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Martinez K, Agirre J, Akune Y, Aoki-Kinoshita KF, Arighi C, Axelsen KB, Bolton E, Bordeleau E, Edwards NJ, Fadda E, Feizi T, Hayes C, Ives CM, Joshi HJ, Krishna Prasad K, Kossida S, Lisacek F, Liu Y, Lütteke T, Ma J, Malik A, Martin M, Mehta AY, Neelamegham S, Panneerselvam K, Ranzinger R, Ricard-Blum S, Sanou G, Shanker V, Thomas PD, Tiemeyer M, Urban J, Vita R, Vora J, Yamamoto Y, Mazumder R. Functional implications of glycans and their curation: insights from the workshop held at the 16th Annual International Biocuration Conference in Padua, Italy. Database (Oxford) 2024; 2024:baae073. [PMID: 39137905 PMCID: PMC11321244 DOI: 10.1093/database/baae073] [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: 04/01/2024] [Revised: 06/24/2024] [Accepted: 07/10/2024] [Indexed: 08/15/2024]
Abstract
Dynamic changes in protein glycosylation impact human health and disease progression. However, current resources that capture disease and phenotype information focus primarily on the macromolecules within the central dogma of molecular biology (DNA, RNA, proteins). To gain a better understanding of organisms, there is a need to capture the functional impact of glycans and glycosylation on biological processes. A workshop titled "Functional impact of glycans and their curation" was held in conjunction with the 16th Annual International Biocuration Conference to discuss ongoing worldwide activities related to glycan function curation. This workshop brought together subject matter experts, tool developers, and biocurators from over 20 projects and bioinformatics resources. Participants discussed four key topics for each of their resources: (i) how they curate glycan function-related data from publications and other sources, (ii) what type of data they would like to acquire, (iii) what data they currently have, and (iv) what standards they use. Their answers contributed input that provided a comprehensive overview of state-of-the-art glycan function curation and annotations. This report summarizes the outcome of discussions, including potential solutions and areas where curators, data wranglers, and text mining experts can collaborate to address current gaps in glycan and glycosylation annotations, leveraging each other's work to improve their respective resources and encourage impactful data sharing among resources. Database URL: https://wiki.glygen.org/Glycan_Function_Workshop_2023.
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Affiliation(s)
- Karina Martinez
- Department of Biochemistry & Molecular Medicine, The George Washington University School of Medicine and Health Sciences, 2300 I St. NW, Washington, DC 20052, United States
| | - Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, Wentworth Way, York YO10 5DD, United Kingdom
| | - Yukie Akune
- The Glycosciences Laboratory, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, United Kingdom
| | - Kiyoko F Aoki-Kinoshita
- Glycan and Life Systems Integration Center (GaLSIC), Soka University, 1-236 Tangi-machi, Hachioji, Tokyo 192-8577, Japan
| | - Cecilia Arighi
- Department of Computer and Information Sciences, University of Delaware, 18 Amstel Ave, Newark, DE 19716, United States
| | - Kristian B Axelsen
- Swiss-Prot Group, Swiss Institute of Bioinformatics (SIB), CMU, 1 rue Michel Servet, Geneva 4 1211, Switzerland
| | - Evan Bolton
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, United States
| | - Emily Bordeleau
- Michael Smith Laboratories, The University of British Columbia, 2185 East Mall, Vancouver, British Columbia V6T 1Z4, Canada
| | - Nathan J Edwards
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, 2115 Wisconsin Ave NW, Washington, DC 20007, United States
| | - Elisa Fadda
- Department of Chemistry and Hamilton Institute, Maynooth University, Kilcock Road, Maynooth, Co. Kildare W23 AH3Y, Ireland
| | - Ten Feizi
- The Glycosciences Laboratory, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, United Kingdom
| | - Catherine Hayes
- Proteome Informatics Group, Swiss Institute of Bioinformatics (SIB), route de Drize 7, Geneva CH-1227, Switzerland
| | - Callum M Ives
- Department of Chemistry and Hamilton Institute, Maynooth University, Kilcock Road, Maynooth, Co. Kildare W23 AH3Y, Ireland
| | - Hiren J Joshi
- Copenhagen Center for Glycomics, Department of Cellular and Molecular Medicine, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, Copenhagen DK-2200, Denmark
| | - Khakurel Krishna Prasad
- ELI Beamlines Facility, The Extreme Light Infrastructure ERIC, Za Radnicí 835, Dolní Břežany 25241, Czech Republic
| | - Sofia Kossida
- IMGT, The International ImMunoGeneTics Information System, National Center for Scientific Research (CNRS), Institute of Human Genetics (IGH), University of Montpellier (UM), 141 rue de la Cardonille, Montpellier 34 090, France
| | - Frederique Lisacek
- Proteome Informatics Group, Swiss Institute of Bioinformatics (SIB), route de Drize 7, Geneva CH-1227, Switzerland
| | - Yan Liu
- The Glycosciences Laboratory, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, United Kingdom
| | - Thomas Lütteke
- Institute of Veterinary Physiology and Biochemistry, Justus-Liebig-University Gießen, Frankfurter Str. 100, Gießen 35392, Germany
| | - Junfeng Ma
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, 3900 Reservior Road NW, Washington, DC 20007, United States
| | - Adnan Malik
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Maria Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Akul Y Mehta
- Department of Surgery, Beth Israel Deaconess Medical Center, National Center for Functional Glycomics, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, United States
| | - Sriram Neelamegham
- Departments of Chemical & Biological Engineering, Biomedical Engineering and Medicine, University at Buffalo, State University of New York, 906 Furnas Hall, Buffalo, NY 14260, United States
| | - Kalpana Panneerselvam
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - René Ranzinger
- Complex Carbohydrate Research Center, University of Georgia, 315 Riverbend Rd, Athens, GA 30602, United States
| | - Sylvie Ricard-Blum
- Institute of Molecular and Supramolecular Chemistry and Biochemistry (ICBMS), UMR 5246, University Lyon 1, CNRS, 43 Boulevard du 11 novembre 1918, Villeurbanne cedex F-69622, France
| | - Gaoussou Sanou
- IMGT, The International ImMunoGeneTics Information System, National Center for Scientific Research (CNRS), Institute of Human Genetics (IGH), University of Montpellier (UM), 141 rue de la Cardonille, Montpellier 34 090, France
| | - Vijay Shanker
- Department of Computer and Information Sciences, University of Delaware, 18 Amstel Ave, Newark, DE 19716, United States
| | - Paul D Thomas
- Department of Population and Public Health Sciences, University of Southern California, 2001 N Soto Street, Los Angeles, CA 90032, United States
| | - Michael Tiemeyer
- Complex Carbohydrate Research Center, University of Georgia, 315 Riverbend Rd, Athens, GA 30602, United States
| | - James Urban
- Department of Chemistry and Molecular Biology, University of Gothenburg, Medicinaregatan 7 B, Gothenburg 41390, Sweden
| | - Randi Vita
- Immune Epitope Database and Analysis Project, La Jolla Institute for Allergy & Immunology, 9420 Athena Circle, La Jolla, CA 92037, United States
| | - Jeet Vora
- Department of Biochemistry & Molecular Medicine, The George Washington University School of Medicine and Health Sciences, 2300 I St. NW, Washington, DC 20052, United States
| | - Yasunori Yamamoto
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan
| | - Raja Mazumder
- Department of Biochemistry & Molecular Medicine, The George Washington University School of Medicine and Health Sciences, 2300 I St. NW, Washington, DC 20052, United States
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2
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Palomino TV, Muddiman DC. Mass spectrometry imaging of N-linked glycans: Fundamentals and recent advances. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38934211 DOI: 10.1002/mas.21895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 06/06/2024] [Accepted: 06/09/2024] [Indexed: 06/28/2024]
Abstract
With implications in several medical conditions, N-linked glycosylation is one of the most important posttranslation modifications present in all living organisms. Due to their nontemplate synthesis, glycan structures are extraordinarily complex and require multiple analytical techniques for complete structural elucidation. Mass spectrometry is the most common way to investigate N-linked glycans; however, with techniques such as liquid-chromatography mass spectrometry, there is complete loss of spatial information. Mass spectrometry imaging is a transformative analytical technique that can visualize the spatial distribution of ions within a biological sample and has been shown to be a powerful tool to investigate N-linked glycosylation. This review covers the fundamentals of mass spectrometry imaging and N-linked glycosylation and highlights important findings of recent key studies aimed at expanding and improving the glycomics imaging field.
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Affiliation(s)
- Tana V Palomino
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
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Kellman BP, Mariethoz J, Zhang Y, Shaul S, Alteri M, Sandoval D, Jeffris M, Armingol E, Bao B, Lisacek F, Bojar D, Lewis NE. Decoding glycosylation potential from protein structure across human glycoproteins with a multi-view recurrent neural network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.15.594334. [PMID: 38798633 PMCID: PMC11118808 DOI: 10.1101/2024.05.15.594334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Glycosylation is described as a non-templated biosynthesis. Yet, the template-free premise is antithetical to the observation that different N-glycans are consistently placed at specific sites. It has been proposed that glycosite-proximal protein structures could constrain glycosylation and explain the observed microheterogeneity. Using site-specific glycosylation data, we trained a hybrid neural network to parse glycosites (recurrent neural network) and match them to feasible N-glycosylation events (graph neural network). From glycosite-flanking sequences, the algorithm predicts most human N-glycosylation events documented in the GlyConnect database and proposed structures corresponding to observed monosaccharide composition of the glycans at these sites. The algorithm also recapitulated glycosylation in Enhanced Aromatic Sequons, SARS-CoV-2 spike, and IgG3 variants, thus demonstrating the ability of the algorithm to predict both glycan structure and abundance. Thus, protein structure constrains glycosylation, and the neural network enables predictive in silico glycosylation of uncharacterized or novel protein sequences and genetic variants.
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Affiliation(s)
- Benjamin P. Kellman
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
- Augment Biologics, La Jolla, CA 92092
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Julien Mariethoz
- Proteome Informatics Group, Swiss Institute of Bioinformatics, CH-1227 Geneva, Switzerland
| | - Yujie Zhang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sigal Shaul
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Mia Alteri
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Daniel Sandoval
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Mia Jeffris
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Erick Armingol
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Bokan Bao
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Frederique Lisacek
- Proteome Informatics Group, Swiss Institute of Bioinformatics, CH-1227 Geneva, Switzerland
- Computer Science Department & Section of Biology, University of Geneva, route de Drize 7, CH-1227, Geneva, Switzerland
| | - Daniel Bojar
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg 41390, Sweden
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg 41390, Sweden
| | - Nathan E. Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
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4
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Liu H, Yao M, Ren J. Codonopsis pilosula-derived glycopeptide dCP1 promotes the polarization of tumor-associated macrophage from M2-like to M1 phenotype. Cancer Immunol Immunother 2024; 73:128. [PMID: 38743074 PMCID: PMC11093951 DOI: 10.1007/s00262-024-03694-6] [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: 07/21/2023] [Accepted: 03/28/2024] [Indexed: 05/16/2024]
Abstract
The majority of the immune cell population in the tumor microenvironment (TME) consists of tumor-associated macrophages (TAM), which are the main players in coordinating tumor-associated inflammation. TAM has a high plasticity and is divided into two main phenotypes, pro-inflammatory M1 type and anti-inflammatory M2 type, with tumor-suppressive and tumor-promoting functions, respectively. Considering the beneficial effects of M1 macrophages for anti-tumor and the high plasticity of macrophages, the conversion of M2 TAM to M1 TAM is feasible and positive for tumor treatment. This study sought to evaluate whether the glycopeptide derived from simulated digested Codonopsis pilosula extracts could regulate the polarization of M2-like TAM toward the M1 phenotype and the potential regulatory mechanisms. The results showed that after glycopeptide dCP1 treatment, the mRNA relative expression levels of some M2 phenotype marker genes in M2-like TAM in simulated TME were reduced, and the relative expression levels of M1 phenotype marker genes and inflammatory factor genes were increased. Analysis of RNA-Seq of M2-like TAM after glycopeptide dCP1 intervention showed that the gene sets such as glycolysis, which is associated with macrophage polarization in the M1 phenotype, were significantly up-regulated, whereas those of gene sets such as IL-6-JAK-STAT3 pathway, which is associated with polarization in the M2 phenotype, were significantly down-regulated. Moreover, PCA analysis and Pearson's correlation also indicated that M2-like TAM polarized toward the M1 phenotype at the transcriptional level after treatment with the glycopeptide dCP1. Lipid metabolomics was used to further explore the efficacy of the glycopeptide dCP1 in regulating the polarization of M2-like TAM to the M1 phenotype. It was found that the lipid metabolite profiles in dCP1-treated M2-like TAM showed M1 phenotype macrophage lipid metabolism profiles compared with blank M2-like TAM. Analysis of the key differential lipid metabolites revealed that the interconversion between phosphatidylcholine (PC) and diacylglycerol (DG) metabolites may be the central reaction of the glycopeptide dCP1 in regulating the conversion of M2-like TAM to the M1 phenotype. The above results suggest that the glycopeptide dCP1 has the efficacy to regulate the polarization of M2-like TAM to M1 phenotype in simulated TME.
