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The Fine Art of Destruction: A Guide to In‐Depth Glycoproteomic Analyses—Exploiting the Diagnostic Potential of Fragment Ions
Author(s) -
Hoffmann Marcus,
Pioch Markus,
Pralow Alexander,
Hennig René,
Kottler Robert,
Reichl Udo,
Rapp Erdmann
Publication year - 2018
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201800282
Subject(s) - glycoproteomics , glycopeptide , glycan , chemistry , fragmentation (computing) , chromatography , computational biology , glycoprotein , oxonium ion , biochemistry , biology , ion , organic chemistry , antibiotics , ecology
The unambiguous mass spectrometric identification and characterization of glycopeptides is crucial to elucidate the micro‐ and macroheterogeneity of glycoproteins. Here, combining lower and stepped collisional energy fragmentation for the in‐depth and site‐specific analysis of N ‐ and O ‐glycopeptides is proposed. Using a set of four representative and biopharmaceutically relevant glycoproteins (IgG, fibrinogen, lactotransferrin, and ribonuclease B), the benefits and limitations of the developed workflow are highlighted and a state‐of‐the‐art blueprint for conducting high‐quality in‐depth N ‐ and O ‐glycoproteomic analyses is provided. Further, a modified and improved version of cotton hydrophilic interaction liquid chromatography‐based solid phase extraction for glycopeptide enrichment is described. For the unambiguous identification of N ‐glycopeptides, the use of a conserved yet, rarely employed‐fragmentation signature [M peptide +H+ 0,2 X GlcNAc] + is proposed. It is shown for the first time that this fragmentation signature can consistently be found across all N ‐glycopeptides, but not on O ‐glycopeptides. Moreover, the use of the relative abundance of oxonium ions to retrieve glycan structure information, for example, differentiation of hybrid‐ and high‐mannose‐type N ‐glycans or differentiation between antenna GlcNAc and bisecting GlcNAc, is systematically and comprehensively evaluated. The findings may increase confidence and comprehensiveness in manual and software‐assisted glycoproteomics.