1
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Akune-Taylor Y, Kon A, Aoki-Kinoshita KF. In silico simulation of glycosylation and related pathways. Anal Bioanal Chem 2024; 416:3687-3696. [PMID: 38748247 PMCID: PMC11180631 DOI: 10.1007/s00216-024-05331-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 04/30/2024] [Accepted: 05/02/2024] [Indexed: 06/18/2024]
Abstract
Glycans participate in a vast number of recognition systems in diverse organisms in health and in disease. However, glycans cannot be sequenced because there is no sequencer technology that can fully characterize them. There is no "template" for replicating glycans as there are for amino acids and nucleic acids. Instead, glycans are synthesized by a complicated orchestration of multitudes of glycosyltransferases and glycosidases. Thus glycans can vary greatly in structure, but they are not genetically reproducible and are usually isolated in minute amounts. To characterize (sequence) the glycome (defined as the glycans in a particular organism, tissue, cell, or protein), glycosylation pathway prediction using in silico methods based on glycogene expression data, and glycosylation simulations have been attempted. Since many of the mammalian glycogenes have been identified and cloned, it has become possible to predict the glycan biosynthesis pathway in these systems. By then incorporating systems biology and bioprocessing technologies to these pathway models, given the right enzymatic parameters including enzyme and substrate concentrations and kinetic reaction parameters, it is possible to predict the potentially synthesized glycans in the pathway. This review presents information on the data resources that are currently available to enable in silico simulations of glycosylation and related pathways. Then some of the software tools that have been developed in the past to simulate and analyze glycosylation pathways will be described, followed by a summary and vision for the future developments and research directions in this area.
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Affiliation(s)
- Yukie Akune-Taylor
- Glycan and Life Systems Integration Center, Soka University, Tokyo, Japan
| | - Akane Kon
- Graduate School of Science and Engineering, Soka University, Tokyo, Japan
| | - Kiyoko F Aoki-Kinoshita
- Glycan and Life Systems Integration Center, Soka University, Tokyo, Japan.
- Graduate School of Science and Engineering, Soka University, Tokyo, Japan.
- iGCORE, Nagoya University, Nagoya, Japan.
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2
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Jin C, Venkatakrishnan V, Thomsson KA, Aoki NP, Shinmachi D, Aoki-Kinoshita KF, Hayes CA, Lisacek F, Karlsson NG. UniCarb-DB: An MS/MS Experimental Glycomic Fragmentation Database. Methods Mol Biol 2024; 2836:77-96. [PMID: 38995537 DOI: 10.1007/978-1-0716-4007-4_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
Glycosylation is a unique posttranslational modification that dynamically shapes the surface of cells. Glycans attached to proteins or lipids in a cell or tissue are studied as a whole and collectively designated as a glycome. UniCarb-DB is a glycomic spectral library of tandem mass spectrometry (MS/MS) fragment data. The current version of the database consists of over 1500 entries and over 1000 unique structures. Each entry contains parent ion information with associated MS/MS spectra, metadata about the original publication, experimental conditions, and biological origin. Each structure is also associated with the GlyTouCan glycan structure repository allowing easy access to other glycomic resources. The database can be directly utilized by mass spectrometry (MS) experimentalists through the conversion of data generated by MS into structural information. Flexible online search tools along with a downloadable version of the database are easily incorporated in either commercial or open-access MS software. This chapter highlights UniCarb-DB online search tool to browse differences of isomeric structures between spectra, a peak matching search between user-generated MS/MS spectra and spectra stored in UniCarb-DB and more advanced MS tools for combined quantitative and qualitative glycomics.
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Affiliation(s)
- Chunsheng Jin
- Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Kristina A Thomsson
- Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nobuyuki P Aoki
- Soka University, Hachioji, Tokyo, Japan
- SparqLite.com, Hachioji, Tokyo, Japan
| | | | | | - Catherine A Hayes
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
- Computer Science Department, University of Geneva, Geneva, Switzerland
- Section of Biology, University of Geneva, Geneva, Switzerland
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | - Niclas G Karlsson
- Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Division of Pharmacy, Department of Life Science and Health, Faculty of Health Science, Oslo Metropolitan University, Oslo, Norway.
