Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome

Abstract

Mass spectrometry (MS) based immunopeptidomics is used in several biomedical applications including neo-epitope discovery in oncology, next-generation vaccine development and protein-drug immunogenicity assessment. Immunopeptidome data are highly complex given the expression of multiple HLA alleles on the cell membrane and presence of co-immunoprecipitated contaminants. The absence of tools that deal with these challenges effectively and guide the analysis and interpretation of this complex type of data is currently a major bottleneck for the large-scale application of this technique. To resolve this, we here present the MHCMotifDecon that benefits from state-of-the-art HLA class-I and class-II predictions to accurately deconvolute immunopeptidome datasets and assign individual ligands to the most likely HLA molecule, allowing to identify and characterize HLA binding motifs while discarding co-purified contaminants. We have benchmarked the tool against other state-of-the-art methods and illustrated its application on experimental datasets for HLA-DR demonstrating a previously underappreciated role for HLA-DRB3/4/5 molecules in defining HLA class II immune repertoires. With its ease of use, MHCMotifDecon can efficiently guide interpretation of immunopeptidome datasets, serving the discovery of novel T cell targets. MHCMotifDecon is available at https://services.healthtech.dtu.dk/service.php?MHCMotifDecon-1.0.

Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome by accurate and comprehensive HLA-DQ antigen presentation prediction

“…Cells were harvested from the suspension, washed with PBS and spun down at 4C for 10 minutes. The cell pellets were immediately frozen in LN2 and stored at - 80 until downstream processing (Kaabinejadian et al, 2022). All cell lines were subjected to high-resolution HLA typing (HLA-A, -B, -C, DRB1,3, 4, 5, DP and DQ) immediately upon receipt and growth in our laboratory, for authentication prior to large scale culture and data collection.…”

“…HLA-DQ molecules were purified from the cells by affinity chromatography using the anti-human HLA-DQ specific antibody (clone SPVL3) coupled to CNBr-activated Sepharose 4 Fast Flow (Amersham Pharmacia Biotech, Orsay, France) as described previously (Kaabinejadian et al, 2022). Briefly, frozen cell pellets were pulverized using Retsch Mixer Mill MM400, resuspended in lysis buffer comprised of Tris pH 8.0 (50 mM), Igepal, 0.5%, NaCl (150 mM) and complete protease inhibitor cocktail (Roche, Mannheim, Germany).…”

“…The column effluent was ionized using the nanospray III ion source of an AB Sciex TripleTOF 5600 quadruple time-of-flight mass spectrometer (AB Sciex, Framingham, MA, USA) with the source voltage set to 2,400 V. Information-dependent analysis (IDA) method was used for data acquisition (Kaabinejadian et al, 2022). PeakView Software version 1.2.0.3 (AB Sciex, Framingham, MA, USA) was used for data visualization.…”

“…However, experimental results indicate binding affinity (BA) to be a relatively weak correlate of antigen processing and presentation by HLA molecules (Bassani-Sternberg et al, 2016). In addition, multiple studies have demonstrated that the performance of the HLA-class II peptide-binding prediction models improve significantly when trained with immunopeptidome data acquired by liquid chromatography coupled with mass spectrometry (LC-MS/MS) (Alvarez et al, 2018; Gfeller and Bassani-Sternberg, 2018; Kaabinejadian et al, 2022; Reynisson et al, 2020a). Generally, in an HLA class II immunopeptidome eluted ligand (EL) assay, HLA molecules are affinity purified from lysed antigen presenting cells (APCs) using HLA specific monoclonal antibodies.…”

Proteogenomic analysis reveals RNA as an important source for tumor-agnostic neoantigen identification correlating with T-cell infiltration

“…To assess the quality and purity of the MS-generated immunopeptidomic data, the identified peptide sequences where deconvoluted to the respective patients HLA-allele by their binding motif using MHCMotifDecon-1.0 (63, 64). Here, MHC binding predictions from NetMHCpan-4.1 (for MHC class I) are used to deconvolute and assign likely MHC restriction elements to MHC peptidome data.…”