1
|
Peng W, Reyes CDG, Gautam S, Yu A, Cho BG, Goli M, Donohoo K, Mondello S, Kobeissy F, Mechref Y. MS-based glycomics and glycoproteomics methods enabling isomeric characterization. MASS SPECTROMETRY REVIEWS 2023; 42:577-616. [PMID: 34159615 PMCID: PMC8692493 DOI: 10.1002/mas.21713] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 06/01/2021] [Accepted: 06/02/2021] [Indexed: 05/03/2023]
Abstract
Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.
Collapse
Affiliation(s)
- Wenjing Peng
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | | | - Sakshi Gautam
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Aiying Yu
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Byeong Gwan Cho
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Mona Goli
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | - Kaitlyn Donohoo
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| | | | - Firas Kobeissy
- Program for Neurotrauma, Neuroproteomics & Biomarkers Research, Departments of Emergency Medicine, University of Florida, Gainesville, Florida, USA
| | - Yehia Mechref
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA
| |
Collapse
|
2
|
Rabus JM, Guan S, Schultz LM, Abutokaikah MT, Maître P, Bythell BJ. Protonated α- N-Acetyl Galactose Glycopeptide Dissociation Chemistry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:1745-1752. [PMID: 36018613 DOI: 10.1021/jasms.2c00155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
We recently provided mass spectrometric, H/D labeling, and computational evidence of pyranose to furanose N-acetylated ion isomerization reactions that occurred prior to glycosidic bond cleavage in both O- and N-linked glycosylated amino acid model systems (Guan et al. Phys. Chem. Chem. Phys., 2021, 23, 23256-23266). These reactions occurred irrespective of the glycosidic linkage stereochemistry (α or β) and the N-acetylated hexose structure (GlcNAc or GalNAc). In the present article, we test the generality of the preceding findings by examining threonyl α-GalNAc-glycosylated peptides. We utilize computational chemistry to compare the various dissociation and isomerization pathways accessible with collisional activation. We then interrogate the structure(s) of the resulting charged glycan and peptide fragments with infrared "action" spectroscopy. Isomerization of the original pyranose, the protonated glycopeptide [AT(GalNAc)A+H]+, is predicted to be facile compared to direct dissociation, as is the glycosidic bond cleavage of the newly formed furanose form, i.e., furanose oxazolinium ion structures are predicted to predominate. IR action spectra for the m/z 204, C8H14N1O5+, glycan fragment population support this prediction. The IR action spectra of the complementary m/z 262 peptide fragment were assigned as a mixture of the lowest-energy structures of [ATA+H]+ consistent with the literature. If general, the change to a furanose m/z 204 product ion structure fundamentally alters the ion population available for MS3 dissociation and glycopeptide sequence identification.
Collapse
Affiliation(s)
- Jordan M Rabus
- Department of Chemistry and Biochemistry, Ohio University, 307 Chemistry Building, Athens, Ohio 45701, United States
- Department of Chemistry and Biochemistry, University of Missouri-St. Louis, 1 University Boulevard, St. Louis, Missouri 63121, United States
| | - Shanshan Guan
- Department of Chemistry and Biochemistry, Ohio University, 307 Chemistry Building, Athens, Ohio 45701, United States
- Department of Chemistry and Biochemistry, University of Missouri-St. Louis, 1 University Boulevard, St. Louis, Missouri 63121, United States
| | - Lauren M Schultz
- Department of Chemistry and Biochemistry, Ohio University, 307 Chemistry Building, Athens, Ohio 45701, United States
| | - Maha T Abutokaikah
- Department of Chemistry and Biochemistry, University of Missouri-St. Louis, 1 University Boulevard, St. Louis, Missouri 63121, United States
| | - Philippe Maître
- Institut de Chimie Physique, Université Paris-Saclay, CNRS, Orsay 91405, France
| | - Benjamin J Bythell
- Department of Chemistry and Biochemistry, Ohio University, 307 Chemistry Building, Athens, Ohio 45701, United States
- Department of Chemistry and Biochemistry, University of Missouri-St. Louis, 1 University Boulevard, St. Louis, Missouri 63121, United States
| |
Collapse
|
3
|
Carpenter EJ, Seth S, Yue N, Greiner R, Derda R. GlyNet: a multi-task neural network for predicting protein-glycan interactions. Chem Sci 2022; 13:6669-6686. [PMID: 35756507 PMCID: PMC9172296 DOI: 10.1039/d1sc05681f] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 05/02/2022] [Indexed: 12/14/2022] Open
Abstract
Advances in diagnostics, therapeutics, vaccines, transfusion, and organ transplantation build on a fundamental understanding of glycan–protein interactions. To aid this, we developed GlyNet, a model that accurately predicts interactions (relative binding strengths) between mammalian glycans and 352 glycan-binding proteins, many at multiple concentrations. For each glycan input, our model produces 1257 outputs, each representing the relative interaction strength between the input glycan and a particular protein sample. GlyNet learns these continuous values using relative fluorescence units (RFUs) measured on 599 glycans in the Consortium for Functional Glycomics glycan arrays and extrapolates these to RFUs from additional, untested glycans. GlyNet's output of continuous values provides more detailed results than the standard binary classification models. After incorporating a simple threshold to transform such continuous outputs the resulting GlyNet classifier outperforms those standard classifiers. GlyNet is the first multi-output regression model for predicting protein–glycan interactions and serves as an important benchmark, facilitating development of quantitative computational glycobiology. GlyNet, a neural net model of glycan-protein binding strengths. Given a glycan it outputs binding to each of several protein samples. Reproducing glycan array data, it extrapolates the binding of untested glycans against the protein samples.![]()
Collapse
Affiliation(s)
- Eric J Carpenter
- Department of Chemistry, University of Alberta Edmonton Alberta Canada
| | - Shaurya Seth
- Department of Chemistry, University of Alberta Edmonton Alberta Canada
| | - Noel Yue
- Department of Chemistry, University of Alberta Edmonton Alberta Canada
| | - Russell Greiner
- Department of Computing Science, University of Alberta Edmonton Alberta Canada.,Alberta Machine Intelligence Institute (AMII) Edmonton Alberta Canada
| | - Ratmir Derda
- Department of Chemistry, University of Alberta Edmonton Alberta Canada
| |
Collapse
|
4
|
Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers. Cells 2022; 11:cells11030581. [PMID: 35159390 PMCID: PMC8834236 DOI: 10.3390/cells11030581] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/22/2022] [Accepted: 02/03/2022] [Indexed: 12/16/2022] Open
Abstract
The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation. As of yet, the role of most of these PTMs remains unidentified. In this state-of-the-art review, we present a synopsis of glycosylation processes and the pathophysiological conditions that might ensue secondary to glycosylation shortcomings. The dynamics of protein glycosylation, a crucial mechanism that allows gene and pathway regulation, is described. We also explain how-at a biomolecular level-mutations in glycosylation-related genes may lead to neuropsychiatric manifestations and neurodegenerative disorders. We then analyze the shortcomings of glycoproteomic studies, putting into perspective their downfalls and the different advanced enrichment techniques that emanated to overcome some of these challenges. Furthermore, we summarize studies tackling the association between glycosylation and neuropsychiatric disorders and explore glycoproteomic changes in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, multiple sclerosis, and amyotrophic lateral sclerosis. We finally conclude with the role of glycomics in the area of traumatic brain injury (TBI) and provide perspectives on the clinical application of glycoproteomics as potential diagnostic tools and their application in personalized medicine.
Collapse
|
5
|
Guan S, Bythell BJ. Evidence of gas-phase pyranose-to-furanose isomerization in protonated peptidoglycans. Phys Chem Chem Phys 2021; 23:23256-23266. [PMID: 34632474 DOI: 10.1039/d1cp03842g] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Peptidoglycans are diverse co- and post-translational modifications of key importance in myriad biological processes. Mass spectrometry is employed to infer their biomolecular sequences and stereochemisties, but little is known about the critical gas-phase dissociation processes involved. Here, using tandem mass spectrometry (MS/MS and MSn), isotopic labelling and high-level simulations, we identify and characterize a facile isomerization reaction that produces furanose N-acetylated ions. This reaction occurs for both O- and N-linked peptidoglycans irrespective of glycosidic linkage stereochemistry (α/β). Dissociation of the glycosidic and other bonds thus occur from the furanose isomer critically altering the reaction feasibility and product ion structures.