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3
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Kellman BP, Richelle A, Yang JY, Chapla D, Chiang AWT, Najera JA, Liang C, Fürst A, Bao B, Koga N, Mohammad MA, Bruntse AB, Haymond MW, Moremen KW, Bode L, Lewis NE. Elucidating Human Milk Oligosaccharide biosynthetic genes through network-based multi-omics integration. Nat Commun 2022; 13:2455. [PMID: 35508452 PMCID: PMC9068700 DOI: 10.1038/s41467-022-29867-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 04/04/2022] [Indexed: 12/18/2022] Open
Abstract
Human Milk Oligosaccharides (HMOs) are abundant carbohydrates fundamental to infant health and development. Although these oligosaccharides were discovered more than half a century ago, their biosynthesis in the mammary gland remains largely uncharacterized. Here, we use a systems biology framework that integrates glycan and RNA expression data to construct an HMO biosynthetic network and predict glycosyltransferases involved. To accomplish this, we construct models describing the most likely pathways for the synthesis of the oligosaccharides accounting for >95% of the HMO content in human milk. Through our models, we propose candidate genes for elongation, branching, fucosylation, and sialylation of HMOs. Our model aggregation approach recovers 2 of 2 previously known gene-enzyme relations and 2 of 3 empirically confirmed gene-enzyme relations. The top genes we propose for the remaining 5 linkage reactions are consistent with previously published literature. These results provide the molecular basis of HMO biosynthesis necessary to guide progress in HMO research and application with the goal of understanding and improving infant health and development.
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Affiliation(s)
- Benjamin P Kellman
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Anne Richelle
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Jeong-Yeh Yang
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
| | - Digantkumar Chapla
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
| | - Austin W T Chiang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Julia A Najera
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Chenguang Liang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Annalee Fürst
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Bokan Bao
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Natalia Koga
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, 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, 77030, USA
| | - Anders Bech Bruntse
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, 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, 77030, USA
| | - Kelley W Moremen
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
| | - Lars Bode
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
- Larsson-Rosenquist Foundation Mother-Milk-Infant Center of Research Excellence (MOMI CORE), University of California, San Diego, La Jolla, CA, 92093, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA.
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA.
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4
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Aoki-Kinoshita KF. Functions of Glycosylation and Related Web Resources for Its Prediction. Methods Mol Biol 2022; 2499:135-144. [PMID: 35696078 DOI: 10.1007/978-1-0716-2317-6_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Glycosylation involves the attachment of carbohydrate sugar chains, or glycans, onto an amino acid residue of a protein. These glycans are often branched structures and serve to modulate the function of proteins. Glycans are synthesized through a complex process of enzymatic reactions that occur in the Golgi apparatus in mammalian systems. Because there is currently no sequencer for glycans, technologies such as mass spectrometry is used to characterize glycans in a biological sample to ascertain its glycome. This is a tedious process that requires high levels of expertise and equipment. Thus, the enzymes that work on glycans, called glycogenes or glycoenzymes, have been studied to better understand glycan function. With the development of glycan-related databases and a glycan repository, bioinformatics approaches have attempted to predict the glycosylation pathway and the glycosylation sites on proteins. This chapter introduces these methods and related Web resources for understanding glycan function.
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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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6
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Aoki-Kinoshita KF. Glycome informatics: using systems biology to gain mechanistic insights into glycan biosynthesis. Curr Opin Chem Eng 2021. [DOI: 10.1016/j.coche.2021.100683] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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7
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Guan Y, Zhang M, Wang J, Schlüter H. Comparative Analysis of Different N-glycan Preparation Approaches and Development of Optimized Solid-Phase Permethylation Using Mass Spectrometry. J Proteome Res 2021; 20:2914-2922. [PMID: 33829797 DOI: 10.1021/acs.jproteome.1c00135] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Protein N-glycosylation characterization is challenging due to structural micro- and macro-heterogeneity. Although various N-glycan preparation strategies, including purification and derivatization, have been previously developed prior to mass spectrometric analysis, systematic evaluation still needs to be performed. This study compared the different N-glycan purification strategies, including filter-aided sample preparation, de-N-glycosylated protein precipitation, and trypsin digestion followed by reversed phase-based solid-phase extraction, and derivatization approaches, such as solid-phase permethylation, reductive amination, and reduction. With the comparative analysis, an optimized solid-phase permethylation (OSPP) workflow was developed for mass spectrometric N-glycomics, showing simplified analysis for N-glycan compositions and high yields using etanercept. The N-glycan samples released from trastuzumab and adalimumab were utilized to test OSPP to obtain their N-glycan profiles using mass spectrometry. Based on different standard procedures across laboratories, this study provides the reference for analysts to select an appropriate N-glycan preparation method with their research purposes.
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Affiliation(s)
- Yudong Guan
- The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen 518055, China
| | - Min Zhang
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Jigang Wang
- The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen 518055, China
| | - Hartmut Schlüter
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
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8
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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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9
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Identifying Scientific and Technical “Unicorns”. JOURNAL OF DATA AND INFORMATION SCIENCE 2020. [DOI: 10.2478/jdis-2021-0002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Abstract
Purpose
Using the metaphor of “unicorn,” we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing, which may provide a new pattern to understand very high impact works in science and technology.
