Literature DB >> 19209610

International NMR-based environmental metabolomics intercomparison exercise.

Mark R Viant1, Daniel W Bearden, Jacob G Bundy, Ian W Burton, Timothy W Collette, Drew R Ekman, Vilnis Ezernieks, Tobias K Karakach, Ching Yu Lin, Simone Rochfort, Jeffrey S de Ropp, Quincy Teng, Ronald S Tjeerdema, John A Walter, Huifeng Wu.   

Abstract

Several fundamental requirements must be met so that NMR-based metabolomics and the related technique of metabonomics can be formally adopted into environmental monitoring and chemical risk assessment. Here we report an intercomparison exercise which has evaluated the effectiveness of 1H NMR metabolomics to generate comparable data sets from environmentally derived samples. It focuses on laboratory practice that follows sample collection and metabolite extraction, specifically the final stages of sample preparation, NMR data collection (500, 600, and 800 MHz), data processing, and multivariate analysis. Seven laboratories have participated from the U.S.A., Canada, U.K., and Australia, generating a total of ten data sets. Phase 1 comprised the analysis of synthetic metabolite mixtures, while Phase 2 investigated European flounder (Platichthys flesus) liver extracts from clean and contaminated sites. Overall, the comparability of data sets from the participating laboratories was good. Principal components analyses (PCA) of the individual data sets yielded ten highly similar scores plots for the synthetic mixtures, with a comparable result for the liver extracts. Furthermore, the same metabolic biomarkers that discriminated fish from clean and contaminated sites were discovered by all the laboratories. PCA of the combined data sets showed excellent clustering of the multiple analyses. These results demonstrate that NMR-based metabolomics can generate data that are sufficiently comparable between laboratories to support its continued evaluation for regulatory environmental studies.

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Year:  2009        PMID: 19209610     DOI: 10.1021/es802198z

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  37 in total

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2.  Metabolomics Analysis of Effects of Commercial Soy-based Protein Products in Red Drum (Sciaenops ocellatus).

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Journal:  J Proteome Res       Date:  2017-06-21       Impact factor: 4.466

3.  Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks.

Authors:  Tianwei Yu; Yun Bai
Journal:  Curr Metabolomics       Date:  2013-01-01

4.  Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN.

Authors:  Jie Hao; Manuel Liebeke; William Astle; Maria De Iorio; Jacob G Bundy; Timothy M D Ebbels
Journal:  Nat Protoc       Date:  2014-05-22       Impact factor: 13.491

5.  A scoring metric for multivariate data for reproducibility analysis using chemometric methods.

Authors:  David A Sheen; Werickson Fortunato de Carvalho Rocha; Katrice A Lippa; Daniel W Bearden
Journal:  Chemometr Intell Lab Syst       Date:  2016-12-23       Impact factor: 3.491

6.  MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles.

Authors:  Hélène Ferry-Dumazet; Laurent Gil; Catherine Deborde; Annick Moing; Stéphane Bernillon; Dominique Rolin; Macha Nikolski; Antoine de Daruvar; Daniel Jacob
Journal:  BMC Plant Biol       Date:  2011-06-13       Impact factor: 4.215

7.  An inter-laboratory comparison demonstrates that [H]-NMR metabolite fingerprinting is a robust technique for collaborative plant metabolomic data collection.

Authors:  Jane L Ward; John M Baker; Sonia J Miller; Catherine Deborde; Mickael Maucourt; Benoit Biais; Dominique Rolin; Annick Moing; Sofia Moco; Jacques Vervoort; Arjen Lommen; Hartmut Schäfer; Eberhard Humpfer; Michael H Beale
Journal:  Metabolomics       Date:  2010-02-27       Impact factor: 4.290

Review 8.  Symbiodinium-invertebrate symbioses and the role of metabolomics.

Authors:  Benjamin R Gordon; William Leggat
Journal:  Mar Drugs       Date:  2010-09-30       Impact factor: 5.118

9.  Distinguishing Vaccinium species by chemical fingerprinting based on NMR spectra, validated with spectra collected in different laboratories.

Authors:  Michelle A Markus; Jonathan Ferrier; Sarah M Luchsinger; Jimmy Yuk; Alain Cuerrier; Michael J Balick; Joshua M Hicks; K Brian Killday; Christopher W Kirby; Fabrice Berrue; Russell G Kerr; Kevin Knagge; Tanja Gödecke; Benjamin E Ramirez; David C Lankin; Guido F Pauli; Ian Burton; Tobias K Karakach; John T Arnason; Kimberly L Colson
Journal:  Planta Med       Date:  2014-06-25       Impact factor: 3.352

10.  Integrating omic technologies into aquatic ecological risk assessment and environmental monitoring: hurdles, achievements, and future outlook.

Authors:  Graham Van Aggelen; Gerald T Ankley; William S Baldwin; Daniel W Bearden; William H Benson; J Kevin Chipman; Tim W Collette; John A Craft; Nancy D Denslow; Michael R Embry; Francesco Falciani; Stephen G George; Caren C Helbing; Paul F Hoekstra; Taisen Iguchi; Yoshi Kagami; Ioanna Katsiadaki; Peter Kille; Li Liu; Peter G Lord; Terry McIntyre; Anne O'Neill; Heather Osachoff; Ed J Perkins; Eduarda M Santos; Rachel C Skirrow; Jason R Snape; Charles R Tyler; Don Versteeg; Mark R Viant; David C Volz; Tim D Williams; Lorraine Yu
Journal:  Environ Health Perspect       Date:  2010-01       Impact factor: 9.031

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