PXD027379

PXD027379 is an original dataset announced via ProteomeXchange.

Title	High throughput quantitative analysis of site-specific N-glycosylation reveals glyco-signatures for diagnosis of liver disease
Description	Glycosylation influences diverse life processes and changes in pathological processes. The glycoproteomic has been recognized as a hot area to screen markers as altered glycosylation is a universal feature of cancer cells. However, the high throughput screening of glycosylation markers from a large number of clinical samples faces greater technical challenges than peptides without or with other modifications. The most prominent problem in tandem mass tag-based high throughput quantification of intact glycopeptides is the inefficient cleavage of peptide backbone, glycosidic bonds and tandem mass tag concurrently to offer successful peptide and glycan composition determination as well as good quantification. Here, we managed to implement the tandem mass tag labeling into quantitative glycoproteomics by developing a chemical labeling-assisted complementary dissociation method for multiplexed analysis of intact N-glycopeptides. Chemical labeling of intact N-glycopeptides with charge-increasing reagent improved the efficiency of electron transfer dissociation (ETD) significantly for their identification and also increased the efficiency of higher-energy collision dissociation (HCD) in generating reporter ion for quantification, thereby capitalizing on the complementary nature of these two dissociation methods in quantification of intact N-glycopeptides. By using this new strategy, we investigated the site-specific glycosylation of IgG collected from 90 human serum including three stages of liver diseases, hepatitis B virus (HBV), cirrhosis (CIR), hepatocellular carcinoma (HCC) and healthy controls. As a result, 313 intact N-glycopeptides from IgG were identified in total, which represents the most comprehensive site-specific and subclass-specific N-glycosylation of human serum IgG to date. Quantitative glycoproteomics revealed that the combination of IgG1-H3N5F1 and IgG4-H3N4 displayed powerful prediction capability for distinguishing different stages of liver disease patients, which has potential for non-invasive monitoring and pre-stratification of liver disease diagnosis. Moreover, we analyzed the human serum using this newly developed method and identified near 2000 intact N-glycopeptides from only 10 L serum and showed this method has applicability for quantification of intact N-glycopeptides in different studies.
HostingRepository	iProX
AnnounceDate	2021-07-16
AnnouncementXML	Submission_2023-09-11_20:57:18.230.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Zhenyu Sun
SpeciesList	scientific name: Homo sapiens; NCBI TaxID: 9606;
ModificationList	complex glycosylation
Instrument	Orbitrap Fusion

Revision	Datetime	Status	ChangeLog Entry
0	2021-07-18 20:51:00	ID requested
⏵ 1	2023-09-11 20:57:19	announced

Sun Z, Fu B, Wang G, Zhang L, Xu R, Zhang Y, Lu H, -glycoproteomics reveals glyco-signatures for liver disease diagnosis. Natl Sci Rev, 10(1):nwac059(2023) [pubmed]

submitter keyword: quantification,intact N-glycopeptides

Haojie Lu
contact affiliation	Institutes of Biomedical Sciences, Fudan University
contact email	luhaojie@fudan.edu.cn
lab head
Zhenyu Sun
contact affiliation	Institutes of Biomedical Sciences, Fudan University
contact email	18111510003@fudan.edu.cn
dataset submitter

iProX dataset URI