UniCarb-DB: a database resource for glycomic discovery

Summary: Glycosylation is one of the most important post-translational modifications of proteins, known to be involved in pathogen recognition, innate immune response and protection of epithelial membranes. However, when compared to the tools and databases available for the processing of high-throughput proteomic data, the glycomic domain is severely lacking. While tools to assist the analysis of mass spectrometry (MS) and HPLC are continuously improving, there are few resources available to support liquid chromatography (LC)-MS/MS techniques for glycan structure profiling. Here, we present a platform for presenting oligosaccharide structures and fragment data characterized by LC-MS/MS strategies. The database is annotated with high-quality datasets and is designed to extend and reinforce those standards and ontologies developed by existing glycomics databases. Availability: http://www.unicarb-db.org Contact: [email protected]

GlycoViewer: a tool for visual summary and comparative analysis of the glycome

The GlycoViewer (http://www.systemsbiology.org.au/glycoviewer) is a web-based tool that can visualize, summarize and compare sets of glycan structures. Its input is a group of glycan structures; these can be entered as a list in IUPAC format or via a sugar structure builder. Its output is a detailed graphic, which summarizes all salient features of the glycans according to the shapes of the core structures, the nature and length of any chains, and the types of terminal epitopes. The tool can summarize up to hundreds of structures in a single figure. This allows unique, high-level views to be generated of glycans from one protein, from a cell, a tissue or a whole organism. Use of the tool is illustrated in the analysis of normal and disease-associated glycans from the human glycoproteome

GlycoDigest: a tool for the targeted use of exoglycosidase digestions in glycan structure determination

Summary: Sequencing oligosaccharides by exoglycosidases, either sequentially or in an array format, is a powerful tool to unambiguously determine the structure of complex N- and O-link glycans. Here, we introduce GlycoDigest, a tool that simulates exoglycosidase digestion, based on controlled rules acquired from expert knowledge and experimental evidence available in GlycoBase. The tool allows the targeted design of glycosidase enzyme mixtures by allowing researchers to model the action of exoglycosidases, thereby validating and improving the efficiency and accuracy of glycan analysis. Availability and implementation: http://www.glycodigest.org. Contact: [email protected] or [email protected]

UniCarbKB: building a knowledge platform for glycoproteomics

The UniCarb KnowledgeBase (UniCarbKB; http://unicarbkb.org) offers public access to a growing, curated database of information on the glycan structures of glycoproteins. UniCarbKB is an international effort that aims to further our understanding of structures, pathways and networks involved in glycosylation and glyco-mediated processes by integrating structural, experimental and functional glycoscience information. This initiative builds upon the success of the glycan structure database GlycoSuiteDB, together with the informatic standards introduced by EUROCarbDB, to provide a high-quality and updated resource to support glycomics and glycoproteomics research. UniCarbKB provides comprehensive information concerning glycan structures, and published glycoprotein information including global and site-specific attachment information. For the first release over 890 references, 3740 glycan structure entries and 400 glycoproteins have been curated. Further, 598 protein glycosylation sites have been annotated with experimentally confirmed glycan structures from the literature. Among these are 35 glycoproteins, 502 structures and 60 publications previously not included in GlycoSuiteDB. This article provides an update on the transformation of GlycoSuiteDB (featured in previous NAR Database issues and hosted by ExPASy since 2009) to UniCarbKB and its integration with UniProtKB and GlycoMod. Here, we introduce a refactored database, supported by substantial new curated data collections and intuitive user-interfaces that improve database searchin

Changes in dietary fiber intake in mice reveal associations between colonic mucin O-glycosylation and specific gut bacteria

