An Effective Approach for Glycan Structure De Novo Sequencing From HCD Spectra

New Energy Setup Strategy for Intact N-Glycopeptides Characterization Using Higher-Energy Collisional Dissociation

With the optional setting of multiple stepped collisional energies (NCEs), higher-energy collisional dissociation (HCD) as available on Orbitrap instruments is a widely adopted dissociation method for intact N-glycopeptides characterization, where peptide backbones and N-glycan moieties are selectively fragmented at high and low NCEs, respectively. Initially, a dependent setting of a central value plus minus a variation is available to the users to set up NCEs, and the combination of 30 ± 10% to give the energies 20%/30%/40% has been mostly adopted in the literature. With the recent availability of an independent NCEs setup, we found that the combination of 20%/30%/30% is better than 20%/30%/40%; in the analysis of complex intact N-glycopeptides enriched from gastric cancer tissues, total IDs with spectrum-level FDR ≤ 1%, site-specific IDs with site-determining fragment ions, and structure-specific IDs with structure-diagnostic fragment ions were increased by 42% (4,767 → 6,746), 57% (599 → 942), and 97% (1771 → 3495), respectively. This finding will benefit all the coming N-glycoproteomics studies using HCD as the dissociation method.

An Improved Approach for N-Linked Glycan Structure Identification from HCD MS/MS Spectra

Glycosylation is a frequently observed post-translational modification on proteins. Currently, tandem mass spectrometry (MS/MS) serves as an efficient analytical technique for characterizing structures of oligosaccharides. However, developing effective computational approaches for identifying glycan structures from mass spectra is still a great challenge in glycoproteomics research. In this study, we proposed an approach for matching the input spectra with glycan structures acquired from a glycan structure database by incorporating a de novo sequencing assisted ranking scheme. The proposed approach is implemented as a software tool, GlycoNovoDB, for automated glycan structure identification from HCD MS/MS of glycopeptides. Experimental results showed that GlycoNovoDB can identify glycans effectively and has better performance than our previously proposed de novo sequencing algorithm as well as another software GlycoMaster DB.

Status Report on the High-Throughput Characterization of Complex Intact O-Glycopeptide Mixtures

A very complex mixture of intact, human N- and O-glycopeptides, enriched from the tryptic digest of urinary proteins of three healthy donors using a two-step lectin affinity enrichment, was analyzed by LC-MS/MS, leading to approximately 45,000 glycopeptide EThcD spectra. Two search engines, Byonic and Protein Prospector, were used for the interpretation of the data, and N- and O-linked glycopeptides were assigned from separate searches. The identification rate was very low in all searches, even when results were combined. Thus, we investigated the reasons why was it so, to help to improve the identification success rate. Focusing on O-linked glycopeptides, we noticed that in EThcD, larger glycan oxonium ions better survive the activation than those in HCD. These fragments, combined with reducing terminal Y ions, provide important information about the glycan(s) present, so we investigated whether filtering the peaklists for glycan oxonium ions indicating the presence of a tetra- or hexasaccharide structure would help to reveal all molecules containing such glycans. Our study showed that intact glycans frequently do not survive even mild supplemental activation, meaning one cannot rely on these oxonium ions exclusively. We found that ETD efficiency is still a limiting factor, and for highly glycosylated peptides, the only information revealed in EThcD was related to the glycan structures. The limited overlap of results delivered by the two search engines draws attention to the fact that automated data interpretation of O-linked glycopeptides is not even close to being solved. Graphical abstract ᅟ.

An approach for N-linked glycan identification from MS/MS spectra by target-decoy strategy

Glycan structure determination serves as an essential step for the thorough investigation of the structure and function of protein. Currently, appropriate sample preparation followed by tandem mass spectrometry has emerged as the dominant technique for the characterization of glycans and glycopeptides. Although extensive efforts have been made to the development of computational approaches for the automated interpretation of glycopeptide spectra, the previously appeared methods lack a reasonable quality control strategy for the statistical validation of reported results. In this manuscript, we introduced a novel method that constructed a decoy glycan database based on the glycan structures in the target database, and searched the experimental spectra against both the target and decoy databases to find the best matched glycans. Specifically, a two-layer scoring scheme for calculating a normalized matching score is applied in the search procedure which enables the unbiased ranking of the matched glycans. Experimental analysis showed that our proposed method can report more structures with high confidence compared with previous approaches.