A comparison of two methods for T cell epitope mapping: “cell free” in vitro versus Immunoinformatics

Abstract

Methods for identifying physiologically relevant T-cell epitopes are critically important for development of vaccines and the design of therapeutic proteins. As the number of proteins that are being evaluated for putative immunogenicity expands, rapid and accurate tools are in great demand. Several methods to identify T-cell epitopes have been developed, the most recent of which is a cell free system consisting of a minimal set of proteases incubated with HLA DRB1*0101, HLA-DM and whole antigen. Isolation and sequencing of the HLA bound peptides using mass spectrometry allows for the prospective identification of immuno-dominant T-cell epitopes. We present here, a comparison of this cell free system to an in silico approach to T-cell epitope identification using the EpiMatrix algorithm. Our comparison reveals that in addition to identifying a similar set of epitopes to the cell-free system, the in silico approach prospectively identifies more HLA-DRB1*0101 epitopes and can simultaneously analyze multiple HLA alleles (not just HLA DRB1*0101) covering a larger representation of the general human population. Although the cell-free system allows assessment of intracellular processing, the in silico approach is higher throughput, and can be performed much faster with far fewer resources