Literature DB >> 15265734

Design of experiments: an efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry.

Jonas Gullberg1, Pär Jonsson, Anders Nordström, Michael Sjöström, Thomas Moritz.   

Abstract

The usual aim in metabolomic studies is to quantify the entire metabolome of each of a series of biological samples. To do this for complex biological matrices, e.g., plant tissues, efficient and reproducible extraction protocols must be developed. However, derivatization protocols must also be developed if GC/MS (one of the mostly widely used analytical methods for metabolomics) is involved. The aim of this study was to investigate how different chemical and physical factors (extraction solvent, derivatization reagents, and temperature) affect the extraction and derivatization of the metabolome from leaves of the plant Arabidopsis thaliana. Using design of experiment procedures, variation was systematically introduced, and the effects of this variation were analyzed using regression models. The results show that this approach allows a reliable protocol for metabolomic analysis of Arabidopsis to be determined with a relatively limited number of experiments. Following two different investigations an extraction and derivatization protocol was chosen. Further, the reproducibility of the analysis of 66 endogenous compounds was investigated, and it was shown that both hydrophilic and lipophilic compounds were detected with high reproducibility.

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Year:  2004        PMID: 15265734     DOI: 10.1016/j.ab.2004.04.037

Source DB:  PubMed          Journal:  Anal Biochem        ISSN: 0003-2697            Impact factor:   3.365


  98 in total

1.  A metabolomics based test of independent action and concentration addition using the earthworm Lumbricus rubellus.

Authors:  A J Baylay; D J Spurgeon; C Svendsen; J L Griffin; Suresh C Swain; Stephen R Sturzenbaum; O A H Jones
Journal:  Ecotoxicology       Date:  2012-04-04       Impact factor: 2.823

2.  Pair-wise multicomparison and OPLS analyses of cold-acclimation phases in Siberian spruce.

Authors:  Liudmila Shiryaeva; Henrik Antti; Wolfgang P Schröder; Richard Strimbeck; Anton S Shiriaev
Journal:  Metabolomics       Date:  2011-04-11       Impact factor: 4.290

Review 3.  Mass spectrometry-based metabolomics.

Authors:  Katja Dettmer; Pavel A Aronov; Bruce D Hammock
Journal:  Mass Spectrom Rev       Date:  2007 Jan-Feb       Impact factor: 10.946

Review 4.  The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

Authors:  Julian L Griffin
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-01-29       Impact factor: 6.237

5.  Metabolomic evaluation of pulsed electric field-induced stress on potato tissue.

Authors:  Federico Gómez Galindo; Petr Dejmek; Krister Lundgren; Allan G Rasmusson; António Vicente; Thomas Moritz
Journal:  Planta       Date:  2009-06-04       Impact factor: 4.116

Review 6.  Metabolomics: moving to the clinic.

Authors:  Anders Nordström; Rolf Lewensohn
Journal:  J Neuroimmune Pharmacol       Date:  2009-04-28       Impact factor: 4.147

7.  Evaluation of normalization methods to pave the way towards large-scale LC-MS-based metabolomics profiling experiments.

Authors:  Bedilu Alamirie Ejigu; Dirk Valkenborg; Geert Baggerman; Manu Vanaerschot; Erwin Witters; Jean-Claude Dujardin; Tomasz Burzykowski; Maya Berg
Journal:  OMICS       Date:  2013-06-29

8.  PECTIN ACETYLESTERASE9 Affects the Transcriptome and Metabolome and Delays Aphid Feeding.

Authors:  Karen J Kloth; Ilka N Abreu; Nicolas Delhomme; Ivan Petřík; Cloé Villard; Cecilia Ström; Fariba Amini; Ondřej Novák; Thomas Moritz; Benedicte R Albrectsen
Journal:  Plant Physiol       Date:  2019-09-24       Impact factor: 8.340

Review 9.  Metabolic networks: how to identify key components in the regulation of metabolism and growth.

Authors:  Mark Stitt; Ronan Sulpice; Joost Keurentjes
Journal:  Plant Physiol       Date:  2009-12-11       Impact factor: 8.340

10.  Metabolic phenotyping of a model of adipocyte differentiation.

Authors:  Lee D Roberts; Sam Virtue; Antonio Vidal-Puig; Andrew W Nicholls; Julian L Griffin
Journal:  Physiol Genomics       Date:  2009-07-14       Impact factor: 3.107

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