The colonic mucus layer, comprised of highly O-glycosylated mucins, is vital to mediating host-gut microbiota interactions, yet the impact of dietary changes on colonic mucin O-glycosylation and its associations with the gut microbiota remains unexplored. Here, we used an array of omics techniques including glycomics to examine the effect of dietary fiber consumption on the gut microbiota, colonic mucin O-glycosylation and host physiology of high-fat diet-fed C57BL/6J mice. The high-fat diet group had significantly impaired glucose tolerance and altered liver proteome, gut microbiota composition, and short-chain fatty acid production compared to normal chow diet group. While dietary fiber inclusion did not reverse all high fat-induced modifications, it resulted in specific changes, including an increase in the relative abundance of bacterial families with known fiber digesters and a higher propionate concentration. Conversely, colonic mucin O-glycosylation remained similar between the normal chow and high-fat diet groups, while dietary fiber intervention resulted in major alterations in O-glycosylation. Correlation network analysis revealed previously undescribed associations between specific bacteria and mucin glycan structures. For example, the relative abundance of the bacterium Parabacteroides distasonis positively correlated with glycan structures containing one terminal fucose and correlated negatively with glycans containing two terminal fucose residues or with both an N-acetylneuraminic acid and a sulfate residue. This is the first comprehensive report of the impact of dietary fiber on the colonic mucin O-glycosylation and associations of these mucosal glycans with specific gut bacteria

Biosimilarity and Interchangeability: Principles and Evidence: A Systematic Review

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Background The efficacy, safety and immunogenicity risk of switching between an originator biologic and a biosimilar or from one biosimilar to another are of potential concern. Objectives The aim was to conduct a systematic literature review of the outcomes of switching between biologics and their biosimilars and identify any evidence gaps. Methods A systematic literature search was conducted in PubMed, EMBASE and Cochrane Library from inception to June 2017. Relevant societal meetings were also checked. Peer-reviewed studies reporting efficacy and/or safety data on switching between originator and biosimilar products or from one biosimilar to another were selected. Studies with fewer than 20 switched patients were excluded. Data were extracted on interventions, study population, reason for treatment switching, efficacy outcomes, safety and anti-drug antibodies. Results The systematic literature search identified 63 primary publications covering 57 switching studies. The reason for switching was reported as non-medical in 50 studies (23 clinical, 27 observational). Seven studies (all observational) did not report whether the reasons for switching were medical or non-medical. In 38 of the 57 studies, fewer than 100 patients were switched. Follow-up after switching went beyond 1 year in eight of the 57 studies. Of the 57 studies, 33 included statistical analysis of disease activity or patient outcomes; the majority of these studies found no statistically significant differences between groups for main efficacy parameters (based on P < 0.05 or predefined acceptance ranges), although some studies observed changes for some parameters. Most studies reported similar safety profiles between groups. Conclusions There are important evidence gaps around the safety of switching between biologics and their biosimilars. Sufficiently powered and appropriately statistically analysed clinical trials and pharmacovigilance studies, with long-term follow-ups and multiple switches, are needed to support decision-making around biosimilar switching

Fiber Supplements Derived From Sugarcane Stem, Wheat Dextrin and Psyllium Husk Have Different In Vitro Effects on the Human Gut Microbiota

There is growing public interest in the use of fiber supplements as a way of increasing dietary fiber intake and potentially improving the gut microbiota composition and digestive health. However, currently there is limited research into the effects of commercially available fiber supplements on the gut microbiota. Here we used an in vitro human digestive and gut microbiota model system to investigate the effect of three commercial fiber products; NutriKane™, Benefiber® and Psyllium husk (Macro) on the adult gut microbiota. The 16S rRNA gene amplicon sequencing results showed dramatic fiber-dependent changes in the gut microbiota structure and composition. Specific bacterial OTUs within the families Bacteroidaceae, Porphyromonadaceae, Ruminococcaceae, Lachnospiraceae, and Bifidobacteriaceae showed an increase in the relative abundances in the presence of one or more fiber product(s), while Enterobacteriaceae and Pseudomonadaceae showed a reduction in the relative abundances upon addition of all fiber treatments compared to the no added fiber control. Fiber-specific increases in SCFA concentrations showed correlation with the relative abundance of potential SCFA-producing gut bacteria. The chemical composition, antioxidant potential and polyphenolic content profiles of each fiber product were determined and found to be highly variable. Observed product-specific variations could be linked to differences in the chemical composition of the fiber products. The general nature of the fiber-dependent impact was relatively consistent across the individuals, which may demonstrate the potential of the products to alter the gut microbiota in a similar, and predictable direction, despite variability in the starting composition of the individual gut microbiota

