Studying protein O-glycosylation remains an analytical challenge. Different from N-linked glycans, the O-glycosylation site is not within a known consensus sequence. Additionally, O-glycans are heterogeneous with numerous potential modification sites. Electron transfer dissociation (ETD) is the method of choice in analyzing these glycopeptides since the glycan side chain remains intact in ETD, and the glycosylation site can be localized on the basis of the c and z fragment ions. Nonetheless, new software is necessary for interpreting O-glycopeptide ETD spectra in order to expedite the analysis workflow. To address the urgent need, we studied the fragmentation of O-glycopeptides in ETD and found useful rules that facilitate their identification. By implementing the rules into an algorithm to score potential assignments against ETD-MS/MS data, we applied the method to glycopeptides generated from various O-glycosylated proteins including mucin, erythropoietin, fetuin, and an HIV envelope protein, 1086.C gp120. The site-specific O-glycopeptide composition was correctly assigned in every case, proving the merits of our method in analyzing glycopeptide ETD data. The algorithm described herein can be easily incorporated into other automated glycomics tools.
Studying protein O-glycosylation remains an analytical challenge. Different from N-linked glycans, the O-glycosylation site is not within a known consensus sequence. Additionally, n class="Chemical">O-glycans are heterogeneous with numerous potential modification sites. Electron transfer dissociation (ETD) is the method of choice in analyzing these glycopeptides since the glycan side chain remains intact in ETD, and the glycosylation site can be localized on the basis of the c and z fragment ions. Nonetheless, new software is necessary for interpreting O-glycopeptide ETD spectra in order to expedite the analysis workflow. To address the urgent need, we studied the fragmentation of O-glycopeptides in ETD and found useful rules that facilitate their identification. By implementing the rules into an algorithm to score potential assignments against ETD-MS/MS data, we applied the method to glycopeptides generated from various O-glycosylated proteins including mucin, erythropoietin, fetuin, and an HIV envelope protein, 1086.C gp120. The site-specific O-glycopeptide composition was correctly assigned in every case, proving the merits of our method in analyzing glycopeptide ETD data. The algorithm described herein can be easily incorporated into other automated glycomics tools.
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