1
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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38925550 DOI: 10.1002/mas.21873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/05/2024] [Accepted: 02/12/2024] [Indexed: 06/28/2024]
Abstract
The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.
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2
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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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3
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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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4
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Huang C, Hou M, Yan J, Wang H, Wang Y, Cao C, Wang Y, Gao H, Ma X, Zheng Y, Bu D, Chai W, Li Y, Sun S. GIPS-Mix for Accurate Identification of Isomeric Components in Glycan Mixtures Using Intelligent Group-Opting Strategy. Anal Chem 2022; 95:811-819. [PMID: 36547394 PMCID: PMC9850354 DOI: 10.1021/acs.analchem.2c02978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Accurate identification of glycan structures is highly desirable as they are intimately linked to their different functions. However, glycan samples generally exist as mixtures with multiple isomeric structures, making assignment of individual glycan components very challenging, even with the aid of multistage mass spectrometry (MSn). Here, we present an approach, GIPS-mix, for assignment of isomeric glycans within a mixture using an intelligent group-opting strategy. Our approach enumerates all possible combinations (groupings) of candidate glycans and opts in the best-matched glycan group(s) based on the similarity between the simulated spectra of each glycan group and the acquired experimental spectra of the mixture. In the case that a single group could not be elected, a tie break is performed by additional MSn scanning using intelligently selected precursors. With 11 standard mixtures and 6 human milk oligosaccharide fractions, we demonstrate the application of GIPS-mix in assignment of individual glycans in mixtures with high accuracy and efficiency.
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Affiliation(s)
- Chuncui Huang
- Institute
of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing100101, China
| | - Meijie Hou
- Key
Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6 Kexueyuan South Road, Beijing100080, China,University
of Chinese Academy of Sciences, 19 Yuquan Road, Beijing100049, China
| | - Jingyu Yan
- Dalian
Institute of Chemical Physics, Chinese Academy of Sciences, Key Laboratory of Separation Science
for Analytical Chemistry, Dalian116023, China
| | - Hui Wang
- Key
Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6 Kexueyuan South Road, Beijing100080, China,University
of Chinese Academy of Sciences, 19 Yuquan Road, Beijing100049, China
| | - Yu Wang
- Key
Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6 Kexueyuan South Road, Beijing100080, China,University
of Chinese Academy of Sciences, 19 Yuquan Road, Beijing100049, China
| | - Cuiyan Cao
- Dalian
Institute of Chemical Physics, Chinese Academy of Sciences, Key Laboratory of Separation Science
for Analytical Chemistry, Dalian116023, China
| | - Yaojun Wang
- College
of Information and Electrical Engineering, China Agricultural University, Beijing100083, China
| | - Huanyu Gao
- Institute
of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing100101, China
| | - Xinyue Ma
- Institute
of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing100101, China,University
of Chinese Academy of Sciences, 19 Yuquan Road, Beijing100049, China
| | - Yi Zheng
- Dalian
Institute of Chemical Physics, Chinese Academy of Sciences, Key Laboratory of Separation Science
for Analytical Chemistry, Dalian116023, China
| | - Dongbo Bu
- Key
Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6 Kexueyuan South Road, Beijing100080, China,University
of Chinese Academy of Sciences, 19 Yuquan Road, Beijing100049, China
| | - Wengang Chai
- Glycosciences
Laboratory, Department of Medicine, Imperial
College London, LondonW12 0NN, United Kingdom,
| | - Yan Li
- Institute
of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing100101, China,University
of Chinese Academy of Sciences, 19 Yuquan Road, Beijing100049, China,
| | - Shiwei Sun
- Key
Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6 Kexueyuan South Road, Beijing100080, China,University
of Chinese Academy of Sciences, 19 Yuquan Road, Beijing100049, China,
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5
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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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6
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Iqbal Z, Sadaf S. Commercial Low Molecular Weight Heparins - Patent Ecosystem and Technology Paradigm for Quality Characterization. J Pharm Innov 2022; 18:1-33. [PMID: 35915630 PMCID: PMC9330979 DOI: 10.1007/s12247-022-09665-7] [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] [Accepted: 07/11/2022] [Indexed: 11/29/2022]
Abstract
Heparin is a subject of ever-growing interest for laboratory researchers and pharmaceutical industry. One of the driving factors is its critical life-saving drug status, which during the COVID-19 pandemic has assumed a central role in disease treatment and/or prevention. Apart, heparin is one amongst few drugs enjoying a "demand constant" status. In 2020, heparin market size was valued to US$6.5 bn., and given the ongoing stability in the COVID-19 health crisis, it is expected to reach US$11.43 bn. by 2027 with yearly growth rate momentum (CAGR) of 3.9% during the forecast period (Pepi et al., Mol Cell Proteomics 20:100,025, 2021). As patent is a limited monopoly, every year, many patents on low molecular weight heparin (LMWH; a chemically or enzymatically degraded product of unfractionated heparin) are losing market exclusivity worldwide, inviting the generic/biosimilar drug manufacturers to capture market share with cheaper drug products. By tracking patent expiration, drugs in patent litigation, regulatory setbacks for innovator companies (such as those seeking data exclusivity or patent term extension), or other unexpected events affecting market demand and competition, generics can make investment decisions in manufacturing off-patent LMWH drug products of commercial significance. However, given the US Food and Drug Administration (FDA), European Medicine Agency (EMA), Drug Regulatory Authority of Pakistan (DRAP), and other regulatory authorities scientifically rigorous standards for generic/biosimilar LMWH drug products marketing approval, the market is secured and momentous for drug makers that could demonstrate through scientific and clinical dataset that the generic/biosimilar LMWH drug product is of the same quality and purity as the innovator drug product. This study presents an overview of the patent landscape of commercially available LMWHs and advanced analytical techniques for their structural and biochemical characterization for quality control and quality assurance during manufacturing and post-marketing. The study also covers FDA, EMA, Health Canada, and DRAP's current approaches to evaluating the generic/biosimilar LMWH drug products for quality, safety including immunogenicity, and efficacy.
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Affiliation(s)
- Zarina Iqbal
- IP and Litigation Department, PakPat World Intellectual Property Protection Services, Lahore, Pakistan
| | - Saima Sadaf
- Biopharmaceutical and Biomarkers Discovery Lab, School of Biochemistry and Biotechnology, University of the Punjab, Lahore, 54590 Pakistan
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7
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Frey LJ. Informatics Ecosystems to Advance the Biology of Glycans. Methods Mol Biol 2022; 2303:655-673. [PMID: 34626414 DOI: 10.1007/978-1-0716-1398-6_50] [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
Glycomics researchers have identified the need for integrated database systems for collecting glycomics information in a consistent format. The goal is to create a resource for knowledge discovery and dissemination to wider research communities. This has the potential and has exhibited initial success, to extend the research community to include biologists, clinicians, chemists, and computer scientists. This chapter discusses the technology and approach needed to create integrated data resources and informatics ecosystems to empower the broader community to leverage extant glycomics data. The focus is on glycosaminoglycan (GAGs) and proteoglycan research, but the approach can be generalized. The methods described span the development of glycomics standards from CarbBank to Glyco Connection Tables. Integrated data sets provide a foundation for novel methods of analysis such as machine learning and deep learning for knowledge discovery. The implications of predictive analysis are examined in relation to disease biomarker to expand the target audience of GAG and proteoglycan research.
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Affiliation(s)
- Lewis J Frey
- Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, USA.
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8
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Xie Y, Butler M. Construction of InstantPC derivatized glycan GU database: A foundation work for high-throughput and high-sensitivity glycomic analysis. Glycobiology 2021; 32:289-303. [PMID: 34972858 DOI: 10.1093/glycob/cwab128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 11/08/2021] [Accepted: 11/30/2021] [Indexed: 11/12/2022] Open
Abstract
Glycosylation is well-recognized as a critical quality attribute of biotherapeutics being routinely monitored to ensure desired product quality, safety, and efficacy. Additionally, as one of the most prominent and complex post-translational modifications, glycosylation plays a key role in disease manifestation. Changes in glycosylation may serve as a specific and sensitive biomarker for disease diagnostics and prognostics. However, the conventional 2-aminobenzamide based N-glycosylation analysis procedure is time-consuming and insensitive, with poor reproducibility. We have evaluated an innovative streamlined 96-well-plate-based platform utilizing InstantPC label for high-throughput, high-sensitivity glycan profiling, which is user-friendly, robust, and ready for automation. However, the limited availability of InstantPC labelled glycan standards has significantly hampered the applicability and transferability of this platform for expedited glycan structural profiling. To address this challenge, we have constructed a detailed InstantPC labelled glycan glucose unit database through analysis of human serum and a variety of other glycoproteins from various sources. Following preliminary hydrophilic interaction liquid chromatography with fluorescence detection separation and analysis, glycoproteins with complex glycan profiles were subjected to further fractionation by weak anion exchange hydrophilic interaction liquid chromatography and exoglycosidase sequential digestion for cross-validation of the glycan assignment. Hydrophilic interaction ultra-performance liquid chromatography coupled with electrospray ionization mass spectrometry was subsequently utilised for glycan fragmentation and accurate glycan mass confirmation. The constructed InstantPC glycan GU database is accurate and robust. It is believed that this database will enhance the application of the developed platform for high-throughput, high-sensitivity glycan profiling, and eventually advance glycan-based biopharmaceutical production and disease biomarker discovery.
