4.5 Article

Characterization of intact N- and O-linked glycopeptides using higher energy collisional dissociation

期刊

ANALYTICAL BIOCHEMISTRY
卷 452, 期 -, 页码 96-102

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ab.2014.01.003

关键词

Glycosylation; Glycopeptides; LC-MS/MS; HCD; NCE; Automated identification

资金

  1. Environmental Molecular Science Laboratory (EMSL) intramural research projects
  2. EMSL capability development projects
  3. U.S. Department of Energy (DOE)
  4. Office of Biological and Environmental Research
  5. National Institutes of Health's National Center for Research Resources [RR018522]
  6. Department of Energy Office of Biological and Environmental Research Genome Sciences Program

向作者/读者索取更多资源

Simultaneous elucidation of the glycan structure and the glycosylation site are needed to reveal the biological function of protein glycosylation. In this study, we employed a recent type of fragmentation termed higher energy collisional dissociation (HCD) to examine fragmentation patterns of intact glycopeptides generated from a mixture of standard glycosylated proteins. The normalized collisional energy (NCE) value for HCD was varied from 30 to 60% to evaluate the optimal conditions for the fragmentation of peptide backbones and glycoconjugates. Our results indicated that HCD with lower NCE values preferentially fragmented the sugar chains attached to the peptides to generate a ladder of neutral loss of monosaccharides, thereby enabling the putative glycan structure characterization. In addition, detection of the oxonium ions enabled unambiguous differentiation of glycopeptides from non-glycopeptides. In contrast, HCD with higher NCE values preferentially fragmented the peptide backbone and, thus, provided information needed for confident peptide identification. We evaluated the HCD approach with alternating NCE parameters for confident characterization of intact N-and O-linked glycopeptides in a single liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. In addition, we applied a novel data analysis pipeline, so-called GlycoFinder, to form a basis for automated data analysis. Overall, 38 unique intact glycopeptides corresponding to eight glycosylation sites (six N-linked and two O-linked sites) were confidently identified from a standard protein mixture. This approach provided concurrent characterization of both the peptide and the glycan, thereby enabling comprehensive structural characterization of glycoproteins in a single LC-MS/MS analysis. (C) 2013 Elsevier Inc. All rights reserved.

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