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Beltrao P, Van Den Bossche T, Gabriels R, Holstein T, Kockmann T, Nameni A, Panse C, Schlapbach R, Lautenbacher L, Mattanovich M, Nesvizhskii A, Van Puyvelde B, Scheid J, Schwämmle V, Strauss M, Susmelj AK, The M, Webel H, Wilhelm M, Winkelhardt D, Wolski WE, Xi M. Proceedings of the EuBIC-MS developers meeting 2023. J Proteomics 2024; 305:105246. [PMID: 38964537 DOI: 10.1016/j.jprot.2024.105246] [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: 04/26/2024] [Revised: 06/19/2024] [Accepted: 06/27/2024] [Indexed: 07/06/2024]
Abstract
The 2023 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers Meeting was held from January 15th to January 20th, 2023, in Congressi Stefano Franscin at Monte Verità in Ticino, Switzerland. The participants were scientists and developers working in computational mass spectrometry (MS), metabolomics, and proteomics. The 5-day program was split between introductory keynote lectures and parallel hackathon sessions focusing on "Artificial Intelligence in proteomics" to stimulate future directions in the MS-driven omics areas. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts and actively contribute to highly relevant research projects. We successfully produced several new tools applicable to the proteomics community by improving data analysis and facilitating future research.
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Affiliation(s)
| | - Tim Van Den Bossche
- VIB-UGent Center for Medical Biotechnology, 9052 Zwijnaarde, Belgium; Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Ralf Gabriels
- VIB-UGent Center for Medical Biotechnology, 9052 Zwijnaarde, Belgium; Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Tanja Holstein
- VIB-UGent Center for Medical Biotechnology, 9052 Zwijnaarde, Belgium; Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Tobias Kockmann
- Functional Genomics Center Zürich, ETH Zürich/University of Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland
| | - Alireza Nameni
- VIB-UGent Center for Medical Biotechnology, 9052 Zwijnaarde, Belgium; Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Christian Panse
- Functional Genomics Center Zürich, ETH Zürich/University of Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland; Swiss Institute of Bioinformatics, Quartier Sorge - Batiment Amphipole, 1015 Lausanne, Switzerland.
| | - Ralph Schlapbach
- Functional Genomics Center Zürich, ETH Zürich/University of Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland
| | - Ludwig Lautenbacher
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Maximus-von-Imhof-Forum 3, D - 85354 Freising, Germany
| | - Matthias Mattanovich
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
| | - Alexey Nesvizhskii
- Departments of Pathology and Computational Medicine and Bioinfoirmatics, University of Michigan, Ann Arbor, MI 48105, USA
| | - Bart Van Puyvelde
- ProGenTomics, Laboratory of Pharmaceutical Biotechnology, Ghent University, Ottergemsesteenweg 460, BE-9000 Ghent, Belgium
| | - Jonas Scheid
- Department of Peptide-based Immunotherapy, Institute of Immunology, University and University hospital Tübingen, Auf der Morgenstelle 15, D-72076 Tübingen, Germany; Quantitative Biology Center (QBiC), University of Tübingen, Auf der Morgenstelle 10, D-72076 Tübingen, Germany
| | - Veit Schwämmle
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
| | - Maximilian Strauss
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Matthew The
- TUM School of Life Sciences Technische Universität München, D - 85354 Freising, Germany
| | - Henry Webel
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mathias Wilhelm
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Maximus-von-Imhof-Forum 3, D - 85354 Freising, Germany
| | | | - Witold E Wolski
- Functional Genomics Center Zürich, ETH Zürich/University of Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland; Swiss Institute of Bioinformatics, Quartier Sorge - Batiment Amphipole, 1015 Lausanne, Switzerland
| | - Muyao Xi
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
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2
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Goecker ZC, Burke MC, Remoroza CA, Liu Y, Mirokhin YA, Sheetlin SL, Tchekhovskoi DV, Yang X, Stein SE. Variation of Site-Specific Glycosylation Profiles of Recombinant Influenza Glycoproteins. Mol Cell Proteomics 2024:100827. [PMID: 39128790 DOI: 10.1016/j.mcpro.2024.100827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 07/08/2024] [Accepted: 08/07/2024] [Indexed: 08/13/2024] Open
Abstract
This work presents a detailed determination of site-specific N-glycan distributions of the recombinant influenza glycoproteins hemagglutinin and neuraminidase. Variation in glycosylation among recombinant glycoproteins is not predictable and can depend on details of the biomanufacturing process as well as details of protein structure. In this study, recombinant influenza proteins were analyzed from eight strains of four different suppliers. These include five hemagglutinin and three neuraminidase proteins, each produced from a HEK293 cell line. Digestion was conducted using a series of complex multi-enzymatic methods designed to isolate glycopeptides containing single N-glycosylated sites. Site-specific glycosylation profiles of intact glycopeptides were produced using a recently developed method and comparisons were made using spectral similarity scores. Variation in glycan abundances and distribution was most pronounced between different strains of virus (similarity score = 383 out of 999), whereas digestion replicates and injection replicates showed relatively little variation (similarity score = 957). Notably, glycan distributions for homologous regions of influenza glycoprotein variants showed low variability. Due to the multiple possible sources of variation and inherent analytical difficulties in site-specific glycan determinations, variations were individually examined for multiple factors, including differences in supplier, production batch, protease digestion and replicate measurement. After comparing all glycosylation distributions, four distinguishable classes could be identified for the majority of sites. Finally, attempts to identify glycosylation distributions on adjacent potential N-glycosylated sites of one HA variant were made. Only the second site (NnST) was found to be occupied using two rarely used proteases in proteomics, subtilisin and esperase, both of which did selectively cleave these adjacent sites.
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Affiliation(s)
- Zachary C Goecker
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States.
| | - Meghan C Burke
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
| | - Concepcion A Remoroza
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
| | - Yi Liu
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
| | - Yuri A Mirokhin
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
| | - Sergey L Sheetlin
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
| | - Dmitrii V Tchekhovskoi
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
| | - Xiaoyu Yang
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
| | - Stephen E Stein
- Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States
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3
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Humphries EM, Loudon C, Craft GE, Hains PG, Robinson PJ. Quantitative Comparison of Deparaffinization, Rehydration, and Extraction Methods for FFPE Tissue Proteomics and Phosphoproteomics. Anal Chem 2024. [PMID: 39102789 DOI: 10.1021/acs.analchem.3c04479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/07/2024]
Abstract
Formalin-fixed paraffin-embedded (FFPE) tissues are suitable for proteomic and phosphoproteomic biomarker studies by data-independent acquisition mass spectrometry. The choice of the sample preparation method influences the number, intensity, and reproducibility of identifications. By comparing four deparaffinization and rehydration methods, including heptane, histolene, SubX, and xylene, we found that heptane and methanol produced the lowest coefficients of variation (CVs). Using this, five extraction methods from the literature were modified and evaluated for their performance using kidney, leg muscle, lung, and testicular rat organs. All methods performed well, except for SP3 due to insufficient tissue lysis. Heat n' Beat was the fastest and most reproducible method with the highest digestion efficiency and lowest CVs. S-Trap produced the highest peptide yield, while TFE produced the best phosphopeptide enrichment efficiency. The quantitation of FFPE-derived peptides remains an ongoing challenge with bias in UV and fluorescence assays across methods, most notably in SPEED. Functional enrichment analysis demonstrated that each method favored extracting some gene ontology cellular components over others including chromosome, cytoplasmic, cytoskeleton, endoplasmic reticulum, membrane, mitochondrion, and nucleoplasm protein groups. The outcome is a set of recommendations for choosing the most appropriate method for different settings.
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Affiliation(s)
- Erin M Humphries
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Clare Loudon
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - George E Craft
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Peter G Hains
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Phillip J Robinson
- ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
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Dalal KB, Yang W, Tian E, Chernish A, McCluggage P, Lara AJ, Ten Hagen KG, Tabak LA. In vivo Mapping of the Mouse Galnt3-specific O-Glycoproteome. J Biol Chem 2024:107628. [PMID: 39098533 DOI: 10.1016/j.jbc.2024.107628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 07/23/2024] [Accepted: 07/24/2024] [Indexed: 08/06/2024] Open
Abstract
The UDP-N-acetylgalactosamine polypeptide:N-acetylgalactosaminyltransferase (GalNAc-T) family of enzymes initiates O-linked glycosylation by catalyzing the addition of the first GalNAc sugar to serine or threonine on proteins destined to be membrane-bound or secreted. Defects in individual isoforms of the GalNAc-T family can lead to certain congenital disorders of glycosylation (CDG). The GALNT3-CDG, is caused by mutations in GALNT3, resulting in hyperphosphatemic familial tumoral calcinosis (HFTC) due to impaired glycosylation of the phosphate-regulating hormone FGF23 within osteocytes of the bone. Patients with hyperphosphatemia present altered bone density, abnormal tooth structure and calcified masses throughout the body. It is therefore important to identify all potential substrates of GalNAc-T3 throughout the body to understand the complex disease phenotypes. Here, we compared the Galnt3-/- mouse model, which partially phenocopies GALNT3-CDG, with wild-type mice and employed a multi-component approach utilizing chemoenzymatic conditions, a product-dependent method constructed using EThcD triggered scans in a mass spectrometry workflow, quantitative O-glycoproteomics, and global proteomics to identify 663 Galnt3-specific O-glycosites from 269 glycoproteins across multiple tissues. Consistent with the mouse and human phenotypes, functional networks of glycoproteins that contain GalNAc-T3-specific O-glycosites involved in skeletal morphology, mineral level maintenance and hemostasis were identified. This library of in vivo GalNAc-T3-specific substrate proteins and O-glycosites will serve as a valuable resource to understand the functional implications of O-glycosylation and to unravel the underlying causes of complex human GALNT3-CDG phenotypes.
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Affiliation(s)
- Kruti Bhavik Dalal
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Weiming Yang
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - E Tian
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Aliona Chernish
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Peggy McCluggage
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Alexander J Lara
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Kelly G Ten Hagen
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892
| | - Lawrence A Tabak
- Biological Chemistry Section and Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892.
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5
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Tkalec KI, Hayes AJ, Lim KS, Lewis JM, Davies MR, Scott NE. Glycan-Tailored Glycoproteomic Analysis Reveals Serine is the Sole Residue Subjected to O-Linked Glycosylation in Acinetobacter baumannii. J Proteome Res 2024; 23:2474-2494. [PMID: 38850255 DOI: 10.1021/acs.jproteome.4c00148] [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] [Indexed: 06/10/2024]
Abstract
Protein glycosylation is a ubiquitous process observed across all domains of life. Within the human pathogen Acinetobacter baumannii, O-linked glycosylation is required for virulence; however, the targets and conservation of glycosylation events remain poorly defined. In this work, we expand our understanding of the breadth and site specificity of glycosylation within A. baumannii by demonstrating the value of strain specific glycan electron-transfer/higher-energy collision dissociation (EThcD) triggering for bacterial glycoproteomics. By coupling tailored EThcD-triggering regimes to complementary glycopeptide enrichment approaches, we assessed the observable glycoproteome of three A. baumannii strains (ATCC19606, BAL062, and D1279779). Combining glycopeptide enrichment techniques including ion mobility (FAIMS), metal oxide affinity chromatography (titanium dioxide), and hydrophilic interaction liquid chromatography (ZIC-HILIC), as well as the use of multiple proteases (trypsin, GluC, pepsin, and thermolysis), we expand the known A. baumannii glycoproteome to 33 unique glycoproteins containing 42 glycosylation sites. We demonstrate that serine is the sole residue subjected to glycosylation with the substitution of serine for threonine abolishing glycosylation in model glycoproteins. An A. baumannii pan-genome built from 576 reference genomes identified that serine glycosylation sites are highly conserved. Combined this work expands our knowledge of the conservation and site specificity of A. baumannii O-linked glycosylation.
