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  Database search engines and target database features impinge upon the identification of post‐translationally cis‐spliced peptides in HLA class I immunopeptidomes

Mishto, M., Horokhovskyi, Y., Cormican, J. A., Yang, X., Lynham, S., Urlaub, H., et al. (2022). Database search engines and target database features impinge upon the identification of post‐translationally cis‐spliced peptides in HLA class I immunopeptidomes. Proteomics, In Press; 2100226. doi:10.1002/pmic.202100226.

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 Creators:
Mishto, M., Author
Horokhovskyi, Y.1, Author              
Cormican, J. A.1, Author              
Yang, X., Author
Lynham, S., Author
Urlaub, H.2, Author              
Liepe, J.1, Author              
Affiliations:
1Research Group of Quantitative and Systems Biology, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society, ou_3350287              
2Research Group of Bioanalytical Mass Spectrometry, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society, ou_3350290              

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Free keywords: HLA; immunopeptidome; Mascot; PEAKS; peptide splicing
 Abstract: Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry (MS) required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes. We here investigated the impact of three common database search engines – that is, Mascot, Mascot+Percolator, and PEAKS DB – as final identification step, as well as the features of target database on the ability to correctly identify non-spliced and cis-spliced peptides. We used ground truth datasets measured by MS to benchmark methods’ performance and extended the analysis to HLA class I immunopeptidomes. PEAKS DB showed better precision and recall of cis-spliced peptides and larger number of identified peptides in HLA class I immunopeptidomes than the other search engine strategies. The better performance of PEAKS DB appears to result from better discrimination between target and decoy hits and hence a more robust FDR estimation, and seems independent to peptide and spectrum features here investigated.

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Language(s): eng - English
 Dates: 2022-02-20
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1002/pmic.202100226
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Title: Proteomics
Source Genre: Journal
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Pages: - Volume / Issue: - Sequence Number: In Press; 2100226 Start / End Page: - Identifier: -