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Updated: Feb 15, 2026
08:37
The Application of Open Searching-based Approaches for the Identification of Acinetobacter baumannii O-linked Glycopeptides
Published on: November 2, 2021
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Large-scale intact glycopeptide identification by Mascot database search
Ravi Chand Bollineni1, Christian Jeffrey Koehler1, Randi Elin Gislefoss2
1Department of Biosciences, University of Oslo, Oslo, Norway.
Scientific Reports
|February 3, 2018
Summary
A new automated method enhances glycoproteomics by analyzing intact glycopeptide mass spectra. This tool facilitates high-throughput identification of N- and O-linked glycopeptides in large datasets.
Area of Science:
- Biochemistry
- Proteomics
- Mass Spectrometry
Background:
- Glycoproteomics workflows for large-scale analysis are currently limited.
- Automated annotation of intact glycopeptide mass spectra is needed.
Purpose of the Study:
- To develop an automated approach for intact glycopeptide mass spectra annotation.
- To enable high-throughput analysis of large-scale glycoproteomics data.
Main Methods:
- Adapted the Mascot search engine for glycopeptide analysis.
- Developed methods for monosaccharide coding, glycan sequence linearization, and custom database preparation.
- Validated automated annotation using standard glycoproteins.
Main Results:
- Successfully automated the annotation of both N-linked and O-linked glycopeptides.
- Identified 257 glycoproteins, 970 glycosylation sites, and 3447 N-linked glycopeptide variants in 24 serum samples.
- Demonstrated high-throughput, batch-wise analysis capability.
Conclusions:
- A single, automated tool was developed for glycopeptide spectra elucidation and protein matching.
- The approach enables efficient, large-scale glycoproteomics data analysis.
- This method addresses a critical gap in glycoproteomics research.
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