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Affiliation(s)
- Hongxu Liu
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510641, Guangdong, People's Republic of China
| | - Maojin Yao
- State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, People's Republic of China.
| | - Jiaoyan Ren
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510641, Guangdong, People's Republic of China.
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5
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Dialpuri JS, Bagdonas H, Schofield LC, Pham PT, Holland L, Agirre J. Monitoring carbohydrate 3D structure quality with the Privateer database. Beilstein J Org Chem 2024; 20:931-939. [PMID: 38711584 PMCID: PMC11070961 DOI: 10.3762/bjoc.20.83] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/10/2024] [Indexed: 05/08/2024] Open
Abstract
The remediation of the carbohydrate data of the Protein Data Bank (PDB) has brought numerous enhancements to the findability and interpretability of deposited glycan structures, yet crucial quality indicators are either missing or hard to find on the PDB pages. Without a way to access wider glycochemical context, problematic structures may be taken as fact by keen but inexperienced scientists. The Privateer software is a validation and analysis tool that provides access to a number of metrics and links to external experimental resources, allowing users to evaluate structures using carbohydrate-specific methods. Here, we present the Privateer database, a free resource that aims to complement the growing glycan content of the PDB.
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Affiliation(s)
- Jordan S Dialpuri
- York Structural Biology Laboratory, Department of Chemistry, University of York, UK
| | - Haroldas Bagdonas
- York Structural Biology Laboratory, Department of Chemistry, University of York, UK
| | - Lucy C Schofield
- York Structural Biology Laboratory, Department of Chemistry, University of York, UK
| | - Phuong Thao Pham
- York Structural Biology Laboratory, Department of Chemistry, University of York, UK
| | - Lou Holland
- York Structural Biology Laboratory, Department of Chemistry, University of York, UK
| | - Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, UK
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Shanmugam NRS, Kulandaisamy A, Veluraja K, Gromiha MM. CarbDisMut: database on neutral and disease-causing mutations in human carbohydrate-binding proteins. Glycobiology 2024; 34:cwae011. [PMID: 38335248 DOI: 10.1093/glycob/cwae011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 01/03/2024] [Indexed: 02/12/2024] Open
Abstract
Protein-carbohydrate interactions are involved in several cellular and biological functions. Integrating structure and function of carbohydrate-binding proteins with disease-causing mutations help to understand the molecular basis of diseases. Although databases are available for protein-carbohydrate complexes based on structure, binding affinity and function, no specific database for mutations in human carbohydrate-binding proteins is reported in the literature. We have developed a novel database, CarbDisMut, a comprehensive integrated resource for disease-causing mutations with sequence and structural features. It has 1.17 million disease-associated mutations and 38,636 neutral mutations from 7,187 human carbohydrate-binding proteins. The database is freely available at https://web.iitm.ac.in/bioinfo2/carbdismut. The web-site is implemented using HTML, PHP and JavaScript and supports recent versions of all major browsers, such as Firefox, Chrome and Opera.
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Affiliation(s)
- N R Siva Shanmugam
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
| | - A Kulandaisamy
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
- Basic and Translational Research, Department of Cardiology, Boston Children's Hospital, Boston, MA 02115, United States
| | - K Veluraja
- PSN College of Engineering and Technology, Melathediyoor, Tirunelveli, Tamil Nadu 627451, India
| | - M Michael Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
- Department of Computer Science, Tokyo Tech World Research Hub Initiative (WRHI), Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsutacho, Midori-ku, Yokohama, Kanagawa 226-8501, Japan
- Department of Computer Science, National University of Singapore, 117417, Singapore
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Altmann F, Helm J, Pabst M, Stadlmann J. Introduction of a human- and keyboard-friendly N-glycan nomenclature. Beilstein J Org Chem 2024; 20:607-620. [PMID: 38505241 PMCID: PMC10949011 DOI: 10.3762/bjoc.20.53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 02/27/2024] [Indexed: 03/21/2024] Open
Abstract
In the beginning was the word. But there were no words for N-glycans, at least, no simple words. Next to chemical formulas, the IUPAC code can be regarded as the best, most reliable and yet immediately comprehensible annotation of oligosaccharide structures of any type from any source. When it comes to N-glycans, the venerable IUPAC code has, however, been widely supplanted by highly simplified terms for N-glycans that count the number of antennae or certain components such as galactoses, sialic acids and fucoses and give only limited room for exact structure description. The highly illustrative - and fortunately now standardized - cartoon depictions gained much ground during the last years. By their very nature, cartoons can neither be written nor spoken. The underlying machine codes (e.g., GlycoCT, WURCS) are definitely not intended for direct use in human communication. So, one might feel the need for a simple, yet intelligible and precise system for alphanumeric descriptions of the hundreds and thousands of N-glycan structures. Here, we present a system that describes N-glycans by defining their terminal elements. To minimize redundancy and length of terms, the common elements of N-glycans are taken as granted. The preset reading order facilitates definition of positional isomers. The combination with elements of the condensed IUPAC code allows to describe even rather complex structural elements. Thus, this "proglycan" coding could be the missing link between drawn structures and software-oriented representations of N-glycan structures. On top, it may greatly facilitate keyboard-based mining for glycan substructures in glycan repositories.
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Affiliation(s)
| | - Johannes Helm
- Department of Chemistry, BOKU University, Vienna, Austria
| | - Martin Pabst
- Department of Biotechnology, Delft University of Technology, Delft, The Netherlands
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Kumar BS. Recent Developments and Application of Mass Spectrometry Imaging in N-Glycosylation Studies: An Overview. Mass Spectrom (Tokyo) 2024; 13:A0142. [PMID: 38435075 PMCID: PMC10904931 DOI: 10.5702/massspectrometry.a0142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 01/06/2024] [Indexed: 03/05/2024] Open
Abstract
Among the most typical posttranslational modifications is glycosylation, which often involves the covalent binding of an oligosaccharide (glycan) to either an asparagine (N-linked) or a serine/threonine (O-linked) residue. Studies imply that the N-glycan portion of a glycoprotein could serve as a particular disease biomarker rather than the protein itself because N-linked glycans have been widely recognized to evolve with the advancement of tumors and other diseases. N-glycans found on protein asparagine sites have been especially significant. Since N-glycans play clearly defined functions in the folding of proteins, cellular transport, and transmission of signals, modifications to them have been linked to several illnesses. However, because these N-glycans' production is not template driven, they have a substantial morphological range, rendering it difficult to distinguish the species that are most relevant to biology and medicine using standard techniques. Mass spectrometry (MS) techniques have emerged as effective analytical tools for investigating the role of glycosylation in health and illness. This is due to developments in MS equipment, data collection, and sample handling techniques. By recording the spatial dimension of a glycan's distribution in situ, mass spectrometry imaging (MSI) builds atop existing methods while offering added knowledge concerning the structure and functionality of biomolecules. In this review article, we address the current development of glycan MSI, starting with the most used tissue imaging techniques and ionization sources before proceeding on to a discussion on applications and concluding with implications for clinical research.
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Phung TK, Berndsen K, Shastry R, Phan TLCHB, Muqit MMK, Alessi DR, Nirujogi RS. CURTAIN-A unique web-based tool for exploration and sharing of MS-based proteomics data. Proc Natl Acad Sci U S A 2024; 121:e2312676121. [PMID: 38324566 PMCID: PMC10873628 DOI: 10.1073/pnas.2312676121] [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: 07/26/2023] [Accepted: 12/14/2023] [Indexed: 02/09/2024] Open
Abstract
To facilitate analysis and sharing of mass spectrometry (MS)-based proteomics data, we created online tools called CURTAIN (https://curtain.proteo.info) and CURTAIN-PTM (https://curtainptm.proteo.info) with an accompanying series of video tutorials (https://www.youtube.com/@CURTAIN-me6hl). These are designed to enable non-MS experts to interactively peruse volcano plots and deconvolute primary experimental data so that replicates can be visualized in bar charts or violin plots and exported in publication-ready format. They also allow assessment of overall experimental quality by correlation matrix and profile plot analysis. After making a selection of protein "hits", the user can analyze known domain structure, AlphaFold predicted structure, reported interactors, relative expression as well as disease links. CURTAIN-PTM permits analysis of all identified PTM sites on protein(s) of interest with selected databases. CURTAIN-PTM also links with the Kinase Library to predict upstream kinases that may phosphorylate sites of interest. We provide examples of the utility of CURTAIN and CURTAIN-PTM in analyzing how targeted degradation of the PPM1H Rab phosphatase that counteracts the Parkinson's LRRK2 kinase impacts cellular protein levels and phosphorylation sites. We also reanalyzed a ubiquitylation dataset, characterizing the PINK1-Parkin pathway activation in primary neurons, revealing data of interest not highlighted previously. CURTAIN and CURTAIN-PTM are free to use and open source, enabling researchers to share and maximize the impact of their proteomics data. We advocate that MS data published in volcano plot format be reported containing a shareable CURTAIN weblink, thereby allowing readers to better analyze and exploit the data.
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Affiliation(s)
- Toan K. Phung
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, DundeeDD1 5EH, United Kingdom
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
| | - Kerryn Berndsen
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, DundeeDD1 5EH, United Kingdom
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
| | - Rosamund Shastry
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, DundeeDD1 5EH, United Kingdom
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
| | - Tran L. C. H. B. Phan
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, DundeeDD1 5EH, United Kingdom
| | - Miratul M. K. Muqit
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, DundeeDD1 5EH, United Kingdom
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
| | - Dario R. Alessi
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, DundeeDD1 5EH, United Kingdom
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
| | - Raja S. Nirujogi
- Medical Research Council Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, DundeeDD1 5EH, United Kingdom
- Aligning Science Across Parkinson’s Collaborative Research Network, Chevy Chase, MD20815
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10
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Dixit B, Vranken W, Ghysels A. Conformational dynamics of α-1 acid glycoprotein (AGP) in cancer: A comparative study of glycosylated and unglycosylated AGP. Proteins 2024; 92:246-264. [PMID: 37837263 DOI: 10.1002/prot.26607] [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: 03/24/2023] [Revised: 09/01/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023]
Abstract
α-1 acid glycoprotein (AGP) is one of the most abundant plasma proteins. It fulfills two important functions: immunomodulation, and binding to various drugs and receptors. These different functions are closely associated and modulated via changes in glycosylation and cancer missense mutations. From a structural point of view, glycans alter the local biophysical properties of the protein leading to a diverse ligand-binding spectrum. However, glycans can typically not be observed in the resolved X-ray crystallography structure of AGP due to their high flexibility and microheterogeneity, so limiting our understanding of AGP's conformational dynamics 70 years after its discovery. We here investigate how mutations and glycosylation interfere with AGP's conformational dynamics changing its biophysical behavior, by using molecular dynamics (MD) simulations and sequence-based dynamics predictions. The MD trajectories show that glycosylation decreases the local backbone flexibility of AGP and increases the flexibility of distant regions through allosteric effects. We observe that mutations near the glycosylation site affect glycan's conformational preferences. Thus, we conclude that mutations control glycan dynamics which modulates the protein's backbone flexibility directly affecting its accessibility. These findings may assist in the drug design targeting AGP's glycosylation and mutations in cancer.
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Affiliation(s)
- Bhawna Dixit
- IBiTech-BioMMeda Group, Ghent University, Ghent, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
| | - Wim Vranken
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
| | - An Ghysels
- IBiTech-BioMMeda Group, Ghent University, Ghent, Belgium
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11
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Schnider B, M’Rad Y, el Ahmadie J, de Brevern AG, Imberty A, Lisacek F. HumanLectome, an update of UniLectin for the annotation and prediction of human lectins. Nucleic Acids Res 2024; 52:D1683-D1693. [PMID: 37889052 PMCID: PMC10767822 DOI: 10.1093/nar/gkad905] [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: 09/04/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 10/28/2023] Open
Abstract
The UniLectin portal (https://unilectin.unige.ch/) was designed in 2019 with the goal of centralising curated and predicted data on carbohydrate-binding proteins known as lectins. UniLectin is also intended as a support for the study of lectomes (full lectin set) of organisms or tissues. The present update describes the inclusion of several new modules and details the latest (https://unilectin.unige.ch/humanLectome/), covering our knowledge of the human lectome and comprising 215 unevenly characterised lectins, particularly in terms of structural information. Each HumanLectome entry is protein-centric and compiles evidence of carbohydrate recognition domain(s), specificity, 3D-structure, tissue-based expression and related genomic data. Other recent improvements regarding interoperability and accessibility are outlined.
