Individuals who develop rapid progression of HIV-1 infection have been shown to have a high burden of relatively homogeneous viruses (quasi species) and a low frequency of cytotoxic T lymphocytes that respond to HIV-1, whereas individuals who progress more slowly or not at all have a lower burden of a much more diverse viral quasi species and evidence of vigorous CTL response to HIV-1. We hypothesize that these individuals' antiviral cellular immune responses (CTL and T helper) are effectively exerting selective pressure upon the viral quasi species, leading to amino acid changes, quasi species diversification, and modified interaction with the host immune system due to altered binding of MHC-binding regions. This proposal describes the development of EpiMatrix, a computer-driven T cell epitope prediction algorithm, and the application of the algorithm to the evaluation of quasi species evolution. It is proposed that the replacement of anchor- based motifs with extended matrix-based motifs (as in EpiMatrix) will improve the predictive capacity of T cell epitope prediction algorithms for selected MHC alleles and will permit evaluation of quasi species evolution.
The specific aims of the proposed work are: To develop EpiMatrix, a second generation T cell epitope prediction program. To apply EpiMatrix to HIV-1 quasi species; predict, synthesize, & test MHC-binding regions/T epitopes. To evaluate the impact of quasi species evolution on T cell response to epitopes defined in the previous aim. The use of EpiMatrix of predict MHC-binding regions and T cell epitopes within variable regions will allow us, for the first time, to accurately assess the influence of sequence diversity within both conserved and variable regions upon the ability of the host cellular immune response to recognize and respond to HIV-1 quasi species. The successful completion of this project will lead to an enhanced understanding of the interplay between the antiviral pressure of the cellular immune responses, viral burden, and diversity of quasi species within infected individuals. These fundamental interactions that define HIV-1 infection are critical to our understanding of HIV-1 pathogenesis. In addition, the epitope prediction method and epitopes defined during these investigations will aid in the development of a vaccine against AIDS.
| Sowers, Maryfran; Karvonen-Gutierrez, Carrie A; Palmieri-Smith, Riann et al. (2009) Knee osteoarthritis in obese women with cardiometabolic clustering. Arthritis Rheum 61:1328-36 |
| De Groot, Anne S (2004) Immunome-derived vaccines. Expert Opin Biol Ther 4:767-72 |
| De Groot, Anne S; Rappuoli, Rino (2004) Genome-derived vaccines. Expert Rev Vaccines 3:59-76 |
| De Groot, Anne S; Martin, William (2003) From immunome to vaccine: epitope mapping and vaccine design tools. Novartis Found Symp 254:57-72; discussion 72-6, 98-101, |
| De Groot, Anne S; Jesdale, Bill; Martin, William et al. (2003) Mapping cross-clade HIV-1 vaccine epitopes using a bioinformatics approach. Vaccine 21:4486-504 |
| De Groot, Anne S; Sbai, Hakima; Aubin, Caitlin Saint et al. (2002) Immuno-informatics: Mining genomes for vaccine components. Immunol Cell Biol 80:255-69 |
| Jin, X; Roberts, C G; Nixon, D F et al. (2000) Identification of subdominant cytotoxic T lymphocyte epitopes encoded by autologous HIV type 1 sequences, using dendritic cell stimulation and computer-driven algorithm. AIDS Res Hum Retroviruses 16:67-76 |
