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Viant MR, Amstalden E, Athersuch T, Bouhifd M, Camuzeaux S, Crizer DM, Driemert P, Ebbels T, Ekman D, Flick B, Giri V, Gómez-Romero M, Haake V, Herold M, Kende A, Lai F, Leonards PEG, Lim PP, Lloyd GR, Mosley J, Namini C, Rice JR, Romano S, Sands C, Smith MJ, Sobanski T, Southam AD, Swindale L, van Ravenzwaay B, Walk T, Weber RJM, Zickgraf FM, Kamp H. Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice. Arch Toxicol 2024; 98:1111-1123. [PMID: 38368582 PMCID: PMC10944399 DOI: 10.1007/s00204-024-03680-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 01/15/2024] [Indexed: 02/19/2024]
Abstract
While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.
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Affiliation(s)
- Mark R Viant
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
| | - E Amstalden
- Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - T Athersuch
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
| | - M Bouhifd
- European Chemicals Agency, Telakkakatu 6, FI-00121, Helsinki, Finland
| | - S Camuzeaux
- Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, W12 0NN, UK
| | - D M Crizer
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - P Driemert
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - T Ebbels
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
| | - D Ekman
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - B Flick
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
- NUVISAN ICB GmbH, Toxicology, 13353, Berlin, Germany
| | - V Giri
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
| | - M Gómez-Romero
- Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, W12 0NN, UK
| | - V Haake
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - M Herold
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - A Kende
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - F Lai
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - P E G Leonards
- Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - P P Lim
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - G R Lloyd
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - J Mosley
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - C Namini
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - J R Rice
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - S Romano
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA
| | - C Sands
- Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, W12 0NN, UK
| | - M J Smith
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - T Sobanski
- European Chemicals Agency, Telakkakatu 6, FI-00121, Helsinki, Finland
| | - A D Southam
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - L Swindale
- Syngenta, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK
| | - B van Ravenzwaay
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
- Environmental Sciences Consulting, 67122, Altrip, Germany
| | - T Walk
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
| | - R J M Weber
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - F M Zickgraf
- BASF SE, Carl-Bosch-Str 38, 67056, Ludwigshafen, Germany
| | - H Kamp
- BASF Metabolome Solutions GmbH, Tegeler Weg 33, 10589, Berlin, Germany
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Barranco-Altirriba M, Alonso N, Weber RJM, Lloyd GR, Hernandez M, Yanes O, Capellades J, Jankevics A, Winder C, Falguera M, Franch-Nadal J, Dunn WB, Perera-Lluna A, Castelblanco E, Mauricio D. Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus. Cardiovasc Diabetol 2024; 23:109. [PMID: 38553758 PMCID: PMC10981308 DOI: 10.1186/s12933-024-02202-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 03/14/2024] [Indexed: 04/01/2024] Open
Abstract
BACKGROUND In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state. METHODS An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D. RESULTS A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D. CONCLUSIONS Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.
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Affiliation(s)
- Maria Barranco-Altirriba
- Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, B2SLab, Barcelona, Spain
- Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine, CIBER-BBN), Madrid, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Núria Alonso
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- Servicio de Endocrinología y Nutrición, Hospital Universitario e Instituto de Investigación en Ciencias de la Salud Germans Trias i Pujol, Badalona, Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Gavin R Lloyd
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Marta Hernandez
- Department of Endocrinology & Nutrition, Hospital Universitari Arnau de Vilanova, Institut de Recerca Biomèdica de Lleida (IRBLleida), Lleida, Spain
| | - Oscar Yanes
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- Department of Electronic Engineering, Universitat Rovira i Virgili, IISPV, Tarragona, Spain
| | - Jordi Capellades
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- Institut Investigació Sanitària Pere Virgili (IISPV), Tarragona, Spain
| | - Andris Jankevics
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands
- Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Catherine Winder
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB, Liverpool, UK
| | - Mireia Falguera
- Institut d'Investigació Biomèdica, Centre Atenció Primària Cervera, Gerència d'Atenció Primària, Universitat de Lleida, Institut Català de la Salut, Lleida, Spain
| | - Josep Franch-Nadal
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- DAP-Cat Group, Unitat de Suport a La Recerca Barcelona Ciutat, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Barcelona, Spain
| | - Warwick B Dunn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB, Liverpool, UK
| | - Alexandre Perera-Lluna
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, B2SLab, Barcelona, Spain
- Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine, CIBER-BBN), Madrid, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Esmeralda Castelblanco
- Division of Endocrinology, Metabolism and Lipid Research, Department of Internal Medicine, Washington University School of Medicine, 63110, St. Louis, MO, USA.
- Unitat de Suport a la Recerca Barcelona, Institut Universitari d'Investigació en Atenció Primària Jordi Gol i Gurina, 08007, Barcelona, Spain.
| | - Didac Mauricio
- Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain.
- Institut d'Investigació Biomèdica Sant Pau (IR Sant Pau), 08041, Barcelona, Spain.
- Faculty of Medicine, University of Vic, Vic, Spain.
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Bowen TJ, Southam AD, Hall AR, Weber RJM, Lloyd GR, Macdonald R, Wilson A, Pointon A, Viant MR. Simultaneously discovering the fate and biochemical effects of pharmaceuticals through untargeted metabolomics. Nat Commun 2023; 14:4653. [PMID: 37537184 PMCID: PMC10400635 DOI: 10.1038/s41467-023-40333-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/20/2023] [Indexed: 08/05/2023] Open
Abstract
Untargeted metabolomics is an established approach in toxicology for characterising endogenous metabolic responses to xenobiotic exposure. Detecting the xenobiotic and its biotransformation products as part of the metabolomics analysis provides an opportunity to simultaneously gain deep insights into its fate and metabolism, and to associate the internal relative dose directly with endogenous metabolic responses. This integration of untargeted exposure and response measurements into a single assay has yet to be fully demonstrated. Here we assemble a workflow to discover and analyse pharmaceutical-related measurements from routine untargeted UHPLC-MS metabolomics datasets, derived from in vivo (rat plasma and cardiac tissue, and human plasma) and in vitro (human cardiomyocytes) studies that were principally designed to investigate endogenous metabolic responses to drug exposure. Our findings clearly demonstrate how untargeted metabolomics can discover extensive biotransformation maps, temporally-changing relative systemic exposure, and direct associations of endogenous biochemical responses to the internal dose.
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Affiliation(s)
- Tara J Bowen
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Andrew D Southam
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Andrew R Hall
- Safety Sciences, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Gavin R Lloyd
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Ruth Macdonald
- Animal Sciences and Technology, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Amanda Wilson
- Integrated Bioanalysis, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Amy Pointon
- Safety Sciences, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
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4
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Busquet F, Laperrouze J, Jankovic K, Krsmanovic T, Ignasiak T, Leoni B, Apic G, Asole G, Guigó R, Marangio P, Palumbo E, Perez-Lluch S, Wucher V, Vlot AH, Anholt R, Mackay T, Escher BI, Grasse N, Huchthausen J, Massei R, Reemtsma T, Scholz S, Schüürmann G, Bondesson M, Cherbas P, Freedman JH, Glaholt S, Holsopple J, Jacobson SC, Kaufman T, Popodi E, Shaw JJ, Smoot S, Tennessen JM, Churchill G, von Clausbruch CC, Dickmeis T, Hayot G, Pace G, Peravali R, Weiss C, Cistjakova N, Liu X, Slaitas A, Brown JB, Ayerbe R, Cabellos J, Cerro-Gálvez E, Diez-Ortiz M, González V, Martínez R, Vives PS, Barnett R, Lawson T, Lee RG, Sostare E, Viant M, Grafström R, Hongisto V, Kohonen P, Patyra K, Bhaskar PK, Garmendia-Cedillos M, Farooq I, Oliver B, Pohida T, Salem G, Jacobson D, Andrews E, Barnard M, Čavoški A, Chaturvedi A, Colbourne JK, Epps DJT, Holden L, Jones MR, Li X, Müller F, Ormanin-Lewandowska A, Orsini L, Roberts R, Weber RJM, Zhou J, Chung ME, Sanchez JCG, Diwan GD, Singh G, Strähle U, Russell RB, Batista D, Sansone SA, Rocca-Serra P, Du Pasquier D, Lemkine G, Robin-Duchesne B, Tindall A. The Precision Toxicology Initiative. Toxicol Lett 2023:S0378-4274(23)00180-7. [PMID: 37211341 DOI: 10.1016/j.toxlet.2023.05.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/01/2023] [Accepted: 05/09/2023] [Indexed: 05/23/2023]
Abstract
The goal of PrecisionTox is to overcome conceptual barriers to replacing traditional mammalian chemical safety testing by accelerating the discovery of evolutionarily conserved toxicity pathways that are shared by descent among humans and more distantly related animals. An international consortium is systematically testing the toxicological effects of a diverse set of chemicals on a suite of five model species comprising fruit flies, nematodes, water fleas, and embryos of clawed frogs and zebrafish along with human cell lines. Multiple forms of omics and comparative toxicology data are integrated to map the evolutionary origins of biomolecular interactions, which are predictive of adverse health effects, to major branches of the animal phylogeny. These conserved elements of adverse outcome pathways (AOPs) and their biomarkers are expect to provide mechanistic insight useful for regulating groups of chemicals based on their shared modes of action. PrecisionTox also aims to quantify risk variation within populations by recognizing susceptibility as a heritable trait that varies with genetic diversity. This initiative incorporates legal experts and collaborates with risk managers to address specific needs within European chemicals legislation, including the uptake of new approach methodologies (NAMs) for setting precise regulatory limits on toxic chemicals.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Nico Grasse
- Helmholtz Centre for Environmental Research, DE
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Afgan E, Nekrutenko A, Grüning BA, Blankenberg D, Goecks J, Schatz MC, Ostrovsky AE, Mahmoud A, Lonie AJ, Syme A, Fouilloux A, Bretaudeau A, Nekrutenko A, Kumar A, Eschenlauer AC, DeSanto AD, Guerler A, Serrano-Solano B, Batut B, Grüning BA, Langhorst BW, Carr B, Raubenolt BA, Hyde CJ, Bromhead CJ, Barnett CB, Royaux C, Gallardo C, Blankenberg D, Fornika DJ, Baker D, Bouvier D, Clements D, de Lima Morais DA, Tabernero DL, Lariviere D, Nasr E, Afgan E, Zambelli F, Heyl F, Psomopoulos F, Coppens F, Price GR, Cuccuru G, Corguillé GL, Von Kuster G, Akbulut GG, Rasche H, Hotz HR, Eguinoa I, Makunin I, Ranawaka IJ, Taylor JP, Joshi J, Hillman-Jackson J, Goecks J, Chilton JM, Kamali K, Suderman K, Poterlowicz K, Yvan LB, Lopez-Delisle L, Sargent L, Bassetti ME, Tangaro MA, van den Beek M, Čech M, Bernt M, Fahrner M, Tekman M, Föll MC, Schatz MC, Crusoe MR, Roncoroni M, Kucher N, Coraor N, Stoler N, Rhodes N, Soranzo N, Pinter N, Goonasekera NA, Moreno PA, Videm P, Melanie P, Mandreoli P, Jagtap PD, Gu Q, Weber RJM, Lazarus R, Vorderman RHP, Hiltemann S, Golitsynskiy S, Garg S, Bray SA, Gladman SL, Leo S, Mehta SP, Griffin TJ, Jalili V, Yves V, Wen V, Nagampalli VK, Bacon WA, de Koning W, Maier W, Briggs PJ. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Res 2022; 50:W345-W351. [PMID: 35446428 PMCID: PMC9252830 DOI: 10.1093/nar/gkac247] [Citation(s) in RCA: 235] [Impact Index Per Article: 117.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/17/2022] [Accepted: 03/30/2022] [Indexed: 01/19/2023] Open
Abstract
Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.
