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Nagai-Okatani C, Tominaga D, Tomioka A, Sakaue H, Goda N, Ko S, Kuno A, Kaji H. GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With MS2 Information. Mol Cell Proteomics 2024; 23:100833. [PMID: 39181535 PMCID: PMC11421343 DOI: 10.1016/j.mcpro.2024.100833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 08/16/2024] [Accepted: 08/19/2024] [Indexed: 08/27/2024] Open
Abstract
High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).
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Affiliation(s)
- Chiaki Nagai-Okatani
- Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.
| | - Daisuke Tominaga
- Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Azusa Tomioka
- Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Hiroaki Sakaue
- Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Norio Goda
- Department of Systems Medicine, Keio University School of Medicine, Shinjuku, Tokyo, Japan
| | - Shigeru Ko
- Department of Systems Medicine, Keio University School of Medicine, Shinjuku, Tokyo, Japan
| | - Atsushi Kuno
- Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Hiroyuki Kaji
- Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan; Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Aichi, Japan.
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2
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Reinig S, Kuo C, Wu CC, Huang SY, Yu JS, Shih SR. Specific long-term changes in anti-SARS-CoV-2 IgG modifications and antibody functions in mRNA, adenovector, and protein subunit vaccines. J Med Virol 2024; 96:e29793. [PMID: 39023111 DOI: 10.1002/jmv.29793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 06/17/2024] [Accepted: 07/02/2024] [Indexed: 07/20/2024]
Abstract
Various vaccine platforms were developed and deployed against the COVID-19 disease. The Fc-mediated functions of IgG antibodies are essential in the adaptive immune response elicited by vaccines. However, the long-term changes of protein subunit vaccines and their combinations with messenger RNA (mRNA) vaccines are unknown. A total of 272 serum and plasma samples were collected from individuals who received first to third doses of the protein subunit Medigen, the mRNA (BNT, Moderna), or the adenovector AstraZeneca vaccines. The IgG subclass level was measured using enzyme-linked immunosorbent assay, and Fc-N glycosylation was measured using liquid chromatography coupled to tandem mass spectrometry. Antibody-dependent-cellular-phagocytosis (ADCP) and complement deposition (ADCD) of anti-spike (S) IgG antibodies were measured by flow cytometry. IgG1 and 3 reached the highest anti-S IgG subclass level. IgG1, 2, and 4 subclass levels significantly increased in mRNA- and Medigen-vaccinated individuals. Fc-glycosylation was stable, except in female BNT vaccinees, who showed increased bisection and decreased galactosylation. Female BNT vaccinees had a higher anti-S IgG titer than that of males. ADCP declined in all groups. ADCD was significantly lower in AstraZeneca-vaccinated individuals. Each vaccine produced specific long-term changes in Fc structure and function. This finding is critical when selecting a vaccine platform or combination to achieve the desired immune response.
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Affiliation(s)
- Sebastian Reinig
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan, Taiwan
| | - Chin Kuo
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan, Taiwan
| | - Chia-Chun Wu
- Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Sheng-Yu Huang
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan, Taiwan
| | - Jau-Song Yu
- Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Liver Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
- Research Center for Food and Cosmetic Safety, College of Human Ecology, Chang Gung University of Science and Technology, Taoyuan, Taiwan
| | - Shin-Ru Shih
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan, Taiwan
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Research Center for Chinese Herbal Medicine, Research Center for Food and Cosmetic Safety, Graduate Institute of Health Industry Technology, College of Human Ecology, Chang Gung University of Science and Technology, Taoyuan, Taiwan
- Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan
- Clinical Virology Laboratory, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
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3
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Kuhnen G, Class LC, Badekow S, Hanisch KL, Rohn S, Kuballa J. Python workflow for the selection and identification of marker peptides-proof-of-principle study with heated milk. Anal Bioanal Chem 2024; 416:3349-3360. [PMID: 38607384 PMCID: PMC11106092 DOI: 10.1007/s00216-024-05286-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 03/26/2024] [Accepted: 04/02/2024] [Indexed: 04/13/2024]
Abstract
The analysis of almost holistic food profiles has developed considerably over the last years. This has also led to larger amounts of data and the ability to obtain more information about health-beneficial and adverse constituents in food than ever before. Especially in the field of proteomics, software is used for evaluation, and these do not provide specific approaches for unique monitoring questions. An additional and more comprehensive way of evaluation can be done with the programming language Python. It offers broad possibilities by a large ecosystem for mass spectrometric data analysis, but needs to be tailored for specific sets of features, the research questions behind. It also offers the applicability of various machine-learning approaches. The aim of the present study was to develop an algorithm for selecting and identifying potential marker peptides from mass spectrometric data. The workflow is divided into three steps: (I) feature engineering, (II) chemometric data analysis, and (III) feature identification. The first step is the transformation of the mass spectrometric data into a structure, which enables the application of existing data analysis packages in Python. The second step is the data analysis for selecting single features. These features are further processed in the third step, which is the feature identification. The data used exemplarily in this proof-of-principle approach was from a study on the influence of a heat treatment on the milk proteome/peptidome.
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Affiliation(s)
- Gesine Kuhnen
- GALAB Laboratories GmbH, Am Schleusengraben 7, 21029, Hamburg, Germany
- Department of Food Chemistry and Analysis, Institute of Food Technology and Food Chemistry, Technical University Berlin, Gustav Meyer Allee 25, 13355, Berlin, Germany
| | - Lisa-Carina Class
- GALAB Laboratories GmbH, Am Schleusengraben 7, 21029, Hamburg, Germany
- Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany
| | - Svenja Badekow
- GALAB Laboratories GmbH, Am Schleusengraben 7, 21029, Hamburg, Germany
| | - Kim Lara Hanisch
- GALAB Laboratories GmbH, Am Schleusengraben 7, 21029, Hamburg, Germany
| | - Sascha Rohn
- Department of Food Chemistry and Analysis, Institute of Food Technology and Food Chemistry, Technical University Berlin, Gustav Meyer Allee 25, 13355, Berlin, Germany
| | - Jürgen Kuballa
- GALAB Laboratories GmbH, Am Schleusengraben 7, 21029, Hamburg, Germany.
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4
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Reinig S, Kuo C, Wu CC, Huang SY, Yu JS, Shih SR. Specific long-term changes in anti-SARS-CoV-2 IgG modifications and antibody functions in mRNA, adenovector, and protein subunit vaccines. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.06.16.23291455. [PMID: 38559243 PMCID: PMC10980124 DOI: 10.1101/2023.06.16.23291455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Various vaccine platforms were developed and deployed against the COVID-19 disease. The Fc-mediated functions of IgG antibodies are essential in the adaptive immune response elicited by vaccines. However, the long-term changes of protein subunit vaccines and their combinations with mRNA vaccines are unknown. A total of 272 serum and plasma samples were collected from individuals who received first to third doses of the protein subunit Medigen, the mRNA (BNT), or the adenovector AstraZeneca vaccines. The IgG subclass level was measured using enzyme-linked immunosorbent assay, and Fc-N glycosylation was measured using LC-MS/MS. Antibody-dependent phagocytosis (ADCP) and complement deposition (ADCD) of anti-spike (S) IgG antibodies were measured. IgG1 and 3 reached the highest anti-S IgG subclass level. IgG1, 2, and 4 subclass levels significantly increased in mRNA- and Medigen-vaccinated individuals. Fc-glycosylation was stable, except in female BNT vaccinees, who showed increased bisection and decreased galactosylation. Female BNT vaccinees had a higher anti-S IgG titer than that of males. ADCP declined in all groups. ADCD increased in Medigen-vaccinated individuals after the third dose. Each vaccine produced specific long-term changes in Fc structure and function. This finding is critical when selecting a vaccine platform or combination to achieve the desired immune response.
