1
|
Glyco-Decipher enables glycan database-independent peptide matching and in-depth characterization of site-specific N-glycosylation. Nat Commun 2022; 13:1900. [PMID: 35393418 PMCID: PMC8990002 DOI: 10.1038/s41467-022-29530-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 03/16/2022] [Indexed: 12/20/2022] Open
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. Poor peptide fragmentation and unusual glycan structures limit mass spectrometry-based analysis of intact N-glycopeptides. Here, the authors develop Glyco-Decipher, a glycan-independent peptide search tool, to tackle these issues and improve the coverage of site-specific glycan analysis.
Collapse
|
2
|
Harvey DJ. ANALYSIS OF CARBOHYDRATES AND GLYCOCONJUGATES BY MATRIX-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY: AN UPDATE FOR 2015-2016. MASS SPECTROMETRY REVIEWS 2021; 40:408-565. [PMID: 33725404 DOI: 10.1002/mas.21651] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 07/24/2020] [Indexed: 06/12/2023]
Abstract
This review is the ninth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2016. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented over 30 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show no sign of deminishing. © 2020 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- David J Harvey
- Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom
| |
Collapse
|
3
|
Yu Q, Wang B, Chen Z, Urabe G, Glover MS, Shi X, Guo LW, Kent KC, Li L. Electron-Transfer/Higher-Energy Collision Dissociation (EThcD)-Enabled Intact Glycopeptide/Glycoproteome Characterization. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2017; 28:1751-1764. [PMID: 28695533 PMCID: PMC5711575 DOI: 10.1007/s13361-017-1701-4] [Citation(s) in RCA: 150] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2016] [Revised: 03/28/2017] [Accepted: 04/29/2017] [Indexed: 05/04/2023]
Abstract
Protein glycosylation, one of the most heterogeneous post-translational modifications, can play a major role in cellular signal transduction and disease progression. Traditional mass spectrometry (MS)-based large-scale glycoprotein sequencing studies heavily rely on identifying enzymatically released glycans and their original peptide backbone separately, as there is no efficient fragmentation method to produce unbiased glycan and peptide product ions simultaneously in a single spectrum, and that can be conveniently applied to high throughput glycoproteome characterization, especially for N-glycopeptides, which can have much more branched glycan side chains than relatively less complex O-linked glycans. In this study, a redefined electron-transfer/higher-energy collision dissociation (EThcD) fragmentation scheme is applied to incorporate both glycan and peptide fragments in one single spectrum, enabling complete information to be gathered and great microheterogeneity details to be revealed. Fetuin was first utilized to prove the applicability with 19 glycopeptides and corresponding five glycosylation sites identified. Subsequent experiments tested its utility for human plasma N-glycoproteins. Large-scale studies explored N-glycoproteomics in rat carotid arteries over the course of restenosis progression to investigate the potential role of glycosylation. The integrated fragmentation scheme provides a powerful tool for the analysis of intact N-glycopeptides and N-glycoproteomics. We also anticipate this approach can be readily applied to large-scale O-glycoproteome characterization. Graphical Abstract ᅟ.
Collapse
Affiliation(s)
- Qing Yu
- School of Pharmacy, University of Wisconsin, Madison, WI, 53705, USA
| | - Bowen Wang
- Department of Surgery, Wisconsin Institutes for Medical Research, Madison, WI, 53705, USA
| | - Zhengwei Chen
- Department of Chemistry, University of Wisconsin, Madison, WI, 53706, USA
| | - Go Urabe
- Department of Surgery, Wisconsin Institutes for Medical Research, Madison, WI, 53705, USA
| | - Matthew S Glover
- School of Pharmacy, University of Wisconsin, Madison, WI, 53705, USA
- Cardiovascular Research Center Training Program in Translational Cardiovascular Science, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Xudong Shi
- Department of Surgery, Wisconsin Institutes for Medical Research, Madison, WI, 53705, USA
| | - Lian-Wang Guo
- Department of Surgery, Wisconsin Institutes for Medical Research, Madison, WI, 53705, USA
| | - K Craig Kent
- The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin, Madison, WI, 53705, USA.
- Department of Chemistry, University of Wisconsin, Madison, WI, 53706, USA.
- Cardiovascular Research Center Training Program in Translational Cardiovascular Science, University of Wisconsin-Madison, Madison, WI, 53705, USA.
| |
Collapse
|