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Affiliation(s)
- Boris Schnider
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
| | - Yacine M’Rad
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
| | - Jalaa el Ahmadie
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
- University Grenoble Alpes, CNRS, CERMAV, F-38000 Grenoble, France
| | - Alexandre G de Brevern
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB Bioinformatics Team, F-75014 Paris, France
| | - Anne Imberty
- University Grenoble Alpes, CNRS, CERMAV, F-38000 Grenoble, France
| | - Frederique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
- Section of Biology, University of Geneva, CH-1205 Geneva, Switzerland
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12
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Dobson L, Gerdán C, Tusnády S, Szekeres L, Kuffa K, Langó T, Zeke A, Tusnády GE. UniTmp: unified resources for transmembrane proteins. Nucleic Acids Res 2024; 52:D572-D578. [PMID: 37870462 PMCID: PMC10767979 DOI: 10.1093/nar/gkad897] [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: 09/14/2023] [Revised: 10/03/2023] [Accepted: 10/04/2023] [Indexed: 10/24/2023] Open
Abstract
The UNIfied database of TransMembrane Proteins (UniTmp) is a comprehensive and freely accessible resource of transmembrane protein structural information at different levels, from localization of protein segments, through the topology of the protein to the membrane-embedded 3D structure. We not only annotated tens of thousands of new structures and experiments, but we also developed a new system that can serve these resources in parallel. UniTmp is a unified platform that merges TOPDB (Topology Data Bank of Transmembrane Proteins), TOPDOM (database of conservatively located domains and motifs in proteins), PDBTM (Protein Data Bank of Transmembrane Proteins) and HTP (Human Transmembrane Proteome) databases and provides interoperability between the incorporated resources and an easy way to keep them regularly updated. The current update contains 9235 membrane-embedded structures, 9088 sequences with 536 035 topology-annotated segments and 8692 conservatively localized protein domains or motifs as well as 5466 annotated human transmembrane proteins. The UniTmp database can be accessed at https://www.unitmp.org.
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Affiliation(s)
- László Dobson
- Protein Bioinformatics Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Magyar Tudósok körútja 2, H-1117, Hungary
- Department of Bioinformatics, Semmelweis University, Budapest, Tűzoltó u. 7, H-1094, Hungary
| | - Csongor Gerdán
- Protein Bioinformatics Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Magyar Tudósok körútja 2, H-1117, Hungary
| | - Simon Tusnády
- Department of Bioinformatics, Semmelweis University, Budapest, Tűzoltó u. 7, H-1094, Hungary
| | - Levente Szekeres
- Protein Bioinformatics Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Magyar Tudósok körútja 2, H-1117, Hungary
| | - Katalin Kuffa
- Protein Bioinformatics Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Magyar Tudósok körútja 2, H-1117, Hungary
- Doctoral School of Biology, Institute of Biology, ELTE Eötvös Loránd University, Budapest, Pázmány P. stny. 1/C, H-1117, Hungary
| | - Tamás Langó
- Protein Bioinformatics Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Magyar Tudósok körútja 2, H-1117, Hungary
| | - András Zeke
- Protein Bioinformatics Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Magyar Tudósok körútja 2, H-1117, Hungary
| | - Gábor E Tusnády
- Protein Bioinformatics Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Magyar Tudósok körútja 2, H-1117, Hungary
- Department of Bioinformatics, Semmelweis University, Budapest, Tűzoltó u. 7, H-1094, Hungary
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13
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Altenhoff A, Bairoch A, Bansal P, Baratin D, Bastian F, Bolleman* J, Bridge A, Burdet F, Crameri K, Dauvillier J, Dessimoz C, Gehant S, Glover N, Gnodtke K, Hayes C, Ibberson M, Kriventseva E, Kuznetsov D, Frédérique L, Mehl F, Mendes de Farias* T, Michel PA, Moretti S, Morgat A, Österle S, Pagni M, Redaschi N, Robinson-Rechavi M, Samarasinghe K, Sima AC, Szklarczyk D, Topalov O, Touré V, Unni D, von Mering C, Wollbrett J, Zahn-Zabal* M, Zdobnov E. The SIB Swiss Institute of Bioinformatics Semantic Web of data. Nucleic Acids Res 2024; 52:D44-D51. [PMID: 37878411 PMCID: PMC10767860 DOI: 10.1093/nar/gkad902] [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: 09/07/2023] [Revised: 10/02/2023] [Accepted: 10/05/2023] [Indexed: 10/27/2023] Open
Abstract
The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss/) is a federation of bioinformatics research and service groups. The international life science community in academia and industry has been accessing the freely available databases provided by SIB since its inception in 1998. In this paper we present the 11 databases which currently offer semantically enriched data in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable), as well as the Swiss Personalized Health Network initiative (SPHN) which also employs this enrichment. The semantic enrichment facilitates the manipulation of large data sets from public databases and private data sets. Examples are provided to illustrate that the data from the SIB databases can not only be queried using precise criteria individually, but also across multiple databases, including a variety of non-SIB databases. Data manipulation, be it exploration, extraction, annotation, combination, and publication, is possible using the SPARQL query language. Providing documentation, tutorials and sample queries makes it easier to navigate this web of semantic data. Through this paper, the reader will discover how the existing SIB knowledge graphs can be leveraged to tackle the complex biological or clinical questions that are being addressed today.
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14
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Jin C, Venkatakrishnan V, Thomsson KA, Aoki NP, Shinmachi D, Aoki-Kinoshita KF, Hayes CA, Lisacek F, Karlsson NG. UniCarb-DB: An MS/MS Experimental Glycomic Fragmentation Database. Methods Mol Biol 2024; 2836:77-96. [PMID: 38995537 DOI: 10.1007/978-1-0716-4007-4_6] [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: 07/13/2024]
Abstract
Glycosylation is a unique posttranslational modification that dynamically shapes the surface of cells. Glycans attached to proteins or lipids in a cell or tissue are studied as a whole and collectively designated as a glycome. UniCarb-DB is a glycomic spectral library of tandem mass spectrometry (MS/MS) fragment data. The current version of the database consists of over 1500 entries and over 1000 unique structures. Each entry contains parent ion information with associated MS/MS spectra, metadata about the original publication, experimental conditions, and biological origin. Each structure is also associated with the GlyTouCan glycan structure repository allowing easy access to other glycomic resources. The database can be directly utilized by mass spectrometry (MS) experimentalists through the conversion of data generated by MS into structural information. Flexible online search tools along with a downloadable version of the database are easily incorporated in either commercial or open-access MS software. This chapter highlights UniCarb-DB online search tool to browse differences of isomeric structures between spectra, a peak matching search between user-generated MS/MS spectra and spectra stored in UniCarb-DB and more advanced MS tools for combined quantitative and qualitative glycomics.
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Affiliation(s)
- Chunsheng Jin
- Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Kristina A Thomsson
- Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nobuyuki P Aoki
- Soka University, Hachioji, Tokyo, Japan
- SparqLite.com, Hachioji, Tokyo, Japan
| | | | | | - Catherine A Hayes
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
- Computer Science Department, University of Geneva, Geneva, Switzerland
- Section of Biology, University of Geneva, Geneva, Switzerland
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | - Niclas G Karlsson
- Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Division of Pharmacy, Department of Life Science and Health, Faculty of Health Science, Oslo Metropolitan University, Oslo, Norway.
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15
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Lundstrøm J, Urban J, Bojar D. Decoding glycomics with a suite of methods for differential expression analysis. CELL REPORTS METHODS 2023; 3:100652. [PMID: 37992708 PMCID: PMC10753297 DOI: 10.1016/j.crmeth.2023.100652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/04/2023] [Accepted: 10/30/2023] [Indexed: 11/24/2023]
Abstract
Glycomics, the comprehensive profiling of all glycan structures in samples, is rapidly expanding to enable insights into physiology and disease mechanisms. However, glycan structure complexity and glycomics data interpretation present challenges, especially for differential expression analysis. Here, we present a framework for differential glycomics expression analysis. Our methodology encompasses specialized and domain-informed methods for data normalization and imputation, glycan motif extraction and quantification, differential expression analysis, motif enrichment analysis, time series analysis, and meta-analytic capabilities, synthesizing results across multiple studies. All methods are integrated into our open-source glycowork package, facilitating performant workflows and user-friendly access. We demonstrate these methods using dedicated simulations and glycomics datasets of N-, O-, lipid-linked, and free glycans. Differential expression tests here focus on human datasets and cancer vs. healthy tissue comparisons. Our rigorous approach allows for robust, reliable, and comprehensive differential expression analyses in glycomics, contributing to advancing glycomics research and its translation to clinical and diagnostic applications.
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Affiliation(s)
- Jon Lundstrøm
- Department of Chemistry and Molecular Biology, University of Gothenburg, 41390 Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 41390 Gothenburg, Sweden
| | - James Urban
- Department of Chemistry and Molecular Biology, University of Gothenburg, 41390 Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 41390 Gothenburg, Sweden
| | - Daniel Bojar
- Department of Chemistry and Molecular Biology, University of Gothenburg, 41390 Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 41390 Gothenburg, Sweden.
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16
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Weigand MR, Moore AM, Hu H, Angel PM, Drake RR, Laskin J. Imaging of N-Linked Glycans in Biological Tissue Sections Using Nanospray Desorption Electrospray Ionization (nano-DESI) Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2481-2490. [PMID: 37779241 DOI: 10.1021/jasms.3c00209] [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: 10/03/2023]
Abstract
N-linked glycans are complex biomolecules vital to cellular functions that have been linked to a wide range of pathological conditions. Mass spectrometry imaging (MSI) has been used to study the localization of N-linked glycans in cells and tissues. However, their structural diversity presents a challenge for MSI techniques, which stimulates the development of new approaches. In this study, we demonstrate for the first time spatial mapping of N-linked glycans in biological tissues using nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI MSI). Nano-DESI MSI is an ambient ionization technique that has been previously used for imaging of metabolites, lipids, and proteins in biological tissue samples without special sample pretreatment. N-linked glycans are released from glycoproteins using an established enzymatic digestion with peptide N-glycosidase F, and their spatial localization is examined using nano-DESI MSI. We demonstrate imaging of N-linked glycans in formalin-fixed paraffin-embedded human hepatocellular carcinoma and human prostate tissues in both positive and negative ionization modes. We examine the localization of 38 N-linked glycans consisting of high mannose, hybrid fucosylated, and sialyated glycans. We demonstrate that negative mode nano-DESI MSI is well-suited for imaging of underivatized sialylated N-linked glycans. On-tissue MS/MS of different adducts of N-linked glycans proves advantageous for elucidation of the glycan sequence. This study demonstrates the applicability of liquid extraction techniques for spatial mapping of N-linked glycans in biological samples, providing an additional tool for glycobiology research.
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Affiliation(s)
- Miranda R Weigand
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
| | - Alyssa M Moore
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
| | - Hang Hu
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
| | - Peggi M Angel
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, South Carolina 29425, United States
| | - Richard R Drake
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, South Carolina 29425, United States
| | - Julia Laskin
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
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17
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Jin C, Lundstrøm J, Korhonen E, Luis AS, Bojar D. Breast Milk Oligosaccharides Contain Immunomodulatory Glucuronic Acid and LacdiNAc. Mol Cell Proteomics 2023; 22:100635. [PMID: 37597722 PMCID: PMC10509713 DOI: 10.1016/j.mcpro.2023.100635] [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: 03/15/2023] [Revised: 07/31/2023] [Accepted: 08/16/2023] [Indexed: 08/21/2023] Open
Abstract
Breast milk is abundant with functionalized milk oligosaccharides (MOs) to nourish and protect the neonate. Yet we lack a comprehensive understanding of the repertoire and evolution of MOs across Mammalia. We report ∼400 MO-species associations (>100 novel structures) from milk glycomics of nine mostly understudied species: alpaca, beluga whale, black rhinoceros, bottlenose dolphin, impala, L'Hoest's monkey, pygmy hippopotamus, domestic sheep, and striped dolphin. This revealed the hitherto unknown existence of the LacdiNAc motif (GalNAcβ1-4GlcNAc) in MOs of all species except alpaca, sheep, and striped dolphin, indicating the widespread occurrence of this potentially antimicrobial motif in MOs. We also characterize glucuronic acid-containing MOs in the milk of impala, dolphins, sheep, and rhinoceros, previously only reported in cows. We demonstrate that these GlcA-MOs exhibit potent immunomodulatory effects. Our study extends the number of known MOs by >15%. Combined with >1900 curated MO-species associations, we characterize MO motif distributions, presenting an exhaustive overview of MO biodiversity.