Collapse
Affiliation(s)
- Shanshan Guan
- Department of Chemistry and Biochemistry, Ohio University, 307 The Chemistry Building, Athens, OH 45701, USA.,Department of Chemistry and Biochemistry, University of Missouri, 1 University Blvd, St. Louis, MO 63121, USA.
| | - Benjamin J Bythell
- Department of Chemistry and Biochemistry, Ohio University, 307 The Chemistry Building, Athens, OH 45701, USA.,Department of Chemistry and Biochemistry, University of Missouri, 1 University Blvd, St. Louis, MO 63121, USA.
| |
Collapse
|
6
|
Turiák L, Sugár S, Ács A, Tóth G, Gömöry Á, Telekes A, Vékey K, Drahos L. Site-specific N-glycosylation of HeLa cell glycoproteins. Sci Rep 2019; 9:14822. [PMID: 31616032 PMCID: PMC6794373 DOI: 10.1038/s41598-019-51428-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Accepted: 09/23/2019] [Indexed: 01/28/2023] Open
Abstract
We have characterized site-specific N-glycosylation of the HeLa cell line glycoproteins, using a complex workflow based on high and low energy tandem mass spectrometry of glycopeptides. The objective was to obtain highly reliable data on common glycoforms, so rigorous data evaluation was performed. The analysis revealed the presence of a high amount of bovine serum contaminants originating from the cell culture media - nearly 50% of all glycans were of bovine origin. Unaccounted, the presence of bovine serum components causes major bias in the human cellular glycosylation pattern; as is shown when literature results using released glycan analysis are compared. We have reliably identified 43 (human) glycoproteins, 69 N-glycosylation sites, and 178 glycoforms. HeLa glycoproteins were found to be highly (68.7%) fucosylated. A medium degree of sialylation was observed, on average 46.8% of possible sialylation sites were occupied. High-mannose sugars were expressed in large amounts, as expected in the case of a cancer cell line. Glycosylation in HeLa cells is highly variable. It is markedly different not only on various proteins but also at the different glycosylation sites of the same protein. Our method enabled the detailed characterization of site-specific N-glycosylation of several glycoproteins expressed in HeLa cell line.
Collapse
Affiliation(s)
- Lilla Turiák
- MS Proteomics Research Group, Research Centre for Natural Sciences, Magyar tudósok körútja 2, H-1117, Budapest, Hungary.
| | - Simon Sugár
- MS Proteomics Research Group, Research Centre for Natural Sciences, Magyar tudósok körútja 2, H-1117, Budapest, Hungary
| | - András Ács
- MS Proteomics Research Group, Research Centre for Natural Sciences, Magyar tudósok körútja 2, H-1117, Budapest, Hungary
- Semmelweis University, Ph.D. School of Pharmaceutical Sciences, Üllői út 26, H-1085, Budapest, Hungary
| | - Gábor Tóth
- MS Proteomics Research Group, Research Centre for Natural Sciences, Magyar tudósok körútja 2, H-1117, Budapest, Hungary
- Budapest University of Technology and Economics, Faculty of Chemical Technology and Biotechnology, Műegyetem rakpart 3, H-1111, Budapest, Hungary
| | - Ágnes Gömöry
- MS Proteomics Research Group, Research Centre for Natural Sciences, Magyar tudósok körútja 2, H-1117, Budapest, Hungary
| | - András Telekes
- Department of Oncology, St Lazarus County Hospital, Füleki út 54-56, H-3100, Salgótarján, Hungary
| | - Károly Vékey
- MS Proteomics Research Group, Research Centre for Natural Sciences, Magyar tudósok körútja 2, H-1117, Budapest, Hungary
| | - László Drahos
- MS Proteomics Research Group, Research Centre for Natural Sciences, Magyar tudósok körútja 2, H-1117, Budapest, Hungary
| |
Collapse
|
7
|
Shipman JT, Su X, Hua D, Desaire H. DecoyDeveloper: An On-Demand, De Novo Decoy Glycopeptide Generator. J Proteome Res 2019; 18:2896-2902. [PMID: 31129958 DOI: 10.1021/acs.jproteome.9b00203] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Glycopeptide analysis is a growing field that is struggling to adopt effective, automated tools. Many creative workflows and software apps have emerged recently that offer promising capabilities for assigning glycopeptides to MS data in an automated fashion. The effectiveness of these tools is best measured and improved by determining how often they would select a glycopeptide decoy as a spectral match, instead of its correct assignment; yet generating the appropriate number and type of glycopeptide decoys can be challenging. To address this need, we have designed DecoyDeveloper, an on-demand decoy glycopeptide generator that can produce a high volume of decoys with low mass differences. DecoyDeveloper has a simple user interface and is capable of producing large sets of decoys containing complete, biologically relevant glycan and peptide sequences. We demonstrate the tool's efficiency by applying it to a set of 80 glycopeptide targets. This tool is freely available and can be found at http://glycopro.chem.ku.edu/J1.php .
Collapse
Affiliation(s)
- Joshua T Shipman
- Department of Chemistry , University of Kansas , Lawrence , Kansas 66045 , United States
| | - Xiaomeng Su
- Department of Chemistry , University of Kansas , Lawrence , Kansas 66045 , United States
| | - David Hua
- Department of Chemistry , University of Kansas , Lawrence , Kansas 66045 , United States
| | - Heather Desaire
- Department of Chemistry , University of Kansas , Lawrence , Kansas 66045 , United States
| |
Collapse
|
8
|
Pioch M, Hoffmann M, Pralow A, Reichl U, Rapp E. glyXtoolMS: An Open-Source Pipeline for Semiautomated Analysis of Glycopeptide Mass Spectrometry Data. Anal Chem 2018; 90:11908-11916. [DOI: 10.1021/acs.analchem.8b02087] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Markus Pioch
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106, Magdeburg, Germany
| | - Marcus Hoffmann
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106, Magdeburg, Germany
| | - Alexander Pralow
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106, Magdeburg, Germany
- glyXera GmbH, 39120, Magdeburg, Germany
| | - Udo Reichl
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106, Magdeburg, Germany
- Bioprocess Engineering, Otto-von-Guericke University, 39106, Magdeburg, Germany
| | - Erdmann Rapp
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106, Magdeburg, Germany
- glyXera GmbH, 39120, Magdeburg, Germany
| |
Collapse
|
9
|
Xiao K, Wang Y, Shen Y, Han Y, Tian Z. Large-scale identification and visualization of N-glycans with primary structures using GlySeeker. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2018; 32:142-148. [PMID: 29105226 DOI: 10.1002/rcm.8023] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 10/19/2017] [Accepted: 10/20/2017] [Indexed: 06/07/2023]
Abstract
RATIONALE Most of the current popular tandem mass spectrometers have the capability of resolving the primary structures (monosaccharide composition, sequence and linkage) of N-glycans; however, compositions or putative structures have mostly been reported so far. Identification and visualization tools of N-glycans are needed. METHODS The isotopic mass-to-charge ratio and envelope fingerprinting algorithm, which has been successfully used for intact protein database search and identification, was adapted for N-glycan database search, and a stand-alone N-glycan database search engine, GlySeeker, for automated N-glycan identification and visualization was developed and successfully benchmarked. Both pseudo 2D graph and one-line text formats with one-letter symbols for monosaccharides were proposed for representing N-glycans. N-glycans were identified with comprehensive interpretation of product ions and false discovery rate (FDR) control. RESULTS In a database search of reversed-phase liquid chromatography/tandem mass spectrometry (RPLC/MS/MS) datasets of the N-glycome enriched from OVCAR-3 ovarian cancer cells, with FDR ≤1% and number of best hits (NoBHs) = 1-30, 1525 N-glycans with comprehensive primary structural information (composition, sequence and linkage) were identified and visualized; among these 1525 N-glycans, 559 had NoBHs = 1, i.e. their structures were uniquely identified. This represents a large-scale identification and visualization of N-glycans with primary structures from tandem mass spectra. CONCLUSIONS A stand-alone N-glycan database search engine called GlySeeker has been developed for large-scale identification and visualization of N-glycans with comprehensive interpretation of tandem mass spectra and FDR control.
Collapse
Affiliation(s)
- Kaijie Xiao
- School of Chemical Science and Engineering and Shanghai Key Laboratory of Chemical Assessment and Sustainability, Tongji University, Shanghai, 200092, China
| | - Yue Wang
- School of Chemical Science and Engineering and Shanghai Key Laboratory of Chemical Assessment and Sustainability, Tongji University, Shanghai, 200092, China
| | - Yun Shen
- School of Chemical Science and Engineering and Shanghai Key Laboratory of Chemical Assessment and Sustainability, Tongji University, Shanghai, 200092, China
| | - Yuyin Han
- School of Chemical Science and Engineering and Shanghai Key Laboratory of Chemical Assessment and Sustainability, Tongji University, Shanghai, 200092, China
| | - Zhixin Tian
- School of Chemical Science and Engineering and Shanghai Key Laboratory of Chemical Assessment and Sustainability, Tongji University, Shanghai, 200092, China
| |
Collapse
|
10
|
Everest-Dass AV, Moh ESX, Ashwood C, Shathili AMM, Packer NH. Human disease glycomics: technology advances enabling protein glycosylation analysis - part 1. Expert Rev Proteomics 2018; 15:165-182. [PMID: 29285957 DOI: 10.1080/14789450.2018.1421946] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
INTRODUCTION Protein glycosylation is recognized as an important post-translational modification, with specific substructures having significant effects on protein folding, conformation, distribution, stability and activity. However, due to the structural complexity of glycans, elucidating glycan structure-function relationships is demanding. The fine detail of glycan structures attached to proteins (including sequence, branching, linkage and anomericity) is still best analysed after the glycans are released from the purified or mixture of glycoproteins (glycomics). The technologies currently available for glycomics are becoming streamlined and standardized and many features of protein glycosylation can now be determined using instruments available in most protein analytical laboratories. Areas covered: This review focuses on the current glycomics technologies being commonly used for the analysis of the microheterogeneity of monosaccharide composition, sequence, branching and linkage of released N- and O-linked glycans that enable the determination of precise glycan structural determinants presented on secreted proteins and on the surface of all cells. Expert commentary: Several emerging advances in these technologies enabling glycomics analysis are discussed. The technological and bioinformatics requirements to be able to accurately assign these precise glycan features at biological levels in a disease context are assessed.