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Affiliation(s)
- Sebastian Reinig
- Research center for Emerging viral infections, Chang Gung University, Taoyuan, Taiwan
| | - Chin Kuo
- Research center for Emerging viral infections, Chang Gung University, Taoyuan, Taiwan
| | - Chia-Chun Wu
- Molecular research center, Chang Gung University, Taoyuan
| | - Sheng-Yu Huang
- Research center for Emerging viral infections, Chang Gung University, Taoyuan, Taiwan
| | - Jau-Song Yu
- Molecular research center, Chang Gung University, Taoyuan
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Liver Research Center, Chang Gung Memorial Hospital, Linkou 33305, Taiwan
- Research Center for Food and Cosmetic Safety, College of Human Ecology, Chang Gung University of Science and Technology, Taoyuan 33302, Taiwan
| | - Shin-Ru Shih
- Research center for Emerging viral infections, Chang Gung University, Taoyuan, Taiwan
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Research Center for Chinese Herbal Medicine, Research Center for Food and Cosmetic Safety, Graduate Institute of Health Industry Technology, College of Human Ecology, Chang Gung University of Science and Technology, Taoyuan, Taiwan
- Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan
- Clinical Virology Laboratory, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
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5
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Sun W, Zhang Q, Zhang X, Tran NH, Ziaur Rahman M, Chen Z, Peng C, Ma J, Li M, Xin L, Shan B. Glycopeptide database search and de novo sequencing with PEAKS GlycanFinder enable highly sensitive glycoproteomics. Nat Commun 2023; 14:4046. [PMID: 37422459 PMCID: PMC10329677 DOI: 10.1038/s41467-023-39699-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 06/19/2023] [Indexed: 07/10/2023] Open
Abstract
Here we present GlycanFinder, a database search and de novo sequencing tool for the analysis of intact glycopeptides from mass spectrometry data. GlycanFinder integrates peptide-based and glycan-based search strategies to address the challenge of complex fragmentation of glycopeptides. A deep learning model is designed to capture glycan tree structures and their fragment ions for de novo sequencing of glycans that do not exist in the database. We performed extensive analyses to validate the false discovery rates (FDRs) at both peptide and glycan levels and to evaluate GlycanFinder based on comprehensive benchmarks from previous community-based studies. Our results show that GlycanFinder achieved comparable performance to other leading glycoproteomics softwares in terms of both FDR control and the number of identifications. Moreover, GlycanFinder was also able to identify glycopeptides not found in existing databases. Finally, we conducted a mass spectrometry experiment for antibody N-linked glycosylation profiling that could distinguish isomeric peptides and glycans in four immunoglobulin G subclasses, which had been a challenging problem to previous studies.
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Affiliation(s)
- Weiping Sun
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Qianqiu Zhang
- David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada
| | - Xiyue Zhang
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Ngoc Hieu Tran
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
- David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada
| | - M Ziaur Rahman
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Zheng Chen
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Chao Peng
- BaizhenBio Inc., Wuhan, China
- Wuhan BioBank, Wuhan, China
| | - Jun Ma
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Ming Li
- David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada.
- Henan Academy of Sciences, Zhengzhou, Henan, China.
| | - Lei Xin
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada.
| | - Baozhen Shan
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada.
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6
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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018. MASS SPECTROMETRY REVIEWS 2023; 42:227-431. [PMID: 34719822 DOI: 10.1002/mas.21721] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 07/26/2021] [Accepted: 07/26/2021] [Indexed: 06/13/2023]
Abstract
This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.
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Affiliation(s)
- David J Harvey
- Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Oxford, UK
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7
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Pujić I, Perreault H. Recent advancements in glycoproteomic studies: Glycopeptide enrichment and derivatization, characterization of glycosylation in SARS CoV2, and interacting glycoproteins. MASS SPECTROMETRY REVIEWS 2022; 41:488-507. [PMID: 33393161 DOI: 10.1002/mas.21679] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 12/13/2020] [Accepted: 12/16/2020] [Indexed: 06/12/2023]
Abstract
Proteomics studies allow for the determination of the identity, amount, and interactions of proteins under specific conditions that allow the biological state of an organism to ultimately change. These conditions can be either beneficial or detrimental. Diseases are due to detrimental changes caused by either protein overexpression or underexpression caused by as a result of a mutation or posttranslational modifications (PTM), among other factors. Identification of disease biomarkers through proteomics can be potentially used as clinical information for diagnostics. Common biomarkers to look for include PTM. For example, aberrant glycosylation of proteins is a common marker and will be a focus of interest in this review. A common way to analyze glycoproteins is by glycoproteomics involving mass spectrometry. Due to factors such as micro- and macroheterogeneity which result in a lower abundance of each version of a glycoprotein, it is difficult to obtain meaningful results unless rigorous sample preparation procedures are in place. Microheterogeneity represents the diversity of glycans at a single site, whereas macroheterogeneity depicts glycosylation levels at each site of a protein. Enrichment and derivatization of glycopeptides help to overcome these limitations. Over the time range of 2016 to 2020, several methods have been proposed in the literature and have contributed to drastically improve the outcome of glycosylation analysis, as presented in the sampling surveyed in this review. As a current topic in 2020, glycoproteins carried by pathogens can also cause disease and this is seen with SARS CoV2, causing the COVID-19 pandemic. This review will discuss glycoproteomic studies of the spike glycoprotein and interacting proteins such as the ACE2 receptor.
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Affiliation(s)
- Ivona Pujić
- Chemistry Department, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Hélène Perreault
- Chemistry Department, University of Manitoba, Winnipeg, Manitoba, Canada
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8
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Kawahara R, Chernykh A, Alagesan K, Bern M, Cao W, Chalkley RJ, Cheng K, Choo MS, Edwards N, Goldman R, Hoffmann M, Hu Y, Huang Y, Kim JY, Kletter D, Liquet B, Liu M, Mechref Y, Meng B, Neelamegham S, Nguyen-Khuong T, Nilsson J, Pap A, Park GW, Parker BL, Pegg CL, Penninger JM, Phung TK, Pioch M, Rapp E, Sakalli E, Sanda M, Schulz BL, Scott NE, Sofronov G, Stadlmann J, Vakhrushev SY, Woo CM, Wu HY, Yang P, Ying W, Zhang H, Zhang Y, Zhao J, Zaia J, Haslam SM, Palmisano G, Yoo JS, Larson G, Khoo KH, Medzihradszky KF, Kolarich D, Packer NH, Thaysen-Andersen M. Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis. Nat Methods 2021; 18:1304-1316. [PMID: 34725484 DOI: 10.1101/2021.03.14.435332] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 09/22/2021] [Indexed: 05/18/2023]
Abstract
Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.
