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Human leukocyte antigen (HLA) molecules present small peptide antigens to T cells, thereby allowing them to recognize pathogen-infected and cancer cells. A central dogma over the last 50+ y is that peptide binding to HLA molecules is mediated by the docking of side chains of particular amino acids in the peptide into pockets in the HLA molecules in a conserved N- to C-terminal orientation. Whether peptides can be presented in a reversed C- to N-terminal orientation remains unclear. Here, we performed large-scale identification of peptides bound to HLA-DP molecules and observed that in addition to peptide binding in an N- to C-terminal orientation, in 9 out of 14 HLA-DP allotypes, reverse motifs are found, compatible with C- to N-terminal peptide binding. Moreover, we isolated high-avidity human cytomegalovirus (CMV)-specific HLA-DP-restricted CD4 + T cells from the memory repertoire of healthy donors and demonstrate that such T cells recognized CMV-derived peptides bound to HLA-DPB1*01:01 or *05:01 in a reverse C- to N-terminal manner. Finally, we obtained a high-resolution HLA-DPB1*01:01-CMVpp65 (142-158) peptide crystal structure, which is the molecular basis for C- to N-terminal peptide binding to HLA-DP. Our results point to unique features of HLA-DP molecules that substantially broaden the HLA class II bound peptide repertoire to combat pathogens and eliminate cancer cells.

In the context of HLA-DP-mismatched allogeneic stem cell transplantation, mismatched HLA-DP alleles can provoke profound allo-HLA-DP-specific immune responses from the donor T-cell repertoire leading to graft-versus-leukemia effect and/or graft-versus-host disease in the patient. The magnitude of allo-HLA-DP-specific immune responses has been shown to depend on the specific HLA-DP disparity between donor and patient and the immunogenicity of the mismatched HLA-DP allele(s). HLA-DP peptidome clustering (DPC) was developed to classify the HLA-DP molecules based on similarities and differences in their peptide-binding motifs. To investigate a possible categorization of HLA-DP molecules based on overlap of presented peptides, we identified and compared the peptidomes of the thirteen most frequently expressed HLA-DP molecules. Our categorization based on shared peptides was in line with the DPC classification. We found that the HLA-DP molecules within the previously defined groups DPC-1 or DPC-3 shared the largest numbers of presented peptides. However, the HLA-DP molecules in DPC-2 segregated into two subgroups based on the overlap in presented peptides. Besides overlap in presented peptides within the DPC groups, a substantial number of peptides was also found to be shared between HLA-DP molecules from different DPC groups, especially for groups DPC-1 and -2. The functional relevance of these findings was illustrated by demonstration of cross-reactivity of allo-HLA-DP-reactive T-cell clones not only against HLA-DP molecules within one DPC group, but also across different DPC groups. The promiscuity of peptides presented in various HLA-DP molecules and the cross-reactivity against different HLA-DP molecules demonstrate that these molecules cannot be strictly categorized in immunogenicity groups. [ABSTRACT FROM AUTHOR]

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules is crucial for rational development of immunotherapies and vaccines targeting CD4+ T cell activation. So far, most prediction methods for HLA class II antigen presentation have focused on HLA-DR because of limited availability of immunopeptidomics data for HLA-DQ and HLA-DP while not taking into account alternative peptide binding modes. We present an update to the NetMHCIIpan prediction method, which closes the performance gap between all three HLA class II loci. We accomplish this by first integrating large immunopeptidomics datasets describing the HLA class II specificity space across all loci using a refined machine learning framework that accommodates inverted peptide binders. Next, we apply targeted immunopeptidomics assays to generate data that covers additional HLA-DP specificities. The final method, NetMHCIIpan-4.3, achieves high accuracy and molecular coverage across all HLA class II allotypes. [ABSTRACT FROM AUTHOR]