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Affiliation(s)
- Kristian I Tkalec
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Andrew J Hayes
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Kataleen S Lim
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Jessica M Lewis
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Mark R Davies
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Nichollas E Scott
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
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DeBono NJ, Moh ESX, Packer NH. Experimentally Determined Diagnostic Ions for Identification of Peptide Glycotopes. J Proteome Res 2024; 23:2661-2673. [PMID: 38888225 DOI: 10.1021/acs.jproteome.3c00858] [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] [Indexed: 06/20/2024]
Abstract
The analysis of the structures of glycans present on glycoproteins is an essential component for determining glycoprotein function; however, detailed glycan structural assignment on glycopeptides from proteomics mass spectrometric data remains challenging. Glycoproteomic analysis by mass spectrometry currently can provide significant, yet incomplete, information about the glycans present, including the glycan monosaccharide composition and in some circumstances the site(s) of glycosylation. Advancements in mass spectrometric resolution, using high-mass accuracy instrumentation and tailored MS/MS fragmentation parameters, coupled with a dedicated definition of diagnostic fragmentation ions have enabled the determination of some glycan structural features, or glycotopes, expressed on glycopeptides. Here we present a collation of diagnostic glycan fragments produced by traditional positive-ion-mode reversed-phase LC-ESI MS/MS proteomic workflows and describe the specific fragmentation energy settings required to identify specific glycotopes presented on N- or O-linked glycopeptides in a typical proteomics MS/MS experiment.
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Affiliation(s)
- Nicholas J DeBono
- ARC Centre of Excellence in Synthetic Biology, School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Edward S X Moh
- ARC Centre of Excellence in Synthetic Biology, School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Nicolle H Packer
- ARC Centre of Excellence in Synthetic Biology, School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia
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7
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Humphries EM, Xavier D, Ashman K, Hains PG, Robinson PJ. High-Throughput Proteomics and Phosphoproteomics of Rat Tissues Using Microflow Zeno SWATH. J Proteome Res 2024; 23:2355-2366. [PMID: 38819404 DOI: 10.1021/acs.jproteome.4c00010] [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] [Indexed: 06/01/2024]
Abstract
High-throughput tissue proteomics has great potential in the advancement of precision medicine. Here, we investigated the combined sensitivity of trap-elute microflow liquid chromatography with a ZenoTOF for DIA proteomics and phosphoproteomics. Method optimization was conducted on HEK293T cell lines to determine the optimal variable window size, MS2 accumulation time and gradient length. The ZenoTOF 7600 was then compared to the previous generation TripleTOF 6600 using eight rat organs, finding up to 23% more proteins using a fifth of the sample load and a third of the instrument time. Spectral reference libraries generated from Zeno SWATH data in FragPipe (MSFragger-DIA/DIA-NN) contained 4 times more fragment ions than the DIA-NN only library and quantified more proteins. Replicate single-shot phosphopeptide enrichments of 50-100 μg of rat tryptic peptide were analyzed by microflow HPLC using Zeno SWATH without fractionation. Using Spectronaut we quantified a shallow phosphoproteome containing 1000-3000 phosphoprecursors per organ. Promisingly, clear hierarchical clustering of organs was observed with high Pearson correlation coefficients >0.95 between replicate enrichments and median CV of 20%. The combined sensitivity of microflow HPLC with Zeno SWATH allows for the high-throughput quantitation of an extensive proteome and shallow phosphoproteome from small tissue samples.
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Affiliation(s)
- Erin M Humphries
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Dylan Xavier
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Keith Ashman
- Sciex, 96 Ricketts Road,Mount Waverley, Victoria 3149, Australia
| | - Peter G Hains
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
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8
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Hu X, Song J, Ye G, Zhu M, Lan J, Zeng L, Ke Z, Yuan J. Integrated serum proteomic and N-glycoproteomic characterization of dengue patients. J Med Virol 2024; 96:e29775. [PMID: 38949184 DOI: 10.1002/jmv.29775] [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: 03/06/2024] [Revised: 06/06/2024] [Accepted: 06/22/2024] [Indexed: 07/02/2024]
Abstract
Dengue fever is a mosquito-borne viral disease caused by the dengue virus (DENV). It poses a public health threat globally and, while most people with dengue have mild symptoms or are asymptomatic, approximately 5% of affected individuals develop severe disease and need hospital care. However, knowledge of the molecular mechanisms underlying dengue infection and the interaction between the virus and its host remains limited. In the present study, we performed a quantitative proteomic and N-glycoproteomic analysis of serum from 19 patients with dengue and 11 healthy people. The results revealed distinct proteomic and N-glycoproteomic landscapes between the two groups. Notably, we report for the first time the changes in the serum N glycosylation pattern following dengue infection and provide abundant information on glycoproteins, glycosylation sites, and intact N-glycopeptides using recently developed site-specific glycoproteomic approaches. Furthermore, a series of key functional pathways in proteomic and N-glycoproteomic were identified. Collectively, our findings significantly improve understanding of host and DENV interactions and the general pathogenesis and pathology of DENV, laying a foundation for functional studies of glycosylation and glycan structures in dengue infection.
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Affiliation(s)
- Xiao Hu
- Infectious Disease Department, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Jiamin Song
- Infectious Disease Department, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Guoguo Ye
- Infectious Disease Department, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Miao Zhu
- Center for Emerging Infectious Diseases, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China
| | - Jianfeng Lan
- Infectious Disease Department, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Lijiao Zeng
- Infectious Disease Department, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Zhiyi Ke
- Infectious Disease Department, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Jing Yuan
- Infectious Disease Department, National Clinical Research Center for Infectious Disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
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9
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Povolo L, Tian W, Vakhrushev SY, Halim A. Global View of Domain-Specific O-Linked Mannose Glycosylation in Glycoengineered Cells. Mol Cell Proteomics 2024; 23:100796. [PMID: 38851451 PMCID: PMC11292533 DOI: 10.1016/j.mcpro.2024.100796] [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: 01/16/2024] [Revised: 06/03/2024] [Accepted: 06/05/2024] [Indexed: 06/10/2024] Open
Abstract
Protein O-linked mannose (O-Man) glycosylation is an evolutionary conserved posttranslational modification that fulfills important biological roles during embryonic development. Three nonredundant enzyme families, POMT1/POMT2, TMTC1-4, and TMEM260, selectively coordinate the initiation of protein O-Man glycosylation on distinct classes of transmembrane proteins, including α-dystroglycan, cadherins, and plexin receptors. However, a systematic investigation of their substrate specificities is lacking, in part due to the ubiquitous expression of O-Man glycosyltransferases in cells, which precludes analysis of pathway-specific O-Man glycosylation on a proteome-wide scale. Here, we apply a targeted workflow for membrane glycoproteomics across five human cell lines to extensively map O-Man substrates and genetically deconstruct O-Man initiation by individual and combinatorial knockout of O-Man glycosyltransferase genes. We established a human cell library for the analysis of substrate specificities of individual O-Man initiation pathways by quantitative glycoproteomics. Our results identify 180 O-Man glycoproteins, demonstrate new protein targets for the POMT1/POMT2 pathway, and show that TMTC1-4 and TMEM260 pathways widely target distinct Ig-like protein domains of plasma membrane proteins involved in cell-cell and cell-extracellular matrix interactions. The identification of O-Man on Ig-like folds adds further knowledge on the emerging concept of domain-specific O-Man glycosylation which opens for functional studies of O-Man-glycosylated adhesion molecules and receptors.
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Affiliation(s)
- Lorenzo Povolo
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Weihua Tian
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Sergey Y Vakhrushev
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Adnan Halim
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark.
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10
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Hu Y, Schnaubelt M, Chen L, Zhang B, Hoang T, Lih TM, Zhang Z, Zhang H. MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses. Anal Chem 2024; 96:10145-10151. [PMID: 38869158 DOI: 10.1021/acs.analchem.3c01497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.
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Affiliation(s)
- Yingwei Hu
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Michael Schnaubelt
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Li Chen
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Bai Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Trung Hoang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - T Mamie Lih
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Zhen Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Hui Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
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11
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Wang Y, Liu Y, Liu S, Cheng L, Liu X. Recent advances in N-glycan biomarker discovery among human diseases. Acta Biochim Biophys Sin (Shanghai) 2024. [PMID: 38910518 DOI: 10.3724/abbs.2024101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/25/2024] Open
Abstract
N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.
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Affiliation(s)
- Yi Wang
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yuanyuan Liu
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Si Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350122, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xin Liu
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
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12
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Polasky DA, Lu L, Yu F, Li K, Shortreed MR, Smith LM, Nesvizhskii AI. Quantitative proteome-wide O-glycoproteomics analysis with FragPipe. Anal Bioanal Chem 2024:10.1007/s00216-024-05382-x. [PMID: 38877149 DOI: 10.1007/s00216-024-05382-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 05/20/2024] [Accepted: 05/24/2024] [Indexed: 06/16/2024]
Abstract
Identification of O-glycopeptides from tandem mass spectrometry data is complicated by the near complete dissociation of O-glycans from the peptide during collisional activation and by the combinatorial explosion of possible glycoforms when glycans are retained intact in electron-based activation. The recent O-Pair search method provides an elegant solution to these problems, using a collisional activation scan to identify the peptide sequence and total glycan mass, and a follow-up electron-based activation scan to localize the glycosite(s) using a graph-based algorithm in a reduced search space. Our previous O-glycoproteomics methods with MSFragger-Glyco allowed for extremely fast and sensitive identification of O-glycopeptides from collisional activation data but had limited support for site localization of glycans and quantification of glycopeptides. Here, we report an improved pipeline for O-glycoproteomics analysis that provides proteome-wide, site-specific, quantitative results by incorporating the O-Pair method as a module within FragPipe. In addition to improved search speed and sensitivity, we add flexible options for oxonium ion-based filtering of glycans and support for a variety of MS acquisition methods and provide a comparison between all software tools currently capable of O-glycosite localization in proteome-wide searches.
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Affiliation(s)
- Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Lei Lu
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pharmaceutical Chemistry, University of San Francisco, San Francisco, CA, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Kai Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | | | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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13
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Baerenfaenger M, Post MA, Zijlstra F, van Gool AJ, Lefeber DJ, Wessels HJCT. Maximizing Glycoproteomics Results through an Integrated Parallel Accumulation Serial Fragmentation Workflow. Anal Chem 2024; 96:8956-8964. [PMID: 38776126 PMCID: PMC11154686 DOI: 10.1021/acs.analchem.3c05874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 05/10/2024] [Accepted: 05/11/2024] [Indexed: 06/05/2024]
Abstract
Glycoproteins play important roles in numerous physiological processes and are often implicated in disease. Analysis of site-specific protein glycobiology through glycoproteomics has evolved rapidly in recent years thanks to hardware and software innovations. Particularly, the introduction of parallel accumulation serial fragmentation (PASEF) on hybrid trapped ion mobility time-of-flight mass spectrometry instruments combined deep proteome sequencing with separation of (near-)isobaric precursor ions or converging isotope envelopes through ion mobility separation. However, the reported use of PASEF in integrated glycoproteomics workflows to comprehensively capture the glycoproteome is still limited. To this end, we developed an integrated methodology using timsTOF Pro 2 to enhance N-glycopeptide identifications in complex mixtures. We systematically optimized the ion optics tuning, collision energies, mobility isolation width, and the use of dopant-enriched nitrogen gas (DEN). Thus, we obtained a marked increase in unique glycopeptide identification rates compared to standard proteomics settings, showcasing our results on a large set of glycopeptides. With short liquid chromatography gradients of 30 min, we increased the number of unique N-glycopeptide identifications in human plasma samples from around 100 identifications under standard proteomics conditions to up to 1500 with our optimized glycoproteomics approach, highlighting the need for tailored optimizations to obtain comprehensive data.