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Allaway D, Alexander JE, Carvell-Miller LJ, Reynolds RM, Winder CL, Weber RJM, Lloyd GR, Southam AD, Dunn WB. Suitability of Dried Blood Spots for Accelerating Veterinary Biobank Collections and Identifying Metabolomics Biomarkers With Minimal Resources. Front Vet Sci 2022; 9:887163. [PMID: 35812865 PMCID: PMC9258959 DOI: 10.3389/fvets.2022.887163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 05/05/2022] [Indexed: 11/13/2022] Open
Abstract
Biomarker discovery using biobank samples collected from veterinary clinics would deliver insights into the diverse population of pets and accelerate diagnostic development. The acquisition, preparation, processing, and storage of biofluid samples in sufficient volumes and at a quality suitable for later analysis with most suitable discovery methods remain challenging. Metabolomics analysis is a valuable approach to detect health/disease phenotypes. Pre-processing changes during preparation of plasma/serum samples may induce variability that may be overcome using dried blood spots (DBSs). We report a proof of principle study by metabolite fingerprinting applying UHPLC-MS of plasma and DBSs acquired from healthy adult dogs and cats (age range 1–9 years), representing each of 4 dog breeds (Labrador retriever, Beagle, Petit Basset Griffon Vendeen, and Norfolk terrier) and the British domestic shorthair cat (n = 10 per group). Blood samples (20 and 40 μL) for DBSs were loaded onto filter paper, air-dried at room temperature (3 h), and sealed and stored (4°C for ~72 h) prior to storage at −80°C. Plasma from the same blood draw (250 μL) was prepared and stored at −80°C within 1 h of sampling. Metabolite fingerprinting of the DBSs and plasma produced similar numbers of metabolite features that had similar abilities to discriminate between biological classes and correctly assign blinded samples. These provide evidence that DBSs, sampled in a manner amenable to application in in-clinic/in-field processing, are a suitable sample for biomarker discovery using UHPLC-MS metabolomics. Further, given appropriate owner consent, the volumes tested (20–40 μL) make the acquisition of remnant blood from blood samples drawn for other reasons available for biobanking and other research activities. Together, this makes possible large-scale biobanking of veterinary samples, gaining sufficient material sooner and enabling quicker identification of biomarkers of interest.
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Affiliation(s)
- David Allaway
- WALTHAM Petcare Science Institute, Freeby Lane, Waltham-on-the-Wolds, Melton Mowbray, United Kingdom
- *Correspondence: David Allaway
| | - Janet E. Alexander
- WALTHAM Petcare Science Institute, Freeby Lane, Waltham-on-the-Wolds, Melton Mowbray, United Kingdom
| | - Laura J. Carvell-Miller
- WALTHAM Petcare Science Institute, Freeby Lane, Waltham-on-the-Wolds, Melton Mowbray, United Kingdom
| | - Rhiannon M. Reynolds
- WALTHAM Petcare Science Institute, Freeby Lane, Waltham-on-the-Wolds, Melton Mowbray, United Kingdom
| | - Catherine L. Winder
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, United Kingdom
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Ralf J. M. Weber
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, United Kingdom
| | - Gavin R. Lloyd
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, United Kingdom
| | - Andrew D. Southam
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, United Kingdom
| | - Warwick B. Dunn
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, United Kingdom
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
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Malinowska JM, Palosaari T, Sund J, Carpi D, Bouhifd M, Weber RJM, Whelan M, Viant MR. Integrating in vitro metabolomics with a 96-well high-throughput screening platform. Metabolomics 2022; 18:11. [PMID: 35000038 PMCID: PMC8743266 DOI: 10.1007/s11306-021-01867-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 12/16/2021] [Indexed: 02/07/2023]
Abstract
INTRODUCTION High-throughput screening (HTS) is emerging as an approach to support decision-making in chemical safety assessments. In parallel, in vitro metabolomics is a promising approach that can help accelerate the transition from animal models to high-throughput cell-based models in toxicity testing. OBJECTIVE In this study we establish and evaluate a high-throughput metabolomics workflow that is compatible with a 96-well HTS platform employing 50,000 hepatocytes of HepaRG per well. METHODS Low biomass cell samples were extracted for metabolomics analyses using a newly established semi-automated protocol, and the intracellular metabolites were analysed using a high-resolution spectral-stitching nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) method that was modified for low sample biomass. RESULTS The method was assessed with respect to sensitivity and repeatability of the entire workflow from cell culturing and sampling to measurement of the metabolic phenotype, demonstrating sufficient sensitivity (> 3000 features in hepatocyte extracts) and intra- and inter-plate repeatability for polar nESI-DIMS assays (median relative standard deviation < 30%). The assays were employed for a proof-of-principle toxicological study with a model toxicant, cadmium chloride, revealing changes in the metabolome across five sampling times in the 48-h exposure period. To allow the option for lipidomics analyses, the solvent system was extended by establishing separate extraction methods for polar metabolites and lipids. CONCLUSIONS Experimental, analytical and informatics workflows reported here met pre-defined criteria in terms of sensitivity, repeatability and ability to detect metabolome changes induced by a toxicant and are ready for application in metabolomics-driven toxicity testing to complement HTS assays.
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Affiliation(s)
- Julia M Malinowska
- School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Taina Palosaari
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Jukka Sund
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Donatella Carpi
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Mounir Bouhifd
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
- European Chemicals Agency, Helsinki, Finland
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT, UK
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK.
- Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT, UK.
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8
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Malinowska JM, Palosaari T, Sund J, Carpi D, Lloyd GR, Weber RJM, Whelan M, Viant MR. Automated Sample Preparation and Data Collection Workflow for High-Throughput In Vitro Metabolomics. Metabolites 2022; 12:52. [PMID: 35050173 PMCID: PMC8778710 DOI: 10.3390/metabo12010052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 12/19/2021] [Accepted: 12/31/2021] [Indexed: 11/16/2022] Open
Abstract
Regulatory bodies have started to recognise the value of in vitro screening and metabolomics as two types of new approach methodologies (NAMs) for chemical risk assessments, yet few high-throughput in vitro toxicometabolomics studies have been reported. A significant challenge is to implement automated sample preparation of the low biomass samples typically used for in vitro screening. Building on previous work, we have developed, characterised and demonstrated an automated sample preparation and analysis workflow for in vitro metabolomics of HepaRG cells in 96-well microplates using a Biomek i7 Hybrid Workstation (Beckman Coulter) and Orbitrap Elite (Thermo Scientific) high-resolution nanoelectrospray direct infusion mass spectrometry (nESI-DIMS), across polar metabolites and lipids. The experimental conditions evaluated included the day of metabolite extraction, order of extraction of samples in 96-well microplates, position of the 96-well microplate on the instrument's deck and well location within a microplate. By using the median relative standard deviation (mRSD (%)) of spectral features, we have demonstrated good repeatability of the workflow (final mRSD < 30%) with a low percentage of features outside the threshold applied for statistical analysis. To improve the quality of the automated workflow further, small method modifications were made and then applied to a large cohort study (4860 sample infusions across three nESI-DIMS assays), which confirmed very high repeatability of the whole workflow from cell culturing to metabolite measurements, whilst providing a significant improvement in sample throughput. It is envisioned that the automated in vitro metabolomics workflow will help to advance the application of metabolomics (as a part of NAMs) in chemical safety, primarily as an approach for high throughput screening and prioritisation.
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Affiliation(s)
| | - Taina Palosaari
- Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy; (T.P.); (J.S.); (D.C.); (M.W.)
| | - Jukka Sund
- Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy; (T.P.); (J.S.); (D.C.); (M.W.)
| | - Donatella Carpi
- Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy; (T.P.); (J.S.); (D.C.); (M.W.)
| | - Gavin R. Lloyd
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, UK;
| | - Ralf J. M. Weber
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK;
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, UK;
| | - Maurice Whelan
- Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy; (T.P.); (J.S.); (D.C.); (M.W.)
| | - Mark R. Viant
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK;
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, UK;
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9
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Affiliation(s)
- Elena Sostare
- Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Birmingham B15 2SQ, UK
| | - Thomas N Lawson
- Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Birmingham B15 2SQ, UK
| | - Lucy R Saunders
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK
| | - John K Colbourne
- Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Birmingham B15 2SQ, UK
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK
| | | | - Mark R Viant
- To whom correspondence should be addressed at Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham B15 2SQ, UK. E-mail:
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10
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Bowen TJ, Hall AR, Lloyd GR, Weber RJM, Wilson A, Pointon A, Viant MR. An Extensive Metabolomics Workflow to Discover Cardiotoxin-Induced Molecular Perturbations in Microtissues. Metabolites 2021; 11:644. [PMID: 34564460 PMCID: PMC8470535 DOI: 10.3390/metabo11090644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/13/2021] [Accepted: 09/15/2021] [Indexed: 11/29/2022] Open
Abstract
Discovering modes of action and predictive biomarkers of drug-induced structural cardiotoxicity offers the potential to improve cardiac safety assessment of lead compounds and enhance preclinical to clinical translation during drug development. Cardiac microtissues are a promising, physiologically relevant, in vitro model, each composed of ca. 500 cells. While untargeted metabolomics is capable of generating hypotheses on toxicological modes of action and discovering metabolic biomarkers, applying this technology to low-biomass microtissues in suspension is experimentally challenging. Thus, we first evaluated a filtration-based approach for harvesting microtissues and assessed the sensitivity and reproducibility of nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) measurements of intracellular extracts, revealing samples consisting of 28 pooled microtissues, harvested by filtration, are suitable for profiling the intracellular metabolome and lipidome. Subsequently, an extensive workflow combining nESI-DIMS untargeted metabolomics and lipidomics of intracellular extracts with ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) analysis of spent culture medium, to profile the metabolic footprint and quantify drug exposure concentrations, was implemented. Using the synthetic drug and model cardiotoxin sunitinib, time-resolved metabolic and lipid perturbations in cardiac microtissues were investigated, providing valuable data for generating hypotheses on toxicological modes of action and identifying putative biomarkers such as disruption of purine metabolism and perturbation of polyunsaturated fatty acid levels.