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Affiliation(s)
- Chunsheng Jin
- Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Jon Lundstrøm
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Emma Korhonen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Ana S Luis
- Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Gothenburg, Sweden
| | - Daniel Bojar
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
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18
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Costa J, Hayes C, Lisacek F. Protein glycosylation and glycoinformatics for novel biomarker discovery in neurodegenerative diseases. Ageing Res Rev 2023; 89:101991. [PMID: 37348818 DOI: 10.1016/j.arr.2023.101991] [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: 03/31/2023] [Revised: 05/25/2023] [Accepted: 06/18/2023] [Indexed: 06/24/2023]
Abstract
Glycosylation is a common post-translational modification of brain proteins including cell surface adhesion molecules, synaptic proteins, receptors and channels, as well as intracellular proteins, with implications in brain development and functions. Using advanced state-of-the-art glycomics and glycoproteomics technologies in conjunction with glycoinformatics resources, characteristic glycosylation profiles in brain tissues are increasingly reported in the literature and growing evidence shows deregulation of glycosylation in central nervous system disorders, including aging associated neurodegenerative diseases. Glycan signatures characteristic of brain tissue are also frequently described in cerebrospinal fluid due to its enrichment in brain-derived molecules. A detailed structural analysis of brain and cerebrospinal fluid glycans collected in publications in healthy and neurodegenerative conditions was undertaken and data was compiled to create a browsable dedicated set in the GlyConnect database of glycoproteins (https://glyconnect.expasy.org/brain). The shared molecular composition of cerebrospinal fluid with brain enhances the likelihood of novel glycobiomarker discovery for neurodegeneration, which may aid in unveiling disease mechanisms, therefore, providing with novel therapeutic targets as well as diagnostic and progression monitoring tools.
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Affiliation(s)
- Júlia Costa
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2780-157 Oeiras, Portugal.
| | - Catherine Hayes
- Proteome Informatics Group, Swiss Institute of Bioinformatics, CH-1227 Geneva, Switzerland
| | - Frédérique Lisacek
- Proteome Informatics Group, Swiss Institute of Bioinformatics, CH-1227 Geneva, Switzerland; Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland; Section of Biology, University of Geneva, CH-1211 Geneva, Switzerland
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19
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Durham SD, Wei Z, Lemay DG, Lange MC, Barile D. Creation of a milk oligosaccharide database, MilkOligoDB, reveals common structural motifs and extensive diversity across mammals. Sci Rep 2023; 13:10345. [PMID: 37365203 DOI: 10.1038/s41598-023-36866-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 06/13/2023] [Indexed: 06/28/2023] Open
Abstract
The carbohydrate fraction of most mammalian milks contains a variety of oligosaccharides that encompass a range of structures and monosaccharide compositions. Human milk oligosaccharides have received considerable attention due to their biological roles in neonatal gut microbiota, immunomodulation, and brain development. However, a major challenge in understanding the biology of milk oligosaccharides across other mammals is that reports span more than 5 decades of publications with varying data reporting methods. In the present study, publications on milk oligosaccharide profiles were identified and harmonized into a standardized format to create a comprehensive, machine-readable database of milk oligosaccharides across mammalian species. The resulting database, MilkOligoDB, includes 3193 entries for 783 unique oligosaccharide structures from the milk of 77 different species harvested from 113 publications. Cross-species and cross-publication comparisons of milk oligosaccharide profiles reveal common structural motifs within mammalian orders. Of the species studied, only chimpanzees, bonobos, and Asian elephants share the specific combination of fucosylation, sialylation, and core structures that are characteristic of human milk oligosaccharides. However, agriculturally important species do produce diverse oligosaccharides that may be valuable for human supplementation. Overall, MilkOligoDB facilitates cross-species and cross-publication comparisons of milk oligosaccharide profiles and the generation of new data-driven hypotheses for future research.
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Affiliation(s)
- Sierra D Durham
- Department of Food Science and Technology, University of California, Davis, One Shields Ave., Davis, CA, 95616, USA
| | - Zhe Wei
- Department of Food Science and Technology, University of California, Davis, One Shields Ave., Davis, CA, 95616, USA
| | - Danielle G Lemay
- Agricultural Research Service, U.S. Department of Agriculture, Western Human Nutrition Research Center, 430 West Health Sciences Dr., Davis, CA, 95616, USA
| | - Matthew C Lange
- International Center for Food Ontology Operability Data and Semantics, 216 F Street Ste. 139, Davis, CA, 95616, USA
| | - Daniela Barile
- Department of Food Science and Technology, University of California, Davis, One Shields Ave., Davis, CA, 95616, USA.
- Foods for Health Institute, University of California, Davis, One Shields Ave., Davis, CA, 95616, USA.
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20
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Vora J, Navelkar R, Vijay-Shanker K, Edwards N, Martinez K, Ding X, Wang T, Su P, Ross K, Lisacek F, Hayes C, Kahsay R, Ranzinger R, Tiemeyer M, Mazumder R. The Glycan Structure Dictionary-a dictionary describing commonly used glycan structure terms. Glycobiology 2023; 33:354-357. [PMID: 36799723 PMCID: PMC10243773 DOI: 10.1093/glycob/cwad014] [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: 02/10/2022] [Revised: 01/28/2023] [Accepted: 02/08/2023] [Indexed: 02/18/2023] Open
Abstract
Recent technological advances in glycobiology have resulted in a large influx of data and the publication of many papers describing discoveries in glycoscience. However, the terms used in describing glycan structural features are not standardized, making it difficult to harmonize data across biomolecular databases, hampering the harvesting of information across studies and hindering text mining and curation efforts. To address this shortcoming, the Glycan Structure Dictionary has been developed as a reference dictionary to provide a standardized list of widely used glycan terms that can help in the curation and mapping of glycan structures described in publications. Currently, the dictionary has 190 glycan structure terms with 297 synonyms linked to 3,332 publications. For a term to be included in the dictionary, it must be present in at least 2 peer-reviewed publications. Synonyms, annotations, and cross-references to GlyTouCan, GlycoMotif, and other relevant databases and resources are also provided when available. The purpose of this effort is to facilitate biocuration, assist in the development of text mining tools, improve the harmonization of search, and browse capabilities in glycoinformatics resources and help to map glycan structures to function and disease. It is also expected that authors will use these terms to describe glycan structures in their manuscripts over time. A mechanism is also provided for researchers to submit terms for potential incorporation. The dictionary is available at https://wiki.glygen.org/Glycan_structure_dictionary.
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Affiliation(s)
- Jeet Vora
- Department of Biochemistry & Molecular Medicine, The George Washington School of Medicine and Health Sciences, 2300 I Street NW, Washington, DC 20037, USA
| | - Rahi Navelkar
- Department of Biochemistry & Molecular Medicine, The George Washington School of Medicine and Health Sciences, 2300 I Street NW, Washington, DC 20037, USA
| | - K Vijay-Shanker
- Department of Computer and Information Science, University of Delaware, Smith Hall, 18 Amstel Ave Newark, DE 19716, USA
| | - Nathan Edwards
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, 3900 Reservoir Rd NW #337, DC 20007, USA
| | - Karina Martinez
- Department of Biochemistry & Molecular Medicine, The George Washington School of Medicine and Health Sciences, 2300 I Street NW, Washington, DC 20037, USA
| | - Xiying Ding
- Department of Biochemistry & Molecular Medicine, The George Washington School of Medicine and Health Sciences, 2300 I Street NW, Washington, DC 20037, USA
| | - Tianyi Wang
- Department of Biochemistry & Molecular Medicine, The George Washington School of Medicine and Health Sciences, 2300 I Street NW, Washington, DC 20037, USA
| | - Peng Su
- Department of Computer and Information Science, University of Delaware, Smith Hall, 18 Amstel Ave Newark, DE 19716, USA
| | - Karen Ross
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, 3900 Reservoir Rd NW #337, DC 20007, USA
| | - Frederique Lisacek
- University of Geneva and Swiss Institute of Bioinformatics, CUI - 7, route de Drize, Geneva 1211, Switzerland
| | - Catherine Hayes
- University of Geneva and Swiss Institute of Bioinformatics, CUI - 7, route de Drize, Geneva 1211, Switzerland
| | - Robel Kahsay
- Department of Biochemistry & Molecular Medicine, The George Washington School of Medicine and Health Sciences, 2300 I Street NW, Washington, DC 20037, USA
| | - Rene Ranzinger
- Complex Carbohydrate Research Center, The University of Georgia, 315 Riverbend Rd, Athens, GA 30602, USA
| | - Michael Tiemeyer
- Complex Carbohydrate Research Center, The University of Georgia, 315 Riverbend Rd, Athens, GA 30602, USA
| | - Raja Mazumder
- Department of Biochemistry & Molecular Medicine, The George Washington School of Medicine and Health Sciences, 2300 I Street NW, Washington, DC 20037, USA
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21
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Chau TH, Chernykh A, Kawahara R, Thaysen-Andersen M. Critical considerations in N-glycoproteomics. Curr Opin Chem Biol 2023; 73:102272. [PMID: 36758418 DOI: 10.1016/j.cbpa.2023.102272] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/30/2022] [Accepted: 01/05/2023] [Indexed: 02/10/2023]
Abstract
N-Glycoproteomics, the system-wide study of glycans asparagine-linked to protein carriers, holds a unique and still largely untapped potential to provide deep insights into the complexity and dynamics of the heterogeneous N-glycoproteome. Despite the advent of innovative analytical and informatics tools aiding the analysis, N-glycoproteomics remains challenging and consequently largely restricted to specialised laboratories. Aiming to stimulate discussions of method harmonisation, data standardisation and reporting guidelines to make N-glycoproteomics more reproducible and accessible to the community, we here discuss critical considerations related to the design and execution of N-glycoproteomics experiments and highlight good practices in N-glycopeptide data collection, analysis, interpretation and sharing. Giving the rapid maturation and, expectedly, a wide-spread implementation of N-glycoproteomics capabilities across the community in future years, this piece aims to point out common pitfalls, to encourage good data sharing and documentation practices, and to highlight practical solutions and strategies to enhance the insight into the N-glycoproteome.
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Affiliation(s)
- The Huong Chau
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia
| | - Anastasia Chernykh
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia
| | - Rebeca Kawahara
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia
| | - Morten Thaysen-Andersen
- School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia; Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan.
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22
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Zhang Y, Krishnan S, Bao B, Chiang AWT, Sorrentino JT, Schinn SM, Kellman BP, Lewis NE. Preparing glycomics data for robust statistical analysis with GlyCompareCT. STAR Protoc 2023; 4:102162. [PMID: 36920914 PMCID: PMC10025275 DOI: 10.1016/j.xpro.2023.102162] [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: 09/12/2022] [Revised: 12/27/2022] [Accepted: 02/13/2023] [Indexed: 03/16/2023] Open
Abstract
GlyCompareCT is a portable command-line tool to facilitate downstream glycomic data analyses, by addressing data inherent sparsity and non-independence. Inputting glycan abundances, users can run GlyCompareCT with one line of code to obtain the abundances of a minimal substructure set, named glycomotif, thereby quantifying hidden biosynthetic relationships between measured glycans. Optional parameters tuning and annotation are supported for personal preference. For complete details on the use and execution of this protocol, please refer to Bao et al. (2021).1.
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Affiliation(s)
- Yujie Zhang
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA; Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA
| | - Sridevi Krishnan
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA
| | - Bokan Bao
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA; Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA
| | - Austin W T Chiang
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA
| | - James T Sorrentino
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA; Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA
| | - Song-Min Schinn
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA; Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA
| | - Benjamin P Kellman
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA; Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA; Augment Biologics, 9450 SW Gemini Dr. #46664, Beaverton, OR 97008, USA.
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA; Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive MC 0760, La Jolla, CA 92093, USA.
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23
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McDowell CT, Lu X, Mehta AS, Angel PM, Drake RR. Applications and continued evolution of glycan imaging mass spectrometry. MASS SPECTROMETRY REVIEWS 2023; 42:674-705. [PMID: 34392557 PMCID: PMC8946722 DOI: 10.1002/mas.21725] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/16/2021] [Accepted: 08/03/2021] [Indexed: 05/03/2023]
Abstract
Glycosylation is an important posttranslational modifier of proteins and lipid conjugates critical for the stability and function of these macromolecules. Particularly important are N-linked glycans attached to asparagine residues in proteins. N-glycans have well-defined roles in protein folding, cellular trafficking and signal transduction, and alterations to them are implicated in a variety of diseases. However, the non-template driven biosynthesis of these N-glycans leads to significant structural diversity, making it challenging to identify the most biologically and clinically relevant species using conventional analyses. Advances in mass spectrometry instrumentation and data acquisition, as well as in enzymatic and chemical sample preparation strategies, have positioned mass spectrometry approaches as powerful analytical tools for the characterization of glycosylation in health and disease. Imaging mass spectrometry expands upon these strategies by capturing the spatial component of a glycan's distribution in-situ, lending additional insight into the organization and function of these molecules. Herein we review the ongoing evolution of glycan imaging mass spectrometry beginning with widely adopted tissue imaging approaches and expanding to other matrices and sample types with potential research and clinical implications. Adaptations of these techniques, along with their applications to various states of disease, are discussed. Collectively, glycan imaging mass spectrometry analyses broaden our understanding of the biological and clinical relevance of N-glycosylation to human disease.
