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. 2016 Apr;15(4):1412-23.
doi: 10.1074/mcp.M115.055780. Epub 2016 Jan 13.

Sampling From the Proteome to the Human Leukocyte Antigen-DR (HLA-DR) Ligandome Proceeds Via High Specificity

Geert P M Mommen  1 , Fabio Marino  2 , Hugo D Meiring  3 , Martien C M Poelen  4 , Jacqueline A M van Gaans-van den Brink  4 , Shabaz Mohammed  5 , Albert J R Heck  2 , Cécile A C M van Els  6
Affiliations

Sampling From the Proteome to the Human Leukocyte Antigen-DR (HLA-DR) Ligandome Proceeds Via High Specificity

Geert P M Mommen et al. Mol Cell Proteomics. 2016 Apr.

Abstract

Comprehensive analysis of the complex nature of the Human Leukocyte Antigen (HLA) class II ligandome is of utmost importance to understand the basis for CD4(+)T cell mediated immunity and tolerance. Here, we implemented important improvements in the analysis of the repertoire of HLA-DR-presented peptides, using hybrid mass spectrometry-based peptide fragmentation techniques on a ligandome sample isolated from matured human monocyte-derived dendritic cells (DC). The reported data set constitutes nearly 14 thousand unique high-confident peptides,i.e.the largest single inventory of human DC derived HLA-DR ligands to date. From a technical viewpoint the most prominent finding is that no single peptide fragmentation technique could elucidate the majority of HLA-DR ligands, because of the wide range of physical chemical properties displayed by the HLA-DR ligandome. Our in-depth profiling allowed us to reveal a strikingly poor correlation between the source proteins identified in the HLA class II ligandome and the DC cellular proteome. Important selective sieving from the sampled proteome to the ligandome was evidenced by specificity in the sequences of the core regions both at their N- and C- termini, hence not only reflecting binding motifs but also dominant protease activity associated to the endolysosomal compartments. Moreover, we demonstrate that the HLA-DR ligandome reflects a surface representation of cell-compartments specific for biological events linked to the maturation of monocytes into antigen presenting cells. Our results present new perspectives into the complex nature of the HLA class II system and will aid future immunological studies in characterizing the full breadth of potential CD4(+)T cell epitopes relevant in health and disease.

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Figures

Fig. 1.
Fig. 1.
HLA-DR ligandome analysis and characteristics. A, Workflow for the analysis of the HLA-DR-presented ligandome and proteome of MUTZ-3 DC. For the ligandome, following affinity purification of HLA-DR-peptide complexes, peptides were released by acid elution, fractionated by strong cation exchange (SCX) and analyzed by LC-MS/MS using ETD, EThCD, and HCD fragmentation. Global proteome analysis was performed following trypsin digestion of lysed MUTZ-3 cells, using SCX fractionation prior to LC-MS/MS analysis. B, Venn diagram displaying the overlap and unique contribution to the identified HLA-DR ligandome by EThcD, ETD and HCD. C, Peptide length distribution in the combined HLA-DR ligandome (n = 13,918). D, Illustrative nested set of HLA-DR-associated peptides derived from Elongation factor 1-α 1, consisting of 10 peptide length variants with a consensus core binding motif but varying extended N- and C termini.
Fig. 2.
Fig. 2.
Binding motifs extracted from the HLA-DR ligandome by either NetMHCIIpan3.0. and by unsupervised clustering using Gibbs-Cluster-1.0. Sequence logo's are shown for the nine amino acid binding motif enabling binding to the expressed HLA-DR molecules. Anchor residues located on position P1, P4, P6, and P9 are known to be important for binding. A–C, consensus binding motifs from the complete set of HLA-DR ligands for HLA-DR10 (A), HLA-DR11 (B) and HLA-DR52 (C) as extracted by using NetMHCIIpan3.0. D–F, Unsupervised analysis by alignment and clustering analysis (using Gibbs-Cluster-1.0) reveals unique HLA-DR binding motifs. The inserts display the number of predicted 9 amino acid binding cores found that contribute to the shown sequence logo's.
Fig. 3.
Fig. 3.
Observed sequence specificity in the proteolytic processing of HLA-DR peptides. Both the N-terminal and C-terminal cleavage specificity observed in HLA-DR ligand processing are shown. The sequence logo's depict six amino acids represented as P6…P1 and six amino acids as P1′…P6′, which are located at the N- (left) and C-terminal (right) scissile sites of HLA-DR-associated peptides, respectively. The residues that are statistically over-represented are shown on the upper part of the IceLogo, whereas under-represented at the lower part (95% confidence level).
Fig. 4.
Fig. 4.
Source proteome of the HLA-DR ligandome. A, The cumulative number of unique peptides as function of the number of proteins identified by global proteome (blue) and the HLA-DR ligandome (red) analysis. Proteins are ranked from highest to the lowest number of representative peptides. B, The CELLO2GO algorithm was used to predict the subcellular localization of source proteins obtained by HLA-DR ligandome (blue bars) and global cellular proteome (red bars) analysis. C, Venn diagram showing the overlap between source-proteins identified in the HLA-DR ligandome and the full proteome. D, Source proteins most frequently sampled by HLA-DR with the number of observed unique HLA-DR peptides and number of nested sets. E, Dynamic range plot of the global cellular proteome of MUTZ-3 (blue dots). The assigned proteins (red dots) were the 19 out of 25 most abundantly expressed proteins in the HLA-DR ligandome (6 proteins HLA-DR-sampled proteins were not identified by global proteome analysis).
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