DICP OpenIR
Subject Area物理化学
Large-scale characterization of intact N-glycopeptides using an automated glycoproteomic method
Cheng, Kai1,4; Chen, Rui1,2; Seebun, Deeptee2; Ye, Mingliang1; Figeys, Daniel2,3; Zou, Hanfa1; Ye ML(叶明亮); DanielFigeys
KeywordN-glycoproteomics Mass Spectrometry Glycan Structure Software Platform
Source PublicationJOURNAL OF PROTEOMICS
2014-10-14
DOI10.1016/j.jprot.2014.08.006
Volume110Issue:1Pages:145-154
Indexed BySCI
SubtypeArticle
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS SubjectBiochemical Research Methods
WOS Research AreaBiochemistry & Molecular Biology
WOS KeywordHYDROPHILIC INTERACTION CHROMATOGRAPHY ; ELECTRON-TRANSFER DISSOCIATION ; MASS-SPECTROMETRY DATA ; PROTEIN GLYCOSYLATION ; GLYCAN STRUCTURE ; CELL-ADHESION ; C-TRAP ; IDENTIFICATION ; COMPLEX ; SEARCH
AbstractThe detailed characterization of site-specific glycosylation requires the identification of glycan composition and specific attachment sites on proteins, which need the identification of intact glycopeptides by mass spectrometry. In this study, we present an analytical and computational strategy for the high throughput characterization of intact N-glycopeptides derived from complex proteome samples. N-glycopeptides were identified using the spectra acquired for intact glycopeptides as well as de-glycopeptides. The Y1 ion (peptide + GlcNAc) was accurately determined from the spectra of intact glycopeptides, and the structure of glycan was then identified by searching a constructed glycan database with calculated molecular weight of glycans and their fragment ions. The peptide sequences of intact glycopeptides were identified by matching the molecular weight calculated from Y1 ion to that of deglycosylated peptides from the same HILIC enrichment and identified by a separated LC-MS/MS analysis. The fully automated software platform integrates all of the above processes involved in the identification of the intact N-glycopeptides. This platform was applied to detailed characterization of site-specific glycosylation in HEK 293T cells, which led to the identification of 2249 unique intact N-glycopeptides. These intact glycopeptides revealed 1769 site-specific N-glycans on 453 glycosylation sites which demonstrated the high heterogeneity of glycosylations.
Language英语
WOS IDWOS:000345183200012
Citation statistics
Cited Times:44[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://cas-ir.dicp.ac.cn/handle/321008/144529
Collection中国科学院大连化学物理研究所
Corresponding AuthorYe ML(叶明亮); DanielFigeys
Affiliation1.Chinese Acad Sci, Dalian Inst Chem Phys, Natl Chromatog R&A Ctr, Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China
2.Univ Ottawa, Fac Med, Dept Biochem Microbiol & Immunol, Ottawa Inst Syst Biol, Ottawa, ON K1H 8M5, Canada
3.Univ Ottawa, Fac Sci, Dept Chem, Ottawa, ON K1N 6N5, Canada
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Cheng, Kai,Chen, Rui,Seebun, Deeptee,et al. Large-scale characterization of intact N-glycopeptides using an automated glycoproteomic method[J]. JOURNAL OF PROTEOMICS,2014,110(1):145-154.
APA Cheng, Kai.,Chen, Rui.,Seebun, Deeptee.,Ye, Mingliang.,Figeys, Daniel.,...&DanielFigeys.(2014).Large-scale characterization of intact N-glycopeptides using an automated glycoproteomic method.JOURNAL OF PROTEOMICS,110(1),145-154.
MLA Cheng, Kai,et al."Large-scale characterization of intact N-glycopeptides using an automated glycoproteomic method".JOURNAL OF PROTEOMICS 110.1(2014):145-154.
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