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.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project (R01)
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AIDS Clinical Studies and Epidemiology Study Section (ACE)
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Gezmu, Misrak
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University of Southern California
Schools of Medicine
Los Angeles
United States
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