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Affiliation(s)
- Colin T. McDowell
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Xiaowei Lu
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Anand S. Mehta
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Peggi M. Angel
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Richard R. Drake
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC, 29425, USA
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24
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Torres-Arteaga I, Blanco-Labra A, Mendiola-Olaya E, García-Gasca T, Aguirre-Mancilla C, Ortega-de-Santiago AL, Barboza M, Lebrilla CB, Castro-Guillén JL. Comparative study, homology modelling and molecular docking with cancer associated glycans of two non-fetuin-binding Tepary bean lectins. Glycoconj J 2023; 40:69-84. [PMID: 36385669 DOI: 10.1007/s10719-022-10091-7] [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: 08/26/2022] [Revised: 10/19/2022] [Accepted: 11/02/2022] [Indexed: 11/18/2022]
Abstract
We present the purification and characterization of the two most abundant isoforms of lectins isolated from Tepary bean (Phaseolus acutifolius) seeds, which have been shown to differentially affect the survival of different cancer cells. They were separated by concanavalin A-affinity chromatography. After purification, to release the N-glycans, they were digested with the endoglycosidases PNGase and Glycanase A. Fractions resulted from the hydrolysis products were analyzed to determine their carbohydrate composition. Mass spectrometry data indicated that both isoforms contained high mannose glycans being mannose 6 the most abundant form. Furthermore, based on sequence Ans-X-Ser/Thr, where X is any amino acid except proline, a glycosylation site was determined on asparagine 36. When their metal requirement to preserve their biological activity was determined, the lectins showed differences. While lectin A (LA) agglutination activity was best in the presence of magnesium, lectin B (LB) was best with calcium. Additionally, only LA exhibited affinity to human type-A erythrocytes. Although both lectins showed small differences in their properties, an identical structure-model for both lectins was generated by the homology modelling process. Also, the analysis of ligand binding sites and in silico glycosylation were achieved. Molecular docking with colon adenocarcinoma associated-N-glycans revealed some highly possible interactions and, on the other hand, that N-glycan interaction zones of Tepary bean lectins is not restricted to the carbohydrate binding domain but to an extended part of their surface, which could lead new strategies to explain their biological activity.
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Affiliation(s)
- Iovanna Torres-Arteaga
- Centro de Investigación y de Estudios Avanzados. Unidad Irapuato. Departamento de Biotecnología y Bioquímica., Libramiento Norte. Carretera Irapuato-León. Km. 9.6, 36824, Irapuato, Guanajuato, México
| | - Alejandro Blanco-Labra
- Centro de Investigación y de Estudios Avanzados. Unidad Irapuato. Departamento de Biotecnología y Bioquímica., Libramiento Norte. Carretera Irapuato-León. Km. 9.6, 36824, Irapuato, Guanajuato, México
| | - Elizabeth Mendiola-Olaya
- Centro de Investigación y de Estudios Avanzados. Unidad Irapuato. Departamento de Biotecnología y Bioquímica., Libramiento Norte. Carretera Irapuato-León. Km. 9.6, 36824, Irapuato, Guanajuato, México
| | - Teresa García-Gasca
- Universidad Autónoma de Querétaro. Campus Juriquilla. Facultad de Ciencias Naturales., Av. de las Ciencias s/n, Juriquilla, 76230, Santiago de Querétaro, Querétaro, México
| | - Cesar Aguirre-Mancilla
- Tecnológico Nacional de México / Instituto Tecnológico de Roque., Carretera Celaya-Juventino Rosas Km. 8., 38110, Celaya, Guanajuato, México
| | - Alondra L Ortega-de-Santiago
- Centro de Investigación y de Estudios Avanzados. Unidad Irapuato. Departamento de Biotecnología y Bioquímica., Libramiento Norte. Carretera Irapuato-León. Km. 9.6, 36824, Irapuato, Guanajuato, México
| | - Mariana Barboza
- University of California. Davis campus. Department of Chemistry, One Shields Ave. Chemistry Department 2465. Chemistry Annex., 95616, CA, Davis, USA
| | - Carlito B Lebrilla
- University of California. Davis campus. Department of Chemistry, One Shields Ave. Chemistry Department 2465. Chemistry Annex., 95616, CA, Davis, USA
| | - José Luis Castro-Guillén
- Tecnológico Nacional de México / Instituto Tecnológico Superior de Irapuato, Carretera Irapuato-Silao Km. 12.5. Colonia El Copal, 36821, Irapuato, Guanajuato, México.
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25
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Lisacek F, Tiemeyer M, Mazumder R, Aoki-Kinoshita KF. Worldwide Glycoscience Informatics Infrastructure: The GlySpace Alliance. JACS AU 2023; 3:4-12. [PMID: 36711080 PMCID: PMC9875223 DOI: 10.1021/jacsau.2c00477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/04/2022] [Accepted: 11/07/2022] [Indexed: 06/18/2023]
Abstract
The GlySpace Alliance was formed in 2018 among the principal investigators of three major glycoscience portals: Glyco@Expasy, GlyCosmos, and GlyGen, representing Europe, Asia, and the United States, respectively. While each of these portals has its unique user interface, the aim is to provide the same basic data set of glycan-related omics data. These portals will be introduced with the aim to enable users to find their target information in the most efficient manner, in particular, in terms of the chemical structures of glycans and their functions.
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Affiliation(s)
- Frederique Lisacek
- Proteome
Informatics Group, SIB Swiss Institute of Bioinformatics, University of Geneva, Geneva CH-1227, Switzerland
- Computer
Science Department & Section of Biology, University of Geneva, Geneva CH-1227, Switzerland
| | - Michael Tiemeyer
- Complex
Carbohydrate Research Center, University
of Georgia, Athens, Georgia 30602, United States
| | - Raja Mazumder
- George
Washington University, Washington, District of Columbia 20037, United States
| | - Kiyoko F. Aoki-Kinoshita
- Glycan
and Life Systems Integration Center (GaLSIC), Soka University, Hachioji, Tokyo 192-8577, Japan
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26
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Ramos-Martínez I, Ramos-Martínez E, Cerbón M, Pérez-Torres A, Pérez-Campos Mayoral L, Hernández-Huerta MT, Martínez-Cruz M, Pérez-Santiago AD, Sánchez-Medina MA, García-Montalvo IA, Zenteno E, Matias-Cervantes CA, Ojeda-Meixueiro V, Pérez-Campos E. The Role of B Cell and T Cell Glycosylation in Systemic Lupus Erythematosus. Int J Mol Sci 2023; 24:ijms24010863. [PMID: 36614306 PMCID: PMC9820943 DOI: 10.3390/ijms24010863] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/05/2022] [Accepted: 12/06/2022] [Indexed: 01/05/2023] Open
Abstract
Glycosylation is a post-translational modification that affects the stability, structure, antigenicity and charge of proteins. In the immune system, glycosylation is involved in the regulation of ligand-receptor interactions, such as in B-cell and T-cell activating receptors. Alterations in glycosylation have been described in several autoimmune diseases, such as systemic lupus erythematosus (SLE), in which alterations have been found mainly in the glycosylation of B lymphocytes, T lymphocytes and immunoglobulins. In immunoglobulin G of lupus patients, a decrease in galactosylation, sialylation, and nucleotide fucose, as well as an increase in the N-acetylglucosamine bisector, are observed. These changes in glycoisolation affect the interactions of immunoglobulins with Fc receptors and are associated with pericarditis, proteinuria, nephritis, and the presence of antinuclear antibodies. In T cells, alterations have been described in the glycosylation of receptors involved in activation, such as the T cell receptor; these changes affect the affinity with their ligands and modulate the binding to endogenous lectins such as galectins. In T cells from lupus patients, a decrease in galectin 1 binding is observed, which could favor activation and reduce apoptosis. Furthermore, these alterations in glycosylation correlate with disease activity and clinical manifestations, and thus have potential use as biomarkers. In this review, we summarize findings on glycosylation alterations in SLE and how they relate to immune system defects and their clinical manifestations.
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Affiliation(s)
- Ivan Ramos-Martínez
- Departamento de Medicina y Zootecnia de Cerdos, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
| | - Edgar Ramos-Martínez
- Facultad de Química, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
- Escuela de Ciencias, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca 68120, Mexico
| | - Marco Cerbón
- Unidad de Investigación en Reproducción Humana, Instituto Nacional de Perinatología “Isidro Espinosa de los Reyes”—Facultad de Química, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
| | - Armando Pérez-Torres
- Departamento de Biología Celular y Tisular, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
| | | | - María Teresa Hernández-Huerta
- CONACyT, Facultad de Medicina y Cirugía, Universidad Autónoma “Benito Juárez” de Oaxaca (UABJO), Oaxaca 68020, Mexico
| | | | | | | | | | - Edgar Zenteno
- Departamento de Bioquímica, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
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27
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Doud EH, Yeh ES. Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery. Technol Cancer Res Treat 2023; 22:15330338221148811. [PMID: 36740994 PMCID: PMC9903044 DOI: 10.1177/15330338221148811] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.
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Affiliation(s)
- Emma H. Doud
- Center for Proteome Analysis, Indiana University School of Medicine, Indianapolis, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, USA
- IU Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, USA
| | - Elizabeth S. Yeh
- IU Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, USA
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28
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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020. MASS SPECTROMETRY REVIEWS 2022:e21806. [PMID: 36468275 DOI: 10.1002/mas.21806] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.
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Affiliation(s)
- David J Harvey
- Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Oxford, UK
- Department of Chemistry, University of Oxford, Oxford, Oxfordshire, United Kingdom
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29
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Miura N, Hanamatsu H, Yokota I, Akasaka-Manya K, Manya H, Endo T, Shinohara Y, Furukawa JI. Toolbox Accelerating Glycomics (TAG): Improving Large-Scale Serum Glycomics and Refinement to Identify SALSA-Modified and Rare Glycans. Int J Mol Sci 2022; 23:ijms232113097. [PMID: 36361885 PMCID: PMC9656093 DOI: 10.3390/ijms232113097] [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: 09/08/2022] [Revised: 10/13/2022] [Accepted: 10/21/2022] [Indexed: 11/16/2022] Open
Abstract
Glycans are involved in many fundamental cellular processes such as growth, differentiation, and morphogenesis. However, their broad structural diversity makes analysis difficult. Glycomics via mass spectrometry has focused on the composition of glycans, but informatics analysis has not kept pace with the development of instrumentation and measurement techniques. We developed Toolbox Accelerating Glycomics (TAG), in which glycans can be added manually to the glycan list that can be freely designed with labels and sialic acid modifications, and fast processing is possible. In the present work, we improved TAG for large-scale analysis such as cohort analysis of serum samples. The sialic acid linkage-specific alkylamidation (SALSA) method converts differences in linkages such as α2,3- and α2,6-linkages of sialic acids into differences in mass. Glycans modified by SALSA and several structures discovered in recent years were added to the glycan list. A routine to generate calibration curves has been implemented to explore quantitation. These improvements are based on redefinitions of residues and glycans in the TAG List to incorporate information on glycans that could not be attributed because it was not assumed in the previous version of TAG. These functions were verified through analysis of purchased sera and 74 spectra with linearity at the level of R2 > 0.8 with 81 estimated glycan structures obtained including some candidate of rare glycans such as those with the N,N’-diacetyllactosediamine structure, suggesting they can be applied to large-scale analyses.
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Affiliation(s)
- Nobuaki Miura
- Division of Bioinformatics, Niigata University Graduate School of Medical and Dental Sciences, 2-5274 Gakkocho-dori, Niigata 951-8514, Japan
- Correspondence: (N.M.); (J.-i.F.)
| | - Hisatoshi Hanamatsu
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Kita 21, Nishi 11, Sapporo 001-0021, Japan
| | - Ikuko Yokota
- Division of Glyco-Systems Biology, Institute for Glyco-Core Research, Tokai National Higher Education and Research System, 65 Tsurumai-cho, Nagoya 466-8550, Japan
| | - Keiko Akasaka-Manya
- Molecular Glycobiology, Research Team for Mechanism of Aging, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, 35-2 Sakaecho, Tokyo 173-0015, Japan
| | - Hiroshi Manya
- Molecular Glycobiology, Research Team for Mechanism of Aging, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, 35-2 Sakaecho, Tokyo 173-0015, Japan
| | - Tamao Endo
- Molecular Glycobiology, Research Team for Mechanism of Aging, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, 35-2 Sakaecho, Tokyo 173-0015, Japan
| | - Yasuro Shinohara
- Graduate School of Pharmaceutical Sciences, Kinjo Gakuin University, Nagoya 463-8521, Japan
| | - Jun-ichi Furukawa
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Kita 21, Nishi 11, Sapporo 001-0021, Japan
- Division of Glyco-Systems Biology, Institute for Glyco-Core Research, Tokai National Higher Education and Research System, 65 Tsurumai-cho, Nagoya 466-8550, Japan
- Correspondence: (N.M.); (J.-i.F.)
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30
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Abstract
Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.