Collapse
Affiliation(s)
- Arun V Everest-Dass
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,b Institute for Glycomics , Griffith University , Gold Coast , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Edward S X Moh
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Christopher Ashwood
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Abdulrahman M M Shathili
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Nicolle H Packer
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,b Institute for Glycomics , Griffith University , Gold Coast , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| |
Collapse
|
11
|
Liu G, Cheng K, Lo CY, Li J, Qu J, Neelamegham S. A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis. Mol Cell Proteomics 2017; 16:2032-2047. [PMID: 28887379 DOI: 10.1074/mcp.m117.068239] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 08/23/2017] [Indexed: 12/12/2022] Open
Abstract
Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MSn proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MSn data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MSn spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data.
Collapse
Affiliation(s)
- Gang Liu
- From the ‡Chemical and Biological Engineering
| | - Kai Cheng
- From the ‡Chemical and Biological Engineering.,§Clinical & Translational Research Center
| | - Chi Y Lo
- From the ‡Chemical and Biological Engineering
| | - Jun Li
- ¶Pharmaceutical Sciences; and.,‖New York State Center for Excellence in Bioinformatics and Life Sciences, Buffalo, New York
| | - Jun Qu
- ¶Pharmaceutical Sciences; and.,‖New York State Center for Excellence in Bioinformatics and Life Sciences, Buffalo, New York
| | - Sriram Neelamegham
- From the ‡Chemical and Biological Engineering; .,§Clinical & Translational Research Center
| |
Collapse
|
12
|
Tsai PL, Chen SF. A Brief Review of Bioinformatics Tools for Glycosylation Analysis by Mass Spectrometry. Mass Spectrom (Tokyo) 2017; 6:S0064. [PMID: 28337402 PMCID: PMC5358406 DOI: 10.5702/massspectrometry.s0064] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 01/14/2017] [Indexed: 12/28/2022] Open
Abstract
The purpose of this review is to provide updated information regarding bioinformatic software for the use in the characterization of glycosylated structures since 2013. A comprehensive review by Woodin et al.Analyst 138: 2793-2803, 2013 (ref. 1) described two main approaches that are introduced for starting researchers in this area; analysis of released glycans and the identification of glycopeptide in enzymatic digests, respectively. Complementary to that report, this review focuses on mass spectrometry related bioinformatics tools for the characterization of N-linked and O-linked glycopeptides. Specifically, it also provides information regarding automated tools that can be used for glycan profiling using mass spectrometry.
Collapse
Affiliation(s)
- Pei-Lun Tsai
- Department of Chemistry, National Taiwan Normal University
- Mithra Biotechnology Inc
| | - Sung-Fang Chen
- Department of Chemistry, National Taiwan Normal University
| |
Collapse
|
13
|
Campbell MP. A Review of Software Applications and Databases for the Interpretation of Glycopeptide Data. TRENDS GLYCOSCI GLYC 2017. [DOI: 10.4052/tigg.1601.1e] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
|
14
|
Kailemia MJ, Park D, Lebrilla CB. Glycans and glycoproteins as specific biomarkers for cancer. Anal Bioanal Chem 2017; 409:395-410. [PMID: 27590322 PMCID: PMC5203967 DOI: 10.1007/s00216-016-9880-6] [Citation(s) in RCA: 240] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2016] [Revised: 07/28/2016] [Accepted: 08/12/2016] [Indexed: 12/12/2022]
Abstract
Protein glycosylation and other post-translational modifications are involved in potentially all aspects of human growth and development. Defective glycosylation has adverse effects on human physiological conditions and accompanies many chronic and infectious diseases. Altered glycosylation can occur at the onset and/or during tumor progression. Identifying these changes at early disease stages may aid in making decisions regarding treatments, as early intervention can greatly enhance survival. This review highlights some of the efforts being made to identify N- and O-glycosylation profile shifts in cancer using mass spectrometry. The analysis of single or panels of potential glycoprotein cancer markers are covered. Other emerging technologies such as global glycan release and site-specific glycosylation analysis and quantitation are also discussed. Graphical Abstract Steps involved in the biomarker discovery.
Collapse
Affiliation(s)
- Muchena J Kailemia
- Department of Chemistry, University of California, Davis, CA, 95616, USA
| | - Dayoung Park
- Department of Chemistry, University of California, Davis, CA, 95616, USA
| | - Carlito B Lebrilla
- Department of Chemistry, University of California, Davis, CA, 95616, USA.
| |
Collapse
|
15
|
Kim JW, Hwang H, Lim JS, Lee HJ, Jeong SK, Yoo JS, Paik YK. gFinder: A Web-Based Bioinformatics Tool for the Analysis of N-Glycopeptides. J Proteome Res 2016; 15:4116-4125. [PMID: 27573070 DOI: 10.1021/acs.jproteome.6b00772] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Glycoproteins influence numerous indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. The identification and characterization of glycoprotein and glycosylation sites by mass spectrometry (MS) remain challenging tasks, and great efforts have been devoted to the development of proteome informatics tools that facilitate the MS analysis of glycans and glycopeptides. Here we report on the development of gFinder, a web-based bioinformatics tool that analyzes mixtures of native N-glycopeptides that have been profiled by tandem MS. gFinder not only enables the simultaneous integration of collision-induced dissociation (CID) and high-energy collisional dissociation (HCD) fragmentation but also merges the spectra for high-throughput analysis. These merged spectra expedite the identification of both glycans and N-glycopeptide backbones in tandem MS data using the glycan database and a proteomic search tool (e.g., Mascot). These data can be used to simultaneously characterize peptide backbone sequences and possible N-glycan structures using assigned scores. gFinder also provides many convenient functions that make it easy to perform manual calculations while viewing the spectrum on-screen. We used gFinder to detect an additional protein (Q8N9B8) that was missed from the previously published data set containing N-linked glycosylation. For N-glycan analysis, we used the GlycomeDB glycan structure database, which integrates the structural and taxonomic data from all of the major carbohydrate databases available in the public domain. Thus, gFinder is a convenient, high-throughput analytical tool for interpreting the tandem mass spectra of N-glycopeptides, which can then be used for identification of potential missing proteins having glycans. gFinder is available publicly at http://gFinder.proteomix.org/ .
Collapse
Affiliation(s)
- Ju-Wan Kim
- Graduate Program in Functional Genomics, College of Life Sciences and Biotechnology, Yonsei University , Seoul 03722, Korea.,Yonsei Proteome Research Center , Seoul 03722, Korea
| | - Heeyoun Hwang
- Korea Basic Science Institute , Ochang 28199, Chungbuk, Korea
| | - Jong-Sun Lim
- Yonsei Proteome Research Center , Seoul 03722, Korea
| | | | - Seul-Ki Jeong
- Yonsei Proteome Research Center , Seoul 03722, Korea
| | - Jong Shin Yoo
- Korea Basic Science Institute , Ochang 28199, Chungbuk, Korea
| | - Young-Ki Paik
- Graduate Program in Functional Genomics, College of Life Sciences and Biotechnology, Yonsei University , Seoul 03722, Korea.,Yonsei Proteome Research Center , Seoul 03722, Korea
| |
Collapse
|
16
|
Ji ES, Hwang H, Park GW, Lee JY, Lee HK, Choi NY, Jeong HK, Kim KH, Kim JY, Lee S, Ahn YH, Yoo JS. Analysis of fucosylation in liver-secreted N-glycoproteins from human hepatocellular carcinoma plasma using liquid chromatography with tandem mass spectrometry. Anal Bioanal Chem 2016; 408:7761-7774. [PMID: 27565792 DOI: 10.1007/s00216-016-9878-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Revised: 08/01/2016] [Accepted: 08/12/2016] [Indexed: 12/11/2022]
Abstract
Fucosylation of N-glycoproteins has been implicated in various diseases, such as hepatocellular carcinoma (HCC). However, few studies have performed site-specific analysis of fucosylation in liver-secreted proteins. In this study, we characterized the fucosylation patterns of liver-secreted proteins in HCC plasma using a workflow to identify site-specific N-glycoproteins, where characteristic B- and/or Y-ion series with and without fucose in collision-induced dissociation were used in tandem mass spectrometry. In total, 71 fucosylated N-glycopeptides from 13 major liver-secreted proteins in human plasma were globally identified by LC-MS/MS. Additionally, 37 fucosylated N-glycopeptides were newly identified from nine liver-secreted proteins, including alpha-1-antichymotrypsin, alpha-1-antitrypsin, alpha-2-HS-glycoprotein, ceruloplasmin, alpha-1-acid glycoprotein 1/2, alpha-2-macroglobulin, serotransferrin, and beta-2-glycoprotein 1. Of the fucosylated N-glycopeptides, bi- and tri-antennary glycoforms were the most common ones identified in liver-secreted proteins from HCC plasma. Therefore, we suggest that this analytical method is effective for characterizing fucosylation in liver-secreted proteins. Graphical abstract A global map of fucosylated and non-fucosylated glycopeptides from 13 liver-secreted glycoproteins in hepatocellular carcinoma plasma.
