4.7 Article

Higher Energy Collision Dissociation (HCD) Product Ion-Triggered Electron Transfer Dissociation (ETD) Mass Spectrometry for the Analysis of N-Linked Glycoproteins

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 11, Issue 9, Pages 4517-4525

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/pr300257c

Keywords

glycosylation; tandem mass spectrometry; HCD; ETD; ZIC-HILIC; post-translational modification; N-linked glycosylation

Funding

  1. Birmingham Science City Translational Medicine: Experimental Medicine Network of Excellence Project
  2. Advantage West Midlands (AWM)

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Large scale mass spectrometry analysis of N-linked glycopeptides is complicated by the inherent complexity of the glycan structures. Here, we evaluate a mass spectrometry approach for the targeted analysis of N-linked glycopeptides in complex mixtures that does not require prior knowledge of the glycan structures or pre-enrichment of the glycopeptides. Despite the complexity of N-glycans, the core of the glycan remains constant, comprising two N-acetylglucosamine and three mannose units. Collision-induced dissociation (CID) mass spectrometry of N-glycopeptides results in the formation of the N-acetylglucosarnine (GlcNAc) oxonium ion and a [mannose+GlcNAc] fragment (in addition to other fragments resulting from cleavage within the glycan). In ion-trap CID, those ions are not detected due to the low m/z cutoff; however, they are detected following the beam-type CID known as higher energy collision dissociation (HCD) on the orbitrap mass spectrometer. The presence of these product ions following HCD can be used as triggers for subsequent electron transfer dissociation (ETD) mass spectrometry analysis of the precursor ion. The ETD mass spectrum provides peptide sequence information, which is unobtainable from HCD. A Lys-C digest of ribonuclease B and trypsin digest of immunoglobulin G were separated by ZIC-HILIC liquid chromatography and analyzed by HCD product ion-triggered ETD. The data were analyzed both manually and by search against protein databases by commonly used algorithms. The result: show that the product ion-triggered approach shows promise for the field of glycoproteomics and highlight the requirement for more sophisticated data mining tools.

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