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Affiliation(s)
- Rebeca Kawahara
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
| | - Anastasia Chernykh
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
| | - Kathirvel Alagesan
- Institute for Glycomics, Griffith University Gold Coast Campus, Southport, QLD, Australia
| | | | - Weiqian Cao
- Institutes of Biomedical Sciences, and the NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China
| | - Robert J Chalkley
- UCSF, School of Pharmacy, Department of Pharmaceutical Chemistry, San Francisco, CA, USA
| | - Kai Cheng
- State University of New York, Buffalo, NY, USA
| | - Matthew S Choo
- Analytics Group, Bioprocessing Technology Institute, Agency for Science, Technology and Research, Singapore, Singapore
| | - Nathan Edwards
- Clinical and Translational Glycoscience Research Center (CTGRC), Georgetown University, Washington, DC, USA
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, DC, USA
| | - Radoslav Goldman
- Clinical and Translational Glycoscience Research Center (CTGRC), Georgetown University, Washington, DC, USA
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, DC, USA
- Department of Oncology, Georgetown University, Washington, DC, USA
| | - Marcus Hoffmann
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg, Germany
| | - Yingwei Hu
- Department of Pathology, The Johns Hopkins University, Baltimore, MD, USA
| | - Yifan Huang
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Jin Young Kim
- Research Center of Bioconvergence Analysis, Korea Basic Science Institute, Daejeon, Republic of Korea
| | | | - Benoit Liquet
- Department of Mathematics and Statistics, Macquarie University, Sydney, NSW, Australia
- CNRS, Laboratoire de Mathématiques et de leurs Applications de PAU, E2S-UPPA, Pau, France
| | - Mingqi Liu
- Institutes of Biomedical Sciences, and the NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China
| | - Yehia Mechref
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Bo Meng
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing, China
| | | | - Terry Nguyen-Khuong
- Analytics Group, Bioprocessing Technology Institute, Agency for Science, Technology and Research, Singapore, Singapore
| | - Jonas Nilsson
- Proteomics Core Facility, Sahlgrenska academy, University of Gothenburg, Gothenburg, Sweden
| | - Adam Pap
- BRC, Laboratory of Proteomics Research, Szeged, Hungary
- Doctoral School in Biology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary
| | - Gun Wook Park
- Research Center of Bioconvergence Analysis, Korea Basic Science Institute, Daejeon, Republic of Korea
| | - Benjamin L Parker
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, VIC, Australia
| | - Cassandra L Pegg
- School of Chemistry and Molecular Biosciences, University of Queensland, Queensland, QLD, Australia
| | - Josef M Penninger
- IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria
- Department of Medical Genetics, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada
| | - Toan K Phung
- School of Chemistry and Molecular Biosciences, University of Queensland, Queensland, QLD, Australia
| | - Markus Pioch
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg, Germany
| | - Erdmann Rapp
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg, Germany
- glyXera GmbH, Magdeburg, Germany
| | - Enes Sakalli
- IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria
| | - Miloslav Sanda
- Clinical and Translational Glycoscience Research Center (CTGRC), Georgetown University, Washington, DC, USA
- Department of Oncology, Georgetown University, Washington, DC, USA
| | - Benjamin L Schulz
- School of Chemistry and Molecular Biosciences, University of Queensland, Queensland, QLD, Australia
| | - Nichollas E Scott
- Deparment of Microbiology and Immunology, University of Melbourne, Melbourne, VIC, Australia
| | - Georgy Sofronov
- Department of Mathematics and Statistics, Macquarie University, Sydney, NSW, Australia
| | - Johannes Stadlmann
- IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria
| | - Sergey Y Vakhrushev
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christina M Woo
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hung-Yi Wu
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Pengyuan Yang
- Institutes of Biomedical Sciences, and the NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China
| | - Wantao Ying
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing, China
| | - Hui Zhang
- Department of Pathology, The Johns Hopkins University, Baltimore, MD, USA
| | - Yong Zhang
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing, China
| | - Jingfu Zhao
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA
| | - Joseph Zaia
- Department of Biochemistry, Boston University Medical Campus, Boston, MA, USA
| | - Stuart M Haslam
- Department of Life Sciences, Imperial College London, London, UK
| | - Giuseppe Palmisano
- Instituto de Ciências Biomédicas, Departamento de Parasitologia, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Jong Shin Yoo
- Research Center of Bioconvergence Analysis, Korea Basic Science Institute, Daejeon, Republic of Korea
- Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, Republic of Korea
| | - Göran Larson
- Department of Laboratory Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Kai-Hooi Khoo
- Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
| | - Katalin F Medzihradszky
- UCSF, School of Pharmacy, Department of Pharmaceutical Chemistry, San Francisco, CA, USA
- BRC, Laboratory of Proteomics Research, Szeged, Hungary
| | - Daniel Kolarich
- Institute for Glycomics, Griffith University Gold Coast Campus, Southport, QLD, Australia
| | - Nicolle H Packer
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
- Institute for Glycomics, Griffith University Gold Coast Campus, Southport, QLD, Australia
- Biomolecular Discovery Research Centre, Macquarie University, Sydney, NSW, Australia
| | - Morten Thaysen-Andersen
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia.
- Biomolecular Discovery Research Centre, Macquarie University, Sydney, NSW, Australia.
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9
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Oliveira T, Thaysen-Andersen M, Packer NH, Kolarich D. The Hitchhiker's guide to glycoproteomics. Biochem Soc Trans 2021; 49:1643-1662. [PMID: 34282822 PMCID: PMC8421054 DOI: 10.1042/bst20200879] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 06/03/2021] [Accepted: 06/23/2021] [Indexed: 02/06/2023]
Abstract
Protein glycosylation is one of the most common post-translational modifications that are essential for cell function across all domains of life. Changes in glycosylation are considered a hallmark of many diseases, thus making glycoproteins important diagnostic and prognostic biomarker candidates and therapeutic targets. Glycoproteomics, the study of glycans and their carrier proteins in a system-wide context, is becoming a powerful tool in glycobiology that enables the functional analysis of protein glycosylation. This 'Hitchhiker's guide to glycoproteomics' is intended as a starting point for anyone who wants to explore the emerging world of glycoproteomics. The review moves from the techniques that have been developed for the characterisation of single glycoproteins to technologies that may be used for a successful complex glycoproteome characterisation. Examples of the variety of approaches, methodologies, and technologies currently used in the field are given. This review introduces the common strategies to capture glycoprotein-specific and system-wide glycoproteome data from tissues, body fluids, or cells, and a perspective on how integration into a multi-omics workflow enables a deep identification and characterisation of glycoproteins - a class of biomolecules essential in regulating cell function.
