(182c) Cd4+ T-Cell Epitope Identification Using Yeast Displaying Single Chain Class II Mhc Molecules as Artificial Apcs

T-cells respond to selected peptide epitopes in complex with major histocompatibility complex (MHC) molecules expressed on antigen presenting cells (APCs) through their unique receptors, triggering their effector functions. The elicited functions determine how effectively the infections can be eliminated and insufficient or inappropriate responses can result in immunopathogenesis or autoimmunity. Therefore, epitopes are vital elements in initiating and modulating T-cell responses and great efforts have been devoted to identification of these T-cell epitopes in the past two decades. T-cell epitopes are currently identified mainly by screening either synthetic peptides spanning the entire pathogenic protein or combinatorial peptide libraries. The former method is normally time-consuming and expensive, while the latter one is often limited by the library size and heavily relies on the knowledge of MHC-binding motif.

To address the limitations of current methods for epitope identification, we developed a novel T-cell epitope identification method using yeast as artificial APCs. Using human classII molecule HLA-DR1 as a model system, we displayed the wild-type single-chain HLA-DR1 molecules with HA306-318 epitope covalently tethered by flexible linkers on yeast surface. It was found that there is a general correlation between the protein expression level and the peptide epitope binding affinity with HLA-DR1. More importantly, it was shown that yeast displaying HLA-DR1-HA complex could be used as artificial APCs to activate hybridoma T-cells. By screening a library of HLA-DR1 in complex with different peptides generated from the pathogenic protein hemagglutinin (HA) of influenza virus A using fluoresence-activated cell sorting (FACS), potential “good binders” were enriched (40%). Following a second screening step using HA1.7 hybridoma cells, the antigenic epitope PKYVKQNTLKLATGMRNVPEKQT was identified. Using this method, no knowledge of MHC binding properties is required and the theoretical library size required to achieve the enrichment is only about 1000. Although the method was demonstrated by identifying a viral epitope, it should be generally applicable to the identification of T-cell epitopes from other systems such as cancer and autoimmune diseases.