Production of α-L-iduronidase in maize for the potential treatment of a human lysosomal storage disease

Lysosomal storage diseases are a class of over 70 rare genetic diseases that are amenable to enzyme replacement therapy. Towards developing a plant-based enzyme replacement therapeutic for the lysosomal storage disease mucopolysaccharidosis I, here we expressed α-L-iduronidase in the endosperm of maize seeds by a previously uncharacterized mRNA-targeting-based mechanism. Immunolocalization, cellular fractionation and in situ RT-PCR demonstrate that the α-L-iduronidase protein and mRNA are targeted to endoplasmic reticulum (ER)-derived protein bodies and to protein body-ER regions, respectively, using regulatory (5′-and 3′-UTR) and signal-peptide coding sequences from the γ-zein gene. The maize α-L-iduronidase exhibits high activity, contains high-mannose N-glycans and is amenable to in vitro phosphorylation. This mRNA-based strategy is of widespread importance as plant N-glycan maturation is controlled and the therapeutic protein is generated in a native form. For our target enzyme, the N-glycan structures are appropriate for downstream processing, a prerequisite for its potential as a therapeutic protein.9 page(s

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submit- Avenue, Silver Spring, Maryland 20993; 22Glycoscience Research Laboratory, Genos, Borongajska cesta 83h, 10 000 Zagreb, Croatia; 23Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacˇ ic´ a 1, 10 000 Zagreb, Croatia; 24Department of Chemistry, Georgia State University, 100 Piedmont Avenue, Atlanta, Georgia 30303; 25glyXera GmbH, Brenneckestrasse 20 * ZENIT / 39120 Magdeburg, Germany; 26Health Products and Foods Branch, Health Canada, AL 2201E, 251 Sir Frederick Banting Driveway, Ottawa, Ontario, K1A 0K9 Canada; 27Graduate School of Advanced Sciences of Matter, Hiroshima University, 1-3-1 Kagamiyama Higashi-Hiroshima 739–8530 Japan; 28ImmunoGen, 830 Winter Street, Waltham, Massachusetts 02451; 29Department of Medical Physiology, Jagiellonian University Medical College, ul. Michalowskiego 12, 31–126 Krakow, Poland; 30Department of Pathology, Johns Hopkins University, 400 N. Broadway Street Baltimore, Maryland 21287; 31Mass Spec Core Facility, KBI Biopharma, 1101 Hamlin Road Durham, North Carolina 27704; 32Division of Mass Spectrometry, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongwon-gu, Cheongju Chungbuk, 363–883 Korea (South); 33Advanced Therapy Products Research Division, Korea National Institute of Food and Drug Safety, 187 Osongsaengmyeong 2-ro Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do, 363–700, Korea (South); 34Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; 35Ludger Limited, Culham Science Centre, Abingdon, Oxfordshire, OX14 3EB, United Kingdom; 36Biomolecular Discovery and Design Research Centre and ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP), Macquarie University, North Ryde, Australia; 37Proteomics, Central European Institute for Technology, Masaryk University, Kamenice 5, A26, 625 00 BRNO, Czech Republic; 38Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, 39106 Magdeburg, Germany; 39Department of Biomolecular Sciences, Max Planck Institute of Colloids and Interfaces, 14424 Potsdam, Germany; 40AstraZeneca, Granta Park, Cambridgeshire, CB21 6GH United Kingdom; 41Merck, 2015 Galloping Hill Rd, Kenilworth, New Jersey 07033; 42Analytical R&D, MilliporeSigma, 2909 Laclede Ave. St. Louis, Missouri 63103; 43MS Bioworks, LLC, 3950 Varsity Drive Ann Arbor, Michigan 48108; 44MSD, Molenstraat 110, 5342 CC Oss, The Netherlands; 45Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5–1 Higashiyama, Myodaiji, Okazaki 444–8787 Japan; 46Graduate School of Pharmaceutical Sciences, Nagoya City University, 3–1 Tanabe-dori, Mizuhoku, Nagoya 467–8603 Japan; 47Medical & Biological Laboratories Co., Ltd, 2-22-8 Chikusa, Chikusa-ku, Nagoya 464–0858 Japan; 48National Institute for Biological Standards and Control, Blanche Lane, South