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Affiliation(s)
- Tiago Oliveira
- Institute for Glycomics, Griffith University, Gold Coast Campus, Gold Coast, Queensland, Australia
| | | | - Nicolle H. Packer
- Institute for Glycomics, Griffith University, Gold Coast Campus, Gold Coast, Queensland, Australia
- Department of Molecular Sciences, Macquarie University, Sydney, New South Wales, Australia
- ARC Centre of Excellence for Nanoscale BioPhotonics, Griffith University, QLD and Macquarie University, NSW, Australia
| | - Daniel Kolarich
- Institute for Glycomics, Griffith University, Gold Coast Campus, Gold Coast, Queensland, Australia
- ARC Centre of Excellence for Nanoscale BioPhotonics, Griffith University, QLD and Macquarie University, NSW, Australia
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10
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Pralow A, Nikolay A, Leon A, Genzel Y, Rapp E, Reichl U. Site-specific N-glycosylation analysis of animal cell culture-derived Zika virus proteins. Sci Rep 2021; 11:5147. [PMID: 33664361 PMCID: PMC7933209 DOI: 10.1038/s41598-021-84682-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 02/18/2021] [Indexed: 01/09/2023] Open
Abstract
Here, we present for the first time, a site-specific N-glycosylation analysis of proteins from a Brazilian Zika virus (ZIKV) strain. The virus was propagated with high yield in an embryo-derived stem cell line (EB66, Valneva SE), and concentrated by g-force step-gradient centrifugation. Subsequently, the sample was proteolytically digested with different enzymes, measured via a LC–MS/MS-based workflow, and analyzed in a semi-automated way using the in-house developed glyXtoolMS software. The viral non-structural protein 1 (NS1) was glycosylated exclusively with high-mannose structures on both potential N-glycosylation sites. In case of the viral envelope (E) protein, no specific N-glycans could be identified with this method. Nevertheless, N-glycosylation could be proved by enzymatic de-N-glycosylation with PNGase F, resulting in a strong MS-signal of the former glycopeptide with deamidated asparagine at the potential N-glycosylation site N444. This confirmed that this site of the ZIKV E protein is highly N-glycosylated but with very high micro-heterogeneity. Our study clearly demonstrates the progress made towards site-specific N-glycosylation analysis of viral proteins, i.e. for Brazilian ZIKV. It allows to better characterize viral isolates, and to monitor glycosylation of major antigens. The method established can be applied for detailed studies regarding the impact of protein glycosylation on antigenicity and human pathogenicity of many viruses including influenza virus, HIV and corona virus.
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Affiliation(s)
- Alexander Pralow
- Bioprocess Engineering Group, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Alexander Nikolay
- Bioprocess Engineering Group, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | | | - Yvonne Genzel
- Bioprocess Engineering Group, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Erdmann Rapp
- Bioprocess Engineering Group, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. .,glyXera GmbH, Magdeburg, Germany.
| | - Udo Reichl
- Bioprocess Engineering Group, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.,Chair of Bioprocess Engineering, Otto von Guericke University, Magdeburg, Germany
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11
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Pralow A, Hoffmann M, Nguyen-Khuong T, Pioch M, Hennig R, Genzel Y, Rapp E, Reichl U. Comprehensive N-glycosylation analysis of the influenza A virus proteins HA and NA from adherent and suspension MDCK cells. FEBS J 2021; 288:4869-4891. [PMID: 33629527 DOI: 10.1111/febs.15787] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 02/04/2021] [Accepted: 02/22/2021] [Indexed: 12/25/2022]
Abstract
Glycosylation is considered as a critical quality attribute for the production of recombinant biopharmaceuticals such as hormones, blood clotting factors, or monoclonal antibodies. In contrast, glycan patterns of immunogenic viral proteins, which differ significantly between the various expression systems, are hardly analyzed yet. The influenza A virus (IAV) proteins hemagglutinin (HA) and neuraminidase (NA) have multiple N-glycosylation sites, and alteration of N-glycan micro- and macroheterogeneity can have strong effects on virulence and immunogenicity. Here, we present a versatile and powerful glycoanalytical workflow that enables a comprehensive N-glycosylation analysis of IAV glycoproteins. We challenged our workflow with IAV (A/PR/8/34 H1N1) propagated in two closely related Madin-Darby canine kidney (MDCK) cell lines, namely an adherent MDCK cell line and its corresponding suspension cell line. As expected, N-glycan patterns of HA and NA from virus particles produced in both MDCK cell lines were similar. Detailed analysis of the HA N-glycan microheterogeneity showed an increasing variability and a higher complexity for N-glycosylation sites located closer to the head region of the molecule. In contrast, NA was found to be exclusively N-glycosylated at site N73. Almost all N-glycan structures were fucosylated. Furthermore, HA and NA N-glycan structures were exclusively hybrid- and complex-type structures, to some extent terminated with alpha-linked galactose(s) but also with blood group H type 2 and blood group A epitopes. In contrast to the similarity of the overall glycan pattern, differences in the relative abundance of individual structures were identified. This concerned, in particular, oligomannose-type, alpha-linked galactose, and multiantennary complex-type N-glycans.
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Affiliation(s)
- Alexander Pralow
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Marcus Hoffmann
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Terry Nguyen-Khuong
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Markus Pioch
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - René Hennig
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.,glyXera GmbH, Magdeburg, Germany
| | - Yvonne Genzel
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Erdmann Rapp
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.,glyXera GmbH, Magdeburg, Germany
| | - Udo Reichl
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.,Chair of Bioprocess Engineering, Otto von Guericke University, Magdeburg, Germany
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12
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Cao W, Liu M, Kong S, Wu M, Zhang Y, Yang P. Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis. Mol Cell Proteomics 2021; 20:100060. [PMID: 33556625 PMCID: PMC8724820 DOI: 10.1074/mcp.r120.002090] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.
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Affiliation(s)
- Weiqian Cao
- The Fifth People's Hospital of Fudan University and Institutes of Biomedical Sciences, Fudan University, Shanghai, China; NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China; The Shanghai Key Laboratory of Medical Epigenetics and the International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Fudan University, Shanghai, China.
| | - Mingqi Liu
- The Fifth People's Hospital of Fudan University and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Siyuan Kong
- The Fifth People's Hospital of Fudan University and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Mengxi Wu
- The Fifth People's Hospital of Fudan University and Institutes of Biomedical Sciences, Fudan University, Shanghai, China; Department of Chemistry, Fudan University, Shanghai, China
| | - Yang Zhang
- The Fifth People's Hospital of Fudan University and Institutes of Biomedical Sciences, Fudan University, Shanghai, China; The Shanghai Key Laboratory of Medical Epigenetics and the International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Fudan University, Shanghai, China
| | - Pengyuan Yang
- The Fifth People's Hospital of Fudan University and Institutes of Biomedical Sciences, Fudan University, Shanghai, China; NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China; The Shanghai Key Laboratory of Medical Epigenetics and the International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Fudan University, Shanghai, China; Department of Chemistry, Fudan University, Shanghai, China.
