Applied Bioinformatics Group


A   A   A
Sections
Home > Publications > Unveiling the Peptide Motifs of HLA-C and HLA-G from Naturally Presented Peptides and Generation of Binding Prediction Matrices

Skip to content. | Skip to navigation

Document Actions

Moreno Di Marco, Heiko Schuster, Linus Backert, Michael Ghosh, Hans-Georg Rammensee, and Stefan Stevanovic (2017)

Unveiling the Peptide Motifs of HLA-C and HLA-G from Naturally Presented Peptides and Generation of Binding Prediction Matrices

J. Immunol., 199(8):2639-2651.

The classical HLA-C and the nonclassical HLA-E and HLA-G molecules play important roles both in the innate and adaptive immune system. Starting already during embryogenesis and continuing throughout our lives, these three Ags exert major functions in immune tolerance, defense against infections, and anticancer immune responses. Despite these important roles, identification and characterization of the peptides presented by these molecules has been lacking behind the more abundant HLA-A and HLA-B gene products. In this study, we elucidated the peptide specificities of these HLA molecules using a comprehensive analysis of naturally presented peptides. To that end, the 15 most frequently expressed HLA-C alleles as well as HLA-E*01:01 and HLA-G*01:01 were transfected into lymphoblastoid C1R cells expressing low endogenous HLA. Identification of naturally presented peptides was performed by immunoprecipitation of HLA and subsequent analysis of HLA-bound peptides by liquid chromatographic tandem mass spectrometry. Peptide motifs of HLA-C unveil anchors in position 2 or 3 with high variances between allotypes, and a less variable anchor at the C-terminal end. The previously reported small ligand repertoire of HLA-E was confirmed within our analysis, and we could show that HLA-G combines a large ligand repertoire with distinct features anchoring peptides at positions 3 and 9, supported by an auxiliary anchor in position 1 and preferred residues in positions 2 and 7. The wealth of HLA ligands resulted in prediction matrices for octa-, nona-, and decamers. Matrices were validated in terms of their binding prediction and compared with the latest NetMHC prediction algorithm NetMHCpan-3.0, which demonstrated their predictive power.

28904123
10.4049/jimmunol.1700938