TY  - JOUR
AU  - Gómez-Zepeda, David
AU  - Arnold-Schild, Danielle
AU  - Beyrle, Julian
AU  - Declercq, Arthur
AU  - Gabriels, Ralf
AU  - Kumm, Elena
AU  - Preikschat, Annica
AU  - Łącki, Mateusz Krzysztof
AU  - Hirschler, Aurélie
AU  - Rijal, Jeewan Babu
AU  - Carapito, Christine
AU  - Martens, Lennart
AU  - Distler, Ute
AU  - Schild, Hansjörg
AU  - Tenzer, Stefan
TI  - Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model.
JO  - Nature Communications
VL  - 15
IS  - 1
SN  - 2041-1723
CY  - [London]
PB  - Nature Publishing Group UK
M1  - DKFZ-2024-00530
SP  - 2288
PY  - 2024
N1  - #EA:D191#LA:D191# / HI-TRON
AB  - 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
LB  - PUB:(DE-HGF)16
C6  - pmid:38480730
DO  - DOI:10.1038/s41467-024-46380-y
UR  - https://inrepo02.dkfz.de/record/288978
ER  -