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Thunder-DDA-PASEF Enables High-Coverage Immunopeptidomics and is Boosted by MS2Rescore with MS2PIP Timstof Fragmentation Prediction Model

Nature communications(2024)SCI 1区

Institute of Immunology | VIB-UGent Center for Medical Biotechnology | BioOrganic Mass Spectrometry Laboratory (LSMBO)

Cited 4|Views34
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 MS 2 PIP model for tryptic and non-tryptic peptides and implement it in MS 2 Rescore (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.
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HLA Class I and II,Tandem Mass Spectrometry,Protein Identification,Immunoinformatics
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要点】:本研究开发了一种高灵敏度的Thunder-DDA-PASEF方法,结合MS2Rescore和timsTOF-specific MS2PIP模型,显著提高了HLAIps的识别覆盖率和准确性。

方法】:通过训练timsTOF特定的峰强度MS2PIP模型,并将其整合入MS2Rescore软件,结合LC-IMS-MS/MS技术,实现了HLAIps的高效识别。

实验】:采用Thunder-DDA-PASEF方法对JY和Raji细胞系进行实验,使用的数据集为转染SARS-CoV-2刺突蛋白的细胞系,最终识别出16个刺突HLAIps,其中13个已知能引发人类患者的免疫反应。