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Affiliation(s)
- Melissa Baerenfaenger
- Department
of Neurology, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen 6525 GA, Netherlands
- Division
of BioAnalytical Chemistry, AIMMS Amsterdam Institute of Molecular
and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, Netherlands
| | - Merel A. Post
- Department
of Neurology, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen 6525 GA, Netherlands
| | - Fokje Zijlstra
- Translational
Metabolic Laboratory, Department of Human Genetics, Radboud University Medical Center, Nijmegen 6525 GA, Netherlands
| | - Alain J. van Gool
- Translational
Metabolic Laboratory, Department of Human Genetics, Radboud University Medical Center, Nijmegen 6525 GA, Netherlands
| | - Dirk J. Lefeber
- Department
of Neurology, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen 6525 GA, Netherlands
- Translational
Metabolic Laboratory, Department of Human Genetics, Radboud University Medical Center, Nijmegen 6525 GA, Netherlands
| | - Hans J. C. T. Wessels
- Translational
Metabolic Laboratory, Department of Human Genetics, Radboud University Medical Center, Nijmegen 6525 GA, Netherlands
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14
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Lewis JM, Jebeli L, Coulon PML, Lay CE, Scott NE. Glycoproteomic and proteomic analysis of Burkholderia cenocepacia reveals glycosylation events within FliF and MotB are dispensable for motility. Microbiol Spectr 2024; 12:e0034624. [PMID: 38709084 PMCID: PMC11237607 DOI: 10.1128/spectrum.00346-24] [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: 02/10/2024] [Accepted: 04/16/2024] [Indexed: 05/07/2024] Open
Abstract
Across the Burkholderia genus O-linked protein glycosylation is highly conserved. While the inhibition of glycosylation has been shown to be detrimental for virulence in Burkholderia cepacia complex species, such as Burkholderia cenocepacia, little is known about how specific glycosylation sites impact protein functionality. Within this study, we sought to improve our understanding of the breadth, dynamics, and requirement for glycosylation across the B. cenocepacia O-glycoproteome. Assessing the B. cenocepacia glycoproteome across different culture media using complementary glycoproteomic approaches, we increase the known glycoproteome to 141 glycoproteins. Leveraging this repertoire of glycoproteins, we quantitively assessed the glycoproteome of B. cenocepacia using Data-Independent Acquisition (DIA) revealing the B. cenocepacia glycoproteome is largely stable across conditions with most glycoproteins constitutively expressed. Examination of how the absence of glycosylation impacts the glycoproteome reveals that the protein abundance of only five glycoproteins (BCAL1086, BCAL2974, BCAL0525, BCAM0505, and BCAL0127) are altered by the loss of glycosylation. Assessing ΔfliF (ΔBCAL0525), ΔmotB (ΔBCAL0127), and ΔBCAM0505 strains, we demonstrate the loss of FliF, and to a lesser extent MotB, mirror the proteomic effects observed in the absence of glycosylation in ΔpglL. While both MotB and FliF are essential for motility, we find loss of glycosylation sites in MotB or FliF does not impact motility supporting these sites are dispensable for function. Combined this work broadens our understanding of the B. cenocepacia glycoproteome supporting that the loss of glycoproteins in the absence of glycosylation is not an indicator of the requirement for glycosylation for protein function. IMPORTANCE Burkholderia cenocepacia is an opportunistic pathogen of concern within the Cystic Fibrosis community. Despite a greater appreciation of the unique physiology of B. cenocepacia gained over the last 20 years a complete understanding of the proteome and especially the O-glycoproteome, is lacking. In this study, we utilize systems biology approaches to expand the known B. cenocepacia glycoproteome as well as track the dynamics of glycoproteins across growth phases, culturing media and in response to the loss of glycosylation. We show that the glycoproteome of B. cenocepacia is largely stable across conditions and that the loss of glycosylation only impacts five glycoproteins including the motility associated proteins FliF and MotB. Examination of MotB and FliF shows, while these proteins are essential for motility, glycosylation is dispensable. Combined this work supports that B. cenocepacia glycosylation can be dispensable for protein function and may influence protein properties beyond stability.
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Affiliation(s)
- Jessica M Lewis
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Leila Jebeli
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Pauline M L Coulon
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Catrina E Lay
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Nichollas E Scott
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
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15
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Cao W. Advancing mass spectrometry-based glycoproteomic software tools for comprehensive site-specific glycoproteome analysis. Curr Opin Chem Biol 2024; 80:102442. [PMID: 38460452 DOI: 10.1016/j.cbpa.2024.102442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/18/2024] [Accepted: 02/19/2024] [Indexed: 03/11/2024]
Abstract
Glycoproteome analysis at a site-specific level and proteome scale stands out as a highly promising approach for gaining insights into the intricate roles of glycans in biological systems. Recent years have witnessed an upsurge in the development of innovative methodologies tailored for precisely this purpose. Breakthroughs in mass spectrometry-based glycoproteomic techniques, enabling the identification, quantification, and systematic exploration of site-specific glycans, have significantly enhanced our capacity to comprehensively and thoroughly characterize glycoproteins. In this short review, we delve into novel tools in advancing site-specific glycoproteomic analysis and summarize pertinent studies published in the past two years. Lastly, we discuss the ongoing challenges and outline future prospects in the field, considering both the analytical strategies of mass spectrometry and the tools employed for data interpretation.
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Affiliation(s)
- Weiqian Cao
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, 200433, China.
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16
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Li Y, Wang J, Chen W, Lu H, Zhang Y. Comprehensive review of MS-based studies on N-glycoproteome and N-glycome of extracellular vesicles. Proteomics 2024; 24:e2300065. [PMID: 37474487 DOI: 10.1002/pmic.202300065] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 07/10/2023] [Accepted: 07/10/2023] [Indexed: 07/22/2023]
Abstract
Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that can be released by all type of cells. Whereas, as one of the most common post-translational modifications, glycosylation plays a vital role in various biological functions of EVs, such as EV biogenesis, sorting, and cellular recognition. Nevertheless, compared with studies on RNAs or proteins, those investigating the glycoconjugates of EVs are limited. An in-depth investigation of N-glycosylation of EVs can improve the understanding of the biological functions of EVs and help to exploit EVs from different perspectives. The general focus of studies on glycosylation of EVs primarily includes isolation and characterization of EVs, preparation of glycoproteome/glycome samples and MS analysis. However, the low content of EVs and non-standard separation methods for downstream analysis are the main limitations of these studies. In this review, we highlight the importance of glycopeptide/glycan enrichment and derivatization owing to the low abundance of glycoproteins and the low ionization efficiency of glycans. Diverse fragmentation patterns and professional analytical software are indispensable for analysing glycosylation via MS. Altogether, this review summarises recent studies on glycosylation of EVs, revealing the role of EVs in disease progression and their remarkable potential as biomarkers.
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Affiliation(s)
- Yang Li
- Institutes of Biomedical Sciences and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, P. R. China
| | - Jun Wang
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
| | - Weiyu Chen
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
| | - Haojie Lu
- Institutes of Biomedical Sciences and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, P. R. China
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
| | - Ying Zhang
- Institutes of Biomedical Sciences and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, P. R. China
- Department of Chemistry and Shanghai Cancer Center, Fudan University, Shanghai, P. R. China
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17
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Tian Y, Ma S, Wen L. Towards chemoenzymatic labeling strategies for profiling protein glycosylation. Curr Opin Chem Biol 2024; 80:102460. [PMID: 38678979 DOI: 10.1016/j.cbpa.2024.102460] [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: 12/26/2023] [Revised: 03/31/2024] [Accepted: 04/07/2024] [Indexed: 05/01/2024]
Abstract
Protein glycosylation is one of the most common and important post-translational modifications of proteins involved in regulating glycoprotein functions. The chemoenzymatic glycan labeling strategy allows rapid, efficient, and selective interrogation of glycoproteins. Glycoproteomics identifies protein glycosylation events at a large scale, providing information such as peptide sequences, glycan structures, and glycosylated sites. This review discusses the recent development of chemoenzymatic labeling strategies for glycoprotein analysis, mainly including glycoprotein and glycosite profiling. Furthermore, we highlight the chemoenzymatic enrichment approaches in mass spectrometry analysis for three classes of glycan modifications, including N-glycosylation, O-GlcNAcylation, and mucin-type O-glycosylation. Finally, we highlight the emerging trends in new tools and cutting-edge technologies available for glycoproteomic research.
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Affiliation(s)
- Yinping Tian
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Shengzhou Ma
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Liuqing Wen
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China; University of Chinese Academy of Sciences, Beijing, China.
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18
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Girgis M, Petruncio G, Russo P, Peyton S, Paige M, Campos D, Sanda M. Analysis of N- and O-linked site-specific glycosylation by ion mobility mass spectrometry: State of the art and future directions. Proteomics 2024; 24:e2300281. [PMID: 38171879 DOI: 10.1002/pmic.202300281] [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: 07/18/2023] [Revised: 11/22/2023] [Accepted: 12/05/2023] [Indexed: 01/05/2024]
Abstract
Glycosylation, the major post-translational modification of proteins, significantly increases the diversity of proteoforms. Glycans are involved in a variety of pivotal structural and functional roles of proteins, and changes in glycosylation are profoundly connected to the progression of numerous diseases. Mass spectrometry (MS) has emerged as the gold standard for glycan and glycopeptide analysis because of its high sensitivity and the wealth of fragmentation information that can be obtained. Various separation techniques have been employed to resolve glycan and glycopeptide isomers at the front end of the MS. However, differentiating structures of isobaric and isomeric glycopeptides constitutes a challenge in MS-based characterization. Many reports described the use of various ion mobility-mass spectrometry (IM-MS) techniques for glycomic analyses. Nevertheless, very few studies have focused on N- and O-linked site-specific glycopeptidomic analysis. Unlike glycomics, glycoproteomics presents a multitude of inherent challenges in microheterogeneity, which are further exacerbated by the lack of dedicated bioinformatics tools. In this review, we cover recent advances made towards the growing field of site-specific glycosylation analysis using IM-MS with a specific emphasis on the MS techniques and capabilities in resolving isomeric peptidoglycan structures. Furthermore, we discuss commonly used software that supports IM-MS data analysis of glycopeptides.
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Affiliation(s)
- Michael Girgis
- Department of Bioengineering, College of Engineering & Computing, George Mason University, Fairfax, Virginia, USA
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
| | - Gregory Petruncio
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
- Department of Chemistry & Biochemistry, College of Science, George Mason University, Fairfax, Virginia, USA
| | - Paul Russo
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia, USA
| | - Steven Peyton
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
| | - Mikell Paige
- Center for Molecular Engineering, George Mason University, Manassas, Virginia, USA
- Department of Chemistry & Biochemistry, College of Science, George Mason University, Fairfax, Virginia, USA
| | - Diana Campos
- Max-Planck-Institut fuer Herz- und Lungenforschung, Bad Nauheim, Germany
| | - Miloslav Sanda
- Max-Planck-Institut fuer Herz- und Lungenforschung, Bad Nauheim, Germany
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19
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Meng X, Zhou Y, Xu L, Hu L, Wang C, Tian X, Zhang X, Hao Y, Cheng B, Ma J, Wang L, Liu J, Xie R. O-GlcNAcylation Facilitates the Interaction between Keratin 18 and Isocitrate Dehydrogenases and Potentially Influencing Cholangiocarcinoma Progression. ACS CENTRAL SCIENCE 2024; 10:1065-1083. [PMID: 38799671 PMCID: PMC11117311 DOI: 10.1021/acscentsci.4c00163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/06/2024] [Accepted: 04/10/2024] [Indexed: 05/29/2024]
Abstract
Glycosylation plays a pivotal role in the intricate landscape of human cholangiocarcinoma (CCA), actively participating in key pathophysiological processes driving tumor progression. Among the various glycosylation modifications, O-linked β-N-acetyl-glucosamine modification (O-GlcNAcylation) emerges as a dynamic regulator influencing diverse tumor-associated biological activities. In this study, we employed a state-of-the-art chemical proteomic approach to analyze intact glycopeptides, unveiling the critical role of O-GlcNAcylation in orchestrating Keratin 18 (K18) and its interplay with tricarboxylic acid (TCA) cycle enzymes, specifically isocitrate dehydrogenases (IDHs), to propel CCA progression. Our findings shed light on the mechanistic intricacies of O-GlcNAcylation, revealing that site-specific modification of K18 on Ser 30 serves as a stabilizing factor, amplifying the expression of cell cycle checkpoints. This molecular event intricately fosters cell cycle progression and augments cellular growth in CCA. Notably, the interaction between O-GlcNAcylated K18 and IDHs orchestrates metabolic reprogramming by down-regulating citrate and isocitrate levels while elevating α-ketoglutarate (α-KG). These metabolic shifts further contribute to the overall tumorigenic potential of CCA. Our study thus expands the current understanding of protein O-GlcNAcylation and introduces a new layer of complexity to post-translational control over metabolism and tumorigenesis.