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Affiliation(s)
- Yongjing Xie
- National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland
| | - Michael Butler
- National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland
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9
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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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10
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Gong Y, Qin S, Dai L, Tian Z. The glycosylation in SARS-CoV-2 and its receptor ACE2. Signal Transduct Target Ther 2021; 6:396. [PMID: 34782609 PMCID: PMC8591162 DOI: 10.1038/s41392-021-00809-8] [Citation(s) in RCA: 96] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 10/10/2021] [Accepted: 10/24/2021] [Indexed: 02/05/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19), a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 235 million individuals and led to more than 4.8 million deaths worldwide as of October 5 2021. Cryo-electron microscopy and topology show that the SARS-CoV-2 genome encodes lots of highly glycosylated proteins, such as spike (S), envelope (E), membrane (M), and ORF3a proteins, which are responsible for host recognition, penetration, binding, recycling and pathogenesis. Here we reviewed the detections, substrates, biological functions of the glycosylation in SARS-CoV-2 proteins as well as the human receptor ACE2, and also summarized the approved and undergoing SARS-CoV-2 therapeutics associated with glycosylation. This review may not only broad the understanding of viral glycobiology, but also provide key clues for the development of new preventive and therapeutic methodologies against SARS-CoV-2 and its variants.
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Affiliation(s)
- Yanqiu Gong
- National Clinical Research Center for Geriatrics and Department of General Practice, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center of Biotherapy, 610041, Chengdu, China
| | - Suideng Qin
- School of Chemical Science & Engineering, Shanghai Key Laboratory of Chemical Assessment and Sustainability, Tongji University, 200092, Shanghai, China
| | - Lunzhi Dai
- National Clinical Research Center for Geriatrics and Department of General Practice, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center of Biotherapy, 610041, Chengdu, China.
| | - Zhixin Tian
- School of Chemical Science & Engineering, Shanghai Key Laboratory of Chemical Assessment and Sustainability, Tongji University, 200092, Shanghai, China.
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11
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Glycoinformatics Tools for Comprehensive Characterization of Glycans Enzymatically Released from Proteins. Methods Mol Biol 2021. [PMID: 34611862 DOI: 10.1007/978-1-0716-1685-7_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Glycosylation is important in biology, contributing to both protein conformation and function. Structurally, glycosylation is complex and diverse. This complexity is reflected in the topology, composition, monosaccharide linkages, and isomerism of each oligosaccharide. Glycoanalytics is a discipline that addresses the understanding and characterization of this complexity and its correlation with biology. It includes analytical steps such as sample preparation, instrument measurements, and data analyses. Of these, data analysis has emerged as a critical bottleneck because data collection has increasingly become high-throughput. This has resulted in data-rich workflows that lack rapid and automated data analytics. To address this issue, the field has been developing software for interpretation of quantitative glycomics studies. Here, we describe a protocol using available informatics tools for analysis of data from analysis of released glycans using high-/ultraperformance liquid chromatography (H/UPLC) coupled with mass spectrometry (MS).
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12
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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: 21] [Impact Index Per Article: 7.0] [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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13
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Glycosylation and Cardiovascular Diseases. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1325:307-319. [PMID: 34495542 DOI: 10.1007/978-3-030-70115-4_15] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide, accounting for approximately 18 million deaths in 2017. Coronary artery disease is the predominant cause of death from CVD, followed by stroke. Owing to recent technological advancements, glycans and glycosylation patterns of proteins have been investigated in association with CVD risk factors and clinical events. These studies have found significant associations of glycans as biomarkers of systemic inflammation and major CVD risk factors and events. While more limited, studies have also shown that glycans may be useful for monitoring response to anti-inflammatory therapies and may be responsive to changes in lifestyle, particularly in patients with chronic inflammatory diseases. Glycans capture summative risk information related to inflammatory, immune, and signaling pathways and are promising biomarkers for CVD risk prediction and therapeutic monitoring.
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14
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Bao B, Kellman BP, Chiang AWT, Zhang Y, Sorrentino JT, York AK, Mohammad MA, Haymond MW, Bode L, Lewis NE. Correcting for sparsity and interdependence in glycomics by accounting for glycan biosynthesis. Nat Commun 2021; 12:4988. [PMID: 34404781 PMCID: PMC8371009 DOI: 10.1038/s41467-021-25183-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 07/27/2021] [Indexed: 11/20/2022] Open
Abstract
Glycans are fundamental cellular building blocks, involved in many organismal functions. Advances in glycomics are elucidating the essential roles of glycans. Still, it remains challenging to properly analyze large glycomics datasets, since the abundance of each glycan is dependent on many other glycans that share many intermediate biosynthetic steps. Furthermore, the overlap of measured glycans can be low across samples. We address these challenges with GlyCompare, a glycomic data analysis approach that accounts for shared biosynthetic steps for all measured glycans to correct for sparsity and non-independence in glycomics, which enables direct comparison of different glycoprofiles and increases statistical power. Using GlyCompare, we study diverse N-glycan profiles from glycoengineered erythropoietin. We obtain biologically meaningful clustering of mutant cell glycoprofiles and identify knockout-specific effects of fucosyltransferase mutants on tetra-antennary structures. We further analyze human milk oligosaccharide profiles and find mother’s fucosyltransferase-dependent secretor-status indirectly impact the sialylation. Finally, we apply our method on mucin-type O-glycans, gangliosides, and site-specific compositional glycosylation data to reveal tissues and disease-specific glycan presentations. Our substructure-oriented approach will enable researchers to take full advantage of the growing power and size of glycomics data. Glycomics can uncover important molecular changes but measured glycans are highly interconnected and incompatible with common statistical methods, introducing pitfalls during analysis. Here, the authors develop an approach to identify glycan dependencies across samples to facilitate comparative glycomics.
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Affiliation(s)
- Bokan Bao
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.,Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Benjamin P Kellman
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.,Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Austin W T Chiang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.,The Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, La Jolla, CA, USA
| | - Yujie Zhang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - James T Sorrentino
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.,Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Austin K York
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Mahmoud A Mohammad
- Department of Pediatrics, Children's Nutrition Research Center, US Department of Agriculture/Agricultural Research Service, Baylor College of Medicine, Houston, TX, USA
| | - Morey W Haymond
- Department of Pediatrics, Children's Nutrition Research Center, US Department of Agriculture/Agricultural Research Service, Baylor College of Medicine, Houston, TX, USA
| | - Lars Bode
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA. .,Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA. .,The Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, La Jolla, CA, USA.
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15
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Harvey DJ. ANALYSIS OF CARBOHYDRATES AND GLYCOCONJUGATES BY MATRIX-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY: AN UPDATE FOR 2015-2016. MASS SPECTROMETRY REVIEWS 2021; 40:408-565. [PMID: 33725404 DOI: 10.1002/mas.21651] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 07/24/2020] [Indexed: 06/12/2023]
Abstract
This review is the ninth 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 2016. 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. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented over 30 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show no sign of deminishing. © 2020 Wiley Periodicals, Inc.
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Affiliation(s)
- David J Harvey
- Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom
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16
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Importance of evaluating protein glycosylation in pluripotent stem cell-derived cardiomyocytes for research and clinical applications. Pflugers Arch 2021; 473:1041-1059. [PMID: 33830329 PMCID: PMC8245383 DOI: 10.1007/s00424-021-02554-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 03/01/2021] [Accepted: 03/06/2021] [Indexed: 01/21/2023]
Abstract
Proper protein glycosylation is critical to normal cardiomyocyte physiology. Aberrant glycosylation can alter protein localization, structure, drug interactions, and cellular function. The in vitro differentiation of human pluripotent stem cells into cardiomyocytes (hPSC-CM) has become increasingly important to the study of protein function and to the fields of cardiac disease modeling, drug testing, drug discovery, and regenerative medicine. Here, we offer our perspective on the importance of protein glycosylation in hPSC-CM. Protein glycosylation is dynamic in hPSC-CM, but the timing and extent of glycosylation are still poorly defined. We provide new data highlighting how observed changes in hPSC-CM glycosylation may be caused by underlying differences in the protein or transcript abundance of enzymes involved in building and trimming the glycan structures or glycoprotein gene products. We also provide evidence that alternative splicing results in altered sites of glycosylation within the protein sequence. Our findings suggest the need to precisely define protein glycosylation events that may have a critical impact on the function and maturation state of hPSC-CM. Finally, we provide an overview of analytical strategies available for studying protein glycosylation and identify opportunities for the development of new bioinformatic approaches to integrate diverse protein glycosylation data types. We predict that these tools will promote the accurate assessment of protein glycosylation in future studies of hPSC-CM that will ultimately be of significant experimental and clinical benefit.