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13
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Noor SI, Hoffmann M, Rinis N, Bartels MF, Winterhalter PR, Hoelscher C, Hennig R, Himmelreich N, Thiel C, Ruppert T, Rapp E, Strahl S. Glycosyltransferase POMGNT1 deficiency strengthens N-cadherin-mediated cell-cell adhesion. J Biol Chem 2021; 296:100433. [PMID: 33610554 PMCID: PMC7994789 DOI: 10.1016/j.jbc.2021.100433] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 02/08/2021] [Accepted: 02/16/2021] [Indexed: 12/12/2022] Open
Abstract
Defects in protein O-mannosylation lead to severe congenital muscular dystrophies collectively known as α-dystroglycanopathy. A hallmark of these diseases is the loss of the O-mannose-bound matriglycan on α-dystroglycan, which reduces cell adhesion to the extracellular matrix. Mutations in protein O-mannose β1,2-N-acetylglucosaminyltransferase 1 (POMGNT1), which is crucial for the elongation of O-mannosyl glycans, have mainly been associated with muscle-eye-brain (MEB) disease. In addition to defects in cell-extracellular matrix adhesion, aberrant cell-cell adhesion has occasionally been observed in response to defects in POMGNT1. However, specific molecular consequences of POMGNT1 deficiency on cell-cell adhesion are largely unknown. We used POMGNT1 knockout HEK293T cells and fibroblasts from an MEB patient to gain deeper insight into the molecular changes in POMGNT1 deficiency. Biochemical and molecular biological techniques combined with proteomics, glycoproteomics, and glycomics revealed that a lack of POMGNT1 activity strengthens cell-cell adhesion. We demonstrate that the altered intrinsic adhesion properties are due to an increased abundance of N-cadherin (N-Cdh). In addition, site-specific changes in the N-glycan structures in the extracellular domain of N-Cdh were detected, which positively impact on homotypic interactions. Moreover, in POMGNT1-deficient cells, ERK1/2 and p38 signaling pathways are activated and transcriptional changes that are comparable with the epithelial-mesenchymal transition (EMT) are triggered, defining a possible molecular mechanism underlying the observed phenotype. Our study indicates that changes in cadherin-mediated cell-cell adhesion and other EMT-related processes may contribute to the complex clinical symptoms of MEB or α-dystroglycanopathy in general and suggests that the impact of changes in O-mannosylation on N-glycosylation has been underestimated.
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Affiliation(s)
- Sina Ibne Noor
- Centre for Organismal Studies (COS), Glycobiology, Heidelberg University, Heidelberg, Germany
| | - Marcus Hoffmann
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg, Germany
| | - Natalie Rinis
- Centre for Organismal Studies (COS), Glycobiology, Heidelberg University, Heidelberg, Germany
| | - Markus F Bartels
- Centre for Organismal Studies (COS), Glycobiology, Heidelberg University, Heidelberg, Germany
| | - Patrick R Winterhalter
- Centre for Organismal Studies (COS), Glycobiology, Heidelberg University, Heidelberg, Germany
| | - Christina Hoelscher
- Centre for Organismal Studies (COS), Glycobiology, Heidelberg University, Heidelberg, Germany
| | - René Hennig
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg, Germany; glyXera GmbH, Magdeburg, Germany
| | - Nastassja Himmelreich
- Center for Child and Adolescent Medicine, Department Pediatrics I, University of Heidelberg, Heidelberg, Germany
| | - Christian Thiel
- Center for Child and Adolescent Medicine, Department Pediatrics I, University of Heidelberg, Heidelberg, Germany
| | - Thomas Ruppert
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Erdmann Rapp
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg, Germany; glyXera GmbH, Magdeburg, Germany
| | - Sabine Strahl
- Centre for Organismal Studies (COS), Glycobiology, Heidelberg University, Heidelberg, Germany.
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14
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Abstract
Glycoproteomics is unquestionably on the rise and its current development benefits from past experience in proteomics, in particular when attending to bioinformatics needs. An extensive range of software solutions is available, but the reproducibility of mass spectrometry data processing remains challenging. One of the key issues in running automated glycopeptide identification software is the selection of a reference glycan composition file. The default choices are often too broad, and a fastidious literature search to properly target this selection can be avoided. This chapter suggests the use of GlyConnect Compozitor to collect relevant information on glycosylation in a given tissue or cell line and shape an appropriate glycan composition set that can be input in the majority of search engines accommodating user-defined compositions.
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15
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Cajic S, Hennig R, Burock R, Rapp E. Capillary (Gel) Electrophoresis-Based Methods for Immunoglobulin (G) Glycosylation Analysis. EXPERIENTIA SUPPLEMENTUM (2012) 2021; 112:137-172. [PMID: 34687009 DOI: 10.1007/978-3-030-76912-3_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The in-depth characterization of protein glycosylation has become indispensable in many research fields and in the biopharmaceutical industry. Especially knowledge about modulations in immunoglobulin G (IgG) N-glycosylation and their effect on immunity enabled a better understanding of human diseases and the development of new, more effective drugs for their treatment. This chapter provides a deeper insight into capillary (gel) electrophoresis-based (C(G)E) glycan analysis, addressing its impressive performance and possibilities, its great potential regarding real high-throughput for large cohort studies, as well as its challenges and limitations. We focus on the latest developments with respect to miniaturization and mass spectrometry coupling, as well as data analysis and interpretation. The use of exoglycosidase sequencing in combination with current C(G)E technology is discussed, highlighting possible difficulties and pitfalls. The application section describes the detailed characterization of N-glycosylation, utilizing multiplexed CGE with laser-induced fluorescence detection (xCGE-LIF). Besides a comprehensive overview on antibody glycosylation by comparing species-specific IgGs and human immunoglobulins A, D, E, G, and M, the chapter comprises a comparison of therapeutic monoclonal antibodies from different production cell lines, as well as a detailed characterization of Fab and Fc glycosylation. These examples illustrate the full potential of C(G)E, resolving the smallest differences in sugar composition and structure.
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Affiliation(s)
- Samanta Cajic
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - René Hennig
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
- glyXera GmbH, Magdeburg, Germany.
| | | | - Erdmann Rapp
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
- glyXera GmbH, Magdeburg, Germany
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16
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Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis. Nat Methods 2021; 18:1304-1316. [PMID: 34725484 PMCID: PMC8566223 DOI: 10.1038/s41592-021-01309-x] [Citation(s) in RCA: 78] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 09/22/2021] [Indexed: 12/17/2022]
Abstract
Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.
