Membranal and Blood‐Soluble HLA Class II Peptidome Analyses Using Data‐Dependent and Independent Acquisition

Abstract

The interaction between HLA class II peptide complexes on antigen-presenting cells and CD4 T cells is of fundamental importance for anticancer and antipathogen immunity as well as for the maintenance of immunological tolerance. To study CD4 T cell reactivities, detailed knowledge of the presented peptides is necessary. In recent years, dramatic advances in the characterization of membranal and soluble HLA class I peptidomes could be observed. However, the same is not true for HLA class II peptidomes, where only few studies identify more than hundred peptides. Here we describe a MS-based workflow for the characterization of membranal and soluble HLA class II DR and DQ peptidomes. Using this workflow, we identify a total of 8595 and 3727 HLA class II peptides from Maver-1 and DOHH2 cells, respectively. Based on this data, a motif-based binding predictor is developed and compared to NetMHCIIpan 3.1. We then apply the workflow to human plasma, resulting in the identification of between 34 and 152 HLA-DR and between 100 and 180 HLA-DQ peptides, respectively. Finally, we implement a data-independent acquisition workflow to increase reproducibility and sensitivity of HLA class II peptidome characterizations.

Applying MAPPs Assays to Assess Drug Immunogenicity

“…Measurement speed and mass accuracy are key parameters that enable identification of peptides in the highly complex HLA class II peptide samples. Often, a dynamic exclusion list is applied (30), which is preventing previously measured high intensity peaks from being triggered continuously, and which is enabling the detection of low abundant peaks. (5) For peptide identification based on the measured mass spectra, database search algorithms such as SEQUEST and MASCOT are commonly employed (5)(6)(7)30).…”

“…Often, a dynamic exclusion list is applied (30), which is preventing previously measured high intensity peaks from being triggered continuously, and which is enabling the detection of low abundant peaks. (5) For peptide identification based on the measured mass spectra, database search algorithms such as SEQUEST and MASCOT are commonly employed (5)(6)(7)30). Settings are typically adjusted to limit false positive identification rates to a maximum of 1-2% (28,30).…”

Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry

“…The release of soluble HLA‐peptide complexes (sHLA) by tumours has been suspected to support them in modulating and evading immune responses . However, mapping the natural sHLA class I and II (tumour) ligandome from plasma, serum or bone marrow samples as well as cell culture supernatants has not been frequently performed . sHLA peptides isolated from clinical samples are often contaminated with blood clotting and plasma proteins .…”

“…20 However, mapping the natural sHLA class I and II (tumour) ligandome from plasma, serum or bone marrow samples as well as cell culture supernatants has not been frequently performed. 12,21,22 sHLA peptides isolated from clinical samples are often contaminated with blood clotting and plasma proteins. 12 Likewise, extracellular vesicles (EVs) containing membrane-bound HLA class I and II molecules have recently been applied to class I immunopeptidomics for the first time.…”

Improved prediction of MHC II antigen presentation through integration and motif deconvolution of mass spectrometry MHC eluted ligand data

“…Publications with full HLA class II typing and more than 1000 ligands were selected for data extraction. Ligand data was subsequently extracted from the individual publications 31,[40][41][42][43][44][45][46][47][48] . Supplementary materials of the publications were processed and ligands extracted along with their source proteins and associated MHC molecules.…”