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17
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Shakyawar SK, Pandey S, Harvey DJ, Bousfield G, Guda C. FGDB: Database of follicle stimulating hormone glycans. Comput Struct Biotechnol J 2021; 19:1635-1640. [PMID: 33897975 PMCID: PMC8050109 DOI: 10.1016/j.csbj.2021.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/04/2021] [Accepted: 03/06/2021] [Indexed: 11/12/2022] Open
Abstract
Glycomics, the study of the entire complement of sugars of an organism has received significant attention in the recent past due to the advances made in high throughput mass spectrometry technologies. These analytical advancements have facilitated the characterization of glycans associated with the follicle-stimulating hormones (FSH), which play a central role in the human reproductive system both in males and females utilizing regulating gonadal (testicular and ovarian) functions. The irregularities in FSH activity are also directly linked with osteoporosis. The glycoanalytical studies have been tremendously helpful in understanding the biological roles of FSH. Subsequently, the increasing number of characterized FSH glycan structures and related glycoform data has thrown a challenge to the glycoinformatics community in terms of data organization, storage and access. Also, a user-friendly platform is needed for providing easy access to the database and performing integrated analysis using a high volume of experimental data to accelerate FSH-focused research. FSH Glycans DataBase (FGDB) serves as a comprehensive and unique repository of structures, features, and related information of glycans associated with FSH. Apart from providing multiple search options, the database also facilitates an integrated user-friendly interface to perform the glycan abundance and comparative analyses using experimental data. The automated integrated pipelines present the possible structures of glycans and variants of FSH based on the input data, and allow the user to perform various analyses. The potential application of FGDB will significantly help both glycoinformaticians as well as wet-lab researchers to stimulate the research in this area. FGDB web access: https://fgdb.unmc.edu/.
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Affiliation(s)
- Sushil K Shakyawar
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, United States
| | - Sanjit Pandey
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, United States
| | - David J Harvey
- Target Discovery Institute, Nuffield Department of Medicine, Oxford University, Oxford OX3 7FZ, United Kingdom
| | - George Bousfield
- Fairmount College of Liberal Arts and Sciences, Wichita State University, KS 67260, United States
| | - Chittibabu Guda
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, United States
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18
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Watanabe Y, Aoki-Kinoshita KF, Ishihama Y, Okuda S. GlycoPOST realizes FAIR principles for glycomics mass spectrometry data. Nucleic Acids Res 2021; 49:D1523-D1528. [PMID: 33174597 PMCID: PMC7778884 DOI: 10.1093/nar/gkaa1012] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 10/13/2020] [Accepted: 10/14/2020] [Indexed: 02/06/2023] Open
Abstract
For the reproducibility and sustainability of scientific research, FAIRness (Findable, Accessible, Interoperable and Re-usable), with respect to the release of raw data obtained by researchers, is one of the most important principles underpinning the future of open science. In genomics and transcriptomics, the sharing of raw data from next-generation sequencers is made possible through public repositories. In addition, in proteomics, the deposition of raw data from mass spectrometry (MS) experiments into repositories is becoming standardized. However, a standard repository for such MS data had not yet been established in glycomics. With the increasing number of glycomics MS data, therefore, we have developed GlycoPOST (https://glycopost.glycosmos.org/), a repository for raw MS data generated from glycomics experiments. In just the first year since the release of GlycoPOST, 73 projects have already been registered by researchers around the world, and the number of registered projects is continuously growing, making a significant contribution to the future FAIRness of the glycomics field. GlycoPOST is a free resource to the community and accepts (and will continue to accept in the future) raw data regardless of vendor-specific formats.
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Affiliation(s)
- Yu Watanabe
- Division of Bioinformatics, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata 951-8510, Japan
| | - Kiyoko F Aoki-Kinoshita
- Faculty of Science and Engineering, Soka University, 1-236 Tangi-machi, Hachioji, Tokyo 192-8577, Japan
| | - Yasushi Ishihama
- Department of Molecular and Cellular BioAnalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan.,Department of Proteomics and Drug Discovery, Graduate School of Pharmaceutical Sciences, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Shujiro Okuda
- Division of Bioinformatics, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata 951-8510, Japan
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19
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Pepi LE, Sanderson P, Stickney M, Amster IJ. Developments in Mass Spectrometry for Glycosaminoglycan Analysis: A Review. Mol Cell Proteomics 2021; 20:100025. [PMID: 32938749 PMCID: PMC8724624 DOI: 10.1074/mcp.r120.002267] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 09/15/2020] [Accepted: 09/16/2020] [Indexed: 12/11/2022] Open
Abstract
This review covers recent developments in glycosaminoglycan (GAG) analysis via mass spectrometry (MS). GAGs participate in a variety of biological functions, including cellular communication, wound healing, and anticoagulation, and are important targets for structural characterization. GAGs exhibit a diverse range of structural features due to the variety of O- and N-sulfation modifications and uronic acid C-5 epimerization that can occur, making their analysis a challenging target. Mass spectrometry approaches to the structure assignment of GAGs have been widely investigated, and new methodologies remain the subject of development. Advances in sample preparation, tandem MS techniques (MS/MS), online separations, and automated analysis software have advanced the field of GAG analysis. These recent developments have led to remarkable improvements in the precision and time efficiency for the structural characterization of GAGs.
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Affiliation(s)
- Lauren E Pepi
- Department of Chemistry, University of Georgia, Athens, Georgia, USA
| | | | - Morgan Stickney
- Department of Chemistry, University of Georgia, Athens, Georgia, USA
| | - I Jonathan Amster
- Department of Chemistry, University of Georgia, Athens, Georgia, USA.
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20
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Lisacek F, Alagesan K, Hayes C, Lippold S, de Haan N. Bioinformatics in Immunoglobulin Glycosylation Analysis. EXPERIENTIA SUPPLEMENTUM (2012) 2021; 112:205-233. [PMID: 34687011 DOI: 10.1007/978-3-030-76912-3_6] [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: 06/13/2023]
Abstract
Analytical methods developed for studying immunoglobulin glycosylation rely heavily on software tailored for this purpose. Many of these tools are now used in high-throughput settings, especially for the glycomic characterization of IgG. A collection of these tools, and the databases they rely on, are presented in this chapter. Specific applications are detailed in examples of immunoglobulin glycomics and glycoproteomics data processing workflows. The results obtained in the glycoproteomics workflow are emphasized with the use of dedicated visualizing tools. These tools enable the user to highlight glycan properties and their differential expression.
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Affiliation(s)
- Frédérique Lisacek
- 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.
| | | | - Catherine Hayes
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
- Computer Science Department, University of Geneva, Geneva, Switzerland
| | - Steffen Lippold
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Noortje de Haan
- Copenhagen Center for Glycomics, University of Copenhagen, Copenhagen, Denmark
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21
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Sytnyk V, Leshchyns'ka I, Schachner M. Neural glycomics: the sweet side of nervous system functions. Cell Mol Life Sci 2021; 78:93-116. [PMID: 32613283 PMCID: PMC11071817 DOI: 10.1007/s00018-020-03578-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 06/06/2020] [Accepted: 06/22/2020] [Indexed: 02/07/2023]
Abstract
The success of investigations on the structure and function of the genome (genomics) has been paralleled by an equally awesome progress in the analysis of protein structure and function (proteomics). We propose that the investigation of carbohydrate structures that go beyond a cell's metabolism is a rapidly developing frontier in our expanding knowledge on the structure and function of carbohydrates (glycomics). No other functional system appears to be suited as well as the nervous system to study the functions of glycans, which had been originally characterized outside the nervous system. In this review, we describe the multiple studies on the functions of LewisX, the human natural killer cell antigen-1 (HNK-1), as well as oligomannosidic and sialic (neuraminic) acids. We attempt to show the sophistication of these structures in ontogenetic development, synaptic function and plasticity, and recovery from trauma, with a view on neurodegeneration and possibilities to ameliorate deterioration. In view of clinical applications, we emphasize the need for glycomimetic small organic compounds which surpass the usefulness of natural glycans in that they are metabolically more stable, more parsimonious to synthesize or isolate, and more advantageous for therapy, since many of them pass the blood brain barrier and are drug-approved for treatments other than those in the nervous system, thus allowing a more ready access for application in neurological diseases. We describe the isolation of such mimetic compounds using not only Western NIH, but also traditional Chinese medical libraries. With this review, we hope to deepen the interests in this exciting field.