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Affiliation(s)
- Tara J. Bowen
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; (T.J.B.); (R.J.M.W.)
| | - Andrew R. Hall
- Functional and Mechanistic Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, UK; (A.R.H.); (A.P.)
| | - Gavin R. Lloyd
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
| | - Ralf J. M. Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; (T.J.B.); (R.J.M.W.)
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
| | - Amanda Wilson
- Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB4 0WG, UK;
| | - Amy Pointon
- Functional and Mechanistic Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, UK; (A.R.H.); (A.P.)
| | - Mark R. Viant
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; (T.J.B.); (R.J.M.W.)
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
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11
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Johnson D, Batista D, Cochrane K, Davey RP, Etuk A, Gonzalez-Beltran A, Haug K, Izzo M, Larralde M, Lawson TN, Minotto A, Moreno P, Nainala VC, O'Donovan C, Pireddu L, Roger P, Shaw F, Steinbeck C, Weber RJM, Sansone SA, Rocca-Serra P. ISA API: An open platform for interoperable life science experimental metadata. Gigascience 2021; 10:giab060. [PMID: 34528664 PMCID: PMC8444265 DOI: 10.1093/gigascience/giab060] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 03/19/2021] [Accepted: 08/23/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND The Investigation/Study/Assay (ISA) Metadata Framework is an established and widely used set of open source community specifications and software tools for enabling discovery, exchange, and publication of metadata from experiments in the life sciences. The original ISA software suite provided a set of user-facing Java tools for creating and manipulating the information structured in ISA-Tab-a now widely used tabular format. To make the ISA framework more accessible to machines and enable programmatic manipulation of experiment metadata, the JSON serialization ISA-JSON was developed. RESULTS In this work, we present the ISA API, a Python library for the creation, editing, parsing, and validating of ISA-Tab and ISA-JSON formats by using a common data model engineered as Python object classes. We describe the ISA API feature set, early adopters, and its growing user community. CONCLUSIONS The ISA API provides users with rich programmatic metadata-handling functionality to support automation, a common interface, and an interoperable medium between the 2 ISA formats, as well as with other life science data formats required for depositing data in public databases.
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Affiliation(s)
- David Johnson
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
- Department of Informatics and Media, Uppsala University, Box 513, 75120 Uppsala, Sweden
| | - Dominique Batista
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Keeva Cochrane
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Robert P Davey
- Earlham Institute, Data infrastructure and algorithms, Norwich Research Park, Norwich NR4 7UZ, UK
| | - Anthony Etuk
- Earlham Institute, Data infrastructure and algorithms, Norwich Research Park, Norwich NR4 7UZ, UK
| | - Alejandra Gonzalez-Beltran
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
- Science and Technology Facilities Council, Scientific Computing Department, Rutherford Appleton Laboratory, Harwell Campus, Didcot, OX11 0QX, UK
| | - Kenneth Haug
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- Genome Research Limited, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Saffron Walden, CB10 1RQ, UK
| | - Massimiliano Izzo
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Martin Larralde
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Thomas N Lawson
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Alice Minotto
- Earlham Institute, Data infrastructure and algorithms, Norwich Research Park, Norwich NR4 7UZ, UK
| | - Pablo Moreno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Venkata Chandrasekhar Nainala
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Luca Pireddu
- Distributed Computing Group, CRS4: Center for Advanced Studies, Research & Development in Sardinia, Pula 09050, Italy
| | - Pierrick Roger
- CEA, LIST, Laboratory for Data Analysis and Systems’ Intelligence, MetaboHUB, Gif-Sur-Yvette F-91191, France
| | - Felix Shaw
- Earlham Institute, Data infrastructure and algorithms, Norwich Research Park, Norwich NR4 7UZ, UK
| | - Christoph Steinbeck
- Cheminformatics and Computational Metabolomics, Institute for Analytical Chemistry, Lessingstr. 8, 07743 Jena, Germany
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Philippe Rocca-Serra
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
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12
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Harrill JA, Viant MR, Yauk CL, Sachana M, Gant TW, Auerbach SS, Beger RD, Bouhifd M, O'Brien J, Burgoon L, Caiment F, Carpi D, Chen T, Chorley BN, Colbourne J, Corvi R, Debrauwer L, O'Donovan C, Ebbels TMD, Ekman DR, Faulhammer F, Gribaldo L, Hilton GM, Jones SP, Kende A, Lawson TN, Leite SB, Leonards PEG, Luijten M, Martin A, Moussa L, Rudaz S, Schmitz O, Sobanski T, Strauss V, Vaccari M, Vijay V, Weber RJM, Williams AJ, Williams A, Thomas RS, Whelan M. Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology. Regul Toxicol Pharmacol 2021; 125:105020. [PMID: 34333066 DOI: 10.1016/j.yrtph.2021.105020] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 07/26/2021] [Indexed: 12/12/2022]
Abstract
Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.
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Affiliation(s)
- Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States.
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom.
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, K1N 6N5, Canada.
| | - Magdalini Sachana
- Organisation for Economic Co-operation and Development (OECD), Environment Health and Safety Division, Paris, France
| | - Timothy W Gant
- Centre for Radiation, Chemical and Environmental Hazards (CRCE), Public Health England (PHE), Harwell Science Campus, Oxfordshire, United Kingdom
| | - Scott S Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Richard D Beger
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
| | | | - Jason O'Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, K1A 0H3, Canada
| | - Lyle Burgoon
- US Army Engineer Research and Development Center, 3909 Halls Ferry Rd, Vicksburg, MS, 39180, USA
| | - Florian Caiment
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229, ER, Maastricht, the Netherlands
| | - Donatella Carpi
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Tao Chen
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
| | - Brian N Chorley
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - John Colbourne
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom
| | - Raffaella Corvi
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Laurent Debrauwer
- Toxalim (Research Centre in Food Toxicology), INRAE UMR 1331, ENVT, INP-Purpan, Paul Sabatier University (UPS), Toulouse, France; MetaToul-AXIOM Platform, MetaboHUB, National Infrastructure for Metabolomics and Fluxomics, Toulouse, France
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Timothy M D Ebbels
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, United Kingdom
| | - Drew R Ekman
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Athens, GA, 30605, United States
| | | | - Laura Gribaldo
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Gina M Hilton
- PETA Science Consortium International e.V., Friolzheimer Str. 3, 70499, Stuttgart, Germany
| | - Stephanie P Jones
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, K1A 0H3, Canada
| | - Aniko Kende
- Syngenta Jealott's Hill International Research Centre, Bracknell, RG42 6EY, United Kingdom
| | - Thomas N Lawson
- Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom
| | - Sofia B Leite
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Pim E G Leonards
- Department of Environment and Health, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081HV, Amsterdam, the Netherlands
| | - Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | | | - Laura Moussa
- US Food and Drug Administration, Center for Veterinary Medicine, Rockville, MD, United States
| | - Serge Rudaz
- School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland; Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland; Swiss Centre for Applied Human Toxicology (SCAHT), Switzerland
| | - Oliver Schmitz
- BASF Metabolome Solutions, Metabolome Data Science, Tegeler Weg 33, 10589, Berlin, Germany
| | | | - Volker Strauss
- BASF SE, Toxicology and Ecology, 67056, Ludwigshafen, Germany
| | - Monica Vaccari
- Center for Environmental Health and Prevention, Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, Bologna, Italy
| | - Vikrant Vijay
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Michabo Health Science, University of Birmingham Enterprise, Birmingham Research Park, Vincent Drive, Birmingham, B15 2SQ, United Kingdom
| | - Antony J Williams
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
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13
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Abstract
Incorporating safety data early in the drug discovery pipeline is key to reducing costly lead candidate failures. For a single drug development project, we estimate that several thousand samples per day require screening (<10 s per acquisition). While chromatography-based metabolomics has proven value at predicting toxicity from metabolic biomarker profiles, it lacks sufficiently high sample throughput. Acoustic mist ionization mass spectrometry (AMI-MS) is an atmospheric pressure ionization approach that can measure metabolites directly from 384-well plates with unparalleled speed. We sought to implement a signal processing and data analysis workflow to produce high-quality AMI-MS metabolomics data and to demonstrate its application to drug safety screening. An existing direct infusion mass spectrometry workflow was adapted, extended, optimized, and tested, utilizing three AMI-MS data sets acquired from technical and biological replicates of metabolite standards and HepG2 cell lysates and a toxicity study. Driven by criteria to minimize variance and maximize feature counts, an algorithm to extract the pulsed scan data was designed; parameters for signal-to-noise-ratio, replicate filter, sample filter, missing value filter, and RSD filter were all optimized; normalization and batch correction strategies were adapted; and cell phenotype filtering was implemented to exclude high cytotoxicity samples. The workflow was demonstrated using a highly replicated HepG2 toxicity data set, comprising 2772 samples from exposures to 16 drugs across 9 concentrations and generated in under 5 h, revealing metabolic phenotypes and individual metabolite changes that characterize specific modes of action. This AMI-MS workflow opens the door to ultrahigh-throughput metabolomics screening, increasing the rate of sample analysis by approximately 2 orders of magnitude.
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Affiliation(s)
- Matthew J Smith
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K
| | - Delyan P Ivanov
- Mechanistic Biology & Profiling, Discovery Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, U.K
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K
| | - Jonathan Wingfield
- Mechanistic Biology & Profiling, Discovery Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, U.K
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K
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14
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Corbin LJ, Hughes DA, Chetwynd AJ, Taylor AE, Southam AD, Jankevics A, Weber RJM, Groom A, Dunn WB, Timpson NJ. Correction to: Metabolic characterisation of disturbances in the APOC3/triglyceride‑rich lipoprotein pathway through sample‑based recall by genotype. Metabolomics 2021; 17:15. [PMID: 33484338 PMCID: PMC7919761 DOI: 10.1007/s11306-020-01765-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/22/2020] [Indexed: 11/26/2022]
Affiliation(s)
- Laura J Corbin
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - David A Hughes
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Andrew J Chetwynd
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Amy E Taylor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, BS8 2BN, UK
| | - Andrew D Southam
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Andris Jankevics
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Alix Groom
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Warwick B Dunn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
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15
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Lloyd GR, Jankevics A, Weber RJM. Struct: an R/bioconductor-based framework for standardised metabolomics data analysis and beyond. Bioinformatics 2020; 36:5551-5552. [PMID: 33325493 PMCID: PMC8016465 DOI: 10.1093/bioinformatics/btaa1031] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 10/30/2020] [Accepted: 11/28/2020] [Indexed: 01/21/2023] Open
Abstract
Summary Implementing and combining methods from a diverse range of R/Bioconductor packages into ‘omics’ data analysis workflows represents a significant challenge in terms of standardization, readability and reproducibility. Here, we present an R/Bioconductor package, named struct (Statistics in R using Class-based Templates), which defines a suite of class-based templates that allows users to develop and implement highly standardized and readable statistical analysis workflows. Struct integrates with the STATistics Ontology to ensure consistent reporting and maximizes semantic interoperability. We also present a toolbox, named structToolbox, which includes an extensive set of commonly used data analysis methods that have been implemented using struct. This toolbox can be used to build data-analysis workflows for metabolomics and other omics technologies. Availability and implementation struct and structToolbox are implemented in R, and are freely available from Bioconductor (http://bioconductor.org/packages/struct and http://bioconductor.org/packages/structToolbox), including documentation and vignettes. Source code is available and maintained at https://github.com/computational-metabolomics.
