AUTHOR=Wendorff Mareike , Garcia Alvarez Heli M. , Østerbye Thomas , ElAbd Hesham , Rosati Elisa , Degenhardt Frauke , Buus Søren , Franke Andre , Nielsen Morten 

TITLE=Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction

JOURNAL=Frontiers in Immunology

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2020.01705

DOI=10.3389/fimmu.2020.01705

ISSN=1664-3224

ABSTRACT=Human Leukocyte Antigen class II (HLA-II) molecules present peptides and play an essential role in adaptive immune responses. Characterizing the binding specificity of single HLA-II molecules has profound impacts for understanding cellular immunity, identifying the cause of autoimmune diseases, for immunotherapeutics and vaccine development. Here, novel high-density peptide microarray technology and machine learning techniques were used to address this task at a level of high-throughput that goes well beyond the limitations of alternative technologies. Microarrays with over 200,000 defined peptides were assayed with five exemplary HLA-II molecules. Machine learning was applied to mine the signals. The comparison of identified binding motifs, and power for predicting eluted ligands and CD4+ epitope datasets to that obtained using NetMHCIIpan-3.2, confirmed a high quality of the chip readout. These results suggest that the proposed microarray technology offers a novel and unique platform for large-scale unbiased interrogation of peptide binding preferences of HLA-II molecules.