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Affiliation(s)
- Daniel Bojar
- Department
of Chemistry and Molecular Biology, University
of Gothenburg, Gothenburg 41390, Sweden
- Wallenberg
Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg 41390, Sweden
| | - Frederique Lisacek
- Proteome
Informatics Group, Swiss Institute of Bioinformatics, CH-1227 Geneva, Switzerland
- Computer
Science Department & Section of Biology, University of Geneva, route de Drize 7, CH-1227, Geneva, Switzerland
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31
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Hayes C, Daponte V, Mariethoz J, Lisacek F. This is GlycoQL. Bioinformatics 2022; 38:ii162-ii167. [PMID: 36124803 DOI: 10.1093/bioinformatics/btac500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
MOTIVATION We have previously designed and implemented a tree-based ontology to represent glycan structures with the aim of searching these structures with a glyco-driven syntax. This resulted in creating the GlySTreeM knowledge-base as a linchpin of the structural matching procedure and we now introduce a query language, called GlycoQL, for the actual implementation of a glycan structure search. RESULTS The methodology is described and illustrated with a use-case focused on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike protein glycosylation. We show how to enhance site annotation with federated queries involving UniProt and GlyConnect, our glycoprotein database. AVAILABILITY AND IMPLEMENTATION https://glyconnect.expasy.org/glycoql/.
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Affiliation(s)
- Catherine Hayes
- Department of Computer Science, University of Geneva, Geneva 1227, Switzerland.,Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva 1211, Switzerland
| | - Vincenzo Daponte
- Department of Computer Science, University of Geneva, Geneva 1227, Switzerland.,Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva 1211, Switzerland
| | - Julien Mariethoz
- Department of Computer Science, University of Geneva, Geneva 1227, Switzerland.,Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva 1211, Switzerland
| | - Frederique Lisacek
- Department of Computer Science, University of Geneva, Geneva 1227, Switzerland.,Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva 1211, Switzerland.,Section of Biology, University of Geneva, Geneva 1211, Switzerland
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32
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Krawczyk L, Semwal S, Soubhye J, Lemri Ouadriri S, Prévost M, Van Antwerpen P, Roos G, Bouckaert J. Native glycosylation and binding of the antidepressant paroxetine in a low-resolution crystal structure of human myeloperoxidase. Acta Crystallogr D Struct Biol 2022; 78:1099-1109. [PMID: 36048150 PMCID: PMC9435594 DOI: 10.1107/s2059798322007082] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/10/2022] [Indexed: 11/10/2022] Open
Abstract
Myeloperoxidase, prepared from human neutrophil granulocytes, was crystallized in complex with the serotonin-transporter inhibitor paroxetine in crystals containing eight monomers in the asymmetric unit. Each protomer shows up to five asparagine-linked glycan structures. The strategies used and the difficulties encountered in the building and refinement of glycosylation for their improved presentation in the PDB are explained. Human myeloperoxidase (MPO) utilizes hydrogen peroxide to oxidize organic compounds and as such plays an essential role in cell-component synthesis, in metabolic and elimination pathways, and in the front-line defence against pathogens. Moreover, MPO is increasingly being reported to play a role in inflammation. The enzymatic activity of MPO has also been shown to depend on its glycosylation. Mammalian MPO crystal structures deposited in the Protein Data Bank (PDB) present only a partial identification of their glycosylation. Here, a newly obtained crystal structure of MPO containing four disulfide-linked dimers and showing an elaborate collection of glycans is reported. These are compared with the glycans identified in proteomics studies and from 18 human MPO structures available in the PDB. The crystal structure also contains bound paroxetine, a blocker of serotonin reuptake that has previously been identified as an irreversible inhibitor of MPO, in the presence of thiocyanate, a physiological substrate of MPO.
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Analysis of Minor Proteins Present in Breast Milk by Using WGA Lectin. CHILDREN 2022; 9:children9071084. [PMID: 35884068 PMCID: PMC9318462 DOI: 10.3390/children9071084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 07/13/2022] [Accepted: 07/15/2022] [Indexed: 11/16/2022]
Abstract
Breast milk is a complex and dynamic biological fluid and considered an essential source of nutrition in early life. In its composition, the proteins have a relevant biological activity and are related to the multiple benefits demonstrated when compared with artificial milks derived from cow’s milk. Understanding human milk composition provides an important tool for health care providers toward the management of infant feeding and the establishment of breastfeeding. In this work, a new technique was developed to increase the knowledge of human milk, because many of the components remain unknown. To isolate minor proteins present in breast milk by using WGA lectin, breast milk was centrifuged to remove cells and separate the fat phase from the serum phase. The serum obtained was separated into two groups: control (n = 3; whole serum sample from mature milk) and WGA lectin (n = 3; sample processed with WGA lectin to isolate glycosylated proteins). The samples were analyzed by high-performance liquid chromatography coupled to mass spectrometry (HPLC/MS). A total of 84 different proteins were identified from all of the samples. In the WGA lectin group, 55 different proteins were isolated, 77% of which had biological functions related to the immune response. Of these proteins, there were eight WGA lectin group exclusives, and two had not previously been described in breast milk (polyubiquitin-B and POTE ankyrin domain family member F). Isolation by WGA lectin is a useful technique to detect minor proteins in breast milk and to identify proteins that could not be observed in whole serum.
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In silico analysis of the human milk oligosaccharide glycome reveals key enzymes of their biosynthesis. Sci Rep 2022; 12:10846. [PMID: 35760821 PMCID: PMC9237113 DOI: 10.1038/s41598-022-14260-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 06/03/2022] [Indexed: 11/09/2022] Open
Abstract
Human milk oligosaccharides (HMOs) form the third most abundant component of human milk and are known to convey several benefits to the neonate, including protection from viral and bacterial pathogens, training of the immune system, and influencing the gut microbiome. As HMO production during lactation is driven by enzymes that are common to other glycosylation processes, we adapted a model of mucin-type GalNAc-linked glycosylation enzymes to act on free lactose. We identified a subset of 11 enzyme activities that can account for 206 of 226 distinct HMOs isolated from human milk and constructed a biosynthetic reaction network that identifies 5 new core HMO structures. A comparison of monosaccharide compositions demonstrated that the model was able to discriminate between two possible groups of intermediates between major subnetworks, and to assign possible structures to several previously uncharacterised HMOs. The effect of enzyme knockouts is presented, identifying β-1,4-galactosyltransferase and β-1,3-N-acetylglucosaminyltransferase as key enzyme activities involved in the generation of the observed HMO glycosylation patterns. The model also provides a synthesis chassis for the most common HMOs found in lactating mothers.
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Saghaleyni R, Malm M, Moruzzi N, Zrimec J, Razavi R, Wistbacka N, Thorell H, Pintar A, Hober A, Edfors F, Chotteau V, Berggren PO, Grassi L, Zelezniak A, Svensson T, Hatton D, Nielsen J, Robinson JL, Rockberg J. Enhanced metabolism and negative regulation of ER stress support higher erythropoietin production in HEK293 cells. Cell Rep 2022; 39:110936. [PMID: 35705050 DOI: 10.1016/j.celrep.2022.110936] [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: 09/28/2020] [Revised: 01/05/2022] [Accepted: 05/18/2022] [Indexed: 11/16/2022] Open
Abstract
Recombinant protein production can cause severe stress on cellular metabolism, resulting in limited titer and product quality. To investigate cellular and metabolic characteristics associated with these limitations, we compare HEK293 clones producing either erythropoietin (EPO) (secretory) or GFP (non-secretory) protein at different rates. Transcriptomic and functional analyses indicate significantly higher metabolism and oxidative phosphorylation in EPO producers compared with parental and GFP cells. In addition, ribosomal genes exhibit specific expression patterns depending on the recombinant protein and the production rate. In a clone displaying a dramatically increased EPO secretion, we detect higher gene expression related to negative regulation of endoplasmic reticulum (ER) stress, including upregulation of ATF6B, which aids EPO production in a subset of clones by overexpression or small interfering RNA (siRNA) knockdown. Our results offer potential target pathways and genes for further development of the secretory power in mammalian cell factories.
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Affiliation(s)
- Rasool Saghaleyni
- Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden
| | - Magdalena Malm
- KTH - Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, Department of Protein Science, 106 91 Stockholm, Sweden
| | - Noah Moruzzi
- The Rolf Luft Research Center for Diabetes and Endocrinology, Department of Molecular Medicine and Surgery, Karolinska Institute, 17176 Stockholm, Sweden
| | - Jan Zrimec
- Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden
| | - Ronia Razavi
- KTH - Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, Department of Protein Science, 106 91 Stockholm, Sweden
| | - Num Wistbacka
- KTH - Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, Department of Protein Science, 106 91 Stockholm, Sweden
| | - Hannes Thorell
- KTH - Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, Department of Protein Science, 106 91 Stockholm, Sweden
| | - Anton Pintar
- KTH - Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, Department of Protein Science, 106 91 Stockholm, Sweden
| | - Andreas Hober
- Science for Life Laboratory, KTH - Royal Institute of Technology, 171 65 Solna, Sweden
| | - Fredrik Edfors
- Science for Life Laboratory, KTH - Royal Institute of Technology, 171 65 Solna, Sweden
| | - Veronique Chotteau
- KTH - Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, Department of Industrial Biotechnology, 106 91 Stockholm, Sweden
| | - Per-Olof Berggren
- The Rolf Luft Research Center for Diabetes and Endocrinology, Department of Molecular Medicine and Surgery, Karolinska Institute, 17176 Stockholm, Sweden
| | - Luigi Grassi
- Cell Culture & Fermentation Sciences, BioPharmaceutical Development, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Aleksej Zelezniak
- Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden
| | - Thomas Svensson
- Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Department of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, 41258 Gothenburg, Sweden
| | - Diane Hatton
- Cell Culture & Fermentation Sciences, BioPharmaceutical Development, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Jonathan L Robinson
- Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Department of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, 41258 Gothenburg, Sweden.
| | - Johan Rockberg
- KTH - Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology, and Health, Department of Protein Science, 106 91 Stockholm, Sweden.
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Flevaris K, Kontoravdi C. Immunoglobulin G N-glycan Biomarkers for Autoimmune Diseases: Current State and a Glycoinformatics Perspective. Int J Mol Sci 2022; 23:ijms23095180. [PMID: 35563570 PMCID: PMC9100869 DOI: 10.3390/ijms23095180] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 02/04/2023] Open
Abstract
The effective treatment of autoimmune disorders can greatly benefit from disease-specific biomarkers that are functionally involved in immune system regulation and can be collected through minimally invasive procedures. In this regard, human serum IgG N-glycans are promising for uncovering disease predisposition and monitoring progression, and for the identification of specific molecular targets for advanced therapies. In particular, the IgG N-glycome in diseased tissues is considered to be disease-dependent; thus, specific glycan structures may be involved in the pathophysiology of autoimmune diseases. This study provides a critical overview of the literature on human IgG N-glycomics, with a focus on the identification of disease-specific glycan alterations. In order to expedite the establishment of clinically-relevant N-glycan biomarkers, the employment of advanced computational tools for the interpretation of clinical data and their relationship with the underlying molecular mechanisms may be critical. Glycoinformatics tools, including artificial intelligence and systems glycobiology approaches, are reviewed for their potential to provide insight into patient stratification and disease etiology. Challenges in the integration of such glycoinformatics approaches in N-glycan biomarker research are critically discussed.
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Pujić I, Perreault H. Recent advancements in glycoproteomic studies: Glycopeptide enrichment and derivatization, characterization of glycosylation in SARS CoV2, and interacting glycoproteins. MASS SPECTROMETRY REVIEWS 2022; 41:488-507. [PMID: 33393161 DOI: 10.1002/mas.21679] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 12/13/2020] [Accepted: 12/16/2020] [Indexed: 06/12/2023]
Abstract
Proteomics studies allow for the determination of the identity, amount, and interactions of proteins under specific conditions that allow the biological state of an organism to ultimately change. These conditions can be either beneficial or detrimental. Diseases are due to detrimental changes caused by either protein overexpression or underexpression caused by as a result of a mutation or posttranslational modifications (PTM), among other factors. Identification of disease biomarkers through proteomics can be potentially used as clinical information for diagnostics. Common biomarkers to look for include PTM. For example, aberrant glycosylation of proteins is a common marker and will be a focus of interest in this review. A common way to analyze glycoproteins is by glycoproteomics involving mass spectrometry. Due to factors such as micro- and macroheterogeneity which result in a lower abundance of each version of a glycoprotein, it is difficult to obtain meaningful results unless rigorous sample preparation procedures are in place. Microheterogeneity represents the diversity of glycans at a single site, whereas macroheterogeneity depicts glycosylation levels at each site of a protein. Enrichment and derivatization of glycopeptides help to overcome these limitations. Over the time range of 2016 to 2020, several methods have been proposed in the literature and have contributed to drastically improve the outcome of glycosylation analysis, as presented in the sampling surveyed in this review. As a current topic in 2020, glycoproteins carried by pathogens can also cause disease and this is seen with SARS CoV2, causing the COVID-19 pandemic. This review will discuss glycoproteomic studies of the spike glycoprotein and interacting proteins such as the ACE2 receptor.