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Affiliation(s)
- Gavin Rhys Lloyd
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom
| | - Andris Jankevics
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom
| | - Ralf J M Weber
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom
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16
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Southam AD, Pursell H, Frigerio G, Jankevics A, Weber RJM, Dunn WB. Characterization of Monophasic Solvent-Based Tissue Extractions for the Detection of Polar Metabolites and Lipids Applying Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry Clinical Metabolic Phenotyping Assays. J Proteome Res 2020; 20:831-840. [PMID: 33236910 DOI: 10.1021/acs.jproteome.0c00660] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Metabolic phenotyping of tissues uses metabolomics and lipidomics to measure the relative polar and nonpolar (lipid) metabolite levels in biological samples. This approach aims to understand disease biochemistry and identify biochemical markers of disease. Sample preparation methods must be reproducible, sensitive (high metabolite and lipid yield), and ideally rapid. We evaluated three biphasic methods for polar and nonpolar compound extraction (chloroform/methanol/water, dichloromethane/methanol/water, and methyl tert-butyl ether [MTBE]/methanol/water), a monophasic method for polar compound extraction (acetonitrile/methanol/water), and a monophasic method for nonpolar compound extraction (isopropanol/water). All methods were applied to mammalian heart, kidney, and liver tissues. Polar extracts were analyzed by hydrophilic interaction chromatography (HILIC) ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS) and nonpolar extracts by C18 reversed-phase UHPLC-MS. Method reproducibility and yield were assessed using multiple annotated endogenous compounds (putatively and MS/MS annotated). Monophasic methods had the highest yield and high reproducibility for both polar (positive ion: median relative standard deviation (RSD) < 18%; negative ion: median RSD < 28%) and nonpolar (positive and negative ion: median RSD < 15%) extractions for heart, kidneys, and liver. The polar monophasic method extracted higher levels of lipid than biphasic polar extractions, and these lipids caused minimal detection suppression for other compounds during HILIC UHPLC-MS. The nonpolar monophasic method had similar or greater detection responses of all detected lipid classes compared to biphasic methods (including increased phosphatidylinositol, phosphatidylserine, and cardiolipin responses). Monophasic methods are quicker and simpler than biphasic methods and are therefore most suited for future automation.
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Affiliation(s)
- Andrew D Southam
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.,Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Harriet Pursell
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Gianfranco Frigerio
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan 20122, Italy
| | - Andris Jankevics
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.,Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.,Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Warwick B Dunn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.,Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.,Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
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17
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Corbin LJ, Hughes DA, Chetwynd AJ, Taylor AE, Southam AD, Jankevics A, Weber RJM, Groom A, Dunn WB, Timpson NJ. Metabolic characterisation of disturbances in the APOC3/triglyceride-rich lipoprotein pathway through sample-based recall by genotype. Metabolomics 2020; 16:69. [PMID: 32494907 PMCID: PMC7270992 DOI: 10.1007/s11306-020-01689-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 05/15/2020] [Indexed: 12/11/2022]
Abstract
INTRODUCTION High plasma triacylglyceride levels are known to be associated with increased risk of atherosclerotic cardiovascular disease. Apolipoprotein C-III (apoC-III) is a key regulator of plasma triacylglyceride levels and is associated with hypertriglyceridemia via a number of pathways. There is consistent evidence for an association of cardiovascular events with blood apoC-III level, with support from human genetic studies of APOC3 variants. As such, apoC-III has been recognised as a potential therapeutic target for patients with severe hypertriglyceridaemia with one of the most promising apoC-III-targeting drugs, volanesorsen, having recently progressed through Phase III trials. OBJECTIVES To exploit a rare loss of function variant in APOC3 (rs138326449) to characterise the potential long-term treatment effects of apoC-III targeting interventions on the metabolome. METHODS In a recall-by-genotype study, 115 plasma samples were analysed by UHPLC-MS to acquire non-targeted metabolomics data. The study included samples from 57 adolescents and 33 adults. Overall, 12 985 metabolic features were tested for an association with APOC3 genotype. RESULTS 161 uniquely annotated metabolites were found to be associated with rs138326449(APOC3). The highest proportion of associated metabolites belonged to the acyl-acyl glycerophospholipid and triacylglyceride metabolite classes. In addition to the anticipated (on-target) reduction of metabolites in the triacylglyceride and related classes, carriers of the rare variant exhibited previously unreported increases in levels of a number of metabolites from the acyl-alkyl glycerophospholipid class. CONCLUSION Overall, our results suggest that therapies targeting apoC-III may potentially achieve a broad shift in lipid profile that favours better metabolic health.
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Affiliation(s)
- Laura J Corbin
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - David A Hughes
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Andrew J Chetwynd
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Amy E Taylor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, BS8 2BN, UK
| | - Andrew D Southam
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Andris Jankevics
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Alix Groom
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Warwick B Dunn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
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18
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Southam AD, Haglington LD, Najdekr L, Jankevics A, Weber RJM, Dunn WB. Assessment of human plasma and urine sample preparation for reproducible and high-throughput UHPLC-MS clinical metabolic phenotyping. Analyst 2020; 145:6511-6523. [DOI: 10.1039/d0an01319f] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
In this study we assess multiple sample preparation methods for UHPLC-MS metabolic phenotyping analysis of human urine and plasma. All methods are discussed in terms of metabolite and lipid coverage and reproducibility.
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Affiliation(s)
- Andrew D. Southam
- School of Biosciences
- University of Birmingham
- Birmingham
- UK
- Phenome Centre Birmingham
| | | | - Lukáš Najdekr
- School of Biosciences
- University of Birmingham
- Birmingham
- UK
- Phenome Centre Birmingham
| | - Andris Jankevics
- School of Biosciences
- University of Birmingham
- Birmingham
- UK
- Phenome Centre Birmingham
| | - Ralf J. M. Weber
- School of Biosciences
- University of Birmingham
- Birmingham
- UK
- Phenome Centre Birmingham
| | - Warwick B. Dunn
- School of Biosciences
- University of Birmingham
- Birmingham
- UK
- Phenome Centre Birmingham
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19
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Stanstrup J, Broeckling CD, Helmus R, Hoffmann N, Mathé E, Naake T, Nicolotti L, Peters K, Rainer J, Salek RM, Schulze T, Schymanski EL, Stravs MA, Thévenot EA, Treutler H, Weber RJM, Willighagen E, Witting M, Neumann S. The metaRbolomics Toolbox in Bioconductor and beyond. Metabolites 2019; 9:E200. [PMID: 31548506 PMCID: PMC6835268 DOI: 10.3390/metabo9100200] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Revised: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 11/17/2022] Open
Abstract
Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub.
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Affiliation(s)
- Jan Stanstrup
- Preventive and Clinical Nutrition, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark.
| | - Corey D Broeckling
- Proteomics and Metabolomics Facility, Colorado State University, Fort Collins, CO 80523, USA.
| | - Rick Helmus
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, 1098 XH Amsterdam, The Netherlands.
| | - Nils Hoffmann
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Straße 6b, 44227 Dortmund, Germany.
| | - Ewy Mathé
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
| | - Thomas Naake
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany.
| | - Luca Nicolotti
- The Australian Wine Research Institute, Metabolomics Australia, PO Box 197, Adelaide SA 5064, Australia.
| | - Kristian Peters
- Leibniz Institute of Plant Biochemistry (IPB Halle), Bioinformatics and Scientific Data, 06120 Halle, Germany.
| | - Johannes Rainer
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, 39100 Bolzano, Italy.
| | - Reza M Salek
- The International Agency for Research on Cancer, 150 cours Albert Thomas, CEDEX 08, 69372 Lyon, France.
| | - Tobias Schulze
- Department of Effect-Directed Analysis, Helmholtz Centre for Environmental Research-UFZ, Permoserstraße 15, 04318 Leipzig, Germany.
| | - Emma L Schymanski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 6 avenue du Swing, L-4367 Belvaux, Luxembourg.
| | - Michael A Stravs
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, 8600 Dubendorf, Switzerland.
| | - Etienne A Thévenot
- CEA, LIST, Laboratory for Data Sciences and Decision, MetaboHUB, Gif-Sur-Yvette F-91191, France.
| | - Hendrik Treutler
- Leibniz Institute of Plant Biochemistry (IPB Halle), Bioinformatics and Scientific Data, 06120 Halle, Germany.
| | - Ralf J M Weber
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
| | - Egon Willighagen
- Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, 6229 ER Maastricht, The Netherlands.
| | - Michael Witting
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
- Chair of Analytical Food Chemistry, Technische Universität München, 85354 Weihenstephan, Germany.
| | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry (IPB Halle), Bioinformatics and Scientific Data, 06120 Halle, Germany.
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig Deutscher, Platz 5e, 04103 Leipzig, Germany.
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20
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Viant MR, Ebbels TMD, Beger RD, Ekman DR, Epps DJT, Kamp H, Leonards PEG, Loizou GD, MacRae JI, van Ravenzwaay B, Rocca-Serra P, Salek RM, Walk T, Weber RJM. Use cases, best practice and reporting standards for metabolomics in regulatory toxicology. Nat Commun 2019; 10:3041. [PMID: 31292445 PMCID: PMC6620295 DOI: 10.1038/s41467-019-10900-y] [Citation(s) in RCA: 105] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 06/07/2019] [Indexed: 12/23/2022] Open
Abstract
Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases.
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Affiliation(s)
- Mark R Viant
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
| | | | | | | | - David J T Epps
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | | | | | | | | | | | - Philippe Rocca-Serra
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, OX1 3QG, UK
| | - Reza M Salek
- International Agency for Research on Cancer, Lyon, France
| | - Tilmann Walk
- BASF Metabolome Solutions, 10589, Berlin, Germany
| | - Ralf J M Weber
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
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21
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D'Elia RV, Goodchild SA, Winder CL, Southam AD, Weber RJM, Stahl FM, Docx C, Patel V, Green AC, Viant MR, Lukaszewski RA, Dunn WB. Multiple metabolic pathways are predictive of ricin intoxication in a rat model. Metabolomics 2019; 15:102. [PMID: 31270703 PMCID: PMC6610267 DOI: 10.1007/s11306-019-1547-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 03/28/2019] [Indexed: 01/06/2023]
Abstract
INTRODUCTION Exposure to ricin can be lethal and treatments that are under development have short windows of opportunity for administration after exposure. It is therefore essential to achieve early detection of ricin exposure to provide the best prognosis for exposed individuals. Ricin toxin can be detected in clinical samples via several antibody-based techniques, but the efficacy of these can be limited due to the rapid processing and cellular uptake of toxin in the body and subsequent low blood ricin concentrations. Other diagnostic tools that perform, in an orthogonal manner, are therefore desirable. OBJECTIVES To determine time-dependent metabolic changes in Sprague-Dawley rats following intravenous exposure to ricin. METHODS Sprague-Dawley rats were intravenously exposed to ricin and multiple blood samples were collected from each animal for up to 48 h following exposure in two independent studies. Plasma samples were analysed applying HILIC and C18 reversed phase UHPLC-MS assays followed by univariate and multivariate analysis. RESULTS In Sprague-Dawley rats we have demonstrated that metabolic changes measured in blood can distinguish between rats exposed intravenously to ricin and controls prior to the onset of behavioral signs of intoxication after 24 h. A total of 37 metabolites were significantly altered following exposure to ricin when compared to controls. The arginine/proline, bile acid and triacylglyceride metabolic pathways were highlighted as being important with two triacylglycerides at 8 h post exposure giving an AUROC score of 0.94. At 16 h and 24 h the AUROC score increased to 0.98 and 1.0 with the number of metabolites in the panel increasing to 5 and 7, respectively. CONCLUSIONS These data demonstrate that metabolites may be a useful tool to diagnose and detect ricin exposure, thus increasing the effectiveness of supportive therapy and future ricin-specific medical treatments.