Mimms, Potters Bar, Hertfordshire EN6 3QG United Kingdom; 49Division of Biological Chemistry & Biologicals, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158–8501 Japan; 50New England Biolabs, Inc., 240 County Road, Ipswich, Massachusetts 01938; 51New York University, 100 Washington Square East New York City, New York 10003; 52Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom; 53GlycoScience Group, The National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland; 54Department of Chemistry, North Carolina State University, 2620 Yarborough Drive Raleigh, North Carolina 27695; 55Pantheon, 201 College Road East Princeton, New Jersey 08540; 56Pfizer Inc., 1 Burtt Road Andover, Massachusetts 01810; 57Proteodynamics, ZI La Varenne 20–22 rue Henri et Gilberte Goudier 63200 RIOM, France; 58ProZyme, Inc., 3832 Bay Center Place Hayward, California 94545; 59Koichi Tanaka Mass Spectrometry Research Laboratory, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho Nakagyo-ku, Kyoto, 604 8511 Japan; 60Children’s GMP LLC, St. Jude Children’s Research Hospital, 262 Danny Thomas Place Memphis, Tennessee 38105; 61Sumitomo Bakelite Co., Ltd., 1–5 Muromati 1-Chome, Nishiku, Kobe, 651–2241 Japan; 62Synthon Biopharmaceuticals, Microweg 22 P.O. Box 7071, 6503 GN Nijmegen, The Netherlands; 63Takeda Pharmaceuticals International Co., 40 Landsdowne Street Cambridge, Massachusetts 02139; 64Department of Chemistry and Biochemistry, Texas Tech University, 2500 Broadway, Lubbock, Texas 79409; 65Thermo Fisher Scientific, 1214 Oakmead Parkway Sunnyvale, California 94085; 66United States Pharmacopeia India Pvt. Ltd. IKP Knowledge Park, Genome Valley, Shamirpet, Turkapally Village, Medchal District, Hyderabad 500 101 Telangana, India; 67Alberta Glycomics Centre, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 68Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 69Department of Chemistry, University of California, One Shields Ave, Davis, California 95616; 70Horva´ th Csaba Memorial Laboratory for Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Egyetem ter 1, Hungary; 71Translational Glycomics Research Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Egyetem ut 10, Hungary; 72Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way Newark, Delaware 19711; 73Proteomics Core Facility, University of Gothenburg, Medicinaregatan 1G SE 41390 Gothenburg, Sweden; 74Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Institute of Biomedicine, Sahlgrenska Academy, Medicinaregatan 9A, Box 440, 405 30, Gothenburg, Sweden; 75Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy at the University of Gothenburg, Bruna Straket 16, 41345 Gothenburg, Sweden; 76Department of Chemistry, University of Hamburg, Martin Luther King Pl. 6 20146 Hamburg, Germany; 77Department of Chemistry, University of Manitoba, 144 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2; 78Laboratory of Mass Spectrometry of Interactions and Systems, University of Strasbourg, UMR Unistra-CNRS 7140, France; 79Natural and Medical Sciences Institute, University of Tu¨ bingen, Markwiesenstrae 55, 72770 Reutlingen, Germany; 80Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands; 81Division of Bioanalytical Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; 82Department of Chemistry, Waters Corporation, 34 Maple Street Milford, Massachusetts 01757; 83Zoetis, 333 Portage St. Kalamazoo, Michigan 49007 Author’s Choice—Final version open access under the terms of the Creative Commons CC-BY license. Received July 24, 2019, and in revised form, August 26, 2019 Published, MCP Papers in Press, October 7, 2019, DOI 10.1074/mcp.RA119.001677 ER: NISTmAb Glycosylation Interlaboratory Study 12 Molecular & Cellular Proteomics 19.1 Downloaded from https://www.mcponline.org by guest on January 20, 2020 ted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide communityderived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods. Molecular & Cellular Proteomics 19: 11–30, 2020. DOI: 10.1074/mcp.RA119.001677.L