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17
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Schulze S, Oltmanns A, Fufezan C, Krägenbring J, Mormann M, Pohlschröder M, Hippler M. SugarPy facilitates the universal, discovery-driven analysis of intact glycopeptides. Bioinformatics 2020; 36:5330-5336. [PMID: 33325487 DOI: 10.1093/bioinformatics/btaa1042] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 10/26/2020] [Accepted: 12/07/2020] [Indexed: 02/07/2023] Open
Abstract
MOTIVATION Protein glycosylation is a complex post-translational modification with crucial cellular functions in all domains of life. Currently, large-scale glycoproteomics approaches rely on glycan database dependent algorithms and are thus unsuitable for discovery-driven analyses of glycoproteomes. RESULTS Therefore, we devised SugarPy, a glycan database independent Python module, and validated it on the glycoproteome of human breast milk. We further demonstrated its applicability by analyzing glycoproteomes with uncommon glycans stemming from the green alga Chlamydomonas reinhardtii and the archaeon Haloferax volcanii. SugarPy also facilitated the novel characterization of glycoproteins from the red alga Cyanidioschyzon merolae. AVAILABILITY The source code is freely available on GitHub (https://github.com/SugarPy/SugarPy), and its implementation in Python ensures support for all operating systems. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Stefan Schulze
- University of Pennsylvania, Department of Biology, Leidy Laboratories, Philadelphia, USA.,University of Muenster, Institute of Plant Biology and Biotechnology, Muenster, Germany
| | - Anne Oltmanns
- University of Muenster, Institute of Plant Biology and Biotechnology, Muenster, Germany
| | - Christian Fufezan
- University of Muenster, Institute of Plant Biology and Biotechnology, Muenster, Germany.,Heidelberg University, Institute of Pharmacy and Molecular Biotechnology, Heidelberg, Germany
| | - Julia Krägenbring
- University of Muenster, Institute of Plant Biology and Biotechnology, Muenster, Germany.,University of Muenster, Institute for Hygiene, Muenster, Germany
| | - Michael Mormann
- University of Muenster, Institute for Hygiene, Muenster, Germany
| | - Mechthild Pohlschröder
- University of Pennsylvania, Department of Biology, Leidy Laboratories, Philadelphia, USA
| | - Michael Hippler
- University of Muenster, Institute of Plant Biology and Biotechnology, Muenster, Germany.,Institute of Plant Science and Resources, Okayama University, Kurashiki, Japan
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18
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Lan R, Xin M, Hao Z, You S, Xu Y, Wu J, Dang L, Zhang X, Sun S. Biological Functions and Large-Scale Profiling of Protein Glycosylation in Human Semen. J Proteome Res 2020; 19:3877-3889. [DOI: 10.1021/acs.jproteome.9b00795] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Rongxia Lan
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
| | - Miaomiao Xin
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
- Faculty of Fisheries and Protection of Waters, University of South Bohemia in Ceske Budejovice, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Research Institute of Fish Culture and Hydrobiology, Vodnany 38925, Czech Republic
| | - Zhifang Hao
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
| | - Shanshan You
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
| | - Yintai Xu
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
| | - Jingyu Wu
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
| | - Liuyi Dang
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
| | - Xinwen Zhang
- The Medical Genetics Centre, Xi 'an People's Hospital (Xi 'an Fourth Hospital), Xi’an Obstetrics and Gynecology Hospital, Xi’an, Shaanxi Province 710004, P. R. China
| | - Shisheng Sun
- College of Life Science, Northwest University, Xi’an, Shaanxi Province 710069, P. R. China
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19
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Riley N, Malaker SA, Driessen MD, Bertozzi CR. Optimal Dissociation Methods Differ for N- and O-Glycopeptides. J Proteome Res 2020; 19:3286-3301. [PMID: 32500713 PMCID: PMC7425838 DOI: 10.1021/acs.jproteome.0c00218] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Indexed: 01/29/2023]
Abstract
Site-specific characterization of glycosylation requires intact glycopeptide analysis, and recent efforts have focused on how to best interrogate glycopeptides using tandem mass spectrometry (MS/MS). Beam-type collisional activation, i.e., higher-energy collisional dissociation (HCD), has been a valuable approach, but stepped collision energy HCD (sceHCD) and electron transfer dissociation with HCD supplemental activation (EThcD) have emerged as potentially more suitable alternatives. Both sceHCD and EThcD have been used with success in large-scale glycoproteomic experiments, but they each incur some degree of compromise. Most progress has occurred in the area of N-glycoproteomics. There is growing interest in extending this progress to O-glycoproteomics, which necessitates comparisons of method performance for the two classes of glycopeptides. Here, we systematically explore the advantages and disadvantages of conventional HCD, sceHCD, ETD, and EThcD for intact glycopeptide analysis and determine their suitability for both N- and O-glycoproteomic applications. For N-glycopeptides, HCD and sceHCD generate similar numbers of identifications, although sceHCD generally provides higher quality spectra. Both significantly outperform EThcD methods in terms of identifications, indicating that ETD-based methods are not required for routine N-glycoproteomics even if they can generate higher quality spectra. Conversely, ETD-based methods, especially EThcD, are indispensable for site-specific analyses of O-glycopeptides. Our data show that O-glycopeptides cannot be robustly characterized with HCD-centric methods that are sufficient for N-glycopeptides, and glycoproteomic methods aiming to characterize O-glycopeptides must be constructed accordingly.
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Affiliation(s)
- Nicholas
M. Riley
- Department
of Chemistry, Stanford University, Stanford, California 94305-6104, United States
| | - Stacy A. Malaker
- Department
of Chemistry, Stanford University, Stanford, California 94305-6104, United States
| | - Marc D. Driessen
- Department
of Chemistry, Stanford University, Stanford, California 94305-6104, United States
| | - Carolyn R. Bertozzi
- Department
of Chemistry, Stanford University, Stanford, California 94305-6104, United States
- Howard
Hughes Medical Institute, Stanford, California 94305-6104, United States
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20
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Synthesis of lipid-linked oligosaccharides by a compartmentalized multi-enzyme cascade for the in vitro N-glycosylation of peptides. J Biotechnol 2020; 322:54-65. [PMID: 32653637 DOI: 10.1016/j.jbiotec.2020.07.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 06/18/2020] [Accepted: 07/08/2020] [Indexed: 01/21/2023]
Abstract
A wide range of glycoproteins can be recombinantly expressed in aglycosylated forms in bacterial and cell-free production systems. To investigate the effect of glycosylation of these proteins on receptor binding, stability, efficacy as drugs, pharmacodynamics and pharmacokinetics, an efficient glycosylation platform is required. Here, we present a cell-free synthetic platform for the in vitro N-glycosylation of peptides mimicking the endoplasmic reticulum (ER) glycosylation machinery of eukaryotes. The one-pot, two compartment multi-enzyme cascade consisting of eight recombinant enzymes including the three Leloir glycosyltransferases, Alg1, Alg2 and Alg11, expressed in E. coli and S. cerevisiae, respectively, has been engineered to produce the core lipid-linked (LL) oligosaccharide mannopentaose-di-(N-acetylglucosamine) (LL-Man5). Pythanol (C20H42O), a readily available alcohol consisting of regular isoprenoid units, was utilized as the lipid anchor. As part of the cascade, GDP-mannose was de novo produced from the inexpensive substrates ADP, polyphosphate and mannose. To prevent enzyme inhibition, the nucleotide sugar cascade and the glycosyltransferase were segregated into two compartments by a cellulose ester membrane with 3.5 kDa cut-off allowing for the effective diffusion of GDP-mannose across compartments. Finally, as a proof-of-principle, pythanyl-linked Man5 and the single-subunit oligosaccharyltransferase Trypanosoma brucei STT3A expressed in Sf9 insect cells were used to in vitro N-glycosylate a synthetic peptide of ten amino acids bearing the eukaryotic consensus motif N-X-S/T.
