基因 方案和命运决策(温伯格)。建议的项目与纯粹的 该计划的试验性项目以及基因和生物信息项目；然而，通过将重点放在 通过机械建模，项目6不仅将作为成果和机制的储存库发挥作用，而且 产生额外的和重要的见解。 在这里，我们将首先(目标1)利用TLR信令网络(霍夫曼)的现有专业知识，以数据为基础 来自协作项目，以及我们自己实验室中的一些关键测量结果，以构建 主机响应网络。下一步(目标2)我们将利用现有的艾滋病毒基因电路专业知识(Weinberger)， 基于来自协作项目的数据以及我们自己的实验室中的一些关键测量数据来构建 艾滋病毒感染机制的模型。然后我们将整合HIV感染和宿主的模型 关注HIV抗性因素的反应以及操纵宿主反应的病毒辅助蛋白 发信号。最后(目标3)，我们将应用该模型来确定关键机制和机会 治疗干预，表征与精英-抑制者相关的SNPs的机械作用，以及 对比不同微环境、不同接触史的树突状细胞和T淋巴细胞。此外 (目标4)，我们将开发基于Web的用户界面，以促进将计算模拟集成到 该计划内的实验分析以及更广泛的艾滋病毒研究社区。

This project will build on the large amount of important data generated by projects 1-5 to develop a computational model of the HIV infection and host response interactions in order to study the effectiveness of the host immune response and develop therapeutic and preventative therapeutic strategies based on innate immunity. The Pis have pioneered iterative modeling and experimental studies in the two relevant complementary topics: the host infiammatory and innate immune response (Hoffmann) and HIV genetic programs and fate decision making (Weinberger). The proposed project is closely integrated into the purely experimental as well as genefic and bioinformafic projects ofthe Program; however, by focusing on mechanisfic modeling, the project 6 will not merely funcfion as a repository of results and mechanisms, but yield addifional and significant insights. Here, we will first (Aim 1) leverage exisfing expertise in TLR signaling networks (Hoffmann), build on data from collaborative projects, as well as some key measurements in our own lab to construct a model for the host response network. Next (Aim 2) we will leverage exisfing expertise in HIV gene circuit (Weinberger), build on data from collaborative projects, as well as some key measurements in our own lab to construct a model for the HIV infection mechanism. We will then integrate the models for HIV infecfion and host responses focusing on HIV resistance factors as well as viral accessory proteins manipulating host response signaling. Finally (Aim 3), we will apply the model to identify critical mechanisms and opportunifies for therapeufic intervention, characterize the mechanistic roles of SNPs associated with elite-suppressor, and contrast dendrific cells in different microenvironments and exposure histories and T-lymphocytes. In addition (Aim 4), we will develop web-based user interfaces to facilitate integrafion of computafional simulafions into experimental analysis within the Program as well as the broader HIV research community.