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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: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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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: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Hanreich A, Heyer R, Benndorf D, Rapp E, Pioch M, Reichl U, Klocke M. Metaproteome analysis to determine the metabolically active part of a thermophilic microbial community producing biogas from agricultural biomass. Can J Microbiol 2012; 58:917-22. [DOI: 10.1139/w2012-058] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Complex consortia of microorganisms are responsible for biogas production. A lot of information about the taxonomic structure and enzymatic potential of such communities has been collected by a variety of gene-based approaches, yet little is known about which of all the assumable metabolic pathways are active throughout the process of biogas formation. To tackle this problem, we established a protocol for the metaproteomic analysis of samples taken from biogas reactors fed with agricultural biomass. In contrast to previous studies where an anaerobic digester was fed with synthetic wastewater, the complex matrix in this study required the extraction of proteins with liquid phenol and the application of paper bridge loading for 2-dimensional gel electrophoresis. Proteins were subjected to nanoHPLC (high-performance liquid chromatography) coupled to tandem mass spectrometry for characterization. Several housekeeping proteins as well as methanogenesis-related enzymes were identified by a MASCOT search and de novo sequencing, which proved the feasibility of our approach. The establishment of such an approach is the basis for further metaproteomic studies of biogas-producing communities. In particular, the apparent status of metabolic activities within the communities can be monitored. The knowledge collected from such experiments could lead to further improvements of biogas production.
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Affiliation(s)
- Angelika Hanreich
- Leibniz-Institut für Agrartechnik Potsdam-Bornim e.V., Abteilung Bioverfahrenstechnik, Max-Eyth-Allee 100, 14469 Potsdam, Germany
| | - Robert Heyer
- Otto von Guericke University, Bioprocess Engineering, Universitätsplatz 2, 39106 Magdeburg, Germany
| | - Dirk Benndorf
- Otto von Guericke University, Bioprocess Engineering, Universitätsplatz 2, 39106 Magdeburg, Germany
| | - Erdmann Rapp
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtor Straße 1, 39106 Magdeburg, Germany
| | - Markus Pioch
- Otto von Guericke University, Bioprocess Engineering, Universitätsplatz 2, 39106 Magdeburg, Germany
| | - Udo Reichl
- Otto von Guericke University, Bioprocess Engineering, Universitätsplatz 2, 39106 Magdeburg, Germany
- Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtor Straße 1, 39106 Magdeburg, Germany
| | - Michael Klocke
- Leibniz-Institut für Agrartechnik Potsdam-Bornim e.V., Abteilung Bioverfahrenstechnik, Max-Eyth-Allee 100, 14469 Potsdam, Germany
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