title: A strategy for precise and large scale identification of core fucosylated glycoproteins.
abstract: Core fucosylation (CF) patterns of some glycoproteins are more sensitive and specific than evaluation of their total respective protein levels for diagnosis of many diseases, such as cancers. Global profiling and quantitative characterization of CF glycoproteins may reveal potent biomarkers for clinical applications. However, current techniques are unable to reveal CF glycoproteins precisely on a large scale. Here we developed a robust strategy that integrates molecular weight cutoff, neutral loss-dependent MS(3), database-independent candidate spectrum filtering, and optimization to effectively identify CF glycoproteins. The rationale for spectrum treatment was innovatively based on computation of the mass distribution in spectra of CF glycopeptides. The efficacy of this strategy was demonstrated by implementation for plasma from healthy subjects and subjects with hepatocellular carcinoma. Over 100 CF glycoproteins and CF sites were identified, and over 10,000 mass spectra of CF glycopeptide were found. The scale of identification results indicates great progress for finding biomarkers with a particular and attractive prospect, and the candidate spectra will be a useful resource for the improvement of database searching methods for glycopeptides.
authors.affiliation: State Key Laboratory of Proteomics-Beijing Proteome Research Center-Beijing Institute of Radiation Medicine, No. 33 Life Science Park Road, Changping District, Beijing 102206, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Jia
authors.forename: Zhuang
authors.initials: Z
authors.lastname: Lu
authors.forename: Yan
authors.initials: Y
authors.lastname: Fu
authors.forename: Hai-Peng
authors.initials: HP
authors.lastname: Wang
authors.forename: Le-Heng
authors.initials: LH
authors.lastname: Wang
authors.forename: Hao
authors.initials: H
authors.lastname: Chi
authors.forename: Zuo-Fei
authors.initials: ZF
authors.lastname: Yuan
authors.forename: Zhao-Bin
authors.initials: ZB
authors.lastname: Zheng
authors.forename: Li-Na
authors.initials: LN
authors.lastname: Song
authors.forename: Huan-Huan
authors.initials: HH
authors.lastname: Han
authors.forename: Yi-Min
authors.initials: YM
authors.lastname: Liang
authors.forename: Jing-Lan
authors.initials: JL
authors.lastname: Wang
authors.forename: Yun
authors.initials: Y
authors.lastname: Cai
authors.forename: Yu-Kui
authors.initials: YK
authors.lastname: Zhang
authors.forename: Yu-Lin
authors.initials: YL
authors.lastname: Deng
authors.forename: Wan-Tao
authors.initials: WT
authors.lastname: Ying
authors.forename: Si-Min
authors.initials: SM
authors.lastname: He
authors.forename: Xiao-Hong
authors.initials: XH
authors.lastname: Qian
mesh_terms: D000117:Acetylglucosamine / Q000378:metabolism; D000595:Amino Acid Sequence; D035843:Biomedical Research; D005643:Fucose / Q000378:metabolism*; D006020:Glycopeptides / Q000097:blood / Q000737:chemistry; D006023:Glycoproteins / Q000032:analysis*; D006031:Glycosylation; D006801:Humans; D013058:Mass Spectrometry; D008969:Molecular Sequence Data; D040901:Proteomics / Q000379:methods*; D014462:Ultrafiltration
chemical_list: D006020:Glycopeptides; D006023:Glycoproteins; D005643:Fucose; D000117:Acetylglucosamine