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Affiliation(s)
- Xiangfeng Meng
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Yue Zhou
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Lei Xu
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Limu Hu
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Changjiang Wang
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Xiao Tian
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - Xiang Zhang
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Yi Hao
- College
of
Chemistry and Molecular Engineering, Peking
University, Beijing 100871, China
| | - Bo Cheng
- School
of Pharmaceutical Sciences, Peking University, Beijing 100191, China
| | - Jing Ma
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
- Collaborative
Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210023, China
| | - Lei Wang
- Department
of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated, Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Jialin Liu
- State
Key Laboratory of Medical Proteomics, Beijing Proteome Research Center,
National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Ran Xie
- State
Key Laboratory of Coordination Chemistry, School of Chemistry and
Chemical Engineering, Nanjing University, Nanjing 210023, China
- Chemistry
and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210023, China
- Beijing
National Laboratory for Molecular Sciences, Beijing 100191, China
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20
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Li GX, Chen L, Hsiao Y, Mannan R, Zhang Y, Luo J, Petralia F, Cho H, Hosseini N, Leprevost FDV, Calinawan A, Li Y, Anand S, Dagar A, Geffen Y, Kumar-Sinha C, Chugh S, Le A, Ponce S, Guo S, Zhang C, Schnaubelt M, Al Deen NN, Chen F, Caravan W, Houston A, Hopkins A, Newton CJ, Wang X, Polasky DA, Haynes S, Yu F, Jing X, Chen S, Robles AI, Mesri M, Thiagarajan M, An E, Getz GA, Linehan WM, Hostetter G, Jewell SD, Chan DW, Wang P, Omenn GS, Mehra R, Ricketts CJ, Ding L, Chinnaiyan AM, Cieslik MP, Dhanasekaran SM, Zhang H, Nesvizhskii AI. Comprehensive proteogenomic characterization of rare kidney tumors. Cell Rep Med 2024; 5:101547. [PMID: 38703764 PMCID: PMC11148773 DOI: 10.1016/j.xcrm.2024.101547] [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: 03/20/2023] [Revised: 09/29/2023] [Accepted: 04/10/2024] [Indexed: 05/06/2024]
Abstract
Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes. RCCs with high genome instability display overexpression of IGF2BP3 and PYCR1. Integration of single-cell and bulk transcriptome data predicts diverse cell-of-origin and clarifies RCC subtype-specific proteogenomic signatures. Expression of biomarkers MAPRE3, ADGRF5, and GPNMB differentiates renal oncocytoma from chromophobe RCC, and PIGR and SOSTDC1 distinguish papillary RCC from MTSCC. This study expands our knowledge of proteogenomic signatures, biomarkers, and potential therapeutic targets in non-ccRCC.
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Affiliation(s)
- Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lijun Chen
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Yi Hsiao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Rahul Mannan
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yuping Zhang
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jie Luo
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Francesca Petralia
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hanbyul Cho
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Noshad Hosseini
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Anna Calinawan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yize Li
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Shankara Anand
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Aniket Dagar
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yifat Geffen
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Chandan Kumar-Sinha
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Seema Chugh
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Anne Le
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Sean Ponce
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA
| | - Shenghao Guo
- Department of Biomedical Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA
| | - Cissy Zhang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Michael Schnaubelt
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Nataly Naser Al Deen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Feng Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Wagma Caravan
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Andrew Houston
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Alex Hopkins
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Xiaoming Wang
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sarah Haynes
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xiaojun Jing
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Siqi Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Ana I Robles
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Mehdi Mesri
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | | | - Eunkyung An
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Gad A Getz
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - W Marston Linehan
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Scott D Jewell
- Van Andel Research Institute, Grand Rapids, MI 49503, USA
| | - Daniel W Chan
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gilbert S Omenn
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Christopher J Ricketts
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63130, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Arul M Chinnaiyan
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Department of Urology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Marcin P Cieslik
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Saravana M Dhanasekaran
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA.
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21
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Thesbjerg MN, Poulsen KO, Astono J, Poulsen NA, Larsen LB, Nielsen SDH, Stensballe A, Sundekilde UK. O-linked glycosylations in human milk casein and major whey proteins during lactation. Int J Biol Macromol 2024; 267:131613. [PMID: 38642686 DOI: 10.1016/j.ijbiomac.2024.131613] [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: 12/01/2023] [Revised: 04/10/2024] [Accepted: 04/13/2024] [Indexed: 04/22/2024]
Abstract
As glycosylations are difficult to analyze, their roles and effects are poorly understood. Glycosylations in human milk (HM) differ across lactation. Glycosylations can be involved in antimicrobial activities and may serve as food for beneficial microorganisms. This study aimed to identify and analyze O-linked glycans in HM by high-throughput mass spectrometry. 184 longitudinal HM samples from 66 donors from day 3 and months 1, 2, and 3 postpartum were subjected to a post-translational modification specific enrichment-based strategy using TiO2 and ZrO2 beads for O-linked glycopeptide enrichment. β-CN was found to be a major O-linked glycoprotein, additionally, αS1-CN, κ-CN, lactotransferrin, and albumin also contained O-linked glycans. As glycosyltransferases and glycosidases are involved in assembling the glycans including O-linked glycosylations, these were further investigated. Some glycosyltransferases and glycosidases were found to be significantly decreasing through lactation, including two O-linked glycan initiator enzymes (GLNT1 and GLNT2). Despite their decrease, the overall level of O-linked glycans remained stable in HM over lactation. Three different motifs for O-linked glycosylation were enriched in HM proteins: Gly-Xxx-Xxx-Gly-Ser/Thr, Arg-Ser/Thr and Lys-Ser/Thr. Further O-linked glycan motifs on β-CN were observed to differ between intact proteins and endogenous peptides in HM.
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Affiliation(s)
- Martin Nørmark Thesbjerg
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark; Sino-Danish College (SDC), University of Chinese Academy of Science, Huairou District, Beijing 101408, China.
| | - Katrine Overgaard Poulsen
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark; Sino-Danish College (SDC), University of Chinese Academy of Science, Huairou District, Beijing 101408, China
| | - Julie Astono
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark
| | - Nina Aagaard Poulsen
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark
| | - Lotte Bach Larsen
- Department of Food Science, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark
| | | | - Allan Stensballe
- Department of Health Science and Technology, Aalborg University, Selma Lagerløfsvej 249, DK-9260 Gistrup, Denmark; Clinical cancer center, Aalborg University Hospital, 9000 Aalborg, Denmark
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22
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Hartig J, Young LEA, Grimsley G, Mehta AS, Ippolito JE, Leach RJ, Angel PM, Drake RR. The glycosylation landscape of prostate cancer tissues and biofluids. Adv Cancer Res 2024; 161:1-30. [PMID: 39032948 DOI: 10.1016/bs.acr.2024.04.005] [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] [Indexed: 07/23/2024]
Abstract
An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.
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Affiliation(s)
- Jordan Hartig
- Medical University of South Carolina, Charleston, SC, United States
| | | | - Grace Grimsley
- Medical University of South Carolina, Charleston, SC, United States
| | - Anand S Mehta
- Medical University of South Carolina, Charleston, SC, United States
| | - Joseph E Ippolito
- Washington University School of Medicine in Saint Louis, St. Louis, MO, United States
| | - Robin J Leach
- University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
| | - Peggi M Angel
- Medical University of South Carolina, Charleston, SC, United States
| | - Richard R Drake
- Medical University of South Carolina, Charleston, SC, United States.
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23
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Remoroza CA, Burke MC, Mak TD, Sheetlin SL, Mirokhin YA, Cooper BT, Goecker ZC, Lowenthal MS, Yang X, Wang G, Tchekhovskoi DV, Stein SE. Comparison of N-Glycopeptide to Released N-Glycan Abundances and the Influence of Glycopeptide Mass and Charge States on N-Linked Glycosylation of IgG Antibodies. J Proteome Res 2024; 23:1443-1457. [PMID: 38450643 PMCID: PMC10997438 DOI: 10.1021/acs.jproteome.3c00904] [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] [Indexed: 03/08/2024]
Abstract
We report the comparison of mass-spectral-based abundances of tryptic glycopeptides to fluorescence abundances of released labeled glycans and the effects of mass and charge state and in-source fragmentation on glycopeptide abundances. The primary glycoforms derived from Rituximab, NISTmAb, Evolocumab, and Infliximab were high-mannose and biantennary complex galactosylated and fucosylated N-glycans. Except for Evolocumab, in-source ions derived from the loss of HexNAc or HexNAc-Hex sugars are prominent for other therapeutic IgGs. After excluding in-source fragmentation of glycopeptide ions from the results, a linear correlation was observed between fluorescently labeled N-glycan and glycopeptide abundances over a dynamic range of 500. Different charge states of human IgG-derived glycopeptides containing a wider variety of abundant attached glycans were also investigated to examine the effects of the charge state on ion abundances. These revealed a linear dependence of glycopeptide abundance on the mass of the glycan with higher charge states favoring higher-mass glycans. Findings indicate that the mass spectrometry-based bottom-up approach can provide results as accurate as those of glycan release studies while revealing the origin of each attached glycan. These site-specific relative abundances are conveniently displayed and compared using previously described glycopeptide abundance distribution spectra "GADS" representations. Mass spectrometry data are available from the MAssIVE repository (MSV000093562).
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Affiliation(s)
| | | | | | | | | | - Brian T. Cooper
- Mass Spectrometry Data Center
- Department of Chemistry, University of North Carolina at Charlotte, Charlotte, North Carolina 28223, United States
| | | | - Mark S. Lowenthal
- Bioanalytical Science Group, Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive Gaithersburg, MD 20899, US
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24
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Yang Y, Fang Q. Prediction of glycopeptide fragment mass spectra by deep learning. Nat Commun 2024; 15:2448. [PMID: 38503734 PMCID: PMC10951270 DOI: 10.1038/s41467-024-46771-1] [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: 09/13/2023] [Accepted: 03/11/2024] [Indexed: 03/21/2024] Open
Abstract
Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we present DeepGlyco, a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrate that predicted spectral libraries can be used for data-independent acquisition glycoproteomics as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.
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Affiliation(s)
- Yi Yang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 311200, China.
| | - Qun Fang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 311200, China.
- Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
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25
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White MEH, Sinn LR, Jones DM, de Folter J, Aulakh SK, Wang Z, Flynn HR, Krüger L, Tober-Lau P, Demichev V, Kurth F, Mülleder M, Blanchard V, Messner CB, Ralser M. Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics. Nat Biomed Eng 2024; 8:233-247. [PMID: 37474612 DOI: 10.1038/s41551-023-01067-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 06/15/2023] [Indexed: 07/22/2023]
Abstract
Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.