Collapse
Affiliation(s)
- Eun Sun Ji
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea
| | - Heeyoun Hwang
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea
| | - Gun Wook Park
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea.,Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, Republic of Korea
| | - Ju Yeon Lee
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea
| | - Hyun Kyoung Lee
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea.,Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, Republic of Korea
| | - Na Young Choi
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea.,Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, Republic of Korea
| | - Hoi Keun Jeong
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea.,Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, Republic of Korea
| | - Kwang Hoe Kim
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea.,Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, Republic of Korea
| | - Jin Young Kim
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea
| | - Seungho Lee
- Department of Chemistry, Hannam University, Daejeon, 306-791, Republic of Korea
| | - Yeong Hee Ahn
- Department of Biomedical Science, Cheongju University, Cheongju, 28503, Republic of Korea.
| | - Jong Shin Yoo
- Biomedical Omics Group, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongju, Chungbuk, 28119, Republic of Korea. .,Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, Republic of Korea.
| |
Collapse
|
17
|
Pai PJ, Hu Y, Lam H. Direct glycan structure determination of intact N-linked glycopeptides by low-energy collision-induced dissociation tandem mass spectrometry and predicted spectral library searching. Anal Chim Acta 2016; 934:152-62. [DOI: 10.1016/j.aca.2016.05.049] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Revised: 05/24/2016] [Accepted: 05/30/2016] [Indexed: 11/24/2022]
|
18
|
Jansen BC, Falck D, de Haan N, Hipgrave Ederveen AL, Razdorov G, Lauc G, Wuhrer M. LaCyTools: A Targeted Liquid Chromatography-Mass Spectrometry Data Processing Package for Relative Quantitation of Glycopeptides. J Proteome Res 2016; 15:2198-210. [PMID: 27267458 DOI: 10.1021/acs.jproteome.6b00171] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Bottom-up glycoproteomics by liquid chromatography-mass spectrometry (LC-MS) is an established approach for assessing glycosylation in a protein- and site-specific manner. Consequently, tools are needed to automatically align, calibrate, and integrate LC-MS glycoproteomics data. We developed a modular software package designed to tackle the individual aspects of an LC-MS experiment, called LaCyTools. Targeted alignment is performed using user defined m/z and retention time (tr) combinations. Subsequently, sum spectra are created for each user defined analyte group. Quantitation is performed on the sum spectra, where each user defined analyte can have its own tr, minimum, and maximum charge states. Consequently, LaCyTools deals with multiple charge states, which gives an output per charge state if desired, and offers various analyte and spectra quality criteria. We compared throughput and performance of LaCyTools to combinations of available tools that deal with individual processing steps. LaCyTools yielded relative quantitation of equal precision (relative standard deviation <0.5%) and higher trueness due to the use of MS peak area instead of MS peak intensity. In conclusion, LaCyTools is an accurate automated data processing tool for high-throughput analysis of LC-MS glycoproteomics data. Released under the Apache 2.0 license, it is freely available on GitHub ( https://github.com/Tarskin/LaCyTools ).
Collapse
Affiliation(s)
- Bas C Jansen
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300RC Leiden, The Netherlands
| | - David Falck
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300RC Leiden, The Netherlands
| | - Noortje de Haan
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300RC Leiden, The Netherlands
| | - Agnes L Hipgrave Ederveen
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300RC Leiden, The Netherlands
| | - Genadij Razdorov
- Department of Biochemistry and Molecular Biology, Faculty of Pharmacy and Biochemistry, University of Zagreb , A. Kovačića 1, HR10000 Zagreb, Croatia
| | - Gordan Lauc
- Department of Biochemistry and Molecular Biology, Faculty of Pharmacy and Biochemistry, University of Zagreb , A. Kovačića 1, HR10000 Zagreb, Croatia
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300RC Leiden, The Netherlands
| |
Collapse
|
19
|
Analytical detection and characterization of biopharmaceutical glycosylation by MS. Bioanalysis 2016; 8:711-27. [PMID: 26964748 DOI: 10.4155/bio.16.20] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Glycosylation plays an important role in ensuring the proper structure and function of most biotherapeutic proteins. Even small changes in glycan composition, structure, or location can have a drastic impact on drug safety and efficacy. Recently, glycosylation has become the subject of increased focus as biopharmaceutical companies rush to create not only biosimilars, but also biobetters based on existing biotherapeutic proteins. Against this backdrop of ongoing biopharmaceutical innovation, updated methods for accurate and detailed analysis of protein glycosylation are critical for biopharmaceutical companies and government regulatory agencies alike. This review summarizes current methods of characterizing biopharmaceutical glycosylation, including compositional mass profiling, isomer-specific profiling and structural elucidation by MS and hyphenated techniques.
Collapse
|
20
|
A review of methods for interpretation of glycopeptide tandem mass spectral data. Glycoconj J 2015; 33:285-96. [PMID: 26612686 DOI: 10.1007/s10719-015-9633-3] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Revised: 10/13/2015] [Accepted: 10/21/2015] [Indexed: 12/25/2022]
Abstract
Despite the publication of several software tools for analysis of glycopeptide tandem mass spectra, there remains a lack of consensus regarding the most effective and appropriate methods. In part, this reflects problems with applying standard methods for proteomics database searching and false discovery rate calculation. While the analysis of small post-translational modifications (PTMs) may be regarded as an extension of proteomics database searching, glycosylation requires specialized approaches. This is because glycans are large and heterogeneous by nature, causing glycopeptides to exist as multiple glycosylated variants. Thus, the mass of the peptide cannot be calculated directly from that of the intact glycopeptide. In addition, the chemical nature of the glycan strongly influences product ion patterns observed for glycopeptides. As a result, glycopeptidomics requires specialized bioinformatics methods. We summarize the recent progress towards a consensus for effective glycopeptide tandem mass spectrometric analysis.
Collapse
|
21
|
Tóth E, Vékey K, Ozohanics O, Jekő A, Dominczyk I, Widlak P, Drahos L. Changes of protein glycosylation in the course of radiotherapy. J Pharm Biomed Anal 2015; 118:380-386. [PMID: 26609677 DOI: 10.1016/j.jpba.2015.11.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Revised: 11/04/2015] [Accepted: 11/08/2015] [Indexed: 01/11/2023]
Abstract
This is the first study of changes in protein glycosylation due to exposure of human subjects to ionizing radiation. Site specific glycosylation patterns of 7 major plasma proteins were analyzed; 171 glycoforms were identified; and the abundance of 99 of these was followed in the course of cancer radiotherapy in 10 individual patients. It was found that glycosylation of plasma proteins does change in response to partial body irradiation (∼ 60 Gy), and the effects last during follow-up; the abundance of some glycoforms changed more than twofold. Both the degree of changes and their time-evolution showed large inter-individual variability.
Collapse
Affiliation(s)
- Eszter Tóth
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary; Semmelweis University, School of Ph.D. Studies, Budapest, Hungary
| | - Károly Vékey
- Core Technologies Centre, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
| | - Olivér Ozohanics
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
| | - Anita Jekő
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
| | - Iwona Dominczyk
- Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Piotr Widlak
- Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - László Drahos
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.
| |
Collapse
|
22
|
Jansen BC, Reiding KR, Bondt A, Hipgrave Ederveen AL, Palmblad M, Falck D, Wuhrer M. MassyTools: A High-Throughput Targeted Data Processing Tool for Relative Quantitation and Quality Control Developed for Glycomic and Glycoproteomic MALDI-MS. J Proteome Res 2015; 14:5088-98. [PMID: 26565759 DOI: 10.1021/acs.jproteome.5b00658] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The study of N-linked glycosylation has long been complicated by a lack of bioinformatics tools. In particular, there is still a lack of fast and robust data processing tools for targeted (relative) quantitation. We have developed modular, high-throughput data processing software, MassyTools, that is capable of calibrating spectra, extracting data, and performing quality control calculations based on a user-defined list of glycan or glycopeptide compositions. Typical examples of output include relative areas after background subtraction, isotopic pattern-based quality scores, spectral quality scores, and signal-to-noise ratios. We demonstrated MassyTools' performance on MALDI-TOF-MS glycan and glycopeptide data from different samples. MassyTools yielded better calibration than the commercial software flexAnalysis, generally showing 2-fold better ppm errors after internal calibration. Relative quantitation using MassyTools and flexAnalysis gave similar results, yielding a relative standard deviation (RSD) of the main glycan of ~6%. However, MassyTools yielded 2- to 5-fold lower RSD values for low-abundant analytes than flexAnalysis. Additionally, feature curation based on the computed quality criteria improved the data quality. In conclusion, we show that MassyTools is a robust automated data processing tool for high-throughput, high-performance glycosylation analysis. The package is released under the Apache 2.0 license and is freely available on GitHub ( https://github.com/Tarskin/MassyTools ).