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Affiliation(s)
| | | | - Catherine L Winder
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Andrew D Southam
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Ralf J M Weber
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | | | - Cerys Docx
- Dstl Porton Down, Salisbury, SP4 0JQ, UK
| | | | | | - Mark R Viant
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | | | - Warwick B Dunn
- Phenome Centre Birmingham and School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
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22
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Peters K, Bradbury J, Bergmann S, Capuccini M, Cascante M, de Atauri P, Ebbels TMD, Foguet C, Glen R, Gonzalez-Beltran A, Günther UL, Handakas E, Hankemeier T, Haug K, Herman S, Holub P, Izzo M, Jacob D, Johnson D, Jourdan F, Kale N, Karaman I, Khalili B, Emami Khonsari P, Kultima K, Lampa S, Larsson A, Ludwig C, Moreno P, Neumann S, Novella JA, O'Donovan C, Pearce JTM, Peluso A, Piras ME, Pireddu L, Reed MAC, Rocca-Serra P, Roger P, Rosato A, Rueedi R, Ruttkies C, Sadawi N, Salek RM, Sansone SA, Selivanov V, Spjuth O, Schober D, Thévenot EA, Tomasoni M, van Rijswijk M, van Vliet M, Viant MR, Weber RJM, Zanetti G, Steinbeck C. PhenoMeNal: processing and analysis of metabolomics data in the cloud. Gigascience 2019; 8:giy149. [PMID: 30535405 PMCID: PMC6377398 DOI: 10.1093/gigascience/giy149] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 10/19/2018] [Accepted: 11/20/2018] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological, and many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, data repositories, and data analysis tools. However, the rapid progress has resulted in a mosaic of independent, and sometimes incompatible, analysis methods that are difficult to connect into a useful and complete data analysis solution. FINDINGS PhenoMeNal (Phenome and Metabolome aNalysis) is an advanced and complete solution to set up Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open-source tools that are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated, and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi, and Pachyderm. CONCLUSIONS PhenoMeNal constitutes a keystone solution in cloud e-infrastructures available for metabolomics. PhenoMeNal is a unique and complete solution for setting up cloud e-infrastructures through easy-to-use web interfaces that can be scaled to any custom public and private cloud environment. By harmonizing and automating software installation and configuration and through ready-to-use scientific workflow user interfaces, PhenoMeNal has succeeded in providing scientists with workflow-driven, reproducible, and shareable metabolomics data analysis platforms that are interfaced through standard data formats, representative datasets, versioned, and have been tested for reproducibility and interoperability. The elastic implementation of PhenoMeNal further allows easy adaptation of the infrastructure to other application areas and 'omics research domains.
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Affiliation(s)
- Kristian Peters
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany
| | - James Bradbury
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Marco Capuccini
- Division of Scientific Computing, Department of Information Technology, Uppsala University, Sweden
- Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 751 24 Uppsala, Sweden
| | - Marta Cascante
- Department of Biochemistry and Molecular Biomedicine, Universitat de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Spain
| | - Pedro de Atauri
- Department of Biochemistry and Molecular Biomedicine, Universitat de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Spain
| | - Timothy M D Ebbels
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom
| | - Carles Foguet
- Department of Biochemistry and Molecular Biomedicine, Universitat de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Spain
| | - Robert Glen
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB21EW, United Kingdom
| | - Alejandra Gonzalez-Beltran
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, United Kingdom
| | - Ulrich L Günther
- Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Evangelos Handakas
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom
| | - Thomas Hankemeier
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, 2333 CC, The Netherlands
| | - Kenneth Haug
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Stephanie Herman
- Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 751 24 Uppsala, Sweden
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, 751 85 Uppsala, Sweden
| | | | - Massimiliano Izzo
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, United Kingdom
| | - Daniel Jacob
- INRA, University of Bordeaux, Plateforme Métabolome Bordeaux-MetaboHUB, 33140 Villenave d'Ornon, France
| | - David Johnson
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, United Kingdom
- Department of Informatics and Media, Uppsala University, Box 513, 751 20 Uppsala, Sweden
| | - Fabien Jourdan
- INRA - French National Institute for Agricultural Research, UMR1331, Toxalim, Research Centre in Food Toxicology, Toulouse, France
| | - Namrata Kale
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Ibrahim Karaman
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St. Mary's Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - Bita Khalili
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Payam Emami Khonsari
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, 751 85 Uppsala, Sweden
| | - Kim Kultima
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, 751 85 Uppsala, Sweden
| | - Samuel Lampa
- Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 751 24 Uppsala, Sweden
| | - Anders Larsson
- Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 751 24 Uppsala, Sweden
- National Bioinformatics Infrastructure Sweden, Uppsala University, Uppsala, Sweden
| | - Christian Ludwig
- Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Pablo Moreno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Jon Ander Novella
- Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 751 24 Uppsala, Sweden
- National Bioinformatics Infrastructure Sweden, Uppsala University, Uppsala, Sweden
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Jake T M Pearce
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom
| | - Alina Peluso
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom
| | | | | | - Michelle A C Reed
- Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Philippe Rocca-Serra
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, United Kingdom
| | - Pierrick Roger
- CEA, LIST, Laboratory for Data Analysis and Systems’ Intelligence, MetaboHUB, Gif-Sur-Yvette F-91191, France
| | - Antonio Rosato
- Magnetic Resonance Center (CERM) and Department of Chemistry, University of Florence and CIRMMP, 50019 Sesto Fiorentino, Florence, Italy
| | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Christoph Ruttkies
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany
| | - Noureddin Sadawi
- Department of Computer Science, College of Engineering, Design and Physical Sciences, Brunel University, London, UK
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom
| | - Reza M Salek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, United Kingdom
| | - Vitaly Selivanov
- Department of Biochemistry and Molecular Biomedicine, Universitat de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Spain
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 751 24 Uppsala, Sweden
| | - Daniel Schober
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany
| | - Etienne A Thévenot
- CEA, LIST, Laboratory for Data Analysis and Systems’ Intelligence, MetaboHUB, Gif-Sur-Yvette F-91191, France
| | - Mattia Tomasoni
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Merlijn van Rijswijk
- Netherlands Metabolomics Center, Leiden, 2333 CC, Netherlands
- ELIXIR-NL, Dutch Techcentre for Life Sciences, Utrecht, 3503 RM, Netherlands
| | - Michael van Vliet
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, 2333 CC, The Netherlands
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | | | - Christoph Steinbeck
- Cheminformatics and Computational Metabolomics, Institute for Analytical Chemistry, Lessingstr. 8, 07743 Jena, Germany
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23
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Guo C, Robertson S, Weber RJM, Buckley A, Warren J, Hodgson A, Rappoport JZ, Ignatyev K, Meldrum K, Römer I, Macchiarulo S, Chipman JK, Marczylo T, Leonard MO, Gant TW, Viant MR, Smith R. Pulmonary toxicity of inhaled nano-sized cerium oxide aerosols in Sprague-Dawley rats. Nanotoxicology 2019; 13:733-750. [PMID: 30704321 PMCID: PMC6816500 DOI: 10.1080/17435390.2018.1554751] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Cerium oxide nanoparticles (CeO2NPs), used in some diesel fuel additives to improve fuel combustion efficiency and exhaust filter operation, have been detected in ambient air and concerns have been raised about their potential human health impact. The majority of CeO2NP inhalation studies undertaken to date have used aerosol particles of larger sizes than the evidence suggests are emitted from vehicles using such fuel additives. Hence, the objective of this study was to investigate the effects of inhaled CeO2NP aerosols of a more environmentally relevant size, utilizing a combination of methods, including untargeted multi-omics to enable the broadest possible survey of molecular responses and synchrotron X-ray spectroscopy to investigate cerium speciation. Male Sprague-Dawley rats were exposed by nose-only inhalation to aerosolized CeO2NPs (mass concentration 1.8 mg/m3, aerosol count median diameter 40 nm) for 3 h/d for 4 d/week, for 1 or 2 weeks and sacrificed at 3 and 7 d post-exposure. Markers of inflammation changed significantly in a dose- and time-dependent manner, which, combined with results from lung histopathology and gene expression analyses suggest an inflammatory response greater than that seen in studies using micron-sized ceria aerosols. Lipidomics of lung tissue revealed changes to minor lipid species, implying specific rather than general cellular effects. Cerium speciation analysis indicated a change in Ce3+/Ce4+ ratio within lung tissue. Collectively, these results in conjunction with earlier studies emphasize the importance of aerosol particle size on toxicity determination. Furthermore, the limited effect resolution within 7 d suggested the possibility of longer-term effects.
