Glyco-Decipher enables glycan database-independent peptide matching and in-depth characterization of site-specific N-glycosylation

Zheng Fang, Hongqiang Qin, Jiawei Mao, Zhongyu Wang, Na Zhang, Yan Wang, Luyao Liu, Yongzhan Nie, Mingming Dong () and Mingliang Ye ()
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Zheng Fang: Chinese Academy of Sciences
Hongqiang Qin: Chinese Academy of Sciences
Jiawei Mao: Chinese Academy of Sciences
Zhongyu Wang: Chinese Academy of Sciences
Na Zhang: Chinese Academy of Sciences
Yan Wang: Chinese Academy of Sciences
Luyao Liu: Chinese Academy of Sciences
Yongzhan Nie: Fourth Military Medical University
Mingming Dong: Chinese Academy of Sciences
Mingliang Ye: Chinese Academy of Sciences

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Glycopeptides with unusual glycans or poor peptide backbone fragmentation in tandem mass spectrometry are unaccounted for in typical site-specific glycoproteomics analysis and thus remain unidentified. Here, we develop a glycoproteomics tool, Glyco-Decipher, to address these issues. Glyco-Decipher conducts glycan database-independent peptide matching and exploits the fragmentation pattern of shared peptide backbones in glycopeptides to improve the spectrum interpretation. We benchmark Glyco-Decipher on several large-scale datasets, demonstrating that it identifies more peptide-spectrum matches than Byonic, MSFragger-Glyco, StrucGP and pGlyco 3.0, with a 33.5%-178.5% increase in the number of identified glycopeptide spectra. The database-independent and unbiased profiling of attached glycans enables the discovery of 164 modified glycans in mouse tissues, including glycans with chemical or biological modifications. By enabling in-depth characterization of site-specific protein glycosylation, Glyco-Decipher is a promising tool for advancing glycoproteomics analysis in biological research.

Date: 2022
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DOI: 10.1038/s41467-022-29530-y

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