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Affiliation(s)
- Matthew E H White
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Ludwig R Sinn
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - D Marc Jones
- Bioinformatics and Computational Biology Laboratory, The Francis Crick Institute, London, UK
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK
| | - Joost de Folter
- Software Engineering and Artificial Intelligence Technology Platform, The Francis Crick Institute, London, UK
| | - Simran Kaur Aulakh
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Ziyue Wang
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Helen R Flynn
- Mass Spectrometry Proteomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Lynn Krüger
- Institute of Diagnostic Laboratory Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Human Medicine, Medical School Berlin, Berlin, Germany
| | - Pinkus Tober-Lau
- Department of Infectious Diseases and Critical Care Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Vadim Demichev
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Florian Kurth
- Department of Infectious Diseases and Critical Care Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Mülleder
- Core Facility High-throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Véronique Blanchard
- Institute of Diagnostic Laboratory Medicine, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Human Medicine, Medical School Berlin, Berlin, Germany
| | - Christoph B Messner
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Precision Proteomic Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland.
| | - Markus Ralser
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
- Max Planck Institute for Molecular Genetics, Berlin, Germany.
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26
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Li X, Kong R, Hou W, Cao J, Zhang L, Qian X, Zhao L, Ying W. Integrative proteomics and n-glycoproteomics reveal the synergistic anti-tumor effects of aspirin- and gemcitabine-based chemotherapy on pancreatic cancer cells. Cell Oncol (Dordr) 2024; 47:141-156. [PMID: 37639207 DOI: 10.1007/s13402-023-00856-z] [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] [Accepted: 08/03/2023] [Indexed: 08/29/2023] Open
Abstract
OBJECTIVE AND DESIGN Pancreatic cancer is a highly malignant tumor that is well known for its poor prognosis. Based on glycosylation, we performed integrated quantitative N-glycoproteomics to investigate the synergistic anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells and explore the potential molecular mechanisms of chemotherapy in pancreatic cancer. METHODS AND RESULTS Two pancreatic cancer cell lines (PANC-1 and BxPC-3) were treated with gemcitabine, aspirin, and a combination (gemcitabine + aspirin). We found that the addition of aspirin enhanced the inhibitory effect of gemcitabine on the activity of PANC-1 and BxPC-3 cells. Quantitative N-glycoproteome, proteome, phosphorylation, and transcriptome data were obtained from integrated multi-omics analysis to evaluate the anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells. Mfuzz analysis of intact N-glycopeptide profiles revealed two consistent trends associated with the addition of aspirin, which showed a strong relationship between N-glycosylation and the synergistic effect of aspirin. Further analysis demonstrated that the dynamic regulation of sialylation and high-mannose glycoforms on ECM-related proteins (LAMP1, LAMP2, ITGA3, etc.) was a significant factor for the ability of aspirin to promote the anti-tumor activity of gemcitabine and the drug resistance of pancreatic cancer cells. CONCLUSIONS In-depth analysis of N-glycosylation-related processes and pathways in pancreatic cancer cells can provide new insight for future studies regarding pancreatic cancer therapeutic targets and drug resistance mechanisms.
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Affiliation(s)
- Xiaoyu Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38 Life Park Road, Changping District, Beijing, 102206, China
- Institute of Analysis and Testing, Beijing Center for Physical & Chemical Analysis), Beijing Academy of Science and Technology, Beijing, 100094, China
| | - Ran Kong
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38 Life Park Road, Changping District, Beijing, 102206, China
- Biomedical Engineering Department, Peking University, Beijing, 100191, China
| | - Wenhao Hou
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38 Life Park Road, Changping District, Beijing, 102206, China
| | - Junxia Cao
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38 Life Park Road, Changping District, Beijing, 102206, China
| | - Li Zhang
- Center for Bioinformatics and Computational Biology, School of Life Sciences, Institute of Biomedical Sciences, East China Normal University, Shanghai, China
| | - Xiaohong Qian
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38 Life Park Road, Changping District, Beijing, 102206, China
| | - Lijiao Zhao
- Beijing Key Laboratory of Environmental and Viral Oncology, Faculty of Environment and Life, Beijing University of Technology, No. 100 Ping Le Yuan, Chaoyang District, Beijing, 100124, China.
| | - Wantao Ying
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38 Life Park Road, Changping District, Beijing, 102206, China.
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27
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Wiest A, Kielkowski P. Cu-Catalyzed Azide-Alkyne-Thiol Reaction Forms Ubiquitous Background in Chemical Proteomic Studies. J Am Chem Soc 2024; 146:2151-2159. [PMID: 38214237 PMCID: PMC10811670 DOI: 10.1021/jacs.3c11780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/28/2023] [Accepted: 12/29/2023] [Indexed: 01/13/2024]
Abstract
We report here a Cu-catalyzed azide-alkyne-thiol reaction forming thiotriazoles as the major byproduct under widely used bio-orthogonal protein labeling "click" conditions. The development of Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) had a tremendous impact on many biological discoveries. However, the considered chemoselectivity of CuAAC is hampered by the high reactivity of cysteine free thiols, yielding thiotriazole protein conjugates. The reaction byproducts generate false-positive protein hits in functional proteomic studies. The reported detail investigation of conjugates between chemical probes containing terminal alkynes, azide tags, and cell lysates reveals the formation of thiotriazoles, which can be readily detected by in-gel fluorescence scanning or after peptide and protein enrichment by mass spectrometry-based proteomics. In protein level identification and quantification experiments, the produced fluorescent bands or enriched proteins may not result from the important enzymatically driven reaction and can be falsely assigned as hits. This study provides a complete list of the most common background proteins. The knowledge of this previously overlooked reactivity now leads to the introduction of modified CuAAC conditions, which avoids the undesired product formation, diminishes the background, and hence improves the signal-to-noise ratio.
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Affiliation(s)
- Andreas Wiest
- Department of Chemistry, LMU Munich, Würmtalstr. 201, 81375 Munich, Germany
| | - Pavel Kielkowski
- Department of Chemistry, LMU Munich, Würmtalstr. 201, 81375 Munich, Germany
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28
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Xu X, Yin K, Xu S, Wang Z, Wu R. Mass spectrometry-based methods for investigating the dynamics and organization of the surfaceome: exploring potential clinical implications. Expert Rev Proteomics 2024; 21:99-113. [PMID: 38300624 PMCID: PMC10928381 DOI: 10.1080/14789450.2024.2314148] [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: 11/22/2023] [Accepted: 01/16/2024] [Indexed: 02/02/2024]
Abstract
INTRODUCTION Cell-surface proteins are extremely important for many cellular events, such as regulating cell-cell communication and cell-matrix interactions. Aberrant alterations in surface protein expression, modification (especially glycosylation), and interactions are directly related to human diseases. Systematic investigation of surface proteins advances our understanding of protein functions, cellular activities, and disease mechanisms, which will lead to identifying surface proteins as disease biomarkers and drug targets. AREAS COVERED In this review, we summarize mass spectrometry (MS)-based proteomics methods for global analysis of cell-surface proteins. Then, investigations of the dynamics of surface proteins are discussed. Furthermore, we summarize the studies for the surfaceome interaction networks. Additionally, biological applications of MS-based surfaceome analysis are included, particularly highlighting the significance in biomarker identification, drug development, and immunotherapies. EXPERT OPINION Modern MS-based proteomics provides an opportunity to systematically characterize proteins. However, due to the complexity of cell-surface proteins, the labor-intensive workflow, and the limit of clinical samples, comprehensive characterization of the surfaceome remains extraordinarily challenging, especially in clinical studies. Developing and optimizing surfaceome enrichment methods and utilizing automated sample preparation workflow can expand the applications of surfaceome analysis and deepen our understanding of the functions of cell-surface proteins.
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Affiliation(s)
- Xing Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Kejun Yin
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Senhan Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Zeyu Wang
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Ronghu Wu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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Lazari LC, Santiago VF, de Oliveira GS, Mule SN, Angeli CB, Rosa-Fernandes L, Palmisano G. Glycosort: A Computational Solution to Post-process Quantitative Large-Scale Intact Glycopeptide Analyses. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1443:23-32. [PMID: 38409414 DOI: 10.1007/978-3-031-50624-6_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Protein glycosylation is a post-translational modification involving the addition of carbohydrates to proteins and plays a crucial role in protein folding and various biological processes such as cell recognition, differentiation, and immune response. The vast array of natural sugars available allows the generation of plenty of unique glycan structures in proteins, adding complexity to the regulation and biological functions of glycans. The diversity is further increased by enzymatic site preferences and stereochemical conjugation, leading to an immense amount of different glycan structures. Understanding glycosylation heterogeneity is vital for unraveling the impact of glycans on different biological functions. Evaluating site occupancies and structural heterogeneity aids in comprehending glycan-related alterations in biological processes. Several software tools are available for large-scale glycoproteomics studies; however, integrating identification and quantitative data to assess heterogeneity complexity often requires extensive manual data processing. To address this challenge, we present a python script that automates the integration of Byonic and MaxQuant outputs for glycoproteomic data analysis. The script enables the calculation of site occupancy percentages by glycans and facilitates the comparison of glycan structures and site occupancies between two groups. This automated tool offers researchers a means to organize and interpret their high-throughput quantitative glycoproteomic data effectively.
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Affiliation(s)
- Lucas C Lazari
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Veronica Feijoli Santiago
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Gilberto S de Oliveira
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Simon Ngao Mule
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Claudia B Angeli
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Livia Rosa-Fernandes
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
- Centre for Motor Neuron Disease Research, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
| | - Giuseppe Palmisano
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil.
- School of Natural Sciences, Faculty of Science and Engineering, Sydney, Australia.
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30
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Rojas Ramírez C, Espino JA, Jones LM, Polasky DA, Nesvizhskii AI. Efficient Analysis of Proteome-Wide FPOP Data by FragPipe. Anal Chem 2023; 95:16131-16137. [PMID: 37878603 DOI: 10.1021/acs.analchem.3c02388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows for monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent-accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and a lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP data sets. Our workflow, implemented as part of the FragPipe computational platform, combines the speed of the MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 150% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.
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Affiliation(s)
- Carolina Rojas Ramírez
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Jessica A Espino
- Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland 21202, United States
| | - Lisa M Jones
- Department of Chemistry and Biochemistry, University of California San Diego, San Diego, California 92093, United States
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States
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31
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Abu Aisheh M, Kayili HM, Numanoglu Cevik Y, Kanat MA, Salih B. Composition characterization of various viperidae snake venoms using MS-based proteomics N-glycoproteomics and N-glycomics. Toxicon 2023; 235:107328. [PMID: 37884129 DOI: 10.1016/j.toxicon.2023.107328] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/03/2023] [Accepted: 10/18/2023] [Indexed: 10/28/2023]
Abstract
Viperidae snake species is widely abundant and responsible for most envenomation cases in Turkey. The structural and compositional profiles of snake venom have been investigated to study the venom component variation across different species and to profile the venom biological activity variation against prey. In this context, we used proteomics, glycoproteomics and glycomics strategies to characterize the protein, glycoproteins and glycan structural and compositional profiles of various snake venoms in the Viperidae family. Moreover, we compared these profiles using the downstream bioinformatics and machine learning classification modules. The overall mass spectrometry profiles identified 144 different proteins, 36 glycoproteins and 78 distinct N-glycan structures varying in composition across the five venoms. A high amount of the characterized proteins belongs to the glycosylated protein family Trypsin-like serine protease (Tryp_SPc), Disintegrin (DISIN), and ADAM Cysteine-Rich (ACR). Most identified N-glycans have a complex chain carrying galactosylated N-glycans abundantly. The glycan composition data obtained from glycoproteomics aligns consistently with the findings from glycomics. The clustering and principal component analyses (PCA) illustrated the composition-based similarities and differences between each snake venom species' proteome, glycoproteome and glycan profiles. Specifically, the N-glycan profiles of M. xanthina (Mx) and V. a. ammodytes (Vaa) venoms were identical and difficult to differentiate; in contrast, their proteome profiles were distinct. Interestingly, the variety of the proteins across the species highlighted the impact of glycosylation on the diversity of the glycosylated protein families. This proposed high throughput approach provides accurate and comprehensive profiles of the composition and function of various Viperidae snake venoms.