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21
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Zhu H, Wang S, Liu D, Ding L, Chen C, Liu Y, Wu Z, Bollag R, Liu K, Alexander WM, Yin J, Ma C, Li L, Wang PG. Identifying Sialylation Linkages at the Glycopeptide Level by Glycosyltransferase Labeling Assisted Mass Spectrometry (GLAMS). Anal Chem 2020; 92:6297-6303. [PMID: 32271005 PMCID: PMC7750919 DOI: 10.1021/acs.analchem.9b05068] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Precise assignment of sialylation linkages at the glycopeptide level is of importance in bottom-up glycoproteomics and an indispensable step to understand the function of glycoproteins in pathogen-host interactions and cancer progression. Even though some efforts have been dedicated to the discrimination of α2,3/α2,6-sialylated isomers, unambiguous identification of sialoglycopeptide isomers is still needed. Herein, we developed an innovative glycosyltransferase labeling assisted mass spectrometry (GLAMS) strategy. After specific enzymatic labeling, oxonium ions from higher-energy C-trap dissociation (HCD) fragmentation of α2,3-sailoglycopeptides then generate unique reporters to distinctly differentiate those of α2,6-sailoglycopeptide isomers. With this strategy, a total of 1236 linkage-specific sialoglycopeptides were successfully identified from 161 glycoproteins in human serum.
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Affiliation(s)
- He Zhu
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Shuaishuai Wang
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Ding Liu
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Lang Ding
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Congcong Chen
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Yunpeng Liu
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Zhigang Wu
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Roni Bollag
- Georgia Cancer Center, Augusta University, Augusta, Georgia 30912, United States
| | - Kebin Liu
- Department of Biochemistry and Molecular Biology, Augusta University, Augusta, Georgia 30912, United States
| | - William Max Alexander
- Department of Cancer Biology and Blais Proteomics Center, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, United States
| | - Jun Yin
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Cheng Ma
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Lei Li
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Peng George Wang
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
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22
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Cao WQ, Liu MQ, Kong SY, Wu MX, Huang ZZ, Yang PY. Novel methods in glycomics: a 2019 update. Expert Rev Proteomics 2020; 17:11-25. [PMID: 31914820 DOI: 10.1080/14789450.2020.1708199] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.
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Affiliation(s)
- Wei-Qian Cao
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.,NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China
| | - Ming-Qi Liu
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Si-Yuan Kong
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Meng-Xi Wu
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.,Department of Chemistry, Fudan University, Shanghai, China
| | - Zheng-Ze Huang
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Peng-Yuan Yang
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.,NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China.,Department of Chemistry, Fudan University, Shanghai, China
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23
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Zhu H, Aloor A, Ma C, Kondengaden SM, Wang PG. Mass Spectrometric Analysis of Protein Glycosylation. ACS SYMPOSIUM SERIES 2020. [DOI: 10.1021/bk-2020-1346.ch010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Affiliation(s)
- He Zhu
- These authors contributed equally
| | | | | | | | - Peng George Wang
- Current Address: Department of Chemistry, Southern University of Science and Technology, Shenzhen, Guangdong 518055, P. R. China
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24
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Klein JA, Zaia J. A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts. Biochemistry 2019; 59:3089-3097. [PMID: 31833756 DOI: 10.1021/acs.biochem.9b00730] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Protein glycosylation, resulting from glycosyl transferase reactions under complex control in the secretory pathway, consists of a distribution of related glycoforms at each glycosylation site. Because the biosynthetic substrate concentration and transport rates depend on architecture and other aspects of cellular phenotypes, site-specific glycosylation cannot be predicted accurately from genomic, transcriptomic, or proteomic information. Rather, it is necessary to quantify glycosylation at each protein site and how this changes among a sample cohort to provide information about disease mechanisms. At present, mature mass spectrometry-based methods allow for qualitative assignment of the glycan composition and glycosylation site of singly glycosylated proteolytic peptides. To make such quantitative comparisons, it is necessary to sample the glycosylation distribution with sufficient coverage and accuracy for confident assessment of the glycosylation changes that occur in the biological cohort. In this Perspective, we discuss the unmet needs for mass spectrometry acquisition methods and bioinformatics for the confident comparison of protein site-specific glycosylation among sample cohorts.
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25
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Gray CJ, Migas LG, Barran PE, Pagel K, Seeberger PH, Eyers CE, Boons GJ, Pohl NLB, Compagnon I, Widmalm G, Flitsch SL. Advancing Solutions to the Carbohydrate Sequencing Challenge. J Am Chem Soc 2019; 141:14463-14479. [PMID: 31403778 DOI: 10.1021/jacs.9b06406] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.
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Affiliation(s)
- Christopher J Gray
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
| | - Lukasz G Migas
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
| | - Perdita E Barran
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
| | - Kevin Pagel
- Institute for Chemistry and Biochemistry , Freie Universität Berlin , Takustraße 3 , 14195 Berlin , Germany
| | - Peter H Seeberger
- Biomolecular Systems Department , Max Planck Institute for Colloids and Interfaces , Am Muehlenberg 1 , 14476 Potsdam , Germany
| | - Claire E Eyers
- Department of Biochemistry, Institute of Integrative Biology , University of Liverpool , Crown Street , Liverpool L69 7ZB , U.K
| | - Geert-Jan Boons
- Complex Carbohydrate Research Center , University of Georgia , Athens , Georgia 30602 , United States
| | - Nicola L B Pohl
- Department of Chemistry , Indiana University , Bloomington , Indiana 47405 , United States
| | - Isabelle Compagnon
- Institut Lumière Matière, UMR5306 Université Lyon 1-CNRS , Université de Lyon , 69622 Villeurbanne Cedex , France.,Institut Universitaire de France IUF , 103 Blvd St Michel , 75005 Paris , France
| | - Göran Widmalm
- Department of Organic Chemistry, Arrhenius Laboratory , Stockholm University , S-106 91 Stockholm , Sweden
| | - Sabine L Flitsch
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
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26
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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: 1.2] [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 .