Collapse
Affiliation(s)
- Bas C Jansen
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Karli R Reiding
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Albert Bondt
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands.,Department of Rheumatology, Erasmus University Medical Center , 3000 CA Rotterdam, The Netherlands
| | - Agnes L Hipgrave Ederveen
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Magnus Palmblad
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - David Falck
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands.,Division of BioAnalytical Chemistry, VU University Amsterdam , 1081 HV Amsterdam, The Netherlands
| |
Collapse
|
23
|
Engaging challenges in glycoproteomics: recent advances in MS-based glycopeptide analysis. Bioanalysis 2015; 7:113-31. [PMID: 25558940 DOI: 10.4155/bio.14.272] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
The proteomic analysis of glycosylation is uniquely challenging. The numerous and varied biological roles of protein-linked glycans have fueled a tremendous demand for technologies that enable rapid, in-depth structural examination of glycosylated proteins in complex biological systems. In turn, this demand has driven many innovations in wide ranging fields of bioanalytical science. This review will summarize key developments in glycoprotein separation and enrichment, glycoprotein proteolysis strategies, glycopeptide separation and enrichment, the role of mass measurement accuracy in glycopeptide detection, glycopeptide ion dissociation methods for MS/MS, and informatic tools for glycoproteomic analysis. In aggregate, this selection of topics serves to encapsulate the present status of MS-based analytical technologies for engaging the challenges of glycoproteomic analysis.
Collapse
|
24
|
Liu G, Neelamegham S. Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2015; 7:163-81. [PMID: 25871730 DOI: 10.1002/wsbm.1296] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2014] [Revised: 02/08/2015] [Accepted: 03/04/2015] [Indexed: 12/22/2022]
Abstract
The glycome constitutes the entire complement of free carbohydrates and glycoconjugates expressed on whole cells or tissues. 'Systems Glycobiology' is an emerging discipline that aims to quantitatively describe and analyse the glycome. Here, instead of developing a detailed understanding of single biochemical processes, a combination of computational and experimental tools are used to seek an integrated or 'systems-level' view. This can explain how multiple biochemical reactions and transport processes interact with each other to control glycome biosynthesis and function. Computational methods in this field commonly build in silico reaction network models to describe experimental data derived from structural studies that measure cell-surface glycan distribution. While considerable progress has been made, several challenges remain due to the complex and heterogeneous nature of this post-translational modification. First, for the in silico models to be standardized and shared among laboratories, it is necessary to integrate glycan structure information and glycosylation-related enzyme definitions into the mathematical models. Second, as glycoinformatics resources grow, it would be attractive to utilize 'Big Data' stored in these repositories for model construction and validation. Third, while the technology for profiling the glycome at the whole-cell level has been standardized, there is a need to integrate mass spectrometry derived site-specific glycosylation data into the models. The current review discusses progress that is being made to resolve the above bottlenecks. The focus is on how computational models can bridge the gap between 'data' generated in wet-laboratory studies with 'knowledge' that can enhance our understanding of the glycome.
Collapse
Affiliation(s)
- Gang Liu
- Department of Chemical and Biological Engineering, State University of New York, Buffalo, NY, USA
| | - Sriram Neelamegham
- Department of Chemical and Biological Engineering, State University of New York, Buffalo, NY, USA
| |
Collapse
|
25
|
Ahn YH, Kim JY, Yoo JS. Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods. MASS SPECTROMETRY REVIEWS 2015; 34:148-65. [PMID: 24889823 PMCID: PMC4340049 DOI: 10.1002/mas.21428] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2013] [Accepted: 11/20/2013] [Indexed: 05/12/2023]
Abstract
Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies.
Collapse
Affiliation(s)
- Yeong Hee Ahn
- Division of Mass Spectrometry, Korea Basic Science InstituteCheongwon-Gun, 363-883, Republic of Korea
| | - Jin Young Kim
- Division of Mass Spectrometry, Korea Basic Science InstituteCheongwon-Gun, 363-883, Republic of Korea
| | - Jong Shin Yoo
- Division of Mass Spectrometry, Korea Basic Science InstituteCheongwon-Gun, 363-883, Republic of Korea
| |
Collapse
|
26
|
Lynn KS, Chen CC, Lih TM, Cheng CW, Su WC, Chang CH, Cheng CY, Hsu WL, Chen YJ, Sung TY. MAGIC: An Automated N-Linked Glycoprotein Identification Tool Using a Y1-Ion Pattern Matching Algorithm and in Silico MS2 Approach. Anal Chem 2015; 87:2466-73. [DOI: 10.1021/ac5044829] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Ke-Shiuan Lynn
- Institute
of Information Science, Academia Sinica, Taipei 11529, Taiwan
| | - Chen-Chun Chen
- Genomics
Research Center, Academia Sinica, Taipei 11529, Taiwan
- Department
of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - T. Mamie Lih
- Bioinformatics
Program, Taiwan International Graduate Program, Institute of Information
Science, Academia Sinica, Taipei 11529, Taiwan
- Institute
of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan
| | - Cheng-Wei Cheng
- Institute
of Information Science, Academia Sinica, Taipei 11529, Taiwan
| | - Wan-Chih Su
- Institute
of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Chun-Hao Chang
- Institute
of Information Science, Academia Sinica, Taipei 11529, Taiwan
| | - Chia-Ying Cheng
- Institute
of Information Science, Academia Sinica, Taipei 11529, Taiwan
| | - Wen-Lian Hsu
- Institute
of Information Science, Academia Sinica, Taipei 11529, Taiwan
| | - Yu-Ju Chen
- Institute
of Chemistry, Academia Sinica, Taipei 11529, Taiwan
- Department
of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Ting-Yi Sung
- Institute
of Information Science, Academia Sinica, Taipei 11529, Taiwan
| |
Collapse
|
27
|
High-Throughput Analysis and Automation for Glycomics Studies. Chromatographia 2014; 78:321-333. [PMID: 25814696 PMCID: PMC4363487 DOI: 10.1007/s10337-014-2803-9] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 10/17/2014] [Accepted: 10/17/2014] [Indexed: 11/12/2022]
Abstract
This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics—for example in Genome Wide Association Studies—to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.
Collapse
|
28
|
Cheng K, Chen R, Seebun D, Ye M, Figeys D, Zou H. Large-scale characterization of intact N-glycopeptides using an automated glycoproteomic method. J Proteomics 2014; 110:145-54. [DOI: 10.1016/j.jprot.2014.08.006] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2014] [Revised: 07/29/2014] [Accepted: 08/12/2014] [Indexed: 02/06/2023]
|
29
|
Tóth E, Ozohanics O, Bobály B, Gömöry Á, Jekő A, Drahos L, Vékey K. HPLC enrichment/isolation of proteins for post-translational modification studies from complex mixtures. J Pharm Biomed Anal 2014; 98:393-400. [PMID: 25005889 DOI: 10.1016/j.jpba.2014.06.025] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Revised: 06/11/2014] [Accepted: 06/15/2014] [Indexed: 10/25/2022]
Abstract
The paper describes a macroporous RP-HPLC method for separation and isolation/enrichment of proteins from complex mixtures. The method is robust and efficient; using 2.1 or 4.6mm diameter columns provides sufficient material for subsequent proteomic analysis. The main advantage of the method is that most protein variants are isolated in the same fraction, as separation is not based on differences in isoelectric point. This is highly advantageous for studying complex mixtures and post-translational modifications. Examples related to glycosylation analysis are discussed in detail.
Collapse
Affiliation(s)
- Eszter Tóth
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., Budapest 1117, Hungary
| | - Olivér Ozohanics
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., Budapest 1117, Hungary
| | - Balázs Bobály
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., Budapest 1117, Hungary; Budapest University of Technology and Economics, Department of Inorganic and Analytical Chemistry, Szt. Gellért tér 4., Budapest 1111, Hungary
| | - Ágnes Gömöry
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., Budapest 1117, Hungary
| | - Anita Jekő
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., Budapest 1117, Hungary
| | - László Drahos
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., Budapest 1117, Hungary
| | - Károly Vékey
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., Budapest 1117, Hungary.