Design/methodology/approach
When we set CT as the total citations of papers or patents in the first ten years after publication, with CT≥ 5,000 for scientific “unicorn” and CT≥ 500 for technical “unicorn,” we have an absolute standard for identifying scientific and technical “unicorn” publications.
Findings
We identify 165 scientific “unicorns” in 14,301,875 WoS papers and 224 technical “unicorns” in 13,728,950 DII patents during 2001–2012. About 50% of “unicorns” belong to biomedicine, in which selected cases are individually discussed. The rare “unicorns” increase following linear model, the fitting data show 95% confidence with the RMSE of scientific “unicorn” is 0.2127 while the RMSE of technical “unicorn” is 0.0923.
Research limitations
A “unicorn” is a pure quantitative consideration without concerning its quality, and “potential unicorns” as CT≤5,000 for papers and CT≤500 for patents are left in future studies.
Practical implications
Scientific and technical “unicorns” provide a new pattern to understand high-impact works in science and technology. The “unicorn” pattern supplies a concise approach to identify very high-impact scientific papers and technical patents.
Originality/value
The “unicorn” pattern supplies a concise approach to identify very high impact scientific papers and technical patents.
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10
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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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11
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Ahmad Izaham AR, Scott NE. Open Database Searching Enables the Identification and Comparison of Bacterial Glycoproteomes without Defining Glycan Compositions Prior to Searching. Mol Cell Proteomics 2020. [PMID: 32576591 DOI: 10.1101/2020.04.21.052845] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/15/2023] Open
Abstract
Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.
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Affiliation(s)
- Ameera Raudah Ahmad Izaham
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Nichollas E Scott
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
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12
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Ahmad Izaham AR, Scott NE. Open Database Searching Enables the Identification and Comparison of Bacterial Glycoproteomes without Defining Glycan Compositions Prior to Searching. Mol Cell Proteomics 2020; 19:1561-1574. [PMID: 32576591 PMCID: PMC8143609 DOI: 10.1074/mcp.tir120.002100] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 05/27/2020] [Indexed: 12/23/2022] Open
Abstract
Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.
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Affiliation(s)
- Ameera Raudah Ahmad Izaham
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Nichollas E Scott
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
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13
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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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14
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Sharma S, Shekhar S, Sharma B, Jain P. Decoding glycans: deciphering the sugary secrets to be coherent on the implication. RSC Adv 2020; 10:34099-34113. [PMID: 35519023 PMCID: PMC9056758 DOI: 10.1039/d0ra04471g] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 08/23/2020] [Indexed: 12/28/2022] Open
Abstract
Neoteric techniques, skills, and methodological advances in glycobiology and glycochemistry have been instrumental in pertinent discoveries to pave way for a new era in biomedical sciences. Glycans are sugar-based polymers that coat cells and decorate majority of proteins, forming glycoproteins. They are also found deposited in extracellular spaces between cells, attached to soluble signaling molecules, and are key players in several biological processes including regulation of immune responses and cell–cell interactions. Laboratory manipulations of protein, DNA and other macromolecules celebrate the accelerated research in respective fields, but the same seems unlikely for the complex sugar polymers. The structural complex polymers are neither synthesized using a known template nor are dynamically stable with respect to a cell's metabolic rate. What is more, sugar isomers—structurally distinct molecules with the same chemical formula—can be employed to construct varied glycans, but are almost impossible to tell apart based on molecular weight alone. The apparent lack of a glycan alphabet further reflects on an enduring question: how little do we know about the sugars? Evidently, glycan-based therapeutic potentials and glycomimetics are propitious advances for the future that have not been well exploited, and with a few conspicuous anomalies. Here, we contour the most notable contributions to enhance our ability to utilize the complex glycans as therapeutics. Diagnostic strategies concerning recurrent diseases and headways to address the challenges are also discussed. A glycan toolbox for pathogenic and cancerous interventions. The review article sheds light on the sweet secrets of this complex structure.![]()
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Affiliation(s)
- Shreya Sharma
- Department of Chemistry
- Netaji Subhas University of Technology
- India
| | - Shashank Shekhar
- Department of Chemistry
- Netaji Subhas University of Technology
- India
| | - Bhasha Sharma
- Department of Chemistry
- Netaji Subhas University of Technology
- India
| | - Purnima Jain
- Department of Chemistry
- Netaji Subhas University of Technology
- India
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15
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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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Akiyoshi S, Iwata M, Berenger F, Yamanishi Y. Omics-based Identification of Glycan Structures as Biomarkers for a Variety of Diseases. Mol Inform 2019; 39:e1900112. [PMID: 31622036 DOI: 10.1002/minf.201900112] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 09/24/2019] [Indexed: 12/11/2022]
Abstract
Glycans play important roles in cell communication, protein interaction, and immunity, and structural changes in glycans are associated with the regulation of a range of biological pathways involved in disease. However, our understanding of the detailed relationships between specific diseases and glycans is very limited. In this study, we proposed an omics-based method to investigate the correlations between glycans and a wide range of human diseases. We analyzed the gene expression patterns of glycogenes (glycosyltransferases and glycosidases) for 79 different diseases. A biological pathway-based glycogene signature was constructed to identify the alteration in glycan biosynthesis and the associated glycan structures for each disease state. The degradation of N-glycan and keratan sulfate, for example, may promote the growth or metastasis of multiple types of cancer, including endometrial, gastric, and nasopharyngeal. Our results also revealed that commonalities between diseases can be interpreted using glycogene expression patterns, as well as the associated glycan structure patterns at the level of the affected pathway. The proposed method is expected to be useful for understanding the relationships between glycans, glycogenes, and disease and identifying disease-specific glycan biomarkers.
