Uncovering missing glycans and unexpected fragments with pGlycoNovo for site-specific glycosylation analysis across species

Precision mapping of site-specific glycans using mass spectrometry is vital in glycoproteomics. However, the diversity of glycan compositions across species often exceeds database capacity, hindering the identification of rare glycans. Here, we introduce pGlycoNovo, a software within the pGlyco3 software environment, which employs a glycan first-based full-range Y-ion dynamic searching strategy. pGlycoNovo enables de novo identification of intact glycopeptides with rare glycans by considering all possible monosaccharide combinations, expanding the glycan search space to 16~1000 times compared to non-open search methods, while maintaining accuracy, sensitivity and speed. Reanalysis of SARS Covid-2 spike protein glycosylation data revealed 230 additional site-specific N-glycans and 30 previously unreported O-glycans. pGlycoNovo demonstrated high complementarity to six other tools and superior search speed. It enables characterization of site-specific N-glycosylation across five evolutionarily distant species, contributing to a dataset of 32,549 site-specific glycans on 4602 proteins, including 2409 site-specific rare glycans, and uncovering unexpected glycan fragments.

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Publication Details

Journal
Nature Communications
Published
2024-09-14
DOI
https://doi.org/10.1038/s41467-024-52099-7
Citations
13
Primary Topic
Glycosylation and Glycoproteins Research
Type
article
Field-Weighted Citation Impact
3.04

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article

Uncovering missing glycans and unexpected fragments with pGlycoNovo for site-specific glycosylation analysis across species

Wen‐Feng Zeng, Huanhuan Zhao, Weiqian Cao, Chao Liu et al.
13 citations
Nature Communications
Glycosylation and Glycoproteins Research
3.04
article

Uncovering missing glycans and unexpected fragments with pGlycoNovo for site-specific glycosylation analysis across species

Wen‐Feng Zeng, Huanhuan Zhao, Weiqian Cao, Chao Liu, Guoquan Yan
article en
13 citations

Abstract

Precision mapping of site-specific glycans using mass spectrometry is vital in glycoproteomics. However, the diversity of glycan compositions across species often exceeds database capacity, hindering the identification of rare glycans. Here, we introduce pGlycoNovo, a software within the pGlyco3 software environment, which employs a glycan first-based full-range Y-ion dynamic searching strategy. pGlycoNovo enables de novo identification of intact glycopeptides with rare glycans by considering all possible monosaccharide combinations, expanding the glycan search space to 16~1000 times compared to non-open search methods, while maintaining accuracy, sensitivity and speed. Reanalysis of SARS Covid-2 spike protein glycosylation data revealed 230 additional site-specific N-glycans and 30 previously unreported O-glycans. pGlycoNovo demonstrated high complementarity to six other tools and superior search speed. It enables characterization of site-specific N-glycosylation across five evolutionarily distant species, contributing to a dataset of 32,549 site-specific glycans on 4602 proteins, including 2409 site-specific rare glycans, and uncovering unexpected glycan fragments.

Nature CommunicationsVol. 15(1)
Chinese Academy of Sciences (CN), Fudan University (CN), Westlake University (CN), Institute of Computing Technology (CN), Obstetrics and Gynecology Hospital of Fudan University (CN), Beihang University (CN)
National Natural Science Foundation of China, Fudan University
Openalex Percentile: Top 8%
Glycosylation and Glycoproteins Research
3.04
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Uncovering missing glycans and unexpected fragments with pGlycoNovo for site-specific glycosylation analysis across species — Wen‐Feng Zeng, Huanhuan Zhao, et al. · Nature Communications (2024) | TGRS Research Map | TGRS