PGlyco: a pipeline for the identification of intact N-glycopeptides by using HCD- and CID-MS/MS and MS3.

Wen-Feng Zeng,Weiqian Cao,Yang Zhang,Catherine C L Wong,Guoquan Yan,Si-Min He,Jian-Qiang Wu,Aiying Nie,Chao Liu,Rui-Xiang Sun,Pan Fang,Hao Chi,Pengyuan Yang,Chao Peng,Ming-Qi Liu

doi:10.1038/srep25102

Abstract

Confident characterization of the microheterogeneity of protein glycosylation through identification of intact glycopeptides remains one of the toughest analytical challenges for glycoproteomics. Recently proposed mass spectrometry (MS)-based methods still have some defects such as lack of the false discovery rate (FDR) analysis for the glycan identification and lack of sufficient fragmentation information for the peptide identification. Here we proposed pGlyco, a novel pipeline for the identification of intact glycopeptides by using complementary MS techniques: 1) HCD-MS/MS followed by product-dependent CID-MS/MS was used to provide complementary fragments to identify the glycans, and a novel target-decoy method was developed to estimate the false discovery rate of the glycan identification; 2) data-dependent acquisition of MS3 for some most intense peaks of HCD-MS/MS was used to provide fragments to identify the peptide backbones. By integrating HCD-MS/MS, CID-MS/MS and MS3, intact glycopeptides could be confidently identified. With pGlyco, a standard glycoprotein mixture was analyzed in the Orbitrap Fusion, and 309 non-redundant intact glycopeptides were identified with detailed spectral information of both glycans and peptides.

Highlights

Confident characterization of the microheterogeneity of protein glycosylation remains one of the toughest analytical challenges[1,2]
The b and y ions of the peptide backbone are usually undetectable in a CID-MS/MS spectrum[4], so the peptide backbone identification should be performed by using some other MS techniques
The sensitivity and the applicable scope of ETD-MS/MS are arguably limited as compared with HCD- and CID-MS/MS in current generation of MS instruments[11,12,13], though some supercharging methods such as TMT tagging have been used to improve the sensitivity of glycopeptide identification in ETD-MS/MS analysis[14,15]

Summary

Introduction

Confident characterization of the microheterogeneity of protein glycosylation remains one of the toughest analytical challenges[1,2]. The sensitivity and the applicable scope of ETD-MS/MS are arguably limited as compared with HCD- and CID-MS/MS in current generation of MS instruments[11,12,13], though some supercharging methods such as TMT tagging have been used to improve the sensitivity of glycopeptide identification in ETD-MS/MS analysis[14,15] Another interesting MS technique for peptide backbone identification www.nature.com/scientificreports/. Peptide backbone identification and glycan FDR estimation are two of the most challenging problems in glycoproteomics To address these two issues, we proposed a new pipeline called pGlyco, which included two new features: 1) complementary fragments from both HCD-MS/MS and CID-MS/MS were used to identify glycans, and a novel target-decoy method was developed to estimate the false discovery rate of the glycan identification; 2) data-dependent acquisition (DDA) of MS3 for some most intense peaks in the HCD-MS/MS spectrum was used to identify peptide backbones. We applied pGlyco to the study of a mixture of 6 standard glycoproteins and identified 309 non-redundant intact glycopeptides. pGlyco is currently available for free download at http://pfind.ict.ac.cn/software/pGlyco1505/

Methods

Results

Conclusion