PXD017646
PXD017646 is an original dataset announced via ProteomeXchange.
Dataset Summary
Title | Optimal Dissociation Methods Differ for N- and O-glycopeptides |
Description | Site-specific characterization of glycosylation requires intact glycopeptide analysis, and recent efforts have focused on how to best interrogate glycopeptides using tandem mass spectrometry (MS/MS). Beam-type collisional activation, i.e., higher-energy collisional dissociation (HCD), has been a valuable approach, but stepped collision energy HCD (sceHCD) and electron transfer dissociation with HCD supplemental activation (EThcD) have emerged as potentially more suitable alternatives. Both sceHCD and EThcD have been used with success in large-scale glycoproteomic experiments, but they each incur some degree of compromise. Furthermore, N-glycoproteomics has made significant progress in the last few years, and there is growing interest in extending this progress to O-glycoproteomics, which necessitates comparisons of method performance for the two classes of glycopeptides. Here, we systematically explore the advantages and disadvantages of conventional HCD, sceHCD, ETD, and EThcD for intact glycopeptide analysis and comment on their suitability for both N- and O-glycoproteomic applications. For N-glycopeptides, HCD and sceHCD generate similar numbers of identifications, although sceHCD generally provides higher quality spectra. Both significantly outperform EThcD methods, indicating that ETD-based methods are not required for routine N-glycoproteomics. Conversely, ETD-based methods, especially EThcD, are indispensable for site-specific analyses of O-glycopeptides. Our data show that O-glycopeptides cannot be robustly characterized with HCD-centric methods that are sufficient for N-glycopeptides, and glycoproteomic methods aiming to characterize O-glycopeptides must be constructed accordingly. |
HostingRepository | PRIDE |
AnnounceDate | 2024-10-22 |
AnnouncementXML | Submission_2024-10-22_05:09:28.852.xml |
DigitalObjectIdentifier | |
ReviewLevel | Peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Unsupported dataset by repository |
PrimarySubmitter | Nicholas Riley |
SpeciesList | scientific name: Bos taurus (Bovine); NCBI TaxID: 9913; scientific name: Homo sapiens (Human); NCBI TaxID: 9606; |
ModificationList | complex glycosylation |
Instrument | Orbitrap Fusion |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
---|---|---|---|
0 | 2020-02-20 01:21:05 | ID requested | |
1 | 2020-07-19 21:58:12 | announced | |
⏵ 2 | 2024-10-22 05:09:29 | announced | 2024-10-22: Updated project metadata. |
Publication List
10.1021/acs.jproteome.0c00218; |
Riley NM, Malaker SA, Driessen MD, Bertozzi CR, -Glycopeptides. J Proteome Res, 19(8):3286-3301(2020) [pubmed] |
Keyword List
submitter keyword: glycoproteomics, N-glycopeptides, sceHCD, EThcD, O-glycopeptides, ETD |
Contact List
Carolyn Bertozzi | |
---|---|
contact affiliation | Department of Chemistry, Stanford University, Stanford, California, USA Howard Hughes Medical Institute, Stanford, California, USA |
contact email | bertozzi@stanford.edu |
lab head | |
Nicholas Riley | |
contact affiliation | Stanford University |
contact email | riley.nicholasm@gmail.com |
dataset submitter |
Full Dataset Link List
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PRIDE project URI |
Repository Record List
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