| |
Collapse
|
30
|
Wu SW, Pu TH, Viner R, Khoo KH. Novel LC-MS2 Product Dependent Parallel Data Acquisition Function and Data Analysis Workflow for Sequencing and Identification of Intact Glycopeptides. Anal Chem 2014; 86:5478-86. [DOI: 10.1021/ac500945m] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Sz-Wei Wu
- Institute
of Biological Chemistry, Academia Sinica, 128, Academia Road Sec 2, Nankang, Taipei, 11529, Taiwan
- Thermo Fischer Scientific Taiwan Co., Ltd.,
Neihu, Taipei, 11493, Taiwan
| | - Tsung-Hsien Pu
- Core
Facilities for Protein Structure Analysis at Institute of Biological
Chemistry, Academia Sinica, Taipei, 11529, Taiwan
| | - Rosa Viner
- Thermo Fischer Scientific, San Jose, California 95134, United States
| | - Kay-Hooi Khoo
- Institute
of Biological Chemistry, Academia Sinica, 128, Academia Road Sec 2, Nankang, Taipei, 11529, Taiwan
| |
Collapse
|
31
|
Thaysen-Andersen M, Packer NH. Advances in LC-MS/MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N- and O-glycoproteome. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2014; 1844:1437-52. [PMID: 24830338 DOI: 10.1016/j.bbapap.2014.05.002] [Citation(s) in RCA: 158] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2014] [Revised: 04/23/2014] [Accepted: 05/05/2014] [Indexed: 12/22/2022]
Abstract
Site-specific structural characterization of glycoproteins is important for understanding the exact functional relevance of protein glycosylation. Resulting partly from the multiple layers of structural complexity of the attached glycans, the system-wide site-specific characterization of protein glycosylation, defined as glycoproteomics, is still far from trivial leaving the N- and O-linked glycoproteomes significantly under-defined. However, recent years have seen significant advances in glycoproteomics driven, in part, by the developments of dedicated workflows and efficient sample preparation, including glycopeptide enrichment and prefractionation. In addition, glycoproteomics has benefitted from the continuous performance enhancement and more intelligent use of liquid chromatography and tandem mass spectrometry (LC-MS/MS) instrumentation and a wider selection of specialized software tackling the unique challenges of glycoproteomics data. Together these advances promise more streamlined N- and O-linked glycoproteome analysis. Tangible examples include system-wide glycoproteomics studies detecting thousands of intact glycopeptides from hundreds of glycoproteins from diverse biological samples. With a strict focus on the system-wide site-specific analysis of protein N- and O-linked glycosylation, we review the recent advances in LC-MS/MS based glycoproteomics. The review opens with a more general discussion of experimental designs in glycoproteomics and sample preparation prior to LC-MS/MS based data acquisition. Although many challenges still remain, it becomes clear that glycoproteomics, one of the last frontiers in proteomics, is gradually maturing enabling a wider spectrum of researchers to access this new emerging research discipline. The next milestone in analytical glycobiology is being reached allowing the glycoscientist to address the functional importance of protein glycosylation in a system-wide yet protein-specific manner.
Collapse
Affiliation(s)
- Morten Thaysen-Andersen
- Biomolecular Frontiers Research Centre, Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia.
| | - Nicolle H Packer
- Biomolecular Frontiers Research Centre, Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia
| |
Collapse
|
32
|
Liu M, Zhang Y, Chen Y, Yan G, Shen C, Cao J, Zhou X, Liu X, Zhang L, Shen H, Lu H, He F, Yang P. Efficient and Accurate Glycopeptide Identification Pipeline for High-Throughput Site-Specific N-Glycosylation Analysis. J Proteome Res 2014; 13:3121-9. [DOI: 10.1021/pr500238v] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Mingqi Liu
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Yang Zhang
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Yaohan Chen
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Guoquan Yan
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Chengping Shen
- Cloudscientific Technology Co., Ltd., 585 Long Hua West Road, Xuhui District, Shanghai 200232, P. R. China
| | - Jing Cao
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Xinwen Zhou
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Xiaohui Liu
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Lei Zhang
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Huali Shen
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Haojie Lu
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| | - Fuchu He
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
- State Key Laboratory of Proteomics, 33 Life Science Park, Beijing 102206, P. R. China
| | - Pengyuan Yang
- Department
of Chemistry, Fudan University, 220 Han Dan Road, Shanghai 200433, P. R. China
- Institutes
of Biomedical Sciences, Fudan University, 138 YiXueYuan Road, Shanghai 200032, P. R. China
| |
Collapse
|
33
|
Liang SY, Wu SW, Pu TH, Chang FY, Khoo KH. An adaptive workflow coupled with Random Forest algorithm to identify intact N-glycopeptides detected from mass spectrometry. Bioinformatics 2014; 30:1908-16. [DOI: 10.1093/bioinformatics/btu139] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
|
34
|
Woodin CL, Maxon M, Desaire H. Software for automated interpretation of mass spectrometry data from glycans and glycopeptides. Analyst 2013; 138:2793-803. [PMID: 23293784 DOI: 10.1039/c2an36042j] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The purpose of this review is to provide those interested in glycosylation analysis with the most updated information on the availability of automated tools for MS characterization of N-linked and O-linked glycosylation types. Specifically, this review describes software tools that facilitate elucidation of glycosylation from MS data on the basis of mass alone, as well as software designed to speed the interpretation of glycan and glycopeptide fragmentation from MS/MS data. This review focuses equally on software designed to interpret the composition of released glycans and on tools to characterize N-linked and O-linked glycopeptides. Several websites have been compiled and described that will be helpful to the reader who is interested in further exploring the described tools.
Collapse
Affiliation(s)
- Carrie L Woodin
- Department of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS 66047, USA
| | | | | |
Collapse
|
35
|
Trinidad JC, Schoepfer R, Burlingame AL, Medzihradszky KF. N- and O-glycosylation in the murine synaptosome. Mol Cell Proteomics 2013; 12:3474-88. [PMID: 23816992 DOI: 10.1074/mcp.m113.030007] [Citation(s) in RCA: 136] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
We present the first large scale study characterizing both N- and O-linked glycosylation in a site-specific manner on hundreds of proteins. We demonstrate that a lectin-affinity fractionation step using wheat germ agglutinin enriches not only peptides carrying intracellular O-GlcNAc, but also those bearing ER/Golgi-derived N- and O-linked carbohydrate structures. Liquid chromatography-MS (LC/MS) analysis with high accuracy precursor mass measurements and high sensitivity ion trap electron-transfer dissociation (ETD) were utilized for structural characterization of glycopeptides. Our results reveal both the identity of the precise sites of glycosylation and information on the oligosaccharide structures possible on these proteins. We report a novel iterative approach that allowed us to interpret the ETD data set directly without making prior assumptions about the nature and distribution of oligosaccharides present in our glycopeptide mixture. Over 2500 unique N- and O-linked glycopeptides were identified on 453 proteins. The extent of microheterogeneity varied extensively, and up to 19 different oligosaccharides were attached at a given site. We describe the presence of the well-known mucin-type structures for O-glycosylation, an EGF-domain-specific fucosylation and a rare O-mannosylation on the transmembrane phosphatase Ptprz1. Finally, we identified three examples of O-glycosylation on tyrosine residues.
Collapse
Affiliation(s)
- Jonathan C Trinidad
- Department of Pharmaceutical Chemistry, Mass Spectrometry Facility, School of Pharmacy, University of California San Francisco, San Francisco, California 94158-2517
| | | | | | | |
Collapse
|
36
|
Strum JS, Nwosu CC, Hua S, Kronewitter SR, Seipert RR, Bachelor RJ, An HJ, Lebrilla CB. Automated assignments of N- and O-site specific glycosylation with extensive glycan heterogeneity of glycoprotein mixtures. Anal Chem 2013; 85:5666-75. [PMID: 23662732 DOI: 10.1021/ac4006556] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles.
Collapse
Affiliation(s)
- John S Strum
- Department of Chemistry, University of California, Davis, California 95616, USA
| | | | | | | | | | | | | | | |
Collapse
|
37
|
Albenne C, Canut H, Jamet E. Plant cell wall proteomics: the leadership of Arabidopsis thaliana. FRONTIERS IN PLANT SCIENCE 2013; 4:111. [PMID: 23641247 PMCID: PMC3640192 DOI: 10.3389/fpls.2013.00111] [Citation(s) in RCA: 102] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2012] [Accepted: 04/10/2013] [Indexed: 05/18/2023]
Abstract
Plant cell wall proteins (CWPs) progressively emerged as crucial components of cell walls although present in minor amounts. Cell wall polysaccharides such as pectins, hemicelluloses, and cellulose represent more than 90% of primary cell wall mass, whereas hemicelluloses, cellulose, and lignins are the main components of lignified secondary walls. All these polymers provide mechanical properties to cell walls, participate in cell shape and prevent water loss in aerial organs. However, cell walls need to be modified and customized during plant development and in response to environmental cues, thus contributing to plant adaptation. CWPs play essential roles in all these physiological processes and particularly in the dynamics of cell walls, which requires organization and rearrangements of polysaccharides as well as cell-to-cell communication. In the last 10 years, plant cell wall proteomics has greatly contributed to a wider knowledge of CWPs. This update will deal with (i) a survey of plant cell wall proteomics studies with a focus on Arabidopsis thaliana; (ii) the main protein families identified and the still missing peptides; (iii) the persistent issue of the non-canonical CWPs; (iv) the present challenges to overcome technological bottlenecks; and (v) the perspectives beyond cell wall proteomics to understand CWP functions.