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Affiliation(s)
- Marwa Abu Aisheh
- Department of Chemistry, Faculty of Science, Hacettepe University, 06800, Ankara, Turkey
| | - Haci Mehmet Kayili
- Department of Medical Engineering, Faculty of Engineering, Karabük University, 78000, Karabük, Turkey
| | - Yasemin Numanoglu Cevik
- Microbiology Reference Laboratory, Turkish Public Health Institute, Ministery of Health, 06430, Ankara, Turkey
| | - Mehmet Ali Kanat
- Microbiology and Reference Laboratory and Biological Products Department, General Directorate of Public Health, Minister of Health, 06430, Ankara, Turkey
| | - Bekir Salih
- Department of Chemistry, Faculty of Science, Hacettepe University, 06800, Ankara, Turkey.
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Yang W, Tian E, Chernish A, McCluggage P, Dalal K, Lara A, Ten Hagen KG, Tabak LA. Quantitative mapping of the in vivo O-GalNAc glycoproteome in mouse tissues identifies GalNAc-T2 O-glycosites in metabolic disorder. Proc Natl Acad Sci U S A 2023; 120:e2303703120. [PMID: 37862385 PMCID: PMC10614836 DOI: 10.1073/pnas.2303703120] [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: 03/05/2023] [Accepted: 09/03/2023] [Indexed: 10/22/2023] Open
Abstract
The family of GalNAc-Ts (GalNAcpolypeptide:N-Acetylgalactosaminyl transferases) catalyzes the first committed step in the synthesis of O-glycans, which is an abundant and biologically important protein modification. Abnormalities in the activity of individual GalNAc-Ts can result in congenital disorders of O-glycosylation (CDG) and influence a broad array of biological functions. How site-specific O-glycans regulate biology is unclear. Compiling in vivo O-glycosites would be an invaluable step in determining the function of site-specific O-glycans. We integrated chemical and enzymatic conditions that cleave O-glycosites, a higher-energy dissociation product ions-triggered electron-transfer/higher-energy collision dissociation mass spectrometry (MS) workflow and software to study nine mouse tissues and whole blood. We identified 2,154 O-glycosites from 595 glycoproteins. The O-glycosites and glycoproteins displayed consensus motifs and shared functions as classified by Gene Ontology terms. Limited overlap of O-glycosites was observed with protein O-GlcNAcylation and phosphorylation sites. Quantitative glycoproteomics and proteomics revealed a tissue-specific regulation of O-glycosites that the differential expression of Galnt isoenzymes in tissues partly contributes to. We examined the Galnt2-null mouse model, which phenocopies congenital disorder of glycosylation involving GALNT2 and revealed a network of glycoproteins that lack GalNAc-T2-specific O-glycans. The known direct and indirect functions of these glycoproteins appear consistent with the complex metabolic phenotypes observed in the Galnt2-null animals. Through this study and interrogation of databases and the literature, we have compiled an atlas of experimentally identified mouse O-glycosites consisting of 2,925 O-glycosites from 758 glycoproteins.
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Affiliation(s)
- Weiming Yang
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - E. Tian
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Aliona Chernish
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Peggy McCluggage
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Kruti Dalal
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Alexander Lara
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Kelly G. Ten Hagen
- Developmental Glycobiology Section, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
| | - Lawrence A. Tabak
- Section on Biological Chemistry, National Institute of Dental and Craniofacial Research (NIDCR), NIH, Bethesda, MD20892
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Chen R, Fulton KM, Tran A, Duque D, Kovalchik K, Caron E, Twine SM, Li J. Integrated Immunopeptidomics and Proteomics Study of SARS-CoV-2-Infected Calu-3 Cells Reveals Dynamic Changes in Allele-specific HLA Abundance and Antigen Presentation. Mol Cell Proteomics 2023; 22:100645. [PMID: 37709257 PMCID: PMC10580047 DOI: 10.1016/j.mcpro.2023.100645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 08/29/2023] [Accepted: 09/11/2023] [Indexed: 09/16/2023] Open
Abstract
We present an integrated immunopeptidomics and proteomics study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection to comprehensively decipher the changes in host cells in response to viral infection. Immunopeptidomics analysis identified viral antigens presented by host cells through both class I and class II MHC system for recognition by the adaptive immune system. The host proteome changes were characterized by quantitative proteomics and glycoproteomics and from these data, the activation of toll-like receptor 3-interferon pathway was identified. Glycosylation analysis of human leukocyte antigen (HLA) proteins from the elution and flow-through of immunoprecipitation revealed that SARS-CoV-2 infection changed the glycosylation pattern of certain HLA alleles with different HLA alleles, showing distinct dynamic changes in relative abundance. The difference in the glycosylation and abundance of HLA alleles changed the number of strong binding antigens each allele presented, suggesting the impact of SARS-CoV-2 infection on antigen presentation is allele-specific. These results could be further exploited to explain the imbalanced response from innate and adaptive immune system in coronavirus disease 2019 cases, which would be helpful for the development of therapeutics and vaccine for coronavirus disease 2019 and preparation for future pandemic.
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Affiliation(s)
- Rui Chen
- Human Health Therapeutics Research Centre, National Research Council Canada, Ottawa, Ontario, Canada.
| | - Kelly M Fulton
- Human Health Therapeutics Research Centre, National Research Council Canada, Ottawa, Ontario, Canada
| | - Anh Tran
- Human Health Therapeutics Research Centre, National Research Council Canada, Ottawa, Ontario, Canada
| | - Diana Duque
- Human Health Therapeutics Research Centre, National Research Council Canada, Ottawa, Ontario, Canada
| | - Kevin Kovalchik
- CHU Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Etienne Caron
- CHU Sainte-Justine Research Center, Montreal, Quebec, Canada; Department of Pathology and Cellular Biology, Faculty of Medicine, Université de Montréal, Quebec, Canada
| | - Susan M Twine
- Human Health Therapeutics Research Centre, National Research Council Canada, Ottawa, Ontario, Canada
| | - Jianjun Li
- Human Health Therapeutics Research Centre, National Research Council Canada, Ottawa, Ontario, Canada.
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Liu J, Cheng B, Fan X, Zhou X, Wang J, Zhou W, Li H, Zeng W, Yang P, Chen X. Click-iG: Simultaneous Enrichment and Profiling of Intact N-linked, O-GalNAc, and O-GlcNAcylated Glycopeptides. Angew Chem Int Ed Engl 2023; 62:e202303410. [PMID: 37431278 DOI: 10.1002/anie.202303410] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 07/08/2023] [Accepted: 07/10/2023] [Indexed: 07/12/2023]
Abstract
Proteins are ubiquitously modified with glycans of varied chemical structures through distinct glycosidic linkages, making the landscape of protein glycosylation challenging to map. Profiling of intact glycopeptides with mass spectrometry (MS) has recently emerged as a powerful tool for revealing matched information of the glycosylation sites and attached glycans (i.e., intact glycosites), but is largely limited to individual glycosylation types. Herein, we describe Click-iG, which integrates metabolic labeling of glycans with clickable unnatural sugars, an optimized MS method, and a tailored version of pGlyco3 software to enable simultaneous enrichment and profiling of three types of intact glycopeptides: N-linked, mucin-type O-linked, and O-GlcNAcylated glycopeptides. We demonstrate the utility of Click-iG by the identification of thousands of intact glycosites in cell lines and living mice. From the mouse lung, heart, and spleen, a total of 2053 intact N-glycosites, 262 intact O-GalNAc glycosites, and 1947 O-GlcNAcylation sites were identified. Click-iG-enabled comprehensive coverage of the protein glycosylation landscape lays the foundation for interrogating crosstalk between different glycosylation pathways.
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Affiliation(s)
- Jialin Liu
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
- Institute of Biomedical Sciences and Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Bo Cheng
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Xinqi Fan
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Xinyue Zhou
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Jiankun Wang
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Wen Zhou
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Hengyu Li
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
| | - Wenfeng Zeng
- Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) and Institute of Computing Technology, CAS, Beijing, 100190, China
| | - Pengyuan Yang
- Institute of Biomedical Sciences and Department of Chemistry, Fudan University, Shanghai, 200433, China
| | - Xing Chen
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking-Tsinghua Center for Life Sciences, Synthetic and Functional Biomolecules Center, and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, 100871, China
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35
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Li Y, Guo W, Zhang Q, Yang B, Zhang Y, Yang Y, Liu G, Pan L, Zhang W, Kong D. Improved analysis ZIC-HILIC-HCD-Orbitrap method for mapping the glycopeptide by mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2023; 1228:123852. [PMID: 37633008 DOI: 10.1016/j.jchromb.2023.123852] [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: 05/29/2023] [Revised: 07/29/2023] [Accepted: 08/15/2023] [Indexed: 08/28/2023]
Abstract
Glycosylation is one of the most common post-translational modifications (PTMs). Protein glycosylation analysis is the bottleneck to deeply understand their functions. At present, the LC-MS analysis of glycosylated post-translational modification is mainly focused on the analysis of glycopeptides. However, the factors affecting the identification of glycopeptides were not fully elucidated. In the paper, we have carefully studied the factors, e.g., HILIC materials, search engines, protein amount, gradient duration, extraction solution, etc. According to the results, HILIC materials were the most important factors affecting the glycopeptides identification, and the amphoteric sulfoalkyl betaine stationary phase enriched glycopeptides 6-fold more compared to the amphiphilic ion-bonded fully porous spherical silica stationary phase. We explored the influence of the extraction solutions on glycan identification. Comparing sodium dodecyl sulfate (SDS) and urea (UA), the results showed that N-glycolylneuraminic acid (NeuGc) type of glycan content was found to be increased 1.4-fold in the SDS compared to UA. Besides, we explored the influence of the search engine on glycopeptide identification. Comparing pGlyco3.0 and MSFragger-Glyco, it was observed that pGlyco3.0 outperformed MSFragger-Glyco in identifying glycopeptides. Then, using our optimized method we found that there was a significant difference in the distribution of monosaccharide types in plasma and brain tissue, e.g., the content of NeuAc in brain was 5-fold higher than that in plasma. To importantly, two glycoproteins (Neurexin-2 and SUN domain-containing protein 2) were also found for the first time by our method. In summary, we have comprehensively studied the factors influencing glycopeptide identification than any previous research, and the optimized method could be widely used for identifying the glycoproteins or glycolpeptides biomarkers for disease detection and therapeutic targets.
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Affiliation(s)
- Yahui Li
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Wenyan Guo
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Qingning Zhang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Bingkun Yang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China; School of Pharmacy, Hebei Medical University, Shijiazhuang, China
| | - Yuyu Zhang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Yi Yang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China; The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Guangyuan Liu
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Liangyu Pan
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China
| | - Wei Zhang
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China.
| | - Dezhi Kong
- Department of Pharmacology of Chinese Materia Medica, Institution of Chinese Integrative Medicine, School of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, China.
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36
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Kong L, Li F, Fang W, Du Z, Wang G, Zhang Y, Ge WP, Zhang W, Qin W. Sensitive N-Glycopeptide Profiling of Single and Rare Cells Using an Isobaric Labeling Strategy without Enrichment. Anal Chem 2023; 95:11326-11334. [PMID: 37409763 DOI: 10.1021/acs.analchem.3c01392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
Single-cell omics is critical in revealing population heterogeneity, discovering unique features of individual cells, and identifying minority subpopulations of interest. As one of the major post-translational modifications, protein N-glycosylation plays crucial roles in various important biological processes. Elucidation of the variation in N-glycosylation patterns at single-cell resolution may largely facilitate the understanding of their key roles in the tumor microenvironment and immune therapy. However, comprehensive N-glycoproteome profiling for single cells has not been achieved due to the extremely limited sample amount and incompatibility with the available enrichment strategies. Here, we have developed an isobaric labeling-based carrier strategy for highly sensitive intact N-glycopeptide profiling for single cells or a small number of rare cells without enrichment. Isobaric labeling has unique multiplexing properties, by which the "total" signal from all channels triggers MS/MS fragmentation for N-glycopeptide identification, while the reporter ions provide quantitative information. In our strategy, a carrier channel using N-glycopeptides obtained from bulk-cell samples significantly improved the "total" signal of N-glycopeptides and, therefore, promoted the first quantitative analysis of averagely 260 N-glycopeptides from single HeLa cells. We further applied this strategy to study the regional heterogeneity of N-glycosylation of microglia in mouse brain and discovered region-specific N-glycoproteome patterns and cell subtypes. In conclusion, the glycocarrier strategy provides an attractive solution for sensitive and quantitative N-glycopeptide profiling of single/rare cells that cannot be enriched by traditional workflows.
