%0 Journal Article
%A Gómez-Zepeda, David
%A Arnold-Schild, Danielle
%A Beyrle, Julian
%A Declercq, Arthur
%A Gabriels, Ralf
%A Kumm, Elena
%A Preikschat, Annica
%A Łącki, Mateusz Krzysztof
%A Hirschler, Aurélie
%A Rijal, Jeewan Babu
%A Carapito, Christine
%A Martens, Lennart
%A Distler, Ute
%A Schild, Hansjörg
%A Tenzer, Stefan
%T Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model.
%J Nature Communications
%V 15
%N 1
%@ 2041-1723
%C [London]
%I Nature Publishing Group UK
%M DKFZ-2024-00530
%P 2288
%D 2024
%Z #EA:D191#LA:D191# / HI-TRON
%X 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
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:38480730
%R 10.1038/s41467-024-46380-y
%U https://inrepo02.dkfz.de/record/288978