Dataset Information

Human serum glycoproteome - Glyco-Decipher

ABSTRACT: Identification results of peptide-spectrum matches supporting Glyco-Decipher manuscript (Glyco-Decipher: Glycan database-independent peptide matching enables discovery of new glycans and in-depth characterization of site-specific N-glycosylation). Recently, several elegant bioinformatics tools have been developed to identify glycopeptides from tandem mass spectra for site-specific glycoproteomics studies. These glycan database-dependent tools have substantially improved glycoproteomics analysis but fail to identify glycopeptides with unexpected glycans. We present a platform called Glyco-Decipher to interpret the glycoproteomics data of N-linked glycopeptides. It adopts a glycan database-independent peptide matching scheme that allows the unbiased profiling of glycans and the discovery of new glycans linked with modifications. Reanalysis of several large-scale datasets showed that Glyco-Decipher outperformed the open search method in glycan blind searching and the popular glycan database-dependent software tools in glycopeptide identification. Our glycan database-independent search also revealed that modified glycans are responsible for a large fraction of unassigned glycopeptide spectra in shotgun glycoproteomics.

ORGANISM(S): Homo Sapiens

SUBMITTER: Mingliang Ye

PROVIDER: PXD045630 | iProX | Mon Sep 25 00:00:00 BST 2023

REPOSITORIES: iProX

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Publications

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

Fang Zheng Z Qin Hongqiang H Mao Jiawei J Wang Zhongyu Z Zhang Na N Wang Yan Y Liu Luyao L Nie Yongzhan Y Dong Mingming M Ye Mingliang M

Nature communications 20220407 1

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-Deci ...[more]

PMID: 35393418

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Project description:Recent advances in software-driven glycopeptide identification in LC-MS/MS-based N-glycoproteomics have facilitated biochemical studies reporting thousands of intact N-glycopeptides, i.e. N-glycan-conjugated peptides, but the automated identification process remains to be scrutinized. Herein, we explore the efficiency of site-specific glycoprofiling using the PTM-centric search-engine Byonic relative to manual expert annotation. To allow an appropriately deep comparison, the study utilised typical glycoproteomics acquisition and data analysis strategies, but of a single glycoprotein, the uncharacterised N-glycosylated (Asn160, Asn268 and Asn302) human basigin. Detailed site-specific reference glycoprofiles of purified basigin were manually established using ion trap CID-MS/MS and high-resolution Q-Exactive Orbitrap HCD-MS/MS acquisition of tryptic N-glycopeptides and released N-glycans. The basigin N-glycosylation sites, which showed extensive micro- and macro-heterogeneity, were then glycoprofiled using Byonic with or without a background of complex peptides using Q-Exactive Orbitrap HCD-MS/MS data. The glycoprofiling efficiencies were assessed against the site-specific reference glycoprofiles and target and decoy proteome databases. The search criteria and confidence thresholds (Byonic scores) recommended by the vendor provided very high glycoprofiling accuracy and coverage (both >80%) and low peptide FDRs (<1%). The data complexity, search parameters including search space (proteome/glycome size), mass tolerance and peptide modifications, and confidence thresholds affected the glycoprofiling efficiency and analysis time. Automated identification of peptide modifications (methionine oxidation/carbamidomethylation) that coincide with monosaccharide mass differences (Fuc/Hex/HexNAc) and accurately distinguishing isobaric (Hex1NeuAc1-R/Fuc1NeuGc1-R) or near-isobaric (NeuAc1-R/Fuc2-R) monosaccharide sub-compositions remain challenging, arguing particular attention to such “difficult-to-identify” N-glycopeptides. The presented analysis provides valuable insights into automated glycopeptide identification; knowledge that facilitates further developments in FDR-based glycoproteomics.

Dataset Information

Human serum glycoproteome - Glyco-Decipher

Publications

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

Similar Datasets

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