Literature DB >> 14730673

Process for the integrated extraction, identification and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks.

Wolfram Weckwerth1, Kathrin Wenzel, Oliver Fiehn.   

Abstract

A novel extraction protocol is described with which metabolites, proteins and RNA are sequentially extracted from the same sample, thereby providing a convenient procedure for the analysis of replicates as well as exploiting the inherent biological variation of independent samples for multivariate data analysis. A detection of 652 metabolites, 297 proteins and clear RNA bands in a single Arabidopsis thaliana leaf sample was validated by analysis with gas chromatography coupled to a time of flight mass spectrometer for metabolites, two-dimensional liquid chromatography coupled to mass spectrometry for proteins, and Northern blot analysis for RNA. A subset of the most abundant proteins and metