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 inflammatory 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 genetic and bioinformatics projects ofthe Program;however, by focusing on mechanistic modeling, the project 6 will not merely function as a repository of results and mechanisms, but yield additional and significant insights. Here, we will first (Aim 1) leverage existing 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 existing 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 infection 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 opportunities for therapeutic intervention, characterize the mechanistic roles of SNPs associated with elite-suppressor, and contrast dendritic cells in different microenvironments and exposure histories and T-lymphocytes. In addition (Aim 4), we will develop web-based user interfaces to facilitate integration of computational simulations into experimental analysis within the Program as well as the broader HIV research community.

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program Projects (P01)
Project #
7P01AI090935-05
Application #
8707333
Study Section
Special Emphasis Panel (ZAI1-EC-A)
Project Start
Project End
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
5
Fiscal Year
2014
Total Cost
$450,339
Indirect Cost
$104,849
Name
Sanford-Burnham Medical Research Institute
Department
Type
DUNS #
020520466
City
La Jolla
State
CA
Country
United States
Zip Code
92037
Hansen, Maike M K; Desai, Ravi V; Simpson, Michael L et al. (2018) Cytoplasmic Amplification of Transcriptional Noise Generates Substantial Cell-to-Cell Variability. Cell Syst 7:384-397.e6
Jain, Prashant; Boso, Guney; Langer, Simon et al. (2018) Large-Scale Arrayed Analysis of Protein Degradation Reveals Cellular Targets for HIV-1 Vpu. Cell Rep 22:2493-2503
Hansen, Maike M K; Wen, Winnie Y; Ingerman, Elena et al. (2018) A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization. Cell 173:1609-1621.e15
Alvarez, Raymond A; Maestre, Ana M; Law, Kenneth et al. (2017) Enhanced FCGR2A and FCGR3A signaling by HIV viremic controller IgG. JCI Insight 2:e88226
Park, Ryan J; Wang, Tim; Koundakjian, Dylan et al. (2017) A genome-wide CRISPR screen identifies a restricted set of HIV host dependency factors. Nat Genet 49:193-203
Ball, K Aurelia; Johnson, Jeffrey R; Lewinski, Mary K et al. (2016) Non-degradative Ubiquitination of Protein Kinases. PLoS Comput Biol 12:e1004898
Hultquist, Judd F; Schumann, Kathrin; Woo, Jonathan M et al. (2016) A Cas9 Ribonucleoprotein Platform for Functional Genetic Studies of HIV-Host Interactions in Primary Human T Cells. Cell Rep 17:1438-1452
Cheng, Zhang; Hoffmann, Alexander (2016) A stochastic spatio-temporal (SST) model to study cell-to-cell variability in HIV-1 infection. J Theor Biol 395:87-96
Guo, Haitao; König, Renate; Deng, Meng et al. (2016) NLRX1 Sequesters STING to Negatively Regulate the Interferon Response, Thereby Facilitating the Replication of HIV-1 and DNA Viruses. Cell Host Microbe 19:515-528
Heaton, Nicholas S; Moshkina, Natasha; Fenouil, Romain et al. (2016) Targeting Viral Proteostasis Limits Influenza Virus, HIV, and Dengue Virus Infection. Immunity 44:46-58

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