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.
Highlights
Mass spectrometry (MS) based immunopeptidomics is becoming increasingly relevant for several biomedical applications including cancer neoantigen discovery, vaccine development and protein drug deimmunization pipelines [1,2,3,4]
The tool is available at https://services. healthtech.dtu.dk/service.php?MHCMotifDecon-1.0 and takes one or multiple immunopeptidome datasets as input together with information of the HLA molecules expressed in each individual cell line/sample
On the web-interface, the user can select if motif deconvolution is to be performed for class I or class II molecules, specify the length of peptides to be included in the analysis and define the threshold to identify and discard potential MS co-purified contaminants
Summary
Mass spectrometry (MS) based immunopeptidomics is becoming increasingly relevant for several biomedical applications including cancer neoantigen discovery, vaccine development and protein drug deimmunization pipelines [1,2,3,4]. A major challenge being assigning the accurate MHC allele to each presented MS-derived peptide, a process termed motif deconvolution To tackle this concern, several experimental approaches that artificially engineer cells to only express one individual HLA have been performed both for MHC class I [5, 6], and MHC class II [7]. Several experimental approaches that artificially engineer cells to only express one individual HLA have been performed both for MHC class I [5, 6], and MHC class II [7] This laborious experimental setup has proved extremely useful to understand the rules of HLA presentation and their motifs, it lacks the biological relevance, limiting its application in other scenarios and experimental settings that involve patient samples and biospecimens
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