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Affiliation(s)
- Linlin Kong
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Fengzhi Li
- Chinese Institute for Brain Research, Beijing, Beijing 102206, China
| | - Wei Fang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Zhuokun Du
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Guibin Wang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Yangjun Zhang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Woo-Ping Ge
- Chinese Institute for Brain Research, Beijing, Beijing 102206, China
| | - Wanjun Zhang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
- College of Chemistry and Materials Science, Hebei University, Baoding 071002, China
| | - Weijie Qin
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
- College of Chemistry and Materials Science, Hebei University, Baoding 071002, China
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37
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Yang KL, Yu F, Teo GC, Li K, Demichev V, Ralser M, Nesvizhskii AI. MSBooster: improving peptide identification rates using deep learning-based features. Nat Commun 2023; 14:4539. [PMID: 37500632 PMCID: PMC10374903 DOI: 10.1038/s41467-023-40129-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 07/06/2023] [Indexed: 07/29/2023] Open
Abstract
Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.
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Affiliation(s)
- Kevin L Yang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Kai Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Vadim Demichev
- Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Markus Ralser
- Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany
- Nuffield Department of Medicine, The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
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38
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Geiszler DJ, Polasky DA, Yu F, Nesvizhskii AI. Detecting diagnostic features in MS/MS spectra of post-translationally modified peptides. Nat Commun 2023; 14:4132. [PMID: 37438360 DOI: 10.1038/s41467-023-39828-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 06/23/2023] [Indexed: 07/14/2023] Open
Abstract
Post-translational modifications are an area of great interest in mass spectrometry-based proteomics, with a surge in methods to detect them in recent years. However, post-translational modifications can introduce complexity into proteomics searches by fragmenting in unexpected ways, ultimately hindering the detection of modified peptides. To address these deficiencies, we present a fully automated method to find diagnostic spectral features for any modification. The features can be incorporated into proteomics search engines to improve modified peptide recovery and localization. We show the utility of this approach by interrogating fragmentation patterns for a cysteine-reactive chemoproteomic probe, RNA-crosslinked peptides, sialic acid-containing glycopeptides, and ADP-ribosylated peptides. We also analyze the interactions between a diagnostic ion's intensity and its statistical properties. This method has been incorporated into the open-search annotation tool PTM-Shepherd and the FragPipe computational platform.
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Affiliation(s)
- Daniel J Geiszler
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
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39
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Campos D, Girgis M, Yang Q, Zong G, Goldman R, Wang LX, Sanda M. "Ghost" Fragment Ions in Structure and Site-Specific Glycoproteomics Analysis. Anal Chem 2023; 95:10145-10148. [PMID: 37382290 PMCID: PMC10339278 DOI: 10.1021/acs.analchem.3c02207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 06/26/2023] [Indexed: 06/30/2023]
Abstract
Mass spectrometry (MS) can unlock crucial insights into the intricate world of glycosylation analysis. Despite its immense potential, the qualitative and quantitative analysis of isobaric glycopeptide structures remains one of the most daunting hurdles in the field of glycoproteomics. The ability to distinguish between these complex glycan structures poses a significant challenge, hindering our ability to accurately measure and understand the role of glycoproteins in biological systems. A few recent publications described the use of collision energy (CE) modulation to improve structural elucidation, especially for qualitative purposes. Different linkages of glycan units usually demonstrate different stabilities under CID/HCD fragmentation conditions. Fragmentation of the glycan moiety produces low molecular weight ions (oxonium ions) that can serve as a structure-specific signature for specific glycan moieties; however, the specificity of these fragments has never been examined closely. Here, we particularly focused on N-glycoproteomics analysis and investigated fragmentation specificity using synthetic stable isotope-labeled N-glycopeptide standards. These standards were isotopically labeled at the reducing terminal GlcNAc, which allowed us to resolve fragments produced by the oligomannose core moiety and fragments generated from outer antennary structures. Our research identified the potential for false-positive structure assignments due to the occurrence of "Ghost" fragments resulting from single glyco unit rearrangement or mannose core fragmentation within the collision cell. To mitigate this issue, we have established a minimal intensity threshold for these fragments to prevent misidentification of structure-specific fragments in glycoproteomics analysis. Our findings provide a crucial step forward in the quest for more accurate and reliable glycoproteomics measurements.
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Affiliation(s)
- Diana Campos
- Max-Planck-Institut
fuer Herz- und Lungenforschung, Ludwigstrasse 43, 61231 Bad Nauheim, Germany
| | - Michael Girgis
- Department
of Bioengineering, College of Engineering and Computing, George Mason University, Fairfax, Virginia 22030, United States
| | - Qiang Yang
- GlycoT
Therapeutics, College Park, Maryland 20742, United States
| | - Guanghui Zong
- Department
of Chemistry and Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - Radoslav Goldman
- Department
of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, D.C. 20057, United States
- Clinical
and Translational Glycoscience Research Center, Georgetown University, Washington, D.C. 20057, United States
| | - Lai-Xi Wang
- Department
of Chemistry and Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - Miloslav Sanda
- Max-Planck-Institut
fuer Herz- und Lungenforschung, Ludwigstrasse 43, 61231 Bad Nauheim, Germany
- Department
of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, D.C. 20057, United States
- Clinical
and Translational Glycoscience Research Center, Georgetown University, Washington, D.C. 20057, United States
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40
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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: 0] [Impact Index Per Article: 0] [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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41
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Xu S, Wu R. Glycobiology and proteomics: has mass spectrometry moved the field forward? Expert Rev Proteomics 2023; 20:303-307. [PMID: 37667879 PMCID: PMC10841282 DOI: 10.1080/14789450.2023.2255748] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 07/26/2023] [Indexed: 09/06/2023]
Affiliation(s)
- Senhan Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Ronghu Wu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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42
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Rodríguez EP, Li Y, Vaniya A, Shih PM, Fiehn O. Alternative Identification of Glycosides Using MS/MS Matching with an In Silico-Modified Aglycone Mass Spectra Library. Anal Chem 2023. [PMID: 37390485 DOI: 10.1021/acs.analchem.3c00957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2023]
Abstract
Glycosylation of metabolites serves multiple purposes. Adding sugars makes metabolites more water soluble and improves their biodistribution, stability, and detoxification. In plants, the increase in melting points enables storing otherwise volatile compounds that are released by hydrolysis when needed. Classically, glycosylated metabolites were identified by mass spectrometry (MS/MS) using [M-sugar] neutral losses. Herein, we studied 71 pairs of glycosides with their respective aglycones, including hexose, pentose, and glucuronide moieties. Using liquid chromatography (LC) coupled to electrospray ionization high-resolution mass spectrometry, we detected the classic [M-sugar] product ions for only 68% of glycosides. Instead, we found that most aglycone MS/MS product ions were conserved in the MS/MS spectra of their corresponding glycosides, even when no [M-sugar] neutral losses were observed. We added pentose and hexose units to the precursor masses of an MS/MS library of 3057 aglycones to enable rapid identification of glycosylated natural products with standard MS/MS search algorithms. When searching unknown compounds in untargeted LC-MS/MS metabolomics data of chocolate and tea, we structurally annotated 108 novel glycosides in standard MS-DIAL data processing. We uploaded this new in silico-glycosylated product MS/MS library to GitHub to enable users to detect natural product glycosides without authentic chemical standards.
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Affiliation(s)
- Elys P Rodríguez
- Department of Chemistry, University of California Davis, Davis, California 95616, United States
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
| | - Yuanyue Li
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
| | - Arpana Vaniya
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
| | - Patrick M Shih
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, California 94720, United States
- Feedstocks Division, Joint BioEnergy Institute, Emeryville, California 94608, United States
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 97420, United States
- Innovative Genomics Institute, University of California Berkeley, Berkeley, California 94720, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
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43
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Bedran G, Polasky DA, Hsiao Y, Yu F, da Veiga Leprevost F, Alfaro JA, Cieslik M, Nesvizhskii AI. Unraveling the glycosylated immunopeptidome with HLA-Glyco. Nat Commun 2023; 14:3461. [PMID: 37308510 PMCID: PMC10258777 DOI: 10.1038/s41467-023-39270-2] [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: 11/07/2022] [Accepted: 06/02/2023] [Indexed: 06/14/2023] Open
Abstract
Recent interest in targeted therapies has been sparked by the study of MHC-associated peptides (MAPs) that undergo post-translational modifications (PTMs), particularly glycosylation. In this study, we introduce a fast computational workflow that merges the MSFragger-Glyco search algorithm with a false discovery rate control for glycopeptide analysis from mass spectrometry-based immunopeptidome data. By analyzing eight large-scale publicly available studies, we find that glycosylated MAPs are predominantly presented by MHC class II. Here, we present HLA-Glyco, a comprehensive resource containing over 3,400 human leukocyte antigen (HLA) class II N-glycopeptides from 1,049 distinct protein glycosylation sites. This resource provides valuable insights, including high levels of truncated glycans, conserved HLA-binding cores, and differences in glycosylation positional specificity between HLA allele groups. We integrate the workflow within the FragPipe computational platform and provide HLA-Glyco as a free web resource. Overall, our work provides a valuable tool and resource to aid the nascent field of glyco-immunopeptidomics.
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Affiliation(s)
- Georges Bedran
- International Centre for Cancer Vaccine Science, University of Gdansk, Gdansk, Poland
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Yi Hsiao
- Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | | | - Javier A Alfaro
- International Centre for Cancer Vaccine Science, University of Gdansk, Gdansk, Poland
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - Marcin Cieslik
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
- Michigan Center for Translational Pathology, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA.
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44
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Ramírez CR, Espino JA, Jones LM, Polasky DA, Nesvizhskii AI. Efficient Analysis of Proteome-wide FPOP Data by FragPipe. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.01.543263. [PMID: 37333157 PMCID: PMC10274679 DOI: 10.1101/2023.06.01.543263] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Monitoring protein structure before and after perturbations can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP datasets. Our workflow combines the speed of MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 50% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.
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Affiliation(s)
| | - Jessica Arlett Espino
- Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland 21202, USA
| | - Lisa M Jones
- Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland 21202, USA
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
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45
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Larsen ISB, Povolo L, Zhou L, Tian W, Mygind KJ, Hintze J, Jiang C, Hartill V, Prescott K, Johnson CA, Mullegama SV, McConkie-Rosell A, McDonald M, Hansen L, Vakhrushev SY, Schjoldager KT, Clausen H, Worzfeld T, Joshi HJ, Halim A. The SHDRA syndrome-associated gene TMEM260 encodes a protein-specific O-mannosyltransferase. Proc Natl Acad Sci U S A 2023; 120:e2302584120. [PMID: 37186866 PMCID: PMC10214176 DOI: 10.1073/pnas.2302584120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 04/21/2023] [Indexed: 05/17/2023] Open
Abstract
Mutations in the TMEM260 gene cause structural heart defects and renal anomalies syndrome, but the function of the encoded protein remains unknown. We previously reported wide occurrence of O-mannose glycans on extracellular immunoglobulin, plexin, transcription factor (IPT) domains found in the hepatocyte growth factor receptor (cMET), macrophage-stimulating protein receptor (RON), and plexin receptors, and further demonstrated that two known protein O-mannosylation systems orchestrated by the POMT1/2 and transmembrane and tetratricopeptide repeat-containing proteins 1-4 gene families were not required for glycosylation of these IPT domains. Here, we report that the TMEM260 gene encodes an ER-located protein O-mannosyltransferase that selectively glycosylates IPT domains. We demonstrate that disease-causing TMEM260 mutations impair O-mannosylation of IPT domains and that TMEM260 knockout in cells results in receptor maturation defects and abnormal growth of 3D cell models. Thus, our study identifies the third protein-specific O-mannosylation pathway in mammals and demonstrates that O-mannosylation of IPT domains serves critical functions during epithelial morphogenesis. Our findings add a new glycosylation pathway and gene to a growing group of congenital disorders of glycosylation.