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Affiliation(s)
- Vladimir Sytnyk
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW, Australia.
| | - Iryna Leshchyns'ka
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW, Australia
| | - Melitta Schachner
- Center for Neuroscience, Shantou University Medical College, 22 Xin Ling Road, Shantou, 515041, Guangdong, China
- Department of Cell Biology and Neuroscience, Keck Center for Collaborative Neuroscience, Rutgers University, 604 Allison Road, Piscataway, NJ, 08854, USA
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22
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Rosenbalm KE, Tiemeyer M, Wells L, Aoki K, Zhao P. Glycomics-informed glycoproteomic analysis of site-specific glycosylation for SARS-CoV-2 spike protein. STAR Protoc 2020; 1:100214. [PMID: 33377107 PMCID: PMC7757665 DOI: 10.1016/j.xpro.2020.100214] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
Abstract
This protocol describes an integrated approach for analyzing site-specific N- and O-linked glycosylation of SARS-CoV-2 spike protein by mass spectrometry. Glycoproteomics analyzes intact glycopeptides to examine site-specific microheterogeneity of glycoproteins. Glycomics provides structural characterization on any glycan assignments by glycoproteomics. This procedure can be modified and applied to a variety of N- and/or O-linked glycoproteins. Combined with bioinformatics, the glycomics-informed glycoproteomics may be useful in generating 3D molecular dynamics simulations of certain glycoproteins alone or interacting with one another. For complete details on the use and execution of this protocol, please refer to Zhao et al. (2020).
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Affiliation(s)
- Katelyn E. Rosenbalm
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Michael Tiemeyer
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Lance Wells
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
- Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Kazuhiro Aoki
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA
| | - Peng Zhao
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA
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23
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Kellman BP, Zhang Y, Logomasini E, Meinhardt E, Godinez-Macias KP, Chiang AWT, Sorrentino JT, Liang C, Bao B, Zhou Y, Akase S, Sogabe I, Kouka T, Winzeler EA, Wilson IBH, Campbell MP, Neelamegham S, Krambeck FJ, Aoki-Kinoshita KF, Lewis NE. A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR). Beilstein J Org Chem 2020; 16:2645-2662. [PMID: 33178355 PMCID: PMC7607430 DOI: 10.3762/bjoc.16.215] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 09/17/2020] [Indexed: 12/18/2022] Open
Abstract
Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code.
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24
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Bagdonas H, Ungar D, Agirre J. Leveraging glycomics data in glycoprotein 3D structure validation with Privateer. Beilstein J Org Chem 2020; 16:2523-2533. [PMID: 33093930 PMCID: PMC7554661 DOI: 10.3762/bjoc.16.204] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 10/06/2020] [Indexed: 12/20/2022] Open
Abstract
The heterogeneity, mobility and complexity of glycans in glycoproteins have been, and currently remain, significant challenges in structural biology. These aspects present unique problems to the two most prolific techniques: X-ray crystallography and cryo-electron microscopy. At the same time, advances in mass spectrometry have made it possible to get deeper insights on precisely the information that is most difficult to recover by structure solution methods: the full-length glycan composition, including linkage details for the glycosidic bonds. The developments have given rise to glycomics. Thankfully, several large scale glycomics initiatives have stored results in publicly available databases, some of which can be accessed through API interfaces. In the present work, we will describe how the Privateer carbohydrate structure validation software has been extended to harness results from glycomics projects, and its use to greatly improve the validation of 3D glycoprotein structures.
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Affiliation(s)
- Haroldas Bagdonas
- York Structural Biology Laboratory, Department of Chemistry, University of York, Wentworth Way, York, YO10 5DD, UK
| | - Daniel Ungar
- Department of Biology, University of York, Wentworth Way, York, YO10 5DD, UK
| | - Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, Wentworth Way, York, YO10 5DD, UK
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25
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Zhao P, Praissman JL, Grant OC, Cai Y, Xiao T, Rosenbalm KE, Aoki K, Kellman BP, Bridger R, Barouch DH, Brindley MA, Lewis NE, Tiemeyer M, Chen B, Woods RJ, Wells L. Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor. Cell Host Microbe 2020; 28:586-601.e6. [PMID: 32841605 PMCID: PMC7443692 DOI: 10.1016/j.chom.2020.08.004] [Citation(s) in RCA: 289] [Impact Index Per Article: 72.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/22/2020] [Accepted: 08/10/2020] [Indexed: 12/13/2022]
Abstract
The SARS-CoV-2 betacoronavirus uses its highly glycosylated trimeric Spike protein to bind to the cell surface receptor angiotensin converting enzyme 2 (ACE2) glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatics analyses of natural variants and with existing 3D structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein both alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation. Taken together, these data can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.
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Affiliation(s)
- Peng Zhao
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Jeremy L Praissman
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Oliver C Grant
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Yongfei Cai
- Division of Molecular Medicine, Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Tianshu Xiao
- Division of Molecular Medicine, Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Katelyn E Rosenbalm
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Kazuhiro Aoki
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Benjamin P Kellman
- Departments of Pediatrics and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Robert Bridger
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Dan H Barouch
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Melinda A Brindley
- Department of Infectious Diseases, Department of Population Health, Center for Vaccines and Immunology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA
| | - Nathan E Lewis
- Departments of Pediatrics and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA; Novo Nordisk Foundation Center for Biosustainability at UC San Diego, La Jolla, CA 92093, USA
| | - Michael Tiemeyer
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA
| | - Bing Chen
- Division of Molecular Medicine, Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Robert J Woods
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA.
| | - Lance Wells
- Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, GA 30602, USA.
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26
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Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics. Int J Mol Sci 2020; 21:ijms21186727. [PMID: 32937895 PMCID: PMC7556027 DOI: 10.3390/ijms21186727] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/03/2020] [Accepted: 09/11/2020] [Indexed: 02/07/2023] Open
Abstract
Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan-protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.
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Fogarty CA, Harbison AM, Dugdale AR, Fadda E. How and why plants and human N-glycans are different: Insight from molecular dynamics into the "glycoblocks" architecture of complex carbohydrates. Beilstein J Org Chem 2020; 16:2046-2056. [PMID: 32874351 PMCID: PMC7445399 DOI: 10.3762/bjoc.16.171] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 08/05/2020] [Indexed: 01/01/2023] Open
Abstract
The N-glycosylation is one of the most abundant and diverse post-translational modifications of proteins, implicated in protein folding and structural stability, and mediating interactions with receptors and with the environment. All N-glycans share a common core from which linear or branched arms stem from, with functionalization specific to different species and to the cells’ health and disease state. This diversity generates a rich collection of structures, all diversely able to trigger molecular cascades and to activate pathways, which also include adverse immunogenic responses. These events are inherently linked to the N-glycans’ 3D architecture and dynamics, which remain for the large part unresolved and undetected because of their intrinsic structural disorder. In this work we use molecular dynamics (MD) simulations to provide insight into N-glycans’ 3D structure by analysing the effects of a set of very specific modifications found in plants and invertebrate N-glycans, which are immunogenic in humans. We also compare these structural motifs and combine them with mammalian N-glycan motifs to devise strategies for the control of the N-glycan 3D structure through sequence. Our results suggest that the N-glycans’ architecture can be described in terms of the local spatial environment of groups of monosaccharides. We define these “glycoblocks” as self-contained 3D units, uniquely identified by the nature of the residues they comprise, their linkages and structural/dynamic features. This alternative description of glycans’ 3D architecture can potentially lead to an easier prediction of sequence-to-structure relationships in complex carbohydrates, with important implications in glycoengineering design.
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Affiliation(s)
- Carl A Fogarty
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, Kildare, Ireland
| | - Aoife M Harbison
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, Kildare, Ireland
| | - Amy R Dugdale
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, Kildare, Ireland
| | - Elisa Fadda
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, Kildare, Ireland
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28
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CRISPR-Cas9 Genome Editing Tool for the Production of Industrial Biopharmaceuticals. Mol Biotechnol 2020; 62:401-411. [PMID: 32749657 DOI: 10.1007/s12033-020-00265-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/30/2020] [Indexed: 10/23/2022]
Abstract
A broad range of cell lines with characteristic features are used as bio-factories to produce recombinant proteins for basic research and therapeutic purposes. Genetic engineering strategies have been used to manipulate the genome of mammalian cells, insects, and yeasts for heterologous expression. One reason is that the glycosylation pattern of the expression hosts differs somehow from mammalian cells, which may cause immunogenic reactions upon administration in humans. CRISPR-Cas9 is a simple, efficient, and versatile genome engineering tool that can be programmed to precisely make double-stranded breaks at the desired loci. Compared to the classical genome editing methods, a CRISPR-Cas9 system is an ideal tool, providing the opportunity to integrate or delete genes from the target organisms. Besides broadened applications, limited studies have used CRISPR-Cas9 for editing the endogenous pathways in expression systems for biopharmaceutical applications. In the present review, we discuss the use of CRISPR-Cas9 in expression systems to improve host cell lines, increase product yield, and humanize glycosylation pathways by targeting intrinsic genes.
