Prediction of HLA-DQ8 β cell peptidome using a computational program and its relationship to autoreactive T cells

Abstract

The goal was to identify HLA-DQ8-bound β cell epitopes important in the T cell response in autoimmune diabetes. We first identified HLA-DQ8 (DQA1*0301/DQB1*0302) β cell epitopes using a computational approach and then related their identification to CD4 T cell responses. The computational program (TEA-DQ8) was adapted from one previously developed for identifying peptides bound to the I-Ag7 molecule and based on a library of naturally processed peptides bound to HLA-DQ8 molecules of antigen-presenting cells. We then examined experimentally the response of NOD.DQ8 mice immunized with peptides derived from the Zinc transporter 8 protein. Log-of-odds scores on peptides were experimentally validated as an indicator of peptide binding to HLA-DQ8 molecules. We also examined previously published data on diabetic autoantigens, including glutamic acid decarboxylase-65, insulin and insulinoma-associated antigen-2, all tested in NOD.DQ8 transgenic mice. In all examples, many peptides identified with a favorable binding motif generated an autoimmune T cell response, but importantly many did not. Moreover, some peptides with weak-binding motifs were immunogenic. These results indicate the benefits and limitations in predicting autoimmune T cell responses strictly from MHC-binding data. TEA-DQ8 performed significantly better than other prediction programs