Collapse
Affiliation(s)
- Cécile Albenne
- Laboratoire de Recherche en Sciences Végétales, Université de Toulouse, UPS, UMR 5546Castanet-Tolosan, France
- CNRS, UMR 5546Castanet-Tolosan, France
| | - Hervé Canut
- Laboratoire de Recherche en Sciences Végétales, Université de Toulouse, UPS, UMR 5546Castanet-Tolosan, France
- CNRS, UMR 5546Castanet-Tolosan, France
| | - Elisabeth Jamet
- Laboratoire de Recherche en Sciences Végétales, Université de Toulouse, UPS, UMR 5546Castanet-Tolosan, France
- CNRS, UMR 5546Castanet-Tolosan, France
| |
Collapse
|
38
|
Zhu Z, Hua D, Clark DF, Go EP, Desaire H. GlycoPep Detector: a tool for assigning mass spectrometry data of N-linked glycopeptides on the basis of their electron transfer dissociation spectra. Anal Chem 2013; 85:5023-32. [PMID: 23510108 DOI: 10.1021/ac400287n] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Electron transfer dissociation (ETD) is commonly used in fragmenting N-linked glycopeptides in their mass spectral analyses to complement collision-induced dissociation (CID) experiments. The glycan remains intact through ETD, while the peptide backbone is cleaved, providing the sequence of amino acids for a glycopeptide. Nonetheless, data analysis is a major bottleneck to high-throughput glycopeptide identification based on ETD data, due to the complexity and diversity of ETD mass spectra compared to CID counterparts. GlycoPep Detector (GPD) is a web-based tool to address this challenge. It filters out noise peaks that interfere with glycopeptide sequencing, correlates input glycopeptide compositions with the ETD spectra, and assigns a score for each candidate. By considering multiple ion series (c-, z-, and y-ions) and scoring them separately, the software gives more weighting to the ion series that matches peaks of high intensity in the spectra. This feature enables the correct glycopeptide to receive a high score while keeping scores of incorrect compositions low. GPD has been utilized to interpret data collected on six model glycoproteins (RNase B, avidin, fetuin, asialofetuin, transferrin, and AGP) as well as a clade C HIV envelope glycoprotein, C.97ZA012 gp140ΔCFI. In every assignment made by GPD, the correct glycopeptide composition earns a score that is about 2-fold higher than other incorrect glycopeptide candidates (decoys). The software can be accessed at http://glycopro.chem.ku.edu/ZZKHome.php .
Collapse
Affiliation(s)
- Zhikai Zhu
- Department of Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
| | | | | | | | | |
Collapse
|
39
|
Alley WR, Mann BF, Novotny MV. High-sensitivity analytical approaches for the structural characterization of glycoproteins. Chem Rev 2013; 113:2668-732. [PMID: 23531120 PMCID: PMC3992972 DOI: 10.1021/cr3003714] [Citation(s) in RCA: 239] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- William R. Alley
- Department of Chemistry, Indiana University, Bloomington, Indiana, United States
- National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, Indiana, United States
| | - Benjamin F. Mann
- Department of Chemistry, Indiana University, Bloomington, Indiana, United States
- National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, Indiana, United States
| | - Milos V. Novotny
- Department of Chemistry, Indiana University, Bloomington, Indiana, United States
- National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, Indiana, United States
- Indiana University School of Medicine, Indiana University, Indianapolis, Indiana, United States
| |
Collapse
|
40
|
Wu SW, Liang SY, Pu TH, Chang FY, Khoo KH. Sweet-Heart - an integrated suite of enabling computational tools for automated MS2/MS3 sequencing and identification of glycopeptides. J Proteomics 2013; 84:1-16. [PMID: 23568021 DOI: 10.1016/j.jprot.2013.03.026] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2012] [Revised: 02/12/2013] [Accepted: 03/10/2013] [Indexed: 11/26/2022]
Abstract
UNLABELLED High efficiency identification of intact glycopeptides from a shotgun glycoproteomic LC-MS(2) dataset remains problematic. The prevalent mode of identifying the de-N-glycosylated peptides is littered with false positives and addresses only the issue of site occupancy. Here, we present Sweet-Heart, a computational tool set developed to tackle the heart of the problems in MS(2) sequencing of glycopeptide. It accepts low resolution and low accuracy ion trap MS(2) data, filters for glycopeptides, couples knowledge-based de novo interpretation of glycosylation-dependent fragmentation pattern with protein database search, and uses machine-learning algorithm to score the computed glyco and peptide combinations. Higher ranking candidates are then compiled into a list of MS(2)/MS(3) entries to drive subsequent rounds of targeted MS(3) sequencing of putative peptide backbone, allowing its validation by database search in a fully automated fashion. With additional fishing out of all related glycoforms and final data integration, the platform proves to be sufficiently sensitive and selective, conducive to novel glycosylation discovery, and robust enough to discriminate, among others, N-glycolyl neuraminic acid/fucose from N-acetyl neuraminic acid/hexose. A critical appraisal of its computing performance shows that Sweet-Heart allows high sensitivity comprehensive mapping of site-specific glycosylation for isolated glycoproteins and facilitates analysis of glycoproteomic data. BIOLOGICAL SIGNIFICANCE The biological relevance of protein site-specific glycosylation cannot be meaningfully addressed without first defining its pattern by direct analysis of glycopeptides. Sweet-Heart is a novel suite of computational tools allowing for automated analysis of mass spectrometry-based glycopeptide sequencing data. It is developed to accept ion trap MS2/MS3 data and uses a machine learning algorithm to score and rank the candidate peptide core and glycosyl substituent combinations. By eliminating the need for manual, labor-intensive, and subjective data interpretation, it facilitates high throughput shotgun glycoproteomic data analysis and is conducive to identification of unanticipated glycosylation, as demonstrated here with a recombinant EGFR.
Collapse
Affiliation(s)
- Sz-Wei Wu
- Institute of Biochemical Sciences, National Taiwan University, Taiwan
| | | | | | | | | |
Collapse
|
41
|
Abstract
Glycopeptide-based analysis is used to inform researchers about the glycans on one or more proteins. The method's key attractive feature is its ability to link glycosylation information to exact locations (glycosylation sites) on proteins. Numerous applications for glycopeptide analysis are known, and several examples are described herein. The techniques used to characterize glycopeptides are still emerging, and recently, research focused on facilitating aspects of glycopeptide analysis has advanced significantly in the areas of sample preparation, MS fragmentation, and automation of data analysis. These recent developments, described herein, provide the foundation for the growth of glycopeptide analysis as a blossoming field.
Collapse
Affiliation(s)
- Heather Desaire
- Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, USA.
| |
Collapse
|
42
|
Li F, Glinskii OV, Glinsky VV. Glycobioinformatics: Current strategies and tools for data mining in MS-based glycoproteomics. Proteomics 2012; 13:341-54. [DOI: 10.1002/pmic.201200149] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2012] [Revised: 10/06/2012] [Accepted: 11/06/2012] [Indexed: 12/18/2022]
|
43
|
Lazar IM, Lee W, Lazar AC. Glycoproteomics on the rise: established methods, advanced techniques, sophisticated biological applications. Electrophoresis 2012; 34:113-25. [PMID: 23161435 DOI: 10.1002/elps.201200445] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2012] [Revised: 10/07/2012] [Accepted: 10/07/2012] [Indexed: 02/05/2023]
Abstract
Glycosylation is the most complex form of protein PTMs. Affected proteins may carry dozens of glycosylation sites with tens to hundreds of glycan residues attached to every site. Glycosylated proteins have many important functions in biology, from cellular to organismal levels, being involved in cell-cell signaling, cell adhesion, immune response, host-pathogen interactions, and development and growth. Glycosylation, however, expands the biological functional diversity of proteins at the expense of a tremendous increase in structural heterogeneity. Aberrant glycosylation of cell surface proteins, as well as their detectable fingerprint in plasma samples, has been associated with cancer, inflammatory and degenerative diseases, and congenital disorders of glycosylation. Therefore, there are on-going efforts directed toward developing new technologies and approaches for glycan sequencing and high-throughput analysis of glycosylated proteins in complex samples with simultaneous characterization of both the protein and glycan moieties. This work is aimed primarily at pinpointing the challenges associated with the large-scale analysis of glycoproteins and the latest developments in glycoproteomic research, with focus on recent advancements (2011-2012) in microcolumn separations and MS detection.
Collapse
Affiliation(s)
- Iulia M Lazar
- Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.
| | | | | |
Collapse
|
44
|
Dodds ED. Gas-phase dissociation of glycosylated peptide ions. MASS SPECTROMETRY REVIEWS 2012; 31:666-82. [PMID: 22407588 DOI: 10.1002/mas.21344] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2011] [Revised: 12/22/2011] [Accepted: 12/27/2011] [Indexed: 05/15/2023]
Abstract
Among the myriad of protein post-translational modifications (PTMs), glycosylation presents a singular analytical challenge. On account of the extraordinary diversity of protein-linked carbohydrates and the great complexity with which they decorate glycoproteins, the rigorous establishment of glycan-protein connectivity is often an arduous experimental venture. Consequently, elaborating the interplay between structures of oligosaccharides and functions of proteins they modify is usually not a straightforward task. A more mature biochemical appreciation of carbohydrates as PTMs will significantly hinge upon analytical advances in the field of glycoproteomics. Undoubtedly, the analysis of glycosylated peptides by tandem mass spectrometry (MS/MS) will play a pivotal role in this regard. The goal of this review is to summarize, from an analytical and tutorial perspective, the present state of knowledge regarding the dissociation of glycopeptide ions as accomplished by various MS/MS methods. In addition, this review will endeavor to harmonize some seemingly disparate findings to provide a more complete and broadly applicable description of glycopeptide ion fragmentation. A fuller understanding of the rich variety of glycopeptide dissociation behaviors will allow glycoproteomic researchers to maximize the information yielded by MS/MS experiments, while also paving the way to new innovations in MS-based glycoproteomics.