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Tsuchiya S, Yamada I, Aoki-Kinoshita KF. GlycanFormatConverter: a conversion tool for translating the complexities of glycans. Bioinformatics 2020; 35:2434-2440. [PMID: 30535258 PMCID: PMC6612873 DOI: 10.1093/bioinformatics/bty990] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 10/01/2018] [Accepted: 12/06/2018] [Indexed: 11/14/2022] Open
Abstract
Motivation Glycans are biomolecules that take an important role in the biological processes of living organisms. They form diverse, complicated structures such as branched and cyclic forms. Web3 Unique Representation of Carbohydrate Structures (WURCS) was proposed as a new linear notation for uniquely representing glycans during the GlyTouCan project. WURCS defines rules for complex glycan structures that other text formats did not support, and so it is possible to represent a wide variety glycans. However, WURCS uses a complicated nomenclature, so it is not human-readable. Therefore, we aimed to support the interpretation of WURCS by converting WURCS to the most basic and widely used format IUPAC. Results In this study, we developed GlycanFormatConverter and succeeded in converting WURCS to the three kinds of IUPAC formats (IUPAC-Extended, IUPAC-Condensed and IUPAC-Short). Furthermore, we have implemented functionality to import IUPAC-Extended, KEGG Chemical Function (KCF) and LinearCode formats and to export WURCS. We have thoroughly tested our GlycanFormatConverter and were able to show that it was possible to convert all the glycans registered in the GlyTouCan repository, with exceptions owing only to the limitations of the original format. The source code for this conversion tool has been released as an open source tool. Availability and implementation https://github.com/glycoinfo/GlycanFormatConverter.git Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | - Kiyoko F Aoki-Kinoshita
- Graduate School of Engineering, Soka University, Hachioji, Tokyo, Japan.,Faculty of Science and Engineering, Soka University, Hachioji, Tokyo, Japan
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30
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Multistage mass spectrometry with intelligent precursor selection for N-glycan branching pattern analysis. Carbohydr Polym 2020; 237:116122. [DOI: 10.1016/j.carbpol.2020.116122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Revised: 02/10/2020] [Accepted: 03/03/2020] [Indexed: 12/28/2022]
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31
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Vita R, Mahajan S, Overton JA, Dhanda SK, Martini S, Cantrell JR, Wheeler DK, Sette A, Peters B. The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Res 2020; 47:D339-D343. [PMID: 30357391 PMCID: PMC6324067 DOI: 10.1093/nar/gky1006] [Citation(s) in RCA: 1042] [Impact Index Per Article: 260.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 10/11/2018] [Indexed: 12/18/2022] Open
Abstract
The Immune Epitope Database (IEDB, iedb.org) captures experimental data confined in figures, text and tables of the scientific literature, making it freely available and easily searchable to the public. The scope of the IEDB extends across immune epitope data related to all species studied and includes antibody, T cell, and MHC binding contexts associated with infectious, allergic, autoimmune, and transplant related diseases. Having been publicly accessible for >10 years, the recent focus of the IEDB has been improved query and reporting functionality to meet the needs of our users to access and summarize data that continues to grow in quantity and complexity. Here we present an update on our current efforts and future goals.
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Affiliation(s)
- Randi Vita
- La Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, CA 92037, USA
| | - Swapnil Mahajan
- La Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, CA 92037, USA
| | | | - Sandeep Kumar Dhanda
- La Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, CA 92037, USA
| | - Sheridan Martini
- La Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, CA 92037, USA
| | | | | | - Alessandro Sette
- La Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, CA 92037, USA.,University of California San Diego, Department of Medicine, La Jolla, CA 92093, USA
| | - Bjoern Peters
- La Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, CA 92037, USA.,University of California San Diego, Department of Medicine, La Jolla, CA 92093, USA
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Vos RA, Katayama T, Mishima H, Kawano S, Kawashima S, Kim JD, Moriya Y, Tokimatsu T, Yamaguchi A, Yamamoto Y, Wu H, Amstutz P, Antezana E, Aoki NP, Arakawa K, Bolleman JT, Bolton E, Bonnal RJP, Bono H, Burger K, Chiba H, Cohen KB, Deutsch EW, Fernández-Breis JT, Fu G, Fujisawa T, Fukushima A, García A, Goto N, Groza T, Hercus C, Hoehndorf R, Itaya K, Juty N, Kawashima T, Kim JH, Kinjo AR, Kotera M, Kozaki K, Kumagai S, Kushida T, Lütteke T, Matsubara M, Miyamoto J, Mohsen A, Mori H, Naito Y, Nakazato T, Nguyen-Xuan J, Nishida K, Nishida N, Nishide H, Ogishima S, Ohta T, Okuda S, Paten B, Perret JL, Prathipati P, Prins P, Queralt-Rosinach N, Shinmachi D, Suzuki S, Tabata T, Takatsuki T, Taylor K, Thompson M, Uchiyama I, Vieira B, Wei CH, Wilkinson M, Yamada I, Yamanaka R, Yoshitake K, Yoshizawa AC, Dumontier M, Kosaki K, Takagi T. BioHackathon 2015: Semantics of data for life sciences and reproducible research. F1000Res 2020; 9:136. [PMID: 32308977 PMCID: PMC7141167 DOI: 10.12688/f1000research.18236.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/05/2020] [Indexed: 01/08/2023] Open
Abstract
We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.
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Affiliation(s)
- Rutger A. Vos
- Institute of Biology Leiden, Leiden University, Leiden, The Netherlands
- Naturalis Biodiversity Center, Leiden, The Netherlands
| | | | - Hiroyuki Mishima
- Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Shin Kawano
- Database Center for Life Science, Tokyo, Japan
| | | | | | - Yuki Moriya
- Database Center for Life Science, Tokyo, Japan
| | | | | | | | - Hongyan Wu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | | | - Erick Antezana
- Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Nobuyuki P. Aoki
- Faculty of Science and Engineering, SOKA University, Tokyo, Japan
| | - Kazuharu Arakawa
- Institute for Advanced Biosciences, Keio University, Tokyo, Japan
| | - Jerven T. Bolleman
- SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Lausanne, Switzerland
| | - Evan Bolton
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, USA
| | - Raoul J. P. Bonnal
- Istituto Nazionale Genetica Molecolare, Romeo ed Enrica Invernizzi, Milan, Italy
| | | | - Kees Burger
- Dutch Techcentre for Life Sciences, Utrecht, The Netherlands
| | - Hirokazu Chiba
- National Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Japan
| | - Kevin B. Cohen
- Computational Bioscience Program, University of Colorado School of Medicine, Denver, USA
- Université Paris-Saclay, LIMSI, CNRS, Paris, France
| | | | | | - Gang Fu
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, USA
| | | | | | | | - Naohisa Goto
- Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Tudor Groza
- St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Darlinghurst, Australia
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Colin Hercus
- Novocraft Technologies Sdn. Bhd., Selangor, Malaysia
| | - Robert Hoehndorf
- Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Kotone Itaya
- Institute for Advanced Biosciences, Keio University, Tokyo, Japan
| | - Nick Juty
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | | | - Jee-Hyub Kim
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Akira R. Kinjo
- Institute for Protein Research, Osaka University, Osaka, Japan
| | - Masaaki Kotera
- School of Life Science and Technology, Tokyo Institute of Technology, Tokyo, Japan
| | - Kouji Kozaki
- The Institute of Scientific and Industrial Research, Osaka University, Osaka, Japan
| | | | - Tatsuya Kushida
- National Bioscience Database Center, Japan Science and Technology Agency, Tokyo, Japan
| | - Thomas Lütteke
- Institute of Veterinary Physiology and Biochemistry, Justus-Liebig University Giessen, Giessen, Germany
- Gesellschaft für innovative Personalwirtschaftssysteme mbH (GIP GmbH), Offenbach, Germany
| | | | | | - Attayeb Mohsen
- National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan
| | - Hiroshi Mori
- Center for Information Biology, National Institute of Genetics, Mishima, Japan
| | - Yuki Naito
- Database Center for Life Science, Tokyo, Japan
| | | | | | | | - Naoki Nishida
- Department of Systems Science, Osaka University, Osaka, Japan
| | - Hiroyo Nishide
- National Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Japan
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Tazro Ohta
- Database Center for Life Science, Tokyo, Japan
| | - Shujiro Okuda
- Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, USA
| | | | - Philip Prathipati
- National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan
| | - Pjotr Prins
- University Medical Center Utrecht, Utrecht, The Netherlands
- University of Tennessee Health Science Center, Memphis, USA
| | - Núria Queralt-Rosinach
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Shinya Suzuki
- School of Life Science and Technology, Tokyo Institute of Technology, Tokyo, Japan
| | - Tsuyosi Tabata
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | | | - Kieron Taylor
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Mark Thompson
- Leiden University Medical Center, Leiden, The Netherlands
| | - Ikuo Uchiyama
- National Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Japan
| | - Bruno Vieira
- WurmLab, School of Biological & Chemical Sciences, Queen Mary University of London, London, UK
| | - Chih-Hsuan Wei
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, USA
| | - Mark Wilkinson
- Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, Spain
| | | | | | - Kazutoshi Yoshitake
- Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan
| | | | - Michel Dumontier
- Institute of Data Science, Maastricht University, Maastricht, The Netherlands
| | - Kenjiro Kosaki
- Center for Medical Genetics, Keio University School of Medicine, Tokyo, Japan
| | - Toshihisa Takagi
- National Bioscience Database Center, Japan Science and Technology Agency, Tokyo, Japan
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan
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Cao WQ, Liu MQ, Kong SY, Wu MX, Huang ZZ, Yang PY. Novel methods in glycomics: a 2019 update. Expert Rev Proteomics 2020; 17:11-25. [PMID: 31914820 DOI: 10.1080/14789450.2020.1708199] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.
