Improving confidence in detection and characterization of protein N-glycosylation sites and microheterogeneity

• Published in: Rapid communications in mass spectrometry Vol. 25; no. 14; pp. 2007 - 2019
• Main Authors: Mayampurath, Anoop M., Wu, Yin, Segu, Zaneer M., Mechref, Yehia, Tang, Haixu
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 30-07-2011
• Subjects: Amino Acid Sequence; Animals; Carbohydrate Sequence; Cattle; Glycopeptides - chemistry; Glycoproteins - chemistry; Glycosylation; Humans; Molecular Sequence Data; Oxygen - chemistry; Software; Tandem Mass Spectrometry - methods
• ISSN: 0951-4198; 1097-0231
• DOI: 10.1002/rcm.5059

Protein glycosylation is one of the most common post‐translational modifications, estimated to occur in over 50% of human proteins. Mass spectrometry (MS)‐based approaches involving different fragmentation mechanisms have been frequently used to detect and characterize protein N‐linked glycosylations. In addition to the popular Collision‐Induced Dissociation (CID), high‐energy C‐trap dissociation (HCD) fragmentation, which is a feature of a linear ion trap orbitrap hybrid mass spectrometer (LTQ Orbitrap), has been recently used for the fragmentation of tryptic N‐linked glycopeptides in glycoprotein analysis. The oxonium ions observed with high mass accuracy in the HCD spectrum of glycopeptides can be combined with characteristic fragmentation patterns in the CID spectrum resulting from consecutive glycosidic bond cleavages, to improve the detection and characterization of N‐linked glycopeptides. As a means of automating this process, we describe here GlypID 2.0, a software tool that implements several algorithmic approaches to utilize MS information including accurate precursor mass and spectral patterns from both HCD and CID spectra, thus allowing for an unequivocal and accurate characterization of N‐linked glycosylation sites of proteins. Copyright © 2011 John Wiley & Sons, Ltd.