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Affiliation(s)
- Ivona Pujić
- Chemistry Department, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Hélène Perreault
- Chemistry Department, University of Manitoba, Winnipeg, Manitoba, Canada
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38
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Bai X, Buckle AM, Vladar EK, Janoff EN, Khare R, Ordway D, Beckham D, Fornis LB, Majluf-Cruz A, Fugit RV, Freed BM, Kim S, Sandhaus RA, Chan ED. Enoxaparin augments alpha-1-antitrypsin inhibition of TMPRSS2, a promising drug combination against COVID-19. Sci Rep 2022; 12:5207. [PMID: 35338216 PMCID: PMC8953970 DOI: 10.1038/s41598-022-09133-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/09/2022] [Indexed: 02/07/2023] Open
Abstract
The cell surface serine protease Transmembrane Protease 2 (TMPRSS2) is required to cleave the spike protein of SARS-CoV-2 for viral entry into cells. We determined whether negatively-charged heparin enhanced TMPRSS2 inhibition by alpha-1-antitrypsin (AAT). TMPRSS2 activity was determined in HEK293T cells overexpressing TMPRSS2. We quantified infection of primary human airway epithelial cells (hAEc) with human coronavirus 229E (HCoV-229E) by immunostaining for the nucleocapsid protein and by the plaque assay. Detailed molecular modeling was undertaken with the heparin-TMPRSS2-AAT ternary complex. Enoxaparin enhanced AAT inhibition of both TMPRSS2 activity and infection of hAEc with HCoV-229E. Underlying these findings, detailed molecular modeling revealed that: (i) the reactive center loop of AAT adopts an inhibitory-competent conformation compared with the crystal structure of TMPRSS2 bound to an exogenous (nafamostat) or endogenous (HAI-2) TMPRSS2 inhibitor and (ii) negatively-charged heparin bridges adjacent electropositive patches at the TMPRSS2-AAT interface, neutralizing otherwise repulsive forces. In conclusion, enoxaparin enhances AAT inhibition of both TMPRSS2 and coronavirus infection. Such host-directed therapy is less likely to be affected by SARS-CoV-2 mutations. Furthermore, given the known anti-inflammatory activities of both AAT and heparin, this form of treatment may target both the virus and the excessive inflammatory consequences of severe COVID-19.
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Affiliation(s)
- Xiyuan Bai
- grid.422100.50000 0000 9751 469XDepartment of Medicine, Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO USA ,grid.240341.00000 0004 0396 0728Department of Academic Affairs and Medicine, National Jewish Health, Denver, CO USA ,grid.430503.10000 0001 0703 675XDivision of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.240341.00000 0004 0396 0728National Jewish Health, D509, Neustadt Building, 1400 Jackson Street, Denver, CO 80206 USA
| | - Ashley M. Buckle
- grid.1002.30000 0004 1936 7857Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC Australia
| | - Eszter K. Vladar
- grid.430503.10000 0001 0703 675XDivision of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Edward N. Janoff
- grid.422100.50000 0000 9751 469XDepartment of Medicine, Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO USA ,grid.430503.10000 0001 0703 675XDivision of Infectious Diseases, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Reeti Khare
- grid.240341.00000 0004 0396 0728Mycobacteriology Laboratory, Advance Diagnostics, National Jewish Health, Denver, CO USA
| | - Diane Ordway
- grid.47894.360000 0004 1936 8083Department of Microbiology, Immunlogy, and Pathology, Colorado State University, Fort Collins, CO USA
| | - David Beckham
- grid.430503.10000 0001 0703 675XDivision of Infectious Diseases, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Lorelenn B. Fornis
- grid.240341.00000 0004 0396 0728Department of Academic Affairs and Medicine, National Jewish Health, Denver, CO USA
| | - Abraham Majluf-Cruz
- grid.419157.f0000 0001 1091 9430Unidad de Investigacion Medica en Trombosis, Hemostasia y Aterogenesis, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Randolph V. Fugit
- grid.422100.50000 0000 9751 469XDepartment of Pharmacy, Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO USA
| | - Brian M. Freed
- grid.430503.10000 0001 0703 675XDepartment of Immunology, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Soohyun Kim
- grid.258676.80000 0004 0532 8339Laboratory of Cytokine Immunology, Department of Biomedical Science and Technology, Konkuk University, Seoul, South Korea ,grid.258676.80000 0004 0532 8339College of Veterinary Medicine, Konkuk University, Seoul, South Korea
| | - Robert A. Sandhaus
- grid.240341.00000 0004 0396 0728Department of Academic Affairs and Medicine, National Jewish Health, Denver, CO USA
| | - Edward D. Chan
- grid.422100.50000 0000 9751 469XDepartment of Medicine, Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO USA ,grid.240341.00000 0004 0396 0728Department of Academic Affairs and Medicine, National Jewish Health, Denver, CO USA ,grid.430503.10000 0001 0703 675XDivision of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.240341.00000 0004 0396 0728National Jewish Health, D509, Neustadt Building, 1400 Jackson Street, Denver, CO 80206 USA
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Mariethoz J, Alocci D, Karlsson NG, Packer NH, Lisacek F. An Interactive View of Glycosylation. Methods Mol Biol 2022; 2370:41-65. [PMID: 34611864 DOI: 10.1007/978-1-0716-1685-7_3] [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: 06/13/2023]
Abstract
The present chapter focuses on the interactive and explorative aspects of bioinformatics resources that have been recently released in glycobiology. The comparative analysis of data in a field where knowledge is scattered, incomplete, and disconnected from main biology requires efficient visualization, integration, and interactive tools that are currently only partially implemented. This overview highlights converging efforts toward building a consistent picture of protein glycosylation.
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Affiliation(s)
- Julien Mariethoz
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
- Computer Science Department, University of Geneva, Geneva, Switzerland
| | - Davide Alocci
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | - Niclas G Karlsson
- Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nicolle H Packer
- Department of Molecular Sciences and ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, NSW, Australia
- Institute for Glycomics, Griffith University, Gold Coast, QLD, Australia
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, University of Geneva, Geneva, Switzerland.
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40
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Coutinho JVP, Macedo-da-Silva J, Mule SN, Kronenberger T, Rosa-Fernandes L, Wrenger C, Palmisano G. Glycoprotein molecular dynamics analysis: SARS-CoV-2 spike glycoprotein case study. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 131:277-309. [PMID: 35871894 PMCID: PMC9181370 DOI: 10.1016/bs.apcsb.2022.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Molecular Dynamics (MD) is a method used to calculate the movement of atoms and molecules broadly applied to several aspects of science. It involves computational simulation, which makes it, at first glance, not easily accessible. The rise of several automated tools to perform molecular simulations has allowed researchers to navigate through the various steps of MD. This enables to elucidate structural properties of proteins that could not be analyzed otherwise, such as the impact of glycosylation. Glycosylation dictates the physicochemical and biological properties of a protein modulating its solubility, stability, resistance to proteolysis, interaction partners, enzymatic activity, binding and recognition. Given the high conformational and compositional diversity of the glycan chains, assessing their influence on the protein structure is challenging using conventional analytical techniques. In this manuscript, we present a step-by-step workflow to build and perform MD analysis of glycoproteins focusing on the SPIKE glycoprotein of SARS-CoV-2 to appraise the impact of glycans in structure stabilization and antibody occlusion.
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Affiliation(s)
| | - Janaina Macedo-da-Silva
- 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
| | - Thales Kronenberger
- Department of Internal Medicine VIII, University Hospital Tuebingen, Tuebingen, Germany,Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmaceutical Sciences, Eberhard-Karls-Universität, Tuebingen, Germany,Cluster of Excellence iFIT (EXC 2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tuebingen, Tuebingen, Germany,Tuebingen Center for Academic Drug Discovery & Development (TüCAD2), Tuebingen, Germany
| | - Livia Rosa-Fernandes
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Carsten Wrenger
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Giuseppe Palmisano
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil,Faculty of Science and engineering, Macquarie University, Sydney, NSW, Australia,Corresponding author:
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Aoki-Kinoshita KF. Functions of Glycosylation and Related Web Resources for Its Prediction. Methods Mol Biol 2022; 2499:135-144. [PMID: 35696078 DOI: 10.1007/978-1-0716-2317-6_6] [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: 06/15/2023]
Abstract
Glycosylation involves the attachment of carbohydrate sugar chains, or glycans, onto an amino acid residue of a protein. These glycans are often branched structures and serve to modulate the function of proteins. Glycans are synthesized through a complex process of enzymatic reactions that occur in the Golgi apparatus in mammalian systems. Because there is currently no sequencer for glycans, technologies such as mass spectrometry is used to characterize glycans in a biological sample to ascertain its glycome. This is a tedious process that requires high levels of expertise and equipment. Thus, the enzymes that work on glycans, called glycogenes or glycoenzymes, have been studied to better understand glycan function. With the development of glycan-related databases and a glycan repository, bioinformatics approaches have attempted to predict the glycosylation pathway and the glycosylation sites on proteins. This chapter introduces these methods and related Web resources for understanding glycan function.
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Dealing with the Ambiguity of Glycan Substructure Search. MOLECULES (BASEL, SWITZERLAND) 2021; 27:molecules27010065. [PMID: 35011294 PMCID: PMC8746581 DOI: 10.3390/molecules27010065] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 12/17/2021] [Accepted: 12/17/2021] [Indexed: 01/15/2023]
Abstract
The level of ambiguity in describing glycan structure has significantly increased with the upsurge of large-scale glycomics and glycoproteomics experiments. Consequently, an ontology-based model appears as an appropriate solution for navigating these data. However, navigation is not sufficient and the model should also enable advanced search and comparison. A new ontology with a tree logical structure is introduced to represent glycan structures irrespective of the precision of molecular details. The model heavily relies on the GlycoCT encoding of glycan structures. Its implementation in the GlySTreeM knowledge base was validated with GlyConnect data and benchmarked with the Glycowork library. GlySTreeM is shown to be fast, consistent, reliable and more flexible than existing solutions for matching parts of or whole glycan structures. The model is also well suited for painless future expansion.
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Chen YJ, Yen TC, Lin YH, Chen YL, Khoo KH, Chen YJ. ZIC-cHILIC-Based StageTip for Simultaneous Glycopeptide Enrichment and Fractionation toward Large-Scale N-Sialoglycoproteomics. Anal Chem 2021; 93:15931-15940. [PMID: 34780171 DOI: 10.1021/acs.analchem.1c03224] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Alterations of protein glycosylation are closely related with pathophysiological regulation. Due to the structural macro- and microheterogeneity, low stoichiometry, and low ionization efficiency of glycopeptides, high-performance tools to enrich glycopeptides, especially the negatively charged and labile sialoglycopeptides, are essential to enhance the identification of the underexplored glycoproteome. Here, we present the first implementation of zwitterionic hydrophilic interaction chromatography with the exposed choline group (ZIC-cHILIC) in StageTip for simultaneous enrichment and fractionation of intact glycopeptides. In a model study using lung cancer cells, early elution by a high percentage of acetonitrile prominently prefilters nonglycopeptides, facilitating high enrichment specificity for glycopeptides (92-96%) and sialoglycopeptides (77-89%) in the subsequent hydrophilic fractions. The stepwise elution shows a high glycopeptide fractionation efficiency by a <10% overlap of glycopeptides between adjacent fractions. Most importantly, the ZIC-cHILIC stepwise strategy demonstrated good reproducibility (>80% in triplicate analysis) as well as superior coverage of 4.6- to 12.0-fold and 2.1- to 35.6-fold more glycopeptides and sialoglycopeptides compared to conventional TiO2 and ZIC-HILIC, respectively. To the best of our knowledge, the result with 2742 sialoglycopeptides among 7367 unique glycopeptides and 166 glycans from 2434 N-glycosites of 1118 glycoproteins (Byonic score > 100) provides one of the deepest glycoproteomic profiles in single-cell type. Without the immunoprecipitation step, the large-scale glycoproteomic atlas also reveals site-specific glycosylation of many druggable receptor proteins, such as EGFR, MET, ERBB2, ERBB3, AXL, and IGF1R. The demonstrated high enrichment specificity and identification depth show that stepwise ZIC-cHILIC is an efficient method to explore the under-represented sialoglycoproteome.
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Affiliation(s)
- Yi-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Ta-Chi Yen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.,Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Yu-Hsien Lin
- Department of Chemistry, National Taiwan Normal University, Taipei 11677, Taiwan
| | - Yan-Lin Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Kay-Hooi Khoo
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.,Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
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Omenn GS, Lane L, Overall CM, Paik YK, Cristea IM, Corrales FJ, Lindskog C, Weintraub S, Roehrl MHA, Liu S, Bandeira N, Srivastava S, Chen YJ, Aebersold R, Moritz RL, Deutsch EW. Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project. J Proteome Res 2021; 20:5227-5240. [PMID: 34670092 DOI: 10.1021/acs.jproteome.1c00590] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.
