Mathematically Modeling the regulation of immune responses to HIV-infection

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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.