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Chettri D, Chirania M, Boro D, Verma AK. Glycoconjugates: Advances in modern medicines and human health. Life Sci 2024; 348:122689. [PMID: 38710281 DOI: 10.1016/j.lfs.2024.122689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/23/2024] [Accepted: 05/03/2024] [Indexed: 05/08/2024]
Abstract
Glycans and their glycoconjugates are complex biomolecules that are crucial for various biological processes. Glycoconjugates are found in all domains of life. They are covalently linked to key biomolecules such as proteins and lipids to play a pivotal role in cell signaling, adhesion, and recognition. The diversity of glycan structures and the associated complexity of glycoconjugates is the reason for their role in intricate biosynthetic pathways. Glycoconjugates play an important role in various diseases where they are actively involved in the immune response as well as in the pathogenicity of infectious diseases. In addition, various autoimmune diseases have been linked to glycosylation defects of different biomolecules, making them an important molecule in the field of medicine. The glycoconjugates have been explored for the development of therapeutics and vaccines, representing a breakthrough in medical science. They also hold significance in research studies to understand the mechanisms behind various biological processes. Finally, glycoconjugates have found an emerging role in various industrial and environmental applications which have been discussed here.
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Affiliation(s)
- Dixita Chettri
- Department of Microbiology, Sikkim University, Gangtok, Sikkim 737102, India
| | - Manisha Chirania
- Department of Microbiology, Sikkim University, Gangtok, Sikkim 737102, India
| | - Deepjyoti Boro
- Department of Microbiology, Sikkim University, Gangtok, Sikkim 737102, India
| | - Anil Kumar Verma
- Department of Microbiology, Sikkim University, Gangtok, Sikkim 737102, India.
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Takahashi Y, Shiota M, Fujita A, Yamada I, Aoki-Kinoshita KF. GlyComb: A novel glycoconjugate data repository that bridges glycomics and proteomics. J Biol Chem 2024; 300:105624. [PMID: 38176651 PMCID: PMC10850976 DOI: 10.1016/j.jbc.2023.105624] [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: 09/30/2023] [Revised: 12/03/2023] [Accepted: 12/26/2023] [Indexed: 01/06/2024] Open
Abstract
The glycosylation of proteins and lipids is known to be closely related to the mechanisms of various diseases such as influenza, cancer, and muscular dystrophy. Therefore, it has become clear that the analysis of post-translational modifications of proteins, including glycosylation, is important to accurately understand the functions of each protein molecule and the interactions among them. In order to conduct large-scale analyses more efficiently, it is essential to promote the accumulation, sharing, and reuse of experimental and analytical data in accordance with the FAIR (Findability, Accessibility, Interoperability, and Re-usability) data principles. However, a FAIR data repository for storing and sharing glycoconjugate information, including glycopeptides and glycoproteins, in a standardized format did not exist. Therefore, we have developed GlyComb (https://glycomb.glycosmos.org) as a new standardized data repository for glycoconjugate data. Currently, GlyComb can assign a unique identifier to a set of glycosylation information associated with a specific peptide sequence or UniProt ID. By standardizing glycoconjugate data via GlyComb identifiers and coordinating with existing web resources such as GlyTouCan and GlycoPOST, a comprehensive system for data submission and data sharing among researchers can be established. Here we introduce how GlyComb is able to integrate the variety of glycoconjugate data already registered in existing data repositories to obtain a better understanding of the available glycopeptides and glycoproteins, and their glycosylation patterns. We also explain how this system can serve as a foundation for a better understanding of glycan function.
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Affiliation(s)
- Yushi Takahashi
- Department of Bioinformatics, Graduate School of Engineering, Soka University, Tokyo, Japan
| | - Masaaki Shiota
- Glycan and Life Systems Integration Center, Faculty of Science and Engineering, Soka University, Tokyo, Japan
| | - Akihiro Fujita
- Glycan and Life Systems Integration Center, Faculty of Science and Engineering, Soka University, Tokyo, Japan
| | - Issaku Yamada
- Laboratory of Glycoinformatics, The Noguchi Institute, Tokyo, Japan
| | - Kiyoko F Aoki-Kinoshita
- Department of Bioinformatics, Graduate School of Engineering, Soka University, Tokyo, Japan; Glycan and Life Systems Integration Center, Faculty of Science and Engineering, Soka University, Tokyo, Japan.