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Affiliation(s)
- Wei-Qian Cao
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.,NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China
| | - Ming-Qi Liu
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Si-Yuan Kong
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Meng-Xi Wu
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.,Department of Chemistry, Fudan University, Shanghai, China
| | - Zheng-Ze Huang
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Peng-Yuan Yang
- Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.,NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai, China.,Department of Chemistry, Fudan University, Shanghai, China
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34
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Klein JA, Zaia J. A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts. Biochemistry 2019; 59:3089-3097. [PMID: 31833756 DOI: 10.1021/acs.biochem.9b00730] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Protein glycosylation, resulting from glycosyl transferase reactions under complex control in the secretory pathway, consists of a distribution of related glycoforms at each glycosylation site. Because the biosynthetic substrate concentration and transport rates depend on architecture and other aspects of cellular phenotypes, site-specific glycosylation cannot be predicted accurately from genomic, transcriptomic, or proteomic information. Rather, it is necessary to quantify glycosylation at each protein site and how this changes among a sample cohort to provide information about disease mechanisms. At present, mature mass spectrometry-based methods allow for qualitative assignment of the glycan composition and glycosylation site of singly glycosylated proteolytic peptides. To make such quantitative comparisons, it is necessary to sample the glycosylation distribution with sufficient coverage and accuracy for confident assessment of the glycosylation changes that occur in the biological cohort. In this Perspective, we discuss the unmet needs for mass spectrometry acquisition methods and bioinformatics for the confident comparison of protein site-specific glycosylation among sample cohorts.
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Walsh I, Nguyen-Khuong T, Wongtrakul-Kish K, Tay SJ, Chew D, José T, Taron CH, Rudd PM. GlycanAnalyzer: software for automated interpretation of N-glycan profiles after exoglycosidase digestions. Bioinformatics 2019; 35:688-690. [PMID: 30101321 PMCID: PMC6378934 DOI: 10.1093/bioinformatics/bty681] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 06/30/2018] [Accepted: 08/06/2018] [Indexed: 11/13/2022] Open
Abstract
SUMMARY Many eukaryotic proteins are modified by N-glycans. Liquid chromatography (ultra-performance -UPLC and high-performance-HPLC) coupled with mass spectrometry (MS) is conventionally used to characterize N-glycan structures. Software can automatically assign glycan structures by matching their observed retention times and masses with standardized values in reference databases. However, more precise confirmation of N-glycan structures can be derived using exoglycosidases, enzymes that remove specific monosaccharides from glycans. Exoglycosidase removal of monosaccharides results in signature peak shifts, in both UPLC and MS1, yielding an effective way to verify N-glycan structure with high detail (down to the position and isomeric linkage of each monosaccharide). Because manual interpretation of exoglycosidase data is complex and time consuming, we developed GlycanAnalyzer, a web application that pattern matches N-glycan peak shifts following exoglycosidase digestion and automates structure assignments. GlycanAnalyzer significantly improves assignment accuracy over other auto-assignment methods on tests with a monoclonal antibody and four glycan standards (100% versus 82% for the next best software). By automating data interpretation, GlycanAnalyzer enables the easier use of exoglycosidases to precisely define N-glycan structure. AVAILABILITY AND IMPLEMENTATION http://glycananalyzer.neb.com. Datasets available online. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ian Walsh
- Bioprocessing Technology Institute Agency for Science, Technology and Research (A*STAR), Singapore
| | - Terry Nguyen-Khuong
- Bioprocessing Technology Institute Agency for Science, Technology and Research (A*STAR), Singapore
| | | | - Shi Jie Tay
- Bioprocessing Technology Institute Agency for Science, Technology and Research (A*STAR), Singapore
| | - Daniel Chew
- Bioprocessing Technology Institute Agency for Science, Technology and Research (A*STAR), Singapore
| | - Tasha José
- New England Biolabs, 240 County Road, Ipswich, MA, USA
| | | | - Pauline M Rudd
- Bioprocessing Technology Institute Agency for Science, Technology and Research (A*STAR), Singapore
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Klein J, Carvalho L, Zaia J. Application of network smoothing to glycan LC-MS profiling. Bioinformatics 2019; 34:3511-3518. [PMID: 29790907 DOI: 10.1093/bioinformatics/bty397] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 05/10/2018] [Indexed: 11/14/2022] Open
Abstract
Motivation Glycosylation is one of the most heterogeneous and complex protein post-translational modifications. Liquid chromatography coupled mass spectrometry (LC-MS) is a common high throughput method for analyzing complex biological samples. Accurate study of glycans require high resolution mass spectrometry. Mass spectrometry data contains intricate sub-structures that encode mass and abundance, requiring several transformations before it can be used to identify biological molecules, requiring automated tools to analyze samples in a high throughput setting. Existing tools for interpreting the resulting data do not take into account related glycans when evaluating individual observations, limiting their sensitivity. Results We developed an algorithm for assigning glycan compositions from LC-MS data by exploring biosynthetic network relationships among glycans. Our algorithm optimizes a set of likelihood scoring functions based on glycan chemical properties but uses network Laplacian regularization and optionally prior information about expected glycan families to smooth the likelihood and thus achieve a consistent and more representative solution. Our method was able to identify as many, or more glycan compositions compared to previous approaches, and demonstrated greater sensitivity with regularization. Our network definition was tailored to N-glycans but the method may be applied to glycomics data from other glycan families like O-glycans or heparan sulfate where the relationships between compositions can be expressed as a graph. Availability and implementation Built Executable http://www.bumc.bu.edu/msr/glycresoft/ and Source Code: https://github.com/BostonUniversityCBMS/glycresoft. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Joshua Klein
- Program for Bioinformatics, Boston University, Boston, MA, USA
| | - Luis Carvalho
- Program for Bioinformatics, Boston University, Boston, MA, USA.,Department of Math and Statistics, Boston University, Boston, MA, USA
| | - Joseph Zaia
- Program for Bioinformatics, Boston University, Boston, MA, USA.,Department of Biochemistry, Boston University, Boston, MA, USA
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Gray CJ, Migas LG, Barran PE, Pagel K, Seeberger PH, Eyers CE, Boons GJ, Pohl NLB, Compagnon I, Widmalm G, Flitsch SL. Advancing Solutions to the Carbohydrate Sequencing Challenge. J Am Chem Soc 2019; 141:14463-14479. [PMID: 31403778 DOI: 10.1021/jacs.9b06406] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.