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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
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27
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Choo MS, Wan C, Rudd PM, Nguyen-Khuong T. GlycopeptideGraphMS: Improved Glycopeptide Detection and Identification by Exploiting Graph Theoretical Patterns in Mass and Retention Time. Anal Chem 2019; 91:7236-7244. [PMID: 31079452 DOI: 10.1021/acs.analchem.9b00594] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The leading proteomic method for identifying N-glycosylated peptides is liquid chromatography coupled with tandem fragmentation mass spectrometry (LCMS/MS) followed by spectral matching of MS/MS fragment masses to a database of possible glycan and peptide combinations. Such database-dependent approaches come with challenges such as needing high-quality informative MS/MS spectra, ignoring unexpected glycan or peptide sequences, and making incorrect assignments because some glycan combinations are equivalent in mass to amino acids. To address these challenges, we present GlycopeptideGraphMS, a graph theoretical bioinformatic approach complementary to the database-dependent method. Using the AXL receptor tyrosine kinase (AXL) as a model glycoprotein with multiple N-glycosylation sites, we show that those LCMS features that could be grouped into graph networks on the basis of glycan mass and retention time differences were actually N-glycopeptides with the same peptide backbone but different N-glycan compositions. Conversely, unglycosylated peptides did not exhibit this grouping behavior. Furthermore, MS/MS sequencing of the glycan and peptide composition of just one N-glycopeptide in the graph was sufficient to identify the rest of the N-glycopeptides in the graph. By validating the identifications with exoglycosidase cocktails and MS/MS fragmentation, we determined the experimental false discovery rate of identifications to be 2.21%. GlycopeptideGraphMS detected more than 500 unique N-glycopeptides from AXL, triple the number found by a database search with Byonic software, and detected incorrect assignments due to a nonspecific protease cleavage. This method overcomes some limitations of the database approach and is a step closer to comprehensive automated glycoproteomics.
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Affiliation(s)
- Matthew S Choo
- Bioprocessing Technology Institute , 20 Biopolis Way #06-01 , Singapore 138668
| | - Corrine Wan
- Bioprocessing Technology Institute , 20 Biopolis Way #06-01 , Singapore 138668
| | - Pauline M Rudd
- Bioprocessing Technology Institute , 20 Biopolis Way #06-01 , Singapore 138668.,National Institute for Bioprocessing Research and Training , Conway Institute , Dublin , Ireland.,University College Dublin, Belfield , Dublin , Ireland
| | - Terry Nguyen-Khuong
- Bioprocessing Technology Institute , 20 Biopolis Way #06-01 , Singapore 138668
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28
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Gränicher G, Coronel J, Pralow A, Marichal-Gallardo P, Wolff M, Rapp E, Karlas A, Sandig V, Genzel Y, Reichl U. Efficient influenza A virus production in high cell density using the novel porcine suspension cell line PBG.PK2.1. Vaccine 2019; 37:7019-7028. [PMID: 31005427 DOI: 10.1016/j.vaccine.2019.04.030] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Revised: 03/29/2019] [Accepted: 04/08/2019] [Indexed: 12/22/2022]
Abstract
Seasonal and pandemic influenza respiratory infections are still a major public health issue. Vaccination is the most efficient way to prevent influenza infection. One option to produce influenza vaccines is cell-culture based virus propagation. Different host cell lines, such as MDCK, Vero, AGE1.CR or PER.C6 cells have been shown to be a good substrate for influenza virus production. With respect to the ease of scale-up, suspension cells should be preferred over adherent cells. Ideally, they should replicate different influenza virus strains with high cell-specific yields. Evaluation of new cell lines and further development of processes is of considerable interest, as this increases the number of options regarding the design of manufacturing processes, flexibility of vaccine production and efficiency. Here, PBG.PK2.1, a new mammalian cell line that was developed by ProBioGen AG (Germany) for virus production is presented. The cells derived from immortal porcine kidney cells were previously adapted to growth in suspension in a chemically-defined medium. Influenza virus production was improved after virus adaptation to PBG.PK2.1 cells and optimization of infection conditions, namely multiplicity of infection and trypsin concentration. Hemagglutinin titers up to 3.24 log10(HA units/100 µL) were obtained in fed-batch mode in bioreactors (700 mL working volume). Evaluation of virus propagation in high cell density culture using a hollow-fiber based system (ATF2) demonstrated promising performance: Cell concentrations of up to 50 × 106 cells/mL with viabilities exceeding 95%, and a maximum HA titer of 3.93 log10(HA units/100 µL). Analysis of glycosylation of the viral HA antigen expressed showed clear differences compared to HA produced in MDCK or Vero cell lines. With an average cell-specific productivity of 5000 virions/cell, we believe that PBG.PK2.1 cells are a very promising candidate to be considered for next-generation influenza virus vaccine production.
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Affiliation(s)
- Gwendal Gränicher
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany.
| | - Juliana Coronel
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany
| | - Alexander Pralow
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany
| | - Pavel Marichal-Gallardo
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany
| | - Michael Wolff
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany; Institute of Bioprocess Engineering and Pharmaceutical Technology, University of Applied Sciences Mittelhessen, Wiesenstrasse 14, 35390 Gießen, Germany
| | - Erdmann Rapp
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany
| | | | | | - Yvonne Genzel
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany
| | - Udo Reichl
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstr. 1, 39106 Magdeburg, Germany; Chair for Bioprocess Engineering, Otto-von-Guericke-University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany
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29
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Hoffmann M, Pioch M, Pralow A, Hennig R, Kottler R, Reichl U, Rapp E. The Fine Art of Destruction: A Guide to In-Depth Glycoproteomic Analyses-Exploiting the Diagnostic Potential of Fragment Ions. Proteomics 2018; 18:e1800282. [DOI: 10.1002/pmic.201800282] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 09/07/2018] [Indexed: 01/10/2023]
Affiliation(s)
- Marcus Hoffmann
- Max Planck Institute for Dynamics of Complex Technical Systems; Bioprocess Engineering; 39106 Magdeburg Germany
| | - Markus Pioch
- Max Planck Institute for Dynamics of Complex Technical Systems; Bioprocess Engineering; 39106 Magdeburg Germany
| | - Alexander Pralow
- Max Planck Institute for Dynamics of Complex Technical Systems; Bioprocess Engineering; 39106 Magdeburg Germany
| | - René Hennig
- Max Planck Institute for Dynamics of Complex Technical Systems; Bioprocess Engineering; 39106 Magdeburg Germany
- glyXera GmbH; 39120 Magdeburg Germany
| | - Robert Kottler
- Max Planck Institute for Dynamics of Complex Technical Systems; Bioprocess Engineering; 39106 Magdeburg Germany
- glyXera GmbH; 39120 Magdeburg Germany
| | - Udo Reichl
- Max Planck Institute for Dynamics of Complex Technical Systems; Bioprocess Engineering; 39106 Magdeburg Germany
- Chair of Bioprocess Engineering; Otto von Guericke University Magdeburg; 39106 Magdeburg Germany
| | - Erdmann Rapp
- Max Planck Institute for Dynamics of Complex Technical Systems; Bioprocess Engineering; 39106 Magdeburg Germany
- glyXera GmbH; 39120 Magdeburg Germany
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