Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model

David Gomez-Zepeda (), Danielle Arnold-Schild, Julian Beyrle, Arthur Declercq, Ralf Gabriels, Elena Kumm, Annica Preikschat, Mateusz Krzysztof Łącki, Aurélie Hirschler, Jeewan Babu Rijal, Christine Carapito, Lennart Martens, Ute Distler, Hansjörg Schild and Stefan Tenzer ()
Additional contact information
David Gomez-Zepeda: University Medical Center of the Johannes-Gutenberg University
Danielle Arnold-Schild: University Medical Center of the Johannes-Gutenberg University
Julian Beyrle: University Medical Center of the Johannes-Gutenberg University
Arthur Declercq: VIB-UGent Center for Medical Biotechnology, VIB
Ralf Gabriels: VIB-UGent Center for Medical Biotechnology, VIB
Elena Kumm: University Medical Center of the Johannes-Gutenberg University
Annica Preikschat: University Medical Center of the Johannes-Gutenberg University
Mateusz Krzysztof Łącki: University Medical Center of the Johannes-Gutenberg University
Aurélie Hirschler: IPHC UMR 7178, University of Strasbourg, CNRS
Jeewan Babu Rijal: IPHC UMR 7178, University of Strasbourg, CNRS
Christine Carapito: IPHC UMR 7178, University of Strasbourg, CNRS
Lennart Martens: VIB-UGent Center for Medical Biotechnology, VIB
Ute Distler: University Medical Center of the Johannes-Gutenberg University
Hansjörg Schild: University Medical Center of the Johannes-Gutenberg University
Stefan Tenzer: University Medical Center of the Johannes-Gutenberg University

Nature Communications, 2024, vol. 15, issue 1, 1-18

Abstract: Abstract Human leukocyte antigen (HLA) class I peptide ligands (HLAIps) are key targets for developing vaccines and immunotherapies against infectious pathogens or cancer cells. Identifying HLAIps is challenging due to their high diversity, low abundance, and patient individuality. Here, we develop a highly sensitive method for identifying HLAIps using liquid chromatography-ion mobility-tandem mass spectrometry (LC-IMS-MS/MS). In addition, we train a timsTOF-specific peak intensity MS2PIP model for tryptic and non-tryptic peptides and implement it in MS2Rescore (v3) together with the CCS predictor from ionmob. The optimized method, Thunder-DDA-PASEF, semi-selectively fragments singly and multiply charged HLAIps based on their IMS and m/z. Moreover, the method employs the high sensitivity mode and extended IMS resolution with fewer MS/MS frames (300 ms TIMS ramp, 3 MS/MS frames), doubling the coverage of immunopeptidomics analyses, compared to the proteomics-tailored DDA-PASEF (100 ms TIMS ramp, 10 MS/MS frames). Additionally, rescoring boosts the HLAIps identification by 41.7% to 33%, resulting in 5738 HLAIps from as little as one million JY cell equivalents, and 14,516 HLAIps from 20 million. This enables in-depth profiling of HLAIps from diverse human cell lines and human plasma. Finally, profiling JY and Raji cells transfected to express the SARS-CoV-2 spike protein results in 16 spike HLAIps, thirteen of which have been reported to elicit immune responses in human patients.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-024-46380-y Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46380-y

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-46380-y

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().