Better understanding of the primary phase of HIV infection through quantitative computational modeling is crucial for deciphering viral pathogenesis and for developing an effective vaccine, since vaccine-elicited adaptive immune responses are expected to exert their major effects on viral replication and evolution during the primary phase. Previous efforts to model this early stage of infection have been unable to fully exploit available clinical data since current models did not integrate viral replication and sequence evolution in a single framework. We will construct a model for primary HIV infection that will incorporate virus replication dynamics and viral sequence diversification simultaneously. Major innovations of our model will include (i) comprehensive integration of virologic kinetics and sequence data and (ii) invention of web-based software to visualize the spatio-temporal dynamics of HIV infection. We will then use this simulation to model vaccine- elicited effects on host immune control of HIV infection.
In Aim 1, a Monte-Carlo (MC) simulation illustrating both viral kinetics and sequence evolution in the primary phase of HIV infection will be constructed. The HIV provirus population of infected cells will be simulated using virologic parameters, including dynamic reproductive ratio, generation time, and reverse transcriptase single cycle error rate.
In Aim 2, we apply the model to data from the NIAID-supported phase IIB evaluation of Merck's recombinant Ad5-HIV gag/pol/nef vaccine (STEP Study;Merck/HIV Vaccine Trials Network collaboration) in order to understand why this vaccine elicited HIV-specific CD8 cells in many trial participants but had no effect on virus load in those individuals who experienced breakthrough infections. We will use our model to test three hypotheses that might explain this lack of efficacy: (1) high levels of antigenic distance between the transmitted strain and the vaccine strain may have compromised vaccine efficacy (2) viral escape from vaccine-induced CD8+ T cell responses may have resulted in the enhancement of viral replication or (3) vaccine-related CD4+ T cell activation may have amplified virus replication, thereby offsetting the potential benefit conferred by virus- specific CD8 cells. Finally, Aim 3 will invent web-based simulation tools for prediction of vaccine efficacy using clinical data inputs. These studies are expected to result in a novel and comprehensive computational model for primary HIV infection.

Public Health Relevance

The initial phase of infection with human immunodeficiency virus (HIV) plays a crucial role in determining subsequent progression to AIDS and probing vaccine efficacy, but remains poorly understood. This project will develop a computational simulation that can be used to model this critical phase of virus infection. The model is expected to have important utility in helping to design safe and effective HIV/AIDS vaccines.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI083115-05
Application #
8304318
Study Section
AIDS Clinical Studies and Epidemiology Study Section (ACE)
Program Officer
Gezmu, Misrak
Project Start
2009-07-01
Project End
2014-06-30
Budget Start
2012-07-01
Budget End
2014-06-30
Support Year
5
Fiscal Year
2012
Total Cost
$401,841
Indirect Cost
$156,816
Name
University of Southern California
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Park, Sung Yong; Love, Tanzy M T; Perelson, Alan S et al. (2016) Molecular clock of HIV-1 envelope genes under early immune selection. Retrovirology 13:38
Park, Sung Yong; Mack, Wendy J; Lee, Ha Y (2016) Enhancement of viral escape in HIV-1 Nef by STEP vaccination. AIDS 30:2449-2458
Love, Tanzy M T; Park, Sung Yong; Giorgi, Elena E et al. (2016) SPMM: estimating infection duration of multivariant HIV-1 infections. Bioinformatics 32:1308-15
Park, Sung Yong; Goeken, Nolan; Lee, Hyo Jin et al. (2014) Developing high-throughput HIV incidence assay with pyrosequencing platform. J Virol 88:2977-90
Park, Min-Sun; Park, Sung Yong; Miller, Keith R et al. (2013) Accurate structure prediction of peptide-MHC complexes for identifying highly immunogenic antigens. Mol Immunol 56:81-90
Park, Sung Yong; Love, Tanzy M T; Nelson, Jeremy et al. (2011) Designing a genome-based HIV incidence assay with high sensitivity and specificity. AIDS 25:F13-9
Cigler, Petr; Lytton-Jean, Abigail K R; Anderson, Daniel G et al. (2010) DNA-controlled assembly of a NaTl lattice structure from gold nanoparticles and protein nanoparticles. Nat Mater 9:918-22
Love, Tanzy M T; Thurston, Sally W; Keefer, Michael C et al. (2010) Mathematical modeling of ultradeep sequencing data reveals that acute CD8+ T-lymphocyte responses exert strong selective pressure in simian immunodeficiency virus-infected macaques but still fail to clear founder epitope sequences. J Virol 84:5802-14
Lee, Ha Youn; Giorgi, Elena E; Keele, Brandon F et al. (2009) Modeling sequence evolution in acute HIV-1 infection. J Theor Biol 261:341-60
Bimber, Benjamin N; Chugh, Pauline; Giorgi, Elena E et al. (2009) Nef gene evolution from a single transmitted strain in acute SIV infection. Retrovirology 6:57