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Affiliation(s)
- Ida Signe Bohse Larsen
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Lorenzo Povolo
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Luping Zhou
- Faculty of Medicine, Institute of Pharmacology, University of Marburg, 35043Marburg, Germany
| | - Weihua Tian
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Kasper Johansen Mygind
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - John Hintze
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Chen Jiang
- Faculty of Medicine, Institute of Pharmacology, University of Marburg, 35043Marburg, Germany
| | - Verity Hartill
- Leeds Institute of Medical Research, University of Leeds, St James’ University Hospital, LeedsLS2 9JT, United Kingdom
- Yorkshire Regional Genetics Service, Chapel Allerton Hospital, LeedsLS7 4SA, United Kingdom
| | - Katrina Prescott
- Yorkshire Regional Genetics Service, Chapel Allerton Hospital, LeedsLS7 4SA, United Kingdom
| | - Colin A. Johnson
- Leeds Institute of Medical Research, University of Leeds, St James’ University Hospital, LeedsLS2 9JT, United Kingdom
| | | | - Allyn McConkie-Rosell
- Division of Medical Genetics, Department of Pediatrics, Duke University Medical Center, Durham, NC27710
| | - Marie McDonald
- Division of Medical Genetics, Department of Pediatrics, Duke University Medical Center, Durham, NC27710
| | - Lars Hansen
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Sergey Y. Vakhrushev
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Katrine T. Schjoldager
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Henrik Clausen
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Thomas Worzfeld
- Faculty of Medicine, Institute of Pharmacology, University of Marburg, 35043Marburg, Germany
- Max-Planck-Institute for Heart and Lung Research, 61231Bad Nauheim, Germany
| | - Hiren J. Joshi
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
| | - Adnan Halim
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200Copenhagen N, Denmark
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46
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Campos D, Girgis M, Yang Q, Zong G, Goldman R, Wang LX, Sanda M. "Ghost" fragment ions in structure and site-specific glycoproteomics analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.17.541150. [PMID: 37292769 PMCID: PMC10245710 DOI: 10.1101/2023.05.17.541150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Mass spectrometry (MS) can unlock crucial insights into the intricate world of glycosylation analysis. Despite its immense potential, the qualitative and quantitative analysis of isobaric glycopeptide structures remains one of the most daunting hurdles in the field of glycoproteomics. The ability to distinguish between these complex glycan structures poses a significant challenge, hindering our ability to accurately measure and understand the role of glycoproteins in biological systems. A few recent publications described the use of collision energy (CE) modulation to improve structural elucidation, especially for qualitative purposes. Different linkages of glycan units usually demonstrate different stabilities under CID/HCD fragmentation conditions. Fragmentation of the glycan moiety produces low molecular weight ions (oxonium ions) that can serve as a structure-specific signature for specific glycan moieties, however, specificity of these fragments has never been examined closely. Here, we investigated fragmentation specificity using synthetic stable isotope-labelled glycopeptide standards. These standards were isotopically labelled at the reducing terminal GlcNAc, which allowed us to resolve fragments produced by oligomannose core moiety and fragments generated from outer antennary structures. Our research identified the potential for false positive structure assignments due to the occurrence of "Ghost" fragments resulting from single glyco unit rearrangement or mannose core fragmentation within the collision cell. To mitigate this issue, we have established a minimal intensity threshold for these fragments to prevent the misidentification of structure-specific fragments in glycoproteomics analysis. Our findings provide a crucial step forward in the quest for more accurate and reliable glycoproteomics measurements. Graphical abstract
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47
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Toul M, Slonkova V, Mican J, Urminsky A, Tomkova M, Sedlak E, Bednar D, Damborsky J, Hernychova L, Prokop Z. Identification, characterization, and engineering of glycosylation in thrombolyticsa. Biotechnol Adv 2023; 66:108174. [PMID: 37182613 DOI: 10.1016/j.biotechadv.2023.108174] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/09/2023] [Accepted: 05/09/2023] [Indexed: 05/16/2023]
Abstract
Cardiovascular diseases, such as myocardial infarction, ischemic stroke, and pulmonary embolism, are the most common causes of disability and death worldwide. Blood clot hydrolysis by thrombolytic enzymes and thrombectomy are key clinical interventions. The most widely used thrombolytic enzyme is alteplase, which has been used in clinical practice since 1986. Another clinically used thrombolytic protein is tenecteplase, which has modified epitopes and engineered glycosylation sites, suggesting that carbohydrate modification in thrombolytic enzymes is a viable strategy for their improvement. This comprehensive review summarizes current knowledge on computational and experimental identification of glycosylation sites and glycan identity, together with methods used for their reengineering. Practical examples from previous studies focus on modification of glycosylations in thrombolytics, e.g., alteplase, tenecteplase, reteplase, urokinase, saruplase, and desmoteplase. Collected clinical data on these glycoproteins demonstrate the great potential of this engineering strategy. Outstanding combinatorics originating from multiple glycosylation sites and the vast variety of covalently attached glycan species can be addressed by directed evolution or rational design. Directed evolution pipelines would benefit from more efficient cell-free expression and high-throughput screening assays, while rational design must employ structure prediction by machine learning and in silico characterization by supercomputing. Perspectives on challenges and opportunities for improvement of thrombolytic enzymes by engineering and evolution of protein glycosylation are provided.
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Affiliation(s)
- Martin Toul
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Veronika Slonkova
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Jan Mican
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Adam Urminsky
- Research Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Zluty kopec 7, 656 53 Brno, Czech Republic
| | - Maria Tomkova
- Center for Interdisciplinary Biosciences, P. J. Safarik University in Kosice, Jesenna 5, 04154 Kosice, Slovakia
| | - Erik Sedlak
- Center for Interdisciplinary Biosciences, P. J. Safarik University in Kosice, Jesenna 5, 04154 Kosice, Slovakia
| | - David Bednar
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Jiri Damborsky
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Lenka Hernychova
- Research Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Zluty kopec 7, 656 53 Brno, Czech Republic.
| | - Zbynek Prokop
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/C13, 625 00 Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91 Brno, Czech Republic.
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48
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Li X, Du Y, Chen X, Liu C. Emerging roles of O-glycosylation in regulating protein aggregation, phase separation, and functions. Curr Opin Chem Biol 2023; 75:102314. [PMID: 37156204 DOI: 10.1016/j.cbpa.2023.102314] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/28/2023] [Accepted: 04/02/2023] [Indexed: 05/10/2023]
Abstract
Protein O-glycosylation is widely identified in various proteins involved in diverse biological processes. Recent studies have demonstrated that O-glycosylation plays crucial and multifaceted roles in modulating protein amyloid aggregation and liquid-liquid phase separation (LLPS) under physiological conditions. Dysregulation of these processes is closely associated with human diseases such as neurodegenerative diseases (NDs) and cancers. In this review, we first summarize the distinct roles of O-glycosylation in regulating pathological aggregation of different amyloid proteins related to NDs and elaborate the underlying mechanisms of how O-glycosylation modulates protein aggregation kinetics, induces new aggregated structures, and mediates the pathogenesis of amyloid aggregates under diseased conditions. Furthermore, we introduce recent discoveries on O-GlcNAc-mediated regulation of synaptic LLPS and phase separation potency of low-complexity domain-enriched proteins. Finally, we identify challenges in future research and highlight the potential for developing new therapeutic strategies of NDs by targeting protein O-glycosylation.
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Affiliation(s)
- Xiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yifei Du
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China; Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xing Chen
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China; Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China; Synthetic and Functional Biomolecules Center, Peking University, Beijing, China; Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, China.
| | - Cong Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China; State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China.
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Polasky DA, Geiszler DJ, Yu F, Li K, Teo GC, Nesvizhskii AI. MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics. Mol Cell Proteomics 2023; 22:100538. [PMID: 37004988 PMCID: PMC10182319 DOI: 10.1016/j.mcpro.2023.100538] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 03/24/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
Posttranslational modifications of proteins play essential roles in defining and regulating the functions of the proteins they decorate, making identification of these modifications critical to understanding biology and disease. Methods for enriching and analyzing a wide variety of biological and chemical modifications of proteins have been developed using mass spectrometry-based proteomics, largely relying on traditional database search methods to identify the resulting mass spectra of modified peptides. These database search methods treat modifications as static attachments of a mass to particular position in the peptide sequence, but many modifications undergo fragmentation in tandem mass spectrometry experiments alongside, or instead of, the peptide backbone. While this fragmentation can confound traditional search methods, it also offers unique opportunities for improved searches that incorporate modification-specific fragment ions. Here, we present a new labile mode in the MSFragger search engine that provides the flexibility to tailor modification-centric searches to the fragmentation observed. We show that labile mode can dramatically improve spectrum identification rates of phosphopeptides, RNA-crosslinked peptides, and ADP-ribosylated peptides. Each of these modifications presents distinct fragmentation characteristics, showcasing the flexibility of MSFragger labile mode to improve search for a wide variety of biological and chemical modifications.
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Affiliation(s)
- Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
| | - Daniel J Geiszler
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Kai Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
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Xu Z, Liu Y, He S, Sun R, Zhu C, Li S, Hai S, Luo Y, Zhao Y, Dai L. Integrative Proteomics and N-Glycoproteomics Analyses of Rheumatoid Arthritis Synovium Reveal Immune-Associated Glycopeptides. Mol Cell Proteomics 2023; 22:100540. [PMID: 37019382 PMCID: PMC10176071 DOI: 10.1016/j.mcpro.2023.100540] [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: 10/20/2022] [Revised: 03/10/2023] [Accepted: 03/30/2023] [Indexed: 04/05/2023] Open
Abstract
Rheumatoid arthritis (RA) is a typical autoimmune disease characterized by synovial inflammation, synovial tissue hyperplasia, and destruction of bone and cartilage. Protein glycosylation plays key roles in the pathogenesis of RA but in-depth glycoproteomics analysis of synovial tissues is still lacking. Here, by using a strategy to quantify intact N-glycopeptides, we identified 1260 intact N-glycopeptides from 481 N-glycosites on 334 glycoproteins in RA synovium. Bioinformatics analysis revealed that the hyper-glycosylated proteins in RA were closely linked to immune responses. By using DNASTAR software, we identified 20 N-glycopeptides whose prototype peptides were highly immunogenic. We next calculated the enrichment scores of nine types of immune cells using specific gene sets from public single-cell transcriptomics data of RA and revealed that the N-glycosylation levels at some sites, such as IGSF10_N2147, MOXD2P_N404, and PTCH2_N812, were significantly correlated with the enrichment scores of certain immune cell types. Furthermore, we showed that aberrant N-glycosylation in the RA synovium was related to increased expression of glycosylation enzymes. Collectively, this work presents, for the first time, the N-glycoproteome of RA synovium and describes immune-associated glycosylation, providing novel insights into RA pathogenesis.
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Affiliation(s)
- Zhiqiang Xu
- National Clinical Research Center for Geriatrics and Department of General Practice, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Yi Liu
- Department of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China
| | - Siyu He
- National Clinical Research Center for Geriatrics and Department of General Practice, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Rui Sun
- Department of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China
| | - Chenxi Zhu
- Department of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China
| | - Shuangqing Li
- National Clinical Research Center for Geriatrics and Department of General Practice, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Shan Hai
- National Clinical Research Center for Geriatrics and Department of General Practice, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Yubin Luo
- Department of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Zhao
- Department of Rheumatology and Immunology, West China Hospital, Sichuan University, Chengdu, China.
| | - Lunzhi Dai
- National Clinical Research Center for Geriatrics and Department of General Practice, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center of Biotherapy, Chengdu, China.
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