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Affiliation(s)
- Gilbert S Omenn
- University of Michigan, Ann Arbor, Michigan 48109, United States.,Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Lydie Lane
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | | | - Young-Ki Paik
- Yonsei Proteome Research Center and Yonsei University, Seoul 03722, Korea
| | - Ileana M Cristea
- Princeton University, Princeton, New Jersey 08544, United States
| | | | | | - Susan Weintraub
- University of Texas Health, San Antonio, San Antonio, Texas 78229-3900, United States
| | - Michael H A Roehrl
- Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States
| | - Siqi Liu
- BGI Group, Shenzhen 518083, China
| | - Nuno Bandeira
- University of California, San Diego, La Jolla, California 92093, United States
| | | | - Yu-Ju Chen
- National Taiwan University, Academia Sinica, Nankang, Taipei 11529, Taiwan
| | - Ruedi Aebersold
- ETH-Zurich and University of Zurich, 8092 Zurich, Switzerland
| | - Robert L Moritz
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
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45
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Veličković D, Bečejac T, Mamedov S, Sharma K, Ambalavanan N, Alexandrov T, Anderton CR. Rapid Automated Annotation and Analysis of N-Glycan Mass Spectrometry Imaging Data Sets Using NGlycDB in METASPACE. Anal Chem 2021; 93:13421-13425. [PMID: 34581565 DOI: 10.1021/acs.analchem.1c02347] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Imaging N-glycan spatial distribution in tissues using mass spectrometry imaging (MSI) is emerging as a promising tool in biological and clinical applications. However, there is currently no high-throughput tool for visualization and molecular annotation of N-glycans in MSI data, which significantly slows down data processing and hampers the applicability of this approach. Here, we present how METASPACE, an open-source cloud engine for molecular annotation of MSI data, can be used to automatically annotate, visualize, analyze, and interpret high-resolution mass spectrometry-based spatial N-glycomics data. METASPACE is an emerging tool in spatial metabolomics, but the lack of compatible glycan databases has limited its application for comprehensive N-glycan annotations from MSI data sets. We created NGlycDB, a public database of N-glycans, by adapting available glycan databases. We demonstrate the applicability of NGlycDB in METASPACE by analyzing MALDI-MSI data from formalin-fixed paraffin-embedded (FFPE) human kidney and mouse lung tissue sections. We added NGlycDB to METASPACE for public use, thus, facilitating applications of MSI in glycobiology.
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Affiliation(s)
- Dušan Veličković
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Tamara Bečejac
- Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Sergii Mamedov
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany
| | - Kumar Sharma
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health, San Antonio, Texas 78229, United States
| | - Namasivayam Ambalavanan
- Department of Pediatrics, School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama 35294, United States
| | - Theodore Alexandrov
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany.,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany.,Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, California 92093, United States
| | - Christopher R Anderton
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States.,Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health, San Antonio, Texas 78229, United States
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46
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Oliveira T, Zhang M, Joo EJ, Abdel-Azim H, Chen CW, Yang L, Chou CH, Qin X, Chen J, Alagesan K, Almeida A, Jacob F, Packer NH, von Itzstein M, Heisterkamp N, Kolarich D. Glycoproteome remodeling in MLL-rearranged B-cell precursor acute lymphoblastic leukemia. Am J Cancer Res 2021; 11:9519-9537. [PMID: 34646384 PMCID: PMC8490503 DOI: 10.7150/thno.65398] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/03/2021] [Indexed: 01/13/2023] Open
Abstract
B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with mixed-lineage leukemia gene rearrangement (MLL-r) is a poor-prognosis subtype for which additional therapeutic targets are urgently needed. Currently no multi-omics data set for primary MLL r patient cells exists that integrates transcriptomics, proteomics and glycomics to gain an inclusive picture of theranostic targets. Methods: We have integrated transcriptomics, proteomics and glycomics to i) obtain the first inclusive picture of primary patient BCP-ALL cells and identify molecular signatures that distinguish leukemic from normal precursor B-cells and ii) better understand the benefits and limitations of the applied technologies to deliver deep molecular sequence data across major cellular biopolymers. Results: MLL-r cells feature an extensive remodeling of their glycocalyx, with increased levels of Core 2-type O-glycans and complex N-glycans as well as significant changes in sialylation and fucosylation. Notably, glycosaminoglycan remodeling from chondroitin sulfate to heparan sulfate was observed. A survival screen, to determine if glycan remodeling enzymes are redundant, identified MGAT1 and NGLY1, essential components of the N-glycosylation/degradation pathway, as highly relevant within this in vitro screening. OGT and OGA, unique enzymes that regulate intracellular O-GlcNAcylation, were also indispensable. Transcriptomics and proteomics further identified Fes and GALNT7-mediated glycosylation as possible therapeutic targets. While there is overall good correlation between transcriptomics and proteomics data, we demonstrate that a systematic combined multi-omics approach delivers important diagnostic information that is missed when applying a single omics technology. Conclusions: Apart from confirming well-known MLL-r BCP-ALL glycoprotein markers, our integrated multi-omics workflow discovered previously unidentified diagnostic/therapeutic protein targets.
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Affiliation(s)
- Tiago Oliveira
- Institute for Glycomics, Griffith University, Gold Coast Campus, QLD, Australia
| | - Mingfeng Zhang
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA
| | - Eun Ji Joo
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA
| | - Hisham Abdel-Azim
- Division of Hematology/Oncology and Bone Marrow Transplant, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Chun-Wei Chen
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA
| | - Lu Yang
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA
| | - Chih-Hsing Chou
- Division of Hematology/Oncology and Bone Marrow Transplant, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Xi Qin
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA
| | - Jianjun Chen
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA
| | - Kathirvel Alagesan
- Institute for Glycomics, Griffith University, Gold Coast Campus, QLD, Australia
| | - Andreia Almeida
- Institute for Glycomics, Griffith University, Gold Coast Campus, QLD, Australia
| | - Francis Jacob
- Glyco-Oncology, Ovarian Cancer Research, Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Nicolle H Packer
- Institute for Glycomics, Griffith University, Gold Coast Campus, QLD, Australia.,Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW, Australia.,ARC Centre of Excellence for Nanoscale BioPhotonics, Griffith University, QLD and Macquarie University, NSW, Australia
| | - Mark von Itzstein
- Institute for Glycomics, Griffith University, Gold Coast Campus, QLD, Australia
| | - Nora Heisterkamp
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA.,✉ Corresponding authors: Equal contributions of Nora Heisterkamp, E-mail: ; and Daniel Kolarich, E-mail:
| | - Daniel Kolarich
- Institute for Glycomics, Griffith University, Gold Coast Campus, QLD, Australia.,ARC Centre of Excellence for Nanoscale BioPhotonics, Griffith University, QLD and Macquarie University, NSW, Australia.,✉ Corresponding authors: Equal contributions of Nora Heisterkamp, E-mail: ; and Daniel Kolarich, E-mail:
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47
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Donohoo KB, Wang J, Goli M, Yu A, Peng W, Hakim MA, Mechref Y. Advances in mass spectrometry-based glycomics-An update covering the period 2017-2021. Electrophoresis 2021; 43:119-142. [PMID: 34505713 DOI: 10.1002/elps.202100199] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/20/2021] [Accepted: 08/25/2021] [Indexed: 12/21/2022]
Abstract
The wide variety of chemical properties and biological functions found in proteins is attained via post-translational modifications like glycosylation. Covalently bonded to proteins, glycans play a critical role in cell activity. Complex structures with microheterogeneity, the glycan structures that are associated with proteins are difficult to analyze comprehensively. Recent advances in sample preparation methods, separation techniques, and MS have facilitated the quantitation and structural elucidation of glycans. This review focuses on highlighting advances in MS-based techniques for glycomic analysis that occurred over the last 5 years (2017-2021) as an update to the previous review on the subject. The topics of discussion will include progress in glycomic workflow such as glycan release, purification, derivatization, and separation as well as the topics of ionization, tandem MS, and separation techniques that can be coupled with MS. Additionally, bioinformatics tools used for the analysis of glycans will be described.
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Affiliation(s)
- Kaitlyn B Donohoo
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
| | - Junyao Wang
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
| | - Mona Goli
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
| | - Aiying Yu
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
| | - Wenjing Peng
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
| | - Md Abdul Hakim
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
| | - Yehia Mechref
- Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas
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48
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Oliveira T, Thaysen-Andersen M, Packer NH, Kolarich D. The Hitchhiker's guide to glycoproteomics. Biochem Soc Trans 2021; 49:1643-1662. [PMID: 34282822 PMCID: PMC8421054 DOI: 10.1042/bst20200879] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 06/03/2021] [Accepted: 06/23/2021] [Indexed: 02/06/2023]
Abstract
Protein glycosylation is one of the most common post-translational modifications that are essential for cell function across all domains of life. Changes in glycosylation are considered a hallmark of many diseases, thus making glycoproteins important diagnostic and prognostic biomarker candidates and therapeutic targets. Glycoproteomics, the study of glycans and their carrier proteins in a system-wide context, is becoming a powerful tool in glycobiology that enables the functional analysis of protein glycosylation. This 'Hitchhiker's guide to glycoproteomics' is intended as a starting point for anyone who wants to explore the emerging world of glycoproteomics. The review moves from the techniques that have been developed for the characterisation of single glycoproteins to technologies that may be used for a successful complex glycoproteome characterisation. Examples of the variety of approaches, methodologies, and technologies currently used in the field are given. This review introduces the common strategies to capture glycoprotein-specific and system-wide glycoproteome data from tissues, body fluids, or cells, and a perspective on how integration into a multi-omics workflow enables a deep identification and characterisation of glycoproteins - a class of biomolecules essential in regulating cell function.
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Affiliation(s)
- Tiago Oliveira
- Institute for Glycomics, Griffith University, Gold Coast Campus, Gold Coast, Queensland, Australia
| | | | - Nicolle H. Packer
- Institute for Glycomics, Griffith University, Gold Coast Campus, Gold Coast, Queensland, Australia
- Department of Molecular Sciences, Macquarie University, Sydney, New South Wales, Australia
- ARC Centre of Excellence for Nanoscale BioPhotonics, Griffith University, QLD and Macquarie University, NSW, Australia
| | - Daniel Kolarich
- Institute for Glycomics, Griffith University, Gold Coast Campus, Gold Coast, Queensland, Australia
- ARC Centre of Excellence for Nanoscale BioPhotonics, Griffith University, QLD and Macquarie University, NSW, Australia
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49
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Duvaud S, Gabella C, Lisacek F, Stockinger H, Ioannidis V, Durinx C. Expasy, the Swiss Bioinformatics Resource Portal, as designed by its users. Nucleic Acids Res 2021; 49:W216-W227. [PMID: 33849055 PMCID: PMC8265094 DOI: 10.1093/nar/gkab225] [Citation(s) in RCA: 301] [Impact Index Per Article: 100.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 03/11/2021] [Accepted: 04/01/2021] [Indexed: 12/16/2022] Open
Abstract
The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss) creates, maintains and disseminates a portfolio of reliable and state-of-the-art bioinformatics services and resources for the storage, analysis and interpretation of biological data. Through Expasy (https://www.expasy.org), the Swiss Bioinformatics Resource Portal, the scientific community worldwide, freely accesses more than 160 SIB resources supporting a wide range of life science and biomedical research areas. In 2020, Expasy was redesigned through a user-centric approach, known as User-Centred Design (UCD), whose aim is to create user interfaces that are easy-to-use, efficient and targeting the intended community. This approach, widely used in other fields such as marketing, e-commerce, and design of mobile applications, is still scarcely explored in bioinformatics. In total, around 50 people were actively involved, including internal stakeholders and end-users. In addition to an optimised interface that meets users' needs and expectations, the new version of Expasy provides an up-to-date and accurate description of high-quality resources based on a standardised ontology, allowing to connect functionally-related resources.
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Affiliation(s)
- Séverine Duvaud
- SIB Swiss Institute of Bioinformatics, Quartier Sorge - Bâtiment Amphipôle, CH-1015 Lausanne, Switzerland
| | - Chiara Gabella
- SIB Swiss Institute of Bioinformatics, Quartier Sorge - Bâtiment Amphipôle, CH-1015 Lausanne, Switzerland
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, and Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland.,Section of Biology, University of Geneva, CH-1205 Geneva, Switzerland
| | - Heinz Stockinger
- SIB Swiss Institute of Bioinformatics, Quartier Sorge - Bâtiment Amphipôle, CH-1015 Lausanne, Switzerland
| | - Vassilios Ioannidis
- SIB Swiss Institute of Bioinformatics, Quartier Sorge - Bâtiment Amphipôle, CH-1015 Lausanne, Switzerland
| | - Christine Durinx
- SIB Swiss Institute of Bioinformatics, Quartier Sorge - Bâtiment Amphipôle, CH-1015 Lausanne, Switzerland
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50
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Aoki-Kinoshita KF. Glycome informatics: using systems biology to gain mechanistic insights into glycan biosynthesis. Curr Opin Chem Eng 2021. [DOI: 10.1016/j.coche.2021.100683] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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