Abstract
Developing a deep and comprehensive understanding of the collection of peptides presented by class I human leukocyte antigens (HLA ), collectively referred to as the immunopeptidome , is conducive to the success of a wide range of immunotherapies. The development of tools that enable the deconvolution of immunopeptidomes in the context of disease can help improve the specificity and effectiveness of therapeutic strategies targeting these peptides, such as adoptive T-cell therapy and vaccines. Here, we describe a computational workflow that facilitates the processing and interpretation of data-independent acquisition mass spectrometry (DIA-MS). We consider a specific variation of DIA-MS known as SWATH-MS. SWATH-MS is a promising technique that can be utilized to reproducibly characterize and quantify immunopeptidomes isolated from a wide range of biological sources. In this workflow, we use an assortment of database search engines and computational tools to build high-quality HLA allele-specific peptide spectral peptide libraries for the analysis of immunopeptidomic datasets acquired by SWATH-MS. Generating and sharing these spectral libraries are essential for the SWATH-MS technology to meet its full potential and to enable the rapid and reproducible quantification of HLA-specific peptides across multiple samples.
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Acknowledgments
We thank all members of the Caron Lab for helpful discussions. This work was supported by funding from the Fonds de recherche du Québec—Santé (FRQS), the Cole Foundation, CHU Sainte-Justine and the Charles-Bruneau Foundations, Canada Foundation for Innovation, and by the National Sciences and Engineering Research Council (NSERC) (#RGPIN-2020-05232). K.K. is a recipient of IVADO’s postdoctoral scholarship (#4879287150). E.C. is a FRQS Junior 1 Research Scholar.
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Kovalchik, K., Hamelin, D., Caron, E. (2022). Generation of HLA Allele-Specific Spectral Libraries to Identify and Quantify Immunopeptidomes by SWATH/DIA-MS. In: Corrales, F.J., Paradela, A., Marcilla, M. (eds) Clinical Proteomics. Methods in Molecular Biology, vol 2420. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1936-0_11
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DOI: https://doi.org/10.1007/978-1-0716-1936-0_11
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