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Groth T, Diehl AD, Gunawan R, Neelamegham S. GlycoEnzOnto: a GlycoEnzyme pathway and molecular function ontology. Bioinformatics 2022; 38:5413-5420. [PMID: 36282863 PMCID: PMC9750110 DOI: 10.1093/bioinformatics/btac704] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/22/2022] [Accepted: 10/24/2022] [Indexed: 12/25/2022] Open
Abstract
MOTIVATION The 'glycoEnzymes' include a set of proteins having related enzymatic, metabolic, transport, structural and cofactor functions. Currently, there is no established ontology to describe glycoEnzyme properties and to relate them to glycan biosynthesis pathways. RESULTS We present GlycoEnzOnto, an ontology describing 403 human glycoEnzymes curated along 139 glycosylation pathways, 134 molecular functions and 22 cellular compartments. The pathways described regulate nucleotide-sugar metabolism, glycosyl-substrate/donor transport, glycan biosynthesis and degradation. The role of each enzyme in the glycosylation initiation, elongation/branching and capping/termination phases is described. IUPAC linear strings present systematic human/machine-readable descriptions of individual reaction steps and enable automated knowledge-based curation of biochemical networks. All GlycoEnzOnto knowledge is integrated with the Gene Ontology biological processes. GlycoEnzOnto enables improved transcript overrepresentation analyses and glycosylation pathway identification compared to other available schema, e.g. KEGG and Reactome. Overall, GlycoEnzOnto represents a holistic glycoinformatics resource for systems-level analyses. AVAILABILITY AND IMPLEMENTATION https://github.com/neel-lab/GlycoEnzOnto. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Theodore Groth
- Department of Chemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
| | - Alexander D Diehl
- Department of Biomedical Informatics, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
| | - Rudiyanto Gunawan
- Department of Chemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
| | - Sriram Neelamegham
- Department of Chemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
- Department of Biomedical Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
- Department of Medicine, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
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Trbojević-Akmačić I, Lageveen-Kammeijer GSM, Heijs B, Petrović T, Deriš H, Wuhrer M, Lauc G. High-Throughput Glycomic Methods. Chem Rev 2022; 122:15865-15913. [PMID: 35797639 PMCID: PMC9614987 DOI: 10.1021/acs.chemrev.1c01031] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.
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Affiliation(s)
| | | | - Bram Heijs
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Tea Petrović
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Helena Deriš
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Manfred Wuhrer
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Gordan Lauc
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
- Faculty
of Pharmacy and Biochemistry, University
of Zagreb, A. Kovačića 1, 10 000 Zagreb, Croatia
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Toukach PV, Shirkovskaya AI. Carbohydrate Structure Database and Other Glycan Databases as an Important Element of Glycoinformatics. RUSSIAN JOURNAL OF BIOORGANIC CHEMISTRY 2022. [DOI: 10.1134/s1068162022030190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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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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Lee S, Ono T, Aoki-Kinoshita K. RDFizing the biosynthetic pathway of E.coli O-antigen to enable semantic sharing of microbiology data. BMC Microbiol 2021; 21:325. [PMID: 34809564 PMCID: PMC8607589 DOI: 10.1186/s12866-021-02384-y] [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: 05/13/2021] [Accepted: 11/02/2021] [Indexed: 11/25/2022] Open
Abstract
Background The abundance of glycomics data that have accumulated has led to the development of many useful databases to aid in the understanding of the function of the glycans and their impact on cellular activity. At the same time, the endeavor for data sharing between glycomics databases with other biological databases have contributed to the creation of new knowledgebases. However, different data types in data description have impeded the data sharing for knowledge integration. To solve this matter, Semantic Web techniques including Resource Description Framework (RDF) and ontology development have been adopted by various groups to standardize the format for data exchange. These semantic data have contributed to the expansion of knowledgebases and hold promises of providing data that can be intelligently processed. On the other hand, bench biologists who are experts in experimental finding are end users and data producers. Therefore, it is indispensable to reduce the technical barrier required for bench biologists to manipulate their experimental data to be compatible with standard formats for data sharing. Results There are many essential concepts and practical techniques for data integration but there is no method to enable researchers to easily apply Semantic Web techniques to their experimental data. We implemented our procedure on unformatted information of E.coli O-antigen structures collected from the web and show how this information can be expressed as formatted data applicable to Semantic Web standards. In particular, we described the E-coli O-antigen biosynthesis pathway using the BioPAX ontology developed to support data exchange between pathway databases. Conclusions The method we implemented to semantically describe O-antigen biosynthesis should be helpful for biologists to understand how glycan information, including relevant pathway reaction data, can be easily shared. We hope this method can contribute to lower the technical barrier that is required when experimental findings are formulated into formal representations and can lead bench scientists to readily participate in the construction of new knowledgebases that are integrated with existing ones. Such integration over the Semantic Web will enable future work in artificial intelligence and machine learning to enable computers to infer new relationships and hypotheses in the life sciences. Supplementary Information The online version contains supplementary material available at 10.1186/s12866-021-02384-y.
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Affiliation(s)
- Sunmyoung Lee
- Graduate School of Engineering; Glycan and Life Systems Integration Center, Soka University, Hachioji, Tokyo, 192-8577, Japan
| | - Tamiko Ono
- Graduate School of Engineering; Glycan and Life Systems Integration Center, Soka University, Hachioji, Tokyo, 192-8577, Japan
| | - Kiyoko Aoki-Kinoshita
- Graduate School of Engineering; Glycan and Life Systems Integration Center, Soka University, Hachioji, Tokyo, 192-8577, Japan.
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