We present the adaptability of Mascot search engine for automated identification of intact glycopeptide mass spectra. The steps involved in adopting Mascot for intact glycopeptide analysis include: i) assigning unique one letter codes for monosaccharides, ii) linearizing glycan sequences and iii) preparing custom glycoprotein databases. Stepped normalized collision energy (NCE) for HCD mostly provided both the peptide and glycan information in a single MS2 spectrum. Using standard glycoproteins, we showed that Mascot can be adopted for automated annotation of both N- and O-linked glycopeptides. In a large scale validation study, a total of 257 glycoproteins containing 970 unique glycosylation sites and 3447 non-redundant N-linked glycopeptide variants were identified in serum samples. This represent a single tool that collectively allows the i) elucidation of N- and O-linked glycopeptide spectra, ii) matching glycopeptides to known protein sequences, and iii) high-throughput, batch wise analysis of large scale glycoproteomics data sets.
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: Glycoproteomics ; higher-energy collisional induced dissociation (HCD) ; Mascot ; prostate cancer ; serum
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Principal Investigators: (in alphabetical order) |
Bernd Thiede, University of Oslo, Department of Biosciences, N/A |
| Submitting User: | ccms |
Bollineni RC, Koehler CJ, Gislefoss RE, Anonsen JH, Thiede B.
Large-scale intact glycopeptide identification by Mascot database search.
Sci Rep. 2018 Feb 1;8(1):2117. Epub 2018 Feb 1.
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