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PXD014713-3

PXD014713 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleChemical labeling for fine mapping of IgG N-glycosylation by ETD-MS
DescriptionImmunoglobulin G (IgG), which contains four subclasses (IgG1-4), is one of the most important class of glycoproteins in immune system. Because of its importance in immune system, a steady increase of interest in developing IgG as biomarker or biotherapeutic agents for the treatment of diseases has been seen, as most therapeutic mAbs were IgG-based. N-glycosylation of IgG is crucial for its effector function and makes the IgG highly heterogeneous both in structure and function, although all four subclasses of IgG contain only a single N-glycosylation site in the Fc region with highly similar amino acid sequence. Therefore, fine mapping the IgG glycosylation is necessary for understanding the IgG function and avoiding aberrant glycosylation in mAbs. However, site-specific and comprehensive N-glycosylation analysis of IgG subclasses still cannot be achieved by MS alone due to the partial sequence coverage and loss of connections among glycosylation on protein sequence. We report here a chemical labeling strategy to improve the electron transfer dissociation efficiency in mass spectrometry analysis, which enable a 100% peptide sequence coverage of N-glycopeptides in all subclasses of IgG. Combining with high-energy collisional dissociation for the fragmentation of glycans, fine mapping of N-glycosylation profile of IgG is achieved. This comprehensive glycosylation analysis strategy for the first time allows the discrimination of IgG3 and IgG4 intact N-glycopeptides with high similarity in sequence without the antibody-based pre-separation. Using this strategy, aberrant serum IgG N-glycosylation for four IgG subclasses associated with cirrhosis and hepatocellular carcinoma were revealed. Moreover, this method identifies 5 times more intact glycopeptides from human serum than native-ETD method, implying that the approach can also accommodate for large-scale site-specific profiling of glycoproteomics.
HostingRepositoryPRIDE
AnnounceDate2023-11-14
AnnouncementXMLSubmission_2023-11-14_08:50:22.789.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterzhang lei
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListNo PTMs are included in the dataset
InstrumentOrbitrap Fusion
Dataset History
RevisionDatetimeStatusChangeLog Entry
02019-07-23 05:50:23ID requested
12019-08-26 00:58:41announced
22019-12-13 04:24:14announced2019-12-13: Updated publication reference for DOI(s): 10.1039/c9sc02491c.
32023-11-14 08:50:23announced2023-11-14: Updated project metadata.
Publication List
Dataset with its publication pending
Keyword List
submitter keyword: Chemical labeling, IgG,Glycosylation, Glycopeptides, Electron transfer dissociation (ETD) mass spectrometry
Contact List
haojie lu
contact affiliationFudan University
contact emailluhaojie@fudan.edu.cn
lab head
zhang lei
contact affiliationfudan university
contact emailzhanglei123@fudan.edu.cn
dataset submitter
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Dataset FTP location
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