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Affiliation(s)
- Chang Guo
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Sarah Robertson
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Ralf J M Weber
- b School of Biosciences , University of Birmingham , Birmingham, B15 2TT , UK
| | - Alison Buckley
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - James Warren
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Alan Hodgson
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Joshua Z Rappoport
- c Department of Cell and Molecular Biology , Northwestern University , Chicago , IL , USA
| | - Konstantin Ignatyev
- d Diamond Light Source Ltd , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0DE , UK
| | - Kirsty Meldrum
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Isabella Römer
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Sameirah Macchiarulo
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - James Kevin Chipman
- b School of Biosciences , University of Birmingham , Birmingham, B15 2TT , UK
| | - Tim Marczylo
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Martin O Leonard
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Timothy W Gant
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
| | - Mark R Viant
- b School of Biosciences , University of Birmingham , Birmingham, B15 2TT , UK
| | - Rachel Smith
- a Centre for Radiation, Chemical and Environmental Hazards , Public Health England , Harwell Science and Innovation Campus , Didcot, Oxfordshire , OX11 0RQ , UK
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24
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Buesen R, Chorley BN, da Silva Lima B, Daston G, Deferme L, Ebbels T, Gant TW, Goetz A, Greally J, Gribaldo L, Hackermüller J, Hubesch B, Jennen D, Johnson K, Kanno J, Kauffmann HM, Laffont M, McMullen P, Meehan R, Pemberton M, Perdichizzi S, Piersma AH, Sauer UG, Schmidt K, Seitz H, Sumida K, Tollefsen KE, Tong W, Tralau T, van Ravenzwaay B, Weber RJM, Worth A, Yauk C, Poole A. Applying 'omics technologies in chemicals risk assessment: Report of an ECETOC workshop. Regul Toxicol Pharmacol 2017; 91 Suppl 1:S3-S13. [PMID: 28958911 DOI: 10.1016/j.yrtph.2017.09.002] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 08/31/2017] [Accepted: 09/02/2017] [Indexed: 10/18/2022]
Abstract
Prevailing knowledge gaps in linking specific molecular changes to apical outcomes and methodological uncertainties in the generation, storage, processing, and interpretation of 'omics data limit the application of 'omics technologies in regulatory toxicology. Against this background, the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) convened a workshop Applying 'omics technologies in chemicals risk assessment that is reported herein. Ahead of the workshop, multi-expert teams drafted frameworks on best practices for (i) a Good-Laboratory Practice-like context for collecting, storing and curating 'omics data; (ii) the processing of 'omics data; and (iii) weight-of-evidence approaches for integrating 'omics data. The workshop participants confirmed the relevance of these Frameworks to facilitate the regulatory applicability and use of 'omics data, and the workshop discussions provided input for their further elaboration. Additionally, the key objective (iv) to establish approaches to connect 'omics perturbations to phenotypic alterations was addressed. Generally, it was considered promising to strive to link gene expression changes and pathway perturbations to the phenotype by mapping them to specific adverse outcome pathways. While further work is necessary before gene expression changes can be used to establish safe levels of substance exposure, the ECETOC workshop provided important incentives towards achieving this goal.
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Affiliation(s)
| | | | | | | | | | - Timothy Ebbels
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Timothy W Gant
- Centre for Radiation, Chemical and Environmental Hazards (CRCE), Harwell Science and Innovation Campus, Public Health England (PHE), United Kingdom
| | | | - John Greally
- Albert Einstein College of Medicine, Yeshiva University, USA
| | - Laura Gribaldo
- European Commission, Joint Research Centre, European Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM), Italy
| | - Jörg Hackermüller
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research - UFZ, Germany
| | | | - Danyel Jennen
- Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, The Netherlands
| | | | - Jun Kanno
- Japan Organization of Occupational Health and Safety, Japan
| | | | - Madeleine Laffont
- European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC), Belgium
| | | | - Richard Meehan
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Scotland, United Kingdom
| | | | - Stefania Perdichizzi
- Center for Environmental Toxicology, Agency for Prevention, Environment and Energy (Arpae), Emilia-Romagna, Italy
| | - Aldert H Piersma
- National Institute for Public Health and the Environment (RIVM), The Netherlands; IRAS Institute for Risk Assessment Sciences, Utrecht University, The Netherlands
| | | | | | - Hervé Seitz
- Institut de Génétique Humain (IGH), Centre National de la Recherche Scientifique - National Centre of Scientific Research (CNRS), France
| | | | | | - Weida Tong
- National Center for Toxicological Research (NCTR), U.S. Food and Drug Administration (FDA), USA
| | - Tewes Tralau
- Department of Chemical and Product Safety, German Federal Institute of Risk Assessment (BfR), Germany
| | | | - Ralf J M Weber
- Phenome Centre Birmingham, School of Biosciences, University of Birmingham, United Kingdom
| | - Andrew Worth
- European Commission, Joint Research Centre, European Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM), Italy
| | - Carole Yauk
- Environmental Health Science and Research Bureau, Health Canada, Canada
| | - Alan Poole
- European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC), Belgium.
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25
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van Rijswijk M, Beirnaert C, Caron C, Cascante M, Dominguez V, Dunn WB, Ebbels TMD, Giacomoni F, Gonzalez-Beltran A, Hankemeier T, Haug K, Izquierdo-Garcia JL, Jimenez RC, Jourdan F, Kale N, Klapa MI, Kohlbacher O, Koort K, Kultima K, Le Corguillé G, Moreno P, Moschonas NK, Neumann S, O'Donovan C, Reczko M, Rocca-Serra P, Rosato A, Salek RM, Sansone SA, Satagopam V, Schober D, Shimmo R, Spicer RA, Spjuth O, Thévenot EA, Viant MR, Weber RJM, Willighagen EL, Zanetti G, Steinbeck C. The future of metabolomics in ELIXIR. F1000Res 2017; 6. [PMID: 29043062 PMCID: PMC5627583 DOI: 10.12688/f1000research.12342.2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/31/2017] [Indexed: 01/11/2023] Open
Abstract
Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.
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Affiliation(s)
- Merlijn van Rijswijk
- ELIXIR-NL, Dutch Techcentre for Life Sciences, Utrecht, 3503 RM, Netherlands.,Netherlands Metabolomics Center, Leiden, 2333 CC, Netherlands
| | - Charlie Beirnaert
- ADReM, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, 2020, Belgium
| | - Christophe Caron
- ELIXIR-FR, French Institute of Bioinformatics, Gif-sur-Yvette, F-91198, France
| | - Marta Cascante
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, 08028, Spain
| | - Victoria Dominguez
- ELIXIR-FR, French Institute of Bioinformatics, Gif-sur-Yvette, F-91198, France
| | - Warwick B Dunn
- School of Biosciences, Phenome Centre Birmingham and Birmingham Metabolomics Training Centre, University of Birmingham, Birmingham, B15 2TT, UK
| | - Timothy M D Ebbels
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Franck Giacomoni
- INRA, UNH, Human Nutrition Unit, PFEM, Metabolism Exploration Platform, MetaboHUB-Clermont, Clermont Auvergne University, Clermont-Ferrand, F-63000, France
| | | | - Thomas Hankemeier
- Netherlands Metabolomics Center, Leiden, 2333 CC, Netherlands.,Leiden Academic Centre for Drug Research, Leiden University, Leiden, 2300 RA, Netherlands
| | - Kenneth Haug
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, CB10 1SD, UK
| | - Jose L Izquierdo-Garcia
- Centro Nacional Investigaciones Cardiovasculares, Madrid, 28029, Spain.,CIBER de Enfermedades Respiratorias, Madrid, 28029 , Spain
| | | | - Fabien Jourdan
- Toxalim, UMR 1331, Université de Toulouse, Toulouse, F-31300, France
| | - Namrata Kale
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, CB10 1SD, UK
| | - Maria I Klapa
- Metabolic Engineering and Systems Biology Laboratory, Institute of Chemical Engineering Sciences, Foundation for Research & Technology - Hellas (FORTH/ICE-HT), Patras, GR-26504, Greece
| | - Oliver Kohlbacher
- Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, 72076, Germany.,Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany.,Center for Bioinformatics, University of Tübingen, Tübingen, 72076, Germany
| | - Kairi Koort
- The Centre of Excellence in Neural and Behavioural Sciences, Tallinn, Tallinn, 10120, Estonia.,School of Natural Sciences and Health, Tallinn University, 10120, 10120, Estonia
| | - Kim Kultima
- Department of Medical Sciences, Uppsala University, Uppsala, 752 36, Sweden
| | - Gildas Le Corguillé
- ELIXIR-FR, French Institute of Bioinformatics, Gif-sur-Yvette, F-91198, France.,UPMC, CNRS, FR2424, ABiMS, Station Biologique, Roscoff, F-29680, France
| | - Pablo Moreno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, CB10 1SD, UK
| | - Nicholas K Moschonas
- Metabolic Engineering and Systems Biology Laboratory, Institute of Chemical Engineering Sciences, Foundation for Research & Technology - Hellas (FORTH/ICE-HT), Patras, GR-26504, Greece.,Department of General Biology, School of Medicine, University of Patras, Patras, GR-26504, Greece
| | - Steffen Neumann
- Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, 06120, Germany
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, CB10 1SD, UK
| | | | - Philippe Rocca-Serra
- Oxford e-Research Centre, Engineering Science Department, University of Oxford, Oxford, OX1 3QG, UK
| | - Antonio Rosato
- Magnetic Resonance Center, Interuniversity Consortium for Magnetic Resonance on MetalloProteins, University of Florence, Florence, 50121, Italy
| | - Reza M Salek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, CB10 1SD, UK
| | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Engineering Science Department, University of Oxford, Oxford, OX1 3QG, UK
| | - Venkata Satagopam
- Luxembourg Centre For Systems Biomedicine (LCSB), University of Luxembourg, Belvaux, L-4367, Luxembourg
| | - Daniel Schober
- Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, 06120, Germany
| | - Ruth Shimmo
- The Centre of Excellence in Neural and Behavioural Sciences, Tallinn, Tallinn, 10120, Estonia.,School of Natural Sciences and Health, Tallinn University, 10120, 10120, Estonia
| | - Rachel A Spicer
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, CB10 1SD, UK
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, 752 36, Sweden
| | - Etienne A Thévenot
- CEA, LIST, Laboratory for Data Analysis and Systems' Intelligence, MetaboHUB, Gif-sur-Yvette, F-91191, France
| | - Mark R Viant
- School of Biosciences, Phenome Centre Birmingham and Birmingham Metabolomics Training Centre, University of Birmingham, Birmingham, B15 2TT, UK
| | - Ralf J M Weber
- School of Biosciences, Phenome Centre Birmingham and Birmingham Metabolomics Training Centre, University of Birmingham, Birmingham, B15 2TT, UK
| | - Egon L Willighagen
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, NL-6200, Netherlands
| | - Gianluigi Zanetti
- CRS4, Data Intensive Computing Group, Ed.1 POLARIS, Pula, 09010, Italy
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26
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Larralde M, Lawson TN, Weber RJM, Moreno P, Haug K, Rocca-Serra P, Viant MR, Steinbeck C, Salek RM. mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data. Bioinformatics 2017; 33:2598-2600. [PMID: 28402395 PMCID: PMC5870861 DOI: 10.1093/bioinformatics/btx169] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 02/14/2017] [Accepted: 04/05/2017] [Indexed: 02/03/2023] Open
Abstract
SUMMARY Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files. The parsing packages are separated into mzML2ISA (encompassing mzML and imzML formats) and nmrML2ISA (nmrML format only). Overall, the use of mzML2ISA & nmrML2ISA reduces the time needed to capture metadata substantially (capturing 90% of metadata on assay and sample levels), is much less prone to user input errors, improves compliance with minimum information reporting guidelines and facilitates more finely grained data exploration and querying of datasets. AVAILABILITY AND IMPLEMENTATION mzML2ISA & nmrML2ISA are available under version 3 of the GNU General Public Licence at https://github.com/ISA-tools. Documentation is available from http://2isa.readthedocs.io/en/latest/. CONTACT reza.salek@ebi.ac.uk or isatools@googlegroups.com. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Thomas N Lawson