Collapse
Affiliation(s)
- Eric D Dodds
- Department of Chemistry, University of Nebraska-Lincoln, 711 Hamilton Hall, Lincoln, Nebraska 68588-0304, USA.
| |
Collapse
|
45
|
Ozohanics O, Turiák L, Puerta A, Vékey K, Drahos L. High-performance liquid chromatography coupled to mass spectrometry methodology for analyzing site-specific N-glycosylation patterns. J Chromatogr A 2012; 1259:200-12. [DOI: 10.1016/j.chroma.2012.05.031] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2012] [Revised: 05/07/2012] [Accepted: 05/09/2012] [Indexed: 10/28/2022]
|
46
|
Dallas DC, Martin WF, Hua S, German JB. Automated glycopeptide analysis--review of current state and future directions. Brief Bioinform 2012; 14:361-74. [PMID: 22843980 DOI: 10.1093/bib/bbs045] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Glycosylation of proteins is involved in immune defense, cell-cell adhesion, cellular recognition and pathogen binding and is one of the most common and complex post-translational modifications. Science is still struggling to assign detailed mechanisms and functions to this form of conjugation. Even the structural analysis of glycoproteins-glycoproteomics-remains in its infancy due to the scarcity of high-throughput analytical platforms capable of determining glycopeptide composition and structure, especially platforms for complex biological mixtures. Glycopeptide composition and structure can be determined with high mass-accuracy mass spectrometry, particularly when combined with chromatographic separation, but the sheer volume of generated data necessitates computational software for interpretation. This review discusses the current state of glycopeptide assignment software-advances made to date and issues that remain to be addressed. The various software and algorithms developed so far provide important insights into glycoproteomics. However, there is currently no freely available software that can analyze spectral data in batch and unambiguously determine glycopeptide compositions for N- and O-linked glycopeptides from relevant biological sources such as human milk and serum. Few programs are capable of aiding in structural determination of the glycan component. To significantly advance the field of glycoproteomics, analytical software and algorithms are required that: (i) solve for both N- and O-linked glycopeptide compositions, structures and glycosites in biological mixtures; (ii) are high-throughput and process data in batches; (iii) can interpret mass spectral data from a variety of sources and (iv) are open source and freely available.
Collapse
|
47
|
Hahne H, Kuster B. Discovery of O-GlcNAc-6-phosphate modified proteins in large-scale phosphoproteomics data. Mol Cell Proteomics 2012; 11:1063-9. [PMID: 22826440 DOI: 10.1074/mcp.m112.019760] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Phosphorylated O-GlcNAc is a novel post-translational modification that has so far only been found on the neuronal protein AP180 from the rat (Graham et al., J. Proteome Res. 2011, 10, 2725-2733). Upon collision induced dissociation, the modification generates a highly mass deficient fragment ion (m/z 284.0530) that can be used as a reporter for the identification of phosphorylated O-GlcNAc. Using a publically available mouse brain phosphoproteome data set, we employed our recently developed Oscore software to re-evaluate high resolution/high accuracy tandem mass spectra and discovered the modification on 23 peptides corresponding to 11 mouse proteins. The systematic analysis of 220 candidate phosphoGlcNAc tandem mass spectra as well as a synthetic standard enabled the dissection of the major phosphoGlcNAc fragmentation pathways, suggesting that the modification is O-GlcNAc-6-phosphate. We find that the classical O-GlcNAc modification often exists on the same peptides indicating that O-GlcNAc-6-phosphate may biosynthetically arise in two steps involving the O-GlcNAc transferase and a currently unknown kinase. Many of the identified proteins are involved in synaptic transmission and for Ca(2+)/calmodulin kinase IV, the O-GlcNAc-6-phosphate modification was found in the vicinity of two autophosphorylation sites required for full activation of the kinase suggesting a potential regulatory role for O-GlcNAc-6-phosphate. By re-analyzing mass spectrometric data from human embryonic and induced pluripotent stem cells, our study also identified Zinc finger protein 462 (ZNF462) as the first human O-GlcNAc-6-phosphate modified protein. Collectively, the data suggests that O-GlcNAc-6-phosphate is a general post-translation modification of mammalian proteins with a variety of possible cellular functions.
Collapse
Affiliation(s)
- Hannes Hahne
- Center of Life and Food Sciences Weihenstephan, Technische Universität München, Emil-Erlenmeyer-Forum 5, 85354 Freising, Germany
| | | |
Collapse
|
48
|
Lütteke T. The use of glycoinformatics in glycochemistry. Beilstein J Org Chem 2012; 8:915-29. [PMID: 23015842 PMCID: PMC3388882 DOI: 10.3762/bjoc.8.104] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2012] [Accepted: 05/29/2012] [Indexed: 01/10/2023] Open
Abstract
Glycoinformatics is a small but growing branch of bioinformatics and chemoinformatics. Various resources are now available that can be of use to glycobiologists, but also to chemists who work on the synthesis or analysis of carbohydrates. This article gives an overview of existing glyco-specific databases and tools, with a focus on their application to glycochemistry: Databases can provide information on candidate glycan structures for synthesis, or on glyco-enzymes that can be used to synthesize carbohydrates. Statistical analyses of glycan databases help to plan glycan synthesis experiments. 3D-Structural data of protein-carbohydrate complexes are used in targeted drug design, and tools to support glycan structure analysis aid with quality control. Specific problems of glycoinformatics compared to bioinformatics for genomics or proteomics, especially concerning integration and long-term maintenance of the existing glycan databases, are also discussed.
Collapse
Affiliation(s)
- Thomas Lütteke
- Justus-Liebig-University Gießen, Institute of Veterinary Physiology and Biochemistry, Frankfurter Str. 100, 35392 Gießen, Germany
| |
Collapse
|
49
|
Woodin CL, Hua D, Maxon M, Rebecchi KR, Go EP, Desaire H. GlycoPep grader: a web-based utility for assigning the composition of N-linked glycopeptides. Anal Chem 2012; 84:4821-9. [PMID: 22540370 DOI: 10.1021/ac300393t] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
GlycoPep grader (GPG) is a freely available software tool designed to accelerate the process of accurately determining glycopeptide composition from tandem mass spectrometric data. GPG relies on the identification of unique dissociation patterns shown for high mannose, hybrid, and complex N-linked glycoprotein types, including patterns specific to those structures containing fucose or sialic acid residues. The novel GPG scoring algorithm scores potential candidate compositions of the same nominal mass against MS/MS data through evaluation of the Y(1) ion and other peptide-containing product ions, across multiple charge states, when applicable. In addition to evaluating the peptide portion of a given glycopeptide, the GPG algorithm predicts and scores product ions that result from unique neutral losses of terminal glycans. GPG has been applied to a variety of glycoproteins, including RNase B, asialofetuin, and transferrin, and the HIV envelope glycoprotein, CON-S gp140ΔCFI. The GPG software is implemented predominantly in PostgreSQL, with PHP as the presentation tier, and is publicly accessible online. Thus far, the algorithm has identified the correct compositional assignment from multiple candidate N-glycopeptides in all tests performed.
Collapse
Affiliation(s)
- Carrie L Woodin
- Department of Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
| | | | | | | | | | | |
Collapse
|
50
|
Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: an update for 2007-2008. MASS SPECTROMETRY REVIEWS 2012; 31:183-311. [PMID: 21850673 DOI: 10.1002/mas.20333] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2010] [Revised: 01/04/2011] [Accepted: 01/04/2011] [Indexed: 05/31/2023]
Abstract
This review is the fifth update of the original review, published in 1999, on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2008. The first section of the review covers fundamental studies, fragmentation of carbohydrate ions, use of derivatives and new software developments for analysis of carbohydrate spectra. Among newer areas of method development are glycan arrays, MALDI imaging and the use of ion mobility spectrometry. The second section of the review discusses applications of MALDI MS to the analysis of different types of carbohydrate. Specific compound classes that are covered include carbohydrate polymers from plants, N- and O-linked glycans from glycoproteins, biopharmaceuticals, glycated proteins, glycolipids, glycosides and various other natural products. There is a short section on the use of MALDI mass spectrometry for the study of enzymes involved in glycan processing and a section on the use of MALDI MS to monitor products of the chemical synthesis of carbohydrates with emphasis on carbohydrate-protein complexes and glycodendrimers. Corresponding analyses by electrospray ionization now appear to outnumber those performed by MALDI and the amount of literature makes a comprehensive review on this technique impractical. However, most of the work relating to sample preparation and glycan synthesis is equally relevant to electrospray and, consequently, those proposing analyses by electrospray should also find material in this review of interest.
Collapse
Affiliation(s)
- David J Harvey
- Oxford Glycobiology Institute, Department of Biochemistry, University of Oxford, Oxford OX1 3QU, UK.
| |
Collapse
|