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Affiliation(s)
- Christopher J Gray
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
| | - Lukasz G Migas
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
| | - Perdita E Barran
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
| | - Kevin Pagel
- Institute for Chemistry and Biochemistry , Freie Universität Berlin , Takustraße 3 , 14195 Berlin , Germany
| | - Peter H Seeberger
- Biomolecular Systems Department , Max Planck Institute for Colloids and Interfaces , Am Muehlenberg 1 , 14476 Potsdam , Germany
| | - Claire E Eyers
- Department of Biochemistry, Institute of Integrative Biology , University of Liverpool , Crown Street , Liverpool L69 7ZB , U.K
| | - Geert-Jan Boons
- Complex Carbohydrate Research Center , University of Georgia , Athens , Georgia 30602 , United States
| | - Nicola L B Pohl
- Department of Chemistry , Indiana University , Bloomington , Indiana 47405 , United States
| | - Isabelle Compagnon
- Institut Lumière Matière, UMR5306 Université Lyon 1-CNRS , Université de Lyon , 69622 Villeurbanne Cedex , France.,Institut Universitaire de France IUF , 103 Blvd St Michel , 75005 Paris , France
| | - Göran Widmalm
- Department of Organic Chemistry, Arrhenius Laboratory , Stockholm University , S-106 91 Stockholm , Sweden
| | - Sabine L Flitsch
- School of Chemistry & Manchester Institute of Biotechnology , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K
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Abstract
Glycoinformatics is a critical resource for the study of glycobiology, and glycobiology is a necessary component for understanding the complex interface between intra- and extracellular spaces. Despite this, there is limited software available to scientists studying these topics, requiring each to create fundamental data structures and representations anew for each of their applications. This leads to poor uptake of standardization and loss of focus on the real problems. We present glypy, a library written in Python for reading, writing, manipulating, and transforming glycans at several levels of precision. In addition to understanding several common formats for textual representation of glycans, the library also provides application programming interfaces (APIs) for major community databases, including GlyTouCan and UnicarbKB. The library is freely available under the Apache 2 common license with source code available at https://github.com/mobiusklein/ and documentation at https://glypy.readthedocs.io/ .
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Affiliation(s)
- Joshua Klein
- Program for Bioinformatics , Boston University , Boston , Massachusetts 02215 , United States
| | - Joseph Zaia
- Program for Bioinformatics , Boston University , Boston , Massachusetts 02215 , United States.,Department of Biochemistry , Boston University , Boston , Massachusetts 02215 , United States
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39
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Birch J, Van Calsteren MR, Pérez S, Svensson B. The exopolysaccharide properties and structures database: EPS-DB. Application to bacterial exopolysaccharides. Carbohydr Polym 2019; 205:565-570. [DOI: 10.1016/j.carbpol.2018.10.063] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 10/19/2018] [Accepted: 10/21/2018] [Indexed: 11/27/2022]
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40
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A novel broad specificity fucosidase capable of core α1-6 fucose release from N-glycans labeled with urea-linked fluorescent dyes. Sci Rep 2018; 8:9504. [PMID: 29934601 PMCID: PMC6015026 DOI: 10.1038/s41598-018-27797-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 06/07/2018] [Indexed: 11/08/2022] Open
Abstract
Exoglycosidases are often used for detailed characterization of glycan structures. Bovine kidney α-fucosidase is commonly used to determine the presence of core α1-6 fucose on N-glycans, an important modification of glycoproteins. Recently, several studies have reported that removal of core α1-6-linked fucose from N-glycans labeled with the reactive N-hydroxysuccinimide carbamate fluorescent labels 6-aminoquinolyl-N-hydroxysuccinimidylcarbamate (AQC) and RapiFluor-MS is severely impeded. We report here the cloning, expression and biochemical characterization of an α-fucosidase from Omnitrophica bacterium (termed fucosidase O). We show that fucosidase O can efficiently remove α1-6- and α1-3-linked core fucose from N-glycans. Additionally, we demonstrate that fucosidase O is able to efficiently hydrolyze core α1-6-linked fucose from N-glycans labeled with any of the existing NHS-carbamate activated fluorescent dyes.
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41
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The Glycoscience of Immunity. Trends Immunol 2018; 39:523-535. [PMID: 29759949 DOI: 10.1016/j.it.2018.04.004] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 04/12/2018] [Accepted: 04/13/2018] [Indexed: 02/05/2023]
Abstract
Carbohydrates, or glycans, are as integral to biology as nucleic acids and proteins. In immunology, glycans are well known to drive diverse functions ranging from glycosaminoglycan-mediated chemokine presentation and selectin-dependent leukocyte trafficking to the discrimination of self and non-self through the recognition of sialic acids by Siglec (sialic acid-binding Ig-like lectin) receptors. In recent years, a number of key immunological discoveries are driving a renewed and burgeoning appreciation for the importance of glycans. In this review, we highlight these findings which collectively help to define and refine our knowledge of the function and impact of glycans within the immune response.
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42
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Emerging glycobiology tools: A renaissance in accessibility. Cell Immunol 2018; 333:2-8. [PMID: 29759530 DOI: 10.1016/j.cellimm.2018.04.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/23/2018] [Accepted: 04/24/2018] [Indexed: 01/01/2023]
Abstract
The glycobiology of the immune response is a topic that has garnered increased attention due to a number of key discoveries surrounding IgG function, the specificity of some broadly neutralizing anti-HIV antibodies, cancer immunoregulation by galectin molecules and others. This review is the opening article in a Special Edition of Cellular Immunology focused on glycoimmunology, and has the goal of setting the context for these articles by providing a mini-review of how glycans impact immunity. We also focus on some of the technological and methodological advances in the field of glycobiology that are being deployed to lower the barrier of entry into the glycosciences, and to more fully interrogate the glycome and its function.
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43
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Ruhaak LR, Xu G, Li Q, Goonatilleke E, Lebrilla CB. Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses. Chem Rev 2018; 118:7886-7930. [PMID: 29553244 DOI: 10.1021/acs.chemrev.7b00732] [Citation(s) in RCA: 253] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycans are produced through a complicated nontemplate driven process involving the competition of enzymes that extend the nascent chain. The large diversity of structures, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies of glycans all conspire to make the analysis arguably much more difficult than any other biopolymer. Furthermore, the large number of glycoforms associated with a specific protein site makes it more difficult to characterize than any post-translational modification. Nonetheless, there have been significant progress, and advanced separation and mass spectrometry methods have been at its center and the main reason for the progress. While glycomic and glycoproteomic analyses are still typically available only through highly specialized laboratories, new software and workflow is making it more accessible. This review focuses on the role of mass spectrometry and separation methods in advancing glycomic and glycoproteomic analyses. It describes the current state of the field and progress toward making it more available to the larger scientific community.
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Affiliation(s)
- L Renee Ruhaak
- Department of Clinical Chemistry and Laboratory Medicine , Leiden University Medical Center , 2333 ZA Leiden , The Netherlands
| | - Gege Xu
- Department of Chemistry , University of California, Davis , One Shields Avenue , Davis , California 95616 , United States
| | - Qiongyu Li
- Department of Chemistry , University of California, Davis , One Shields Avenue , Davis , California 95616 , United States
| | - Elisha Goonatilleke
- Department of Chemistry , University of California, Davis , One Shields Avenue , Davis , California 95616 , United States
| | - Carlito B Lebrilla
- Department of Chemistry , University of California, Davis , One Shields Avenue , Davis , California 95616 , United States.,Department of Biochemistry and Molecular Medicine , University of California, Davis , Davis , California 95616 , United States.,Foods for Health Institute , University of California, Davis , Davis , California 95616 , United States
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44
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Finite Dimension: A Mathematical Tool to Analise Glycans. Sci Rep 2018. [PMID: 29535393 PMCID: PMC5849774 DOI: 10.1038/s41598-018-22575-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
There is a need to develop widely applicable tools to understand glycan organization, diversity and structure. We present a graph-theoretical study of a large sample of glycans in terms of finite dimension, a new metric which is an adaptation to finite sets of the classical Hausdorff “fractal” dimension. Every glycan in the sample is encoded, via finite dimension, as a point of Glycan Space, a new notion introduced in this paper. Two major outcomes were found: (a) the existence of universal bounds that restrict the universe of possible glycans and show, for instance, that the graphs of glycans are a very special type of chemical graph, and (b) how Glycan Space is related to biological domains associated to the analysed glycans. In addition, we discuss briefly how this encoding may help to improve search in glycan databases.
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45
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Sun W, Liu Y, Zhang K. An approach for N-linked glycan identification from MS/MS spectra by target-decoy strategy. Comput Biol Chem 2018; 74:391-398. [PMID: 29580737 DOI: 10.1016/j.compbiolchem.2018.03.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 03/13/2018] [Indexed: 12/28/2022]
Abstract
Glycan structure determination serves as an essential step for the thorough investigation of the structure and function of protein. Currently, appropriate sample preparation followed by tandem mass spectrometry has emerged as the dominant technique for the characterization of glycans and glycopeptides. Although extensive efforts have been made to the development of computational approaches for the automated interpretation of glycopeptide spectra, the previously appeared methods lack a reasonable quality control strategy for the statistical validation of reported results. In this manuscript, we introduced a novel method that constructed a decoy glycan database based on the glycan structures in the target database, and searched the experimental spectra against both the target and decoy databases to find the best matched glycans. Specifically, a two-layer scoring scheme for calculating a normalized matching score is applied in the search procedure which enables the unbiased ranking of the matched glycans. Experimental analysis showed that our proposed method can report more structures with high confidence compared with previous approaches.