- School of Biosciences, University of Birmingham, Birmingham, UK
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Birmingham, UK
- Phenome Centre Birmingham, University of Birmingham, Birmingham, UK
| | - Pablo Moreno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK
| | - Kenneth Haug
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK
| | | | - Mark R Viant
- School of Biosciences, University of Birmingham, Birmingham, UK
- Phenome Centre Birmingham, University of Birmingham, Birmingham, UK
| | - Christoph Steinbeck
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK
- Institute for Inorganic and Analytical Chemistry, Friedrich-Schiller-University, Lessingstr. 8, Jena, Germany
| | - Reza M Salek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK
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27
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Lawson TN, Weber RJM, Jones MR, Chetwynd AJ, Rodrı́guez-Blanco G, Di Guida R, Viant MR, Dunn WB. msPurity: Automated Evaluation of Precursor Ion Purity for Mass Spectrometry-Based Fragmentation in Metabolomics. Anal Chem 2017; 89:2432-2439. [DOI: 10.1021/acs.analchem.6b04358] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Thomas N. Lawson
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Ralf J. M. Weber
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Martin R. Jones
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Andrew J. Chetwynd
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Giovanny Rodrı́guez-Blanco
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Riccardo Di Guida
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Mark R. Viant
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Warwick B. Dunn
- School
of Biosciences and ‡Phenome Centre Birmingham, College of Life and Environmental
Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
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28
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Weber RJM, Lawson TN, Salek RM, Ebbels TMD, Glen RC, Goodacre R, Griffin JL, Haug K, Koulman A, Moreno P, Ralser M, Steinbeck C, Dunn WB, Viant MR. Computational tools and workflows in metabolomics: An international survey highlights the opportunity for harmonisation through Galaxy. Metabolomics 2017; 13:12. [PMID: 28090198 PMCID: PMC5192046 DOI: 10.1007/s11306-016-1147-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 11/30/2016] [Indexed: 01/19/2023]
Affiliation(s)
- Ralf J. M. Weber
- 0000 0004 1936 7486grid.6572.6School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
- 0000 0004 1936 7486grid.6572.6Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT UK
| | - Thomas N. Lawson
- 0000 0004 1936 7486grid.6572.6School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
| | - Reza M. Salek
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, CB10 1SD UK
| | - Timothy M. D. Ebbels
- 0000 0001 2113 8111grid.7445.2Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ UK
| | - Robert C. Glen
- 0000 0001 2113 8111grid.7445.2Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ UK
- Centre for Molecular Informatics, Department of Chemistry, Lensfield Road, Cambridge, CB2 1EW UK
| | - Royston Goodacre
- 0000000121662407grid.5379.8Manchester Institute of Biotechnology and School of Chemistry, University of Manchester, Manchester, M1 7DN UK
| | - Julian L. Griffin
- 0000 0004 0606 2472grid.415055.0MRC Human Nutrition Research Unit, Cambridge, CB1 9NL UK
- 0000000121885934grid.5335.0The Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA UK
| | - Kenneth Haug
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, CB10 1SD UK
| | - Albert Koulman
- 0000 0004 0606 2472grid.415055.0MRC Human Nutrition Research Unit, Cambridge, CB1 9NL UK
| | - Pablo Moreno
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, CB10 1SD UK
| | - Markus Ralser
- 0000000121885934grid.5335.0The Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA UK
- 0000 0004 1795 1830grid.451388.3The Francis Crick Institute, 1 Midland Road, NW1 1AT London, UK
| | - Christoph Steinbeck
- 0000 0000 9709 7726grid.225360.0European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, CB10 1SD UK
| | - Warwick B. Dunn
- 0000 0004 1936 7486grid.6572.6School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
- 0000 0004 1936 7486grid.6572.6Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT UK
| | - Mark R. Viant
- 0000 0004 1936 7486grid.6572.6School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
- 0000 0004 1936 7486grid.6572.6Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT UK
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Mazzolini J, Weber RJM, Chen HS, Khan A, Guggenheim E, Shaw RK, Chipman JK, Viant MR, Rappoport JZ. Protein Corona Modulates Uptake and Toxicity of Nanoceria via Clathrin-Mediated Endocytosis. Biol Bull 2016; 231:40-60. [PMID: 27638694 DOI: 10.1086/689590] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Particles present in diesel exhaust have been proposed as a significant contributor to the development of acute and chronic lung diseases, including respiratory infection and allergic asthma. Nanoceria (CeO2 nanoparticles) are used to increase fuel efficiency in internal combustion engines, are present in exhaust fumes, and could affect cells of the airway. Components from the environment such as biologically derived proteins, carbohydrates, and lipids can form a dynamic layer, commonly referred to as the "protein corona" which alters cellular nanoparticle interactions and internalization. Using confocal reflectance microscopy, we quantified nanoceria uptake by lung-derived cells in the presence and absence of a serum-derived protein corona. Employing mass spectrometry, we identified components of the protein corona, and demonstrated that the interaction between transferrin in the protein corona and the transferrin receptor is involved in mediating the cellular entry of nanoceria via clathrin-mediated endocytosis. Furthermore, under these conditions nanoceria does not affect cell growth, viability, or metabolism, even at high concentration. Alternatively, despite the antioxidant capacity of nanoceria, in serum-free conditions these nanoparticles induce plasma membrane disruption and cause changes in cellular metabolism. Thus, our results identify a specific receptor-mediated mechanism for nanoceria entry, and provide significant insight into the potential for nanoparticle-dependent toxicity.
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Affiliation(s)
- Julie Mazzolini
- School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Ralf J M Weber
- School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Hsueh-Shih Chen
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu City 30, Taiwan
| | - Abdullah Khan
- School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Emily Guggenheim
- School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Robert K Shaw
- Institute of Biomedical Research, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom; and
| | - James K Chipman
- School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Mark R Viant
- School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Joshua Z Rappoport
- Center for Advanced Microscopy and Nikon Imaging Center, Northwestern University Feinberg School of Medicine, 303 East Chicago Avenue, Chicago, Illinois 60611
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Davidson RL, Weber RJM, Liu H, Sharma-Oates A, Viant MR. Galaxy-M: a Galaxy workflow for processing and analyzing direct infusion and liquid chromatography mass spectrometry-based metabolomics data. Gigascience 2016; 5:10. [PMID: 26913198 PMCID: PMC4765054 DOI: 10.1186/s13742-016-0115-8] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Accepted: 02/06/2016] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Metabolomics is increasingly recognized as an invaluable tool in the biological, medical and environmental sciences yet lags behind the methodological maturity of other omics fields. To achieve its full potential, including the integration of multiple omics modalities, the accessibility, standardization and reproducibility of computational metabolomics tools must be improved significantly. RESULTS Here we present our end-to-end mass spectrometry metabolomics workflow in the widely used platform, Galaxy. Named Galaxy-M, our workflow has been developed for both direct infusion mass spectrometry (DIMS) and liquid chromatography mass spectrometry (LC-MS) metabolomics. The range of tools presented spans from processing of raw data, e.g. peak picking and alignment, through data cleansing, e.g. missing value imputation, to preparation for statistical analysis, e.g. normalization and scaling, and principal components analysis (PCA) with associated statistical evaluation. We demonstrate the ease of using these Galaxy workflows via the analysis of DIMS and LC-MS datasets, and provide PCA scores and associated statistics to help other users to ensure that they can accurately repeat the processing and analysis of these two datasets. Galaxy and data are all provided pre-installed in a virtual machine (VM) that can be downloaded from the GigaDB repository. Additionally, source code, executables and installation instructions are available from GitHub. CONCLUSIONS The Galaxy platform has enabled us to produce an easily accessible and reproducible computational metabolomics workflow. More tools could be added by the community to expand its functionality. We recommend that Galaxy-M workflow files are included within the supplementary information of publications, enabling metabolomics studies to achieve greater reproducibility.
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Affiliation(s)
- Robert L. Davidson
- />GigaScience, BGI-Hong Kong Co. Ltd, Tai Po Industrial Estate, 16 Dai Fu Street, Tai Po, NT Hong Kong
- />School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
| | - Ralf J. M. Weber
- />School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
| | - Haoyu Liu
- />School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
| | | | - Mark R. Viant
- />School of Biosciences, University of Birmingham, Birmingham, B15 2TT UK
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Di Guida R, Engel J, Allwood JW, Weber RJM, Jones MR, Sommer U, Viant MR, Dunn WB. Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling. Metabolomics 2016; 12:93. [PMID: 27123000 PMCID: PMC4831991 DOI: 10.1007/s11306-016-1030-9] [Citation(s) in RCA: 183] [Impact Index Per Article: 22.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2015] [Accepted: 04/05/2016] [Indexed: 12/25/2022]
Abstract
INTRODUCTION The generic metabolomics data processing workflow is constructed with a serial set of processes including peak picking, quality assurance, normalisation, missing value imputation, transformation and scaling. The combination of these processes should present the experimental data in an appropriate structure so to identify the biological changes in a valid and robust manner. OBJECTIVES Currently, different researchers apply different data processing methods and no assessment of the permutations applied to UHPLC-MS datasets has been published. Here we wish to define the most appropriate data processing workflow. METHODS We assess the influence of normalisation, missing value imputation, transformation and scaling methods on univariate and multivariate analysis of UHPLC-MS datasets acquired for different mammalian samples. RESULTS Our studies have shown that once data are filtered, missing values are not correlated with m/z, retention time or response. Following an exhaustive evaluation, we recommend PQN normalisation with no missing value imputation and no transformation or scaling for univariate analysis. For PCA we recommend applying PQN normalisation with Random Forest missing value imputation, glog transformation and no scaling method. For PLS-DA we recommend PQN normalisation, KNN as the missing value imputation method, generalised logarithm transformation and no scaling. These recommendations are based on searching for the biologically important metabolite features independent of their measured abundance. CONCLUSION The appropriate choice of normalisation, missing value imputation, transformation and scaling methods differs depending on the data analysis method and the choice of method is essential to maximise the biological derivations from UHPLC-MS datasets.
