| Literature DB >> 34905171 |
Kevin Kovalchik1, David Hamelin2, Etienne Caron3,4.
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.Entities:
Keywords: Computational proteomics; Immunopeptidome; Mass spectrometry; Spectral library
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Year: 2022 PMID: 34905171 DOI: 10.1007/978-1-0716-1936-0_11
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745