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Affiliation(s)
- Weiping Sun
- Department of Computer Science, University of Western Ontario, London, ON N6A5B7, Canada.
| | - Yi Liu
- Department of Computer Science, University of Western Ontario, London, ON N6A5B7, Canada
| | - Kaizhong Zhang
- Department of Computer Science, University of Western Ontario, London, ON N6A5B7, Canada
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46
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Everest-Dass AV, Moh ESX, Ashwood C, Shathili AMM, Packer NH. Human disease glycomics: technology advances enabling protein glycosylation analysis - part 1. Expert Rev Proteomics 2018; 15:165-182. [PMID: 29285957 DOI: 10.1080/14789450.2018.1421946] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
INTRODUCTION Protein glycosylation is recognized as an important post-translational modification, with specific substructures having significant effects on protein folding, conformation, distribution, stability and activity. However, due to the structural complexity of glycans, elucidating glycan structure-function relationships is demanding. The fine detail of glycan structures attached to proteins (including sequence, branching, linkage and anomericity) is still best analysed after the glycans are released from the purified or mixture of glycoproteins (glycomics). The technologies currently available for glycomics are becoming streamlined and standardized and many features of protein glycosylation can now be determined using instruments available in most protein analytical laboratories. Areas covered: This review focuses on the current glycomics technologies being commonly used for the analysis of the microheterogeneity of monosaccharide composition, sequence, branching and linkage of released N- and O-linked glycans that enable the determination of precise glycan structural determinants presented on secreted proteins and on the surface of all cells. Expert commentary: Several emerging advances in these technologies enabling glycomics analysis are discussed. The technological and bioinformatics requirements to be able to accurately assign these precise glycan features at biological levels in a disease context are assessed.
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Affiliation(s)
- Arun V Everest-Dass
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,b Institute for Glycomics , Griffith University , Gold Coast , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Edward S X Moh
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Christopher Ashwood
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Abdulrahman M M Shathili
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
| | - Nicolle H Packer
- a Biomolecular Discovery and Design Research Centre, Faculty of Science and Engineering , Macquarie University , Sydney , Australia.,b Institute for Glycomics , Griffith University , Gold Coast , Australia.,c ARC Centre for Nanoscale BioPhotonics , Macquarie University , Sydney , Australia
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47
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Kailemia MJ, Xu G, Wong M, Li Q, Goonatilleke E, Leon F, Lebrilla CB. Recent Advances in the Mass Spectrometry Methods for Glycomics and Cancer. Anal Chem 2018; 90:208-224. [PMID: 29049885 PMCID: PMC6200424 DOI: 10.1021/acs.analchem.7b04202] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Muchena J. Kailemia
- Department of Chemistry, University of California, Davis, One Shields Avenue, Davis, CA 95616, United States
- These authors contributed equally to this work
| | - Gege Xu
- Department of Chemistry, University of California, Davis, One Shields Avenue, Davis, CA 95616, United States
- These authors contributed equally to this work
| | - Maurice Wong
- Department of Chemistry, University of California, Davis, One Shields Avenue, Davis, CA 95616, United States
| | - Qiongyu Li
- Department of Chemistry, University of California, Davis, One Shields Avenue, Davis, CA 95616, United States
| | - Elisha Goonatilleke
- Department of Chemistry, University of California, Davis, One Shields Avenue, Davis, CA 95616, United States
| | - Frank Leon
- Department of Chemistry, University of California, Davis, One Shields Avenue, Davis, CA 95616, United States
| | - Carlito B. Lebrilla
- Department of Chemistry, University of California, Davis, One Shields Avenue, Davis, CA 95616, United States
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA 95616, USA
- Foods for Health Institute, University of California, Davis, CA 95616, USA
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48
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Joshi HJ, Jørgensen A, Schjoldager KT, Halim A, Dworkin LA, Steentoft C, Wandall HH, Clausen H, Vakhrushev SY. GlycoDomainViewer: a bioinformatics tool for contextual exploration of glycoproteomes. Glycobiology 2017; 28:131-136. [DOI: 10.1093/glycob/cwx104] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Accepted: 12/07/2017] [Indexed: 11/13/2022] Open
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49
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Minkiewicz P, Iwaniak A, Darewicz M. Annotation of Peptide Structures Using SMILES and Other Chemical Codes-Practical Solutions. Molecules 2017; 22:molecules22122075. [PMID: 29186902 PMCID: PMC6149970 DOI: 10.3390/molecules22122075] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 11/15/2017] [Accepted: 11/25/2017] [Indexed: 12/20/2022] Open
Abstract
Contemporary peptide science exploits methods and tools of bioinformatics, and cheminformatics. These approaches use different languages to describe peptide structures—amino acid sequences and chemical codes (especially SMILES), respectively. The latter may be applied, e.g., in comparative studies involving structures and properties of peptides and peptidomimetics. Progress in peptide science “in silico” may be achieved via better communication between biologists and chemists, involving the translation of peptide representation from amino acid sequence into SMILES code. Recent recommendations concerning good practice in chemical information include careful verification of data and their annotation. This publication discusses the generation of SMILES representations of peptides using existing software. Construction of peptide structures containing unnatural and modified amino acids (with special attention paid on glycosylated peptides) is also included. Special attention is paid to the detection and correction of typical errors occurring in SMILES representations of peptides and their correction using molecular editors. Brief recommendations for training of staff working on peptide annotations, are discussed as well.
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Affiliation(s)
- Piotr Minkiewicz
- Chair of Food Biochemistry, Faculty of Food Science, University of Warmia and Mazury in Olsztyn, Plac Cieszyński 1, 10-726 Olsztyn-Kortowo, Poland.
| | - Anna Iwaniak
- Chair of Food Biochemistry, Faculty of Food Science, University of Warmia and Mazury in Olsztyn, Plac Cieszyński 1, 10-726 Olsztyn-Kortowo, Poland.
| | - Małgorzata Darewicz
- Chair of Food Biochemistry, Faculty of Food Science, University of Warmia and Mazury in Olsztyn, Plac Cieszyński 1, 10-726 Olsztyn-Kortowo, Poland.
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50
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Klamer Z, Staal B, Prudden AR, Liu L, Smith DF, Boons GJ, Haab B. Mining High-Complexity Motifs in Glycans: A New Language To Uncover the Fine Specificities of Lectins and Glycosidases. Anal Chem 2017; 89:12342-12350. [PMID: 29058413 PMCID: PMC5700451 DOI: 10.1021/acs.analchem.7b04293] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
![]()
Knowledge of lectin
and glycosidase specificities is fundamental
to the study of glycobiology. The primary specificities of such molecules
can be uncovered using well-established tools, but the complex details
of their specificities are difficult to determine and describe. Here
we present a language and algorithm for the analysis and description
of glycan motifs with high complexity. The language uses human-readable
notation and wildcards, modifiers, and logical operators to define
motifs of nearly any complexity. By applying the syntax to the analysis
of glycan-array data, we found that the lectin AAL had higher binding
where fucose groups are displayed on separate branches. The lectin
SNA showed gradations in binding based on the length of the extension
displaying sialic acid and on characteristics of the opposing branches.
A new algorithm to evaluate changes in lectin binding upon treatment
with exoglycosidases identified the primary specificities and potential
fine specificities of an α1–2-fucosidase and an α2–3,6,8-neuraminidase.
The fucosidase had significantly lower action where sialic acid neighbors
the fucose, and the neuraminidase showed statistically lower action
where α1–2 fucose neighbors the sialic acid or is on
the opposing branch. The complex features identified here would have
been inaccessible to analysis using previous methods. The new language
and algorithms promise to facilitate the precise determination and
description of lectin and glycosidase specificities.
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Affiliation(s)
- Zachary Klamer
- Van Andel Research Institute , 333 Bostwick NE, Grand Rapids, Michigan 49503, United States
| | - Ben Staal
- Van Andel Research Institute , 333 Bostwick NE, Grand Rapids, Michigan 49503, United States
| | - Anthony R Prudden
- Complex Carbohydrate Research Center, University of Georgia , 315 Riverbend Road, Athens, Georgia 30602, United States
| | - Lin Liu
- Complex Carbohydrate Research Center, University of Georgia , 315 Riverbend Road, Athens, Georgia 30602, United States
| | - David F Smith
- Emory Comprehensive Glycomics Core, Emory University School of Medicine , Atlanta, Georgia 30322, United States
| | - Geert-Jan Boons
- Complex Carbohydrate Research Center, University of Georgia , 315 Riverbend Road, Athens, Georgia 30602, United States
| | - Brian Haab
- Van Andel Research Institute , 333 Bostwick NE, Grand Rapids, Michigan 49503, United States
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