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Affiliation(s)
- Riccardo Di Guida
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
- />MRC-ARUK Centre for Musculoskeletal Ageing Research, University of Birmingham, Birmingham, B15 2TT UK
| | - Jasper Engel
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
- />NERC Biomolecular Analysis Facility—Metabolomics Node (NBAF-B), University of Birmingham, Birmingham, B15 2TT UK
| | - J. William Allwood
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Ralf J. M. Weber
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Martin R. Jones
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Ulf Sommer
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
- />NERC Biomolecular Analysis Facility—Metabolomics Node (NBAF-B), University of Birmingham, Birmingham, B15 2TT UK
| | - Mark R. Viant
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
- />NERC Biomolecular Analysis Facility—Metabolomics Node (NBAF-B), University of Birmingham, Birmingham, B15 2TT UK
- />Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT UK
- />Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Warwick B. Dunn
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
- />MRC-ARUK Centre for Musculoskeletal Ageing Research, University of Birmingham, Birmingham, B15 2TT UK
- />Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT UK
- />Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
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Affiliation(s)
- Ralf J. M. Weber
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Catherine L. Winder
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Lee D. Larcombe
- />Department of Physiology, Anatomy & Genetics, University of Oxford, Oxford, OX1 3PT UK
| | - Warwick B. Dunn
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
| | - Mark R. Viant
- />School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK
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Drury NE, Howell NJ, Calvert MJ, Weber RJM, Senanayake EL, Lewis ME, Hyde JAJ, Green DH, Mascaro JG, Wilson IC, Graham TR, Rooney SJ, Viant MR, Freemantle N, Frenneaux MP, Pagano D. The effect of perhexiline on myocardial protection during coronary artery surgery: a two-centre, randomized, double-blind, placebo-controlled trial. Eur J Cardiothorac Surg 2014; 47:464-72. [PMID: 24948413 PMCID: PMC4324609 DOI: 10.1093/ejcts/ezu238] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
OBJECTIVES Perhexiline is thought to modulate metabolism by inhibiting mitochondrial carnitine palmitoyltransferase-1, reducing fatty acid uptake and increasing carbohydrate utilization. This study assessed whether preoperative perhexiline improves markers of myocardial protection in patients undergoing coronary artery bypass graft surgery and analysed its effect on the myocardial metabolome. METHODS In a prospective, randomized, double-blind, placebo-controlled trial, patients at two centres were randomized to receive either oral perhexiline or placebo for at least 5 days prior to surgery. The primary outcome was a low cardiac output episode in the first 6 h. All pre-specified analyses were conducted according to the intention-to-treat principle with a statistical power of 90% to detect a relative risk of 0.5 and a conventional one-sided α-value of 0.025. A subset of pre-ischaemic left ventricular biopsies was analysed using mass spectrometry-based metabolomics. RESULTS Over a 3-year period, 286 patients were randomized, received the intervention and were included in the analysis. The incidence rate of a low cardiac output episode in the perhexiline arm was 36.7% (51/139) vs 34.7% (51/147) in the control arm [odds ratio (OR) 0.92, 95% confidence interval (CI) 0.56–1.50, P = 0.74]. Perhexiline was associated with a reduction in the cardiac index at 6 h [difference in means 0.19, 95% CI 0.07–0.31, P = 0.001] and an increase in inotropic support in the first 12 h (OR 0.55, 95% CI 0.34–0.89, P = 0.015). There were no significant differences in myocardial injury with troponin-T or electrocardiogram, reoperation, renal dysfunction or length of stay. No difference in the preischaemic left ventricular metabolism was identified between groups on metabolomics analysis. CONCLUSIONS Preoperative perhexiline does not improve myocardial protection in patients undergoing coronary surgery and in fact reduced perioperative cardiac output, increasing the need for inotropic support. Perhexiline has no significant effect on the mass spectrometry-visible polar myocardial metabolome in vivo in humans, supporting the suggestion that it acts via a pathway that is independent of myocardial carnitine palmitoyltransferase inhibition and may explain the lack of clinical benefit observed following surgery. ClinicalTrials.Gov ID NCT00845364.
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Affiliation(s)
- Nigel E Drury
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
| | - Neil J Howell
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
| | - Melanie J Calvert
- School of Health and Population Sciences, University of Birmingham, Birmingham, UK
| | - Ralf J M Weber
- Centre for Systems Biology, School of Biosciences, University of Birmingham, Birmingham, UK
| | - Eshan L Senanayake
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
| | - Michael E Lewis
- Department of Cardiothoracic Surgery, Royal Sussex County Hospital, Brighton
| | - Jonathan A J Hyde
- Department of Cardiothoracic Surgery, Royal Sussex County Hospital, Brighton
| | - David H Green
- Department of Cardiac Anesthesia, Queen Elizabeth Hospital Birmingham, Birmingham, UK
| | - Jorge G Mascaro
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK
| | - Ian C Wilson
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK
| | - Timothy R Graham
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK
| | - Stephen J Rooney
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK
| | - Mark R Viant
- Centre for Systems Biology, School of Biosciences, University of Birmingham, Birmingham, UK
| | - Nick Freemantle
- Department of Primary Care and Population Health, University College London, London, UK
| | | | - Domenico Pagano
- Department of Cardiothoracic Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
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Zhou J, Weber RJM, Allwood JW, Mistrik R, Zhu Z, Ji Z, Chen S, Dunn WB, He S, Viant MR. HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries. ACTA ACUST UNITED AC 2013; 30:581-3. [PMID: 24336413 PMCID: PMC3928522 DOI: 10.1093/bioinformatics/btt711] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
SUMMARY Experimental MS(n) mass spectral libraries currently do not adequately cover chemical space. This limits the robust annotation of metabolites in metabolomics studies of complex biological samples. In silico fragmentation libraries would improve the identification of compounds from experimental multistage fragmentation data when experimental reference data are unavailable. Here, we present a freely available software package to automatically control Mass Frontier software to construct in silico mass spectral libraries and to perform spectral matching. Based on two case studies, we have demonstrated that high-throughput automation of Mass Frontier allows researchers to generate in silico mass spectral libraries in an automated and high-throughput fashion with little or no human intervention required. AVAILABILITY AND IMPLEMENTATION Documentation, examples, results and source code are available at http://www.biosciences-labs.bham.ac.uk/viant/hammer/.
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Affiliation(s)
- Jiarui Zhou
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK, HighChem, Ltd., Leskova 11, 81104 Bratislava, Slovakia, Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, China and School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
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Weber RJM, Selander E, Sommer U, Viant MR. A stable-isotope mass spectrometry-based metabolic footprinting approach to analyze exudates from phytoplankton. Mar Drugs 2013; 11:4158-75. [PMID: 24172212 PMCID: PMC3853721 DOI: 10.3390/md11114158] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2013] [Revised: 09/13/2013] [Accepted: 10/01/2013] [Indexed: 11/16/2022] Open
Abstract
Phytoplankton exudates play an important role in pelagic ecology and biogeochemical cycles of elements. Exuded compounds fuel the microbial food web and often encompass bioactive secondary metabolites like sex pheromones, allelochemicals, antibiotics, or feeding attractants that mediate biological interactions. Despite this importance, little is known about the bioactive compounds present in phytoplankton exudates. We report a stable-isotope metabolic footprinting method to characterise exudates from aquatic autotrophs. Exudates from (13)C-enriched alga were concentrated by solid phase extraction and analysed by high-resolution Fourier transform ion cyclotron resonance mass spectrometry. We used the harmful algal bloom forming dinoflagellate Alexandrium tamarense to prove the method. An algorithm was developed to automatically pinpoint just those metabolites with highly (13)C-enriched isotope signatures, allowing us to discover algal exudates from the complex seawater background. The stable-isotope pattern (SIP) of the detected metabolites then allowed for more accurate assignment to an empirical formula, a critical first step in their identification. This automated workflow provides an effective way to explore the chemical nature of the solutes exuded from phytoplankton cells and will facilitate the discovery of novel dissolved bioactive compounds.
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Affiliation(s)
- Ralf J. M. Weber
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK; E-Mail:
| | - Erik Selander
- Centre for Ocean Life, National Institute of Aquatic Resources, Technical University of Denmark, Kavalergården 6, 2920 Charlottenlund, Denmark; E-Mail:
| | - Ulf Sommer
- NERC Biomolecular Analysis Facility-Metabolomics Node (NBAF-B), University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK; E-Mail:
| | - Mark R. Viant
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK; E-Mail:
- NERC Biomolecular Analysis Facility-Metabolomics Node (NBAF-B), University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK; E-Mail:
- Author to whom correspondence should be addressed; E-Mail: ; Tel.: +44-121-41-42219; Fax: +44-121-41-45925
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Weber RJM, Southam AD, Sommer U, Viant MR. Characterization of isotopic abundance measurements in high resolution FT-ICR and Orbitrap mass spectra for improved confidence of metabolite identification. Anal Chem 2011; 83:3737-43. [PMID: 21466230 DOI: 10.1021/ac2001803] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Currently there is limited information available on the accuracy and precision of relative isotopic abundance (RIA) measurements using high-resolution direct-infusion mass spectrometry (HR DIMS), and it is unclear if this information can benefit automated peak annotation in metabolomics. Here we characterize the accuracy of RIA measurements on the Thermo LTQ FT Ultra (resolution of 100,000-750,000) and LTQ Orbitrap (R = 100,000) mass spectrometers. This first involved reoptimizing the SIM-stitching method (Southam, A. D. Anal. Chem. 2007, 79, 4595-4602) for the LTQ FT Ultra, which achieved a ca. 3-fold sensitivity increase compared to the original method while maintaining a root-mean-squared mass error of 0.16 ppm. Using this method, we show the quality of RIA measurements is highly dependent on signal-to-noise ratio (SNR), with RIA accuracy increasing with higher SNR. Furthermore, a negative offset between the theoretical and empirically calculated numbers of carbon atoms was observed for both mass spectrometers. Increasing the resolution of the LTQ FT Ultra lowered both the sensitivity and the quality of RIA measurements. Overall, although the errors in the empirically calculated number of carbons can be large (e.g., 10 carbons), we demonstrate that RIA measurements do improve automated peak annotation, increasing the number of single empirical formula assignments by >3-fold compared to using accurate mass alone.
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Affiliation(s)
- Ralf J M Weber
- Centre for Systems Biology, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
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Taylor NS, Weber RJM, White TA, Viant MR. Discriminating between different acute chemical toxicities via changes in the daphnid metabolome. Toxicol Sci 2010; 118:307-17. [PMID: 20719749 DOI: 10.1093/toxsci/kfq247] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Currently, there is widespread interest in exploiting "omics" approaches to screen the toxicity of chemicals, potentially enabling their rapid categorization into classes of defined mode of action (MOA). Direct infusion Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) metabolomics provides a sensitive and nontargeted analysis of potentially a thousand endogenous metabolites. Our previous work has shown that mass spectra can be recorded from whole-organism homogenate or hemolymph of single adult Daphnia magna. Here we develop multivariate models and discover perturbations to specific metabolic pathways that can discriminate between the acute toxicities of four chemicals to D. magna using FT-ICR MS metabolomics. We focus on model toxicants (cadmium, fenvalerate, dinitrophenol, and propranolol) with different MOAs. First, we confirmed that a toxicant-induced metabolic effect could be determined for each chemical in both the hemolymph and the whole-organism metabolome, with between 9 and 660 mass spectral peaks changing intensities significantly, dependent upon toxicant and sample type. Subsequently, supervised multivariate models were built that discriminated significantly all four acute metabolic toxicities, yielding mean classification error rates (across all classes) of 3.9 and 6.9% for whole-organism homogenates and hemolymph, respectively. Following extensive peak annotation, we discovered toxicant-specific perturbations to putatively identified metabolic pathways, including propranolol-induced disruption of fatty acid metabolism and eicosanoid biosynthesis and fenvalerate-induced disruption of amino sugar metabolism. We conclude that the metabolic profiles of whole-daphnid homogenates are more discriminatory for toxicant action than hemolymph. Furthermore, our findings highlight the capability of metabolomics to discover early-event metabolic responses that can discriminate between the acute toxicities of chemicals.
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Affiliation(s)
- Nadine S Taylor
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
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