Persistent virus infections (such as the hepatitis C virus and HIV) remain major problems for human health, and have not yielded to traditional approaches for the generation of vaccines. T cell responses are thought to play a key role in the immune response against many persistent viral infections, and are the focus of many vaccine candidates. A key problem is our incomplete understanding of the circumstances under which the T cell response following infection results in protection and when it causes pathology. Our approach involves going from the current qualitative description to a quantitative models for understanding the dynamics of the virus and T cell response during persistent virus in- fections. The development of quantitative models is particularly important in immunology and pathogenesis for two reasons: first, the populations of virus and the T cells of the adaptive im- mune response can change over a thousand fold in magnitude during the course of infection; second, the non-linear interactions between the components of the system (pathogens, cells and molecules of the immune response) can result in complex dynamics that cannot be intu- ited from qualitative descriptions alone. Because of the complexity of biological systems, it is essential for mathematical models to be validated. We will test our models by confronting them with experimental data from Lymphocytic choriomeningitis virus (LCMV) infections of mice. We will validate our models by fitting the models to data on the dynamics of virus and immune responses during persistent LCMV infections, as well as generating and experimentally testing novel predictions of the model. The LCMV system is particularly amenable to studying pro- tection and pathology following vaccination because the ease of adoptive transfer of defined virus-specific T cell populations into recipient mice allows manipulation of both the numbers and properties of the T cells, as well as the host environment, thus facilitating dissection of the factors that control virus and reduce pathology. We will apply our quantitative mathematical models to explore novel strategies for treatment and vaccination against persistent pathogens. These strategies involve the combined use of antiviral drugs and immune-modulating antibodies that reactivate the T cell response. We will test these strategies in the LCMV experimental system.
We will us an integrated mathematical modeling and experimental approach to study the role of CD8 T cell responses to persistent infections in a mouse model system. The work will focus on exploring the conditions under which vaccine-induced CD8 T cells provide protection and when they increase pathology. We will apply our results to explore new strategies for treatment and vaccination against persistent infections.
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