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Affiliation(s)
- Sayaka Akiyoshi
- Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, Fukuoka, 812-8582, Japan
| | - Michio Iwata
- Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan
| | - Francois Berenger
- Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan
| | - Yoshihiro Yamanishi
- Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan
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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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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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Ashwood C, Pratt B, MacLean BX, Gundry RL, Packer NH. Standardization of PGC-LC-MS-based glycomics for sample specific glycotyping. Analyst 2019; 144:3601-3612. [PMID: 31065629 DOI: 10.1039/c9an00486f] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Porous graphitized carbon (PGC) based chromatography achieves high-resolution separation of glycan structures released from glycoproteins. This approach is especially valuable when resolving structurally similar isomers and for discovery of novel and/or sample-specific glycan structures. However, the implementation of PGC-based separations in glycomics studies has been limited because system-independent retention values have not been established to normalize technical variation. To address this limitation, this study combined the use of hydrolyzed dextran as an internal standard and Skyline software for post-acquisition normalization to reduce retention time and peak area technical variation in PGC-based glycan analyses. This approach allowed assignment of system-independent retention values that are applicable to typical PGC-based glycan separations and supported the construction of a library containing >300 PGC-separated glycan structures with normalized glucose unit (GU) retention values. To enable the automation of this normalization method, a spectral MS/MS library was developed of the dextran ladder, achieving confident discrimination against isomeric glycans. The utility of this approach is demonstrated in two ways. First, to inform the search space for bioinformatically predicted but unobserved glycan structures, predictive models for two structural modifications, core-fucosylation and bisecting GlcNAc, were developed based on the GU library. Second, the applicability of this method for the analysis of complex biological samples is evidenced by the ability to discriminate between cell culture and tissue sample types by the normalized intensity of N-glycan structures alone. Overall, the methods and data described here are expected to support the future development of more automated approaches to glycan identification and quantitation.
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Affiliation(s)
- Christopher Ashwood
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia. and ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, NSW, Australia and Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Brian Pratt
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Brendan X MacLean
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Rebekah L Gundry
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA and Center for Biomedical Mass Spectrometry Research, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Nicolle H Packer
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia. and ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, NSW, Australia
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Sun W, Liu Y, Lajoie GA, Ma B, Zhang K. An Improved Approach for N-Linked Glycan Structure Identification from HCD MS/MS Spectra. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019; 16:388-395. [PMID: 28489544 DOI: 10.1109/tcbb.2017.2701819] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Glycosylation is a frequently observed post-translational modification on proteins. Currently, tandem mass spectrometry (MS/MS) serves as an efficient analytical technique for characterizing structures of oligosaccharides. However, developing effective computational approaches for identifying glycan structures from mass spectra is still a great challenge in glycoproteomics research. In this study, we proposed an approach for matching the input spectra with glycan structures acquired from a glycan structure database by incorporating a de novo sequencing assisted ranking scheme. The proposed approach is implemented as a software tool, GlycoNovoDB, for automated glycan structure identification from HCD MS/MS of glycopeptides. Experimental results showed that GlycoNovoDB can identify glycans effectively and has better performance than our previously proposed de novo sequencing algorithm as well as another software GlycoMaster DB.
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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 PMCID: PMC7757723 DOI: 10.1021/acs.chemrev.7b00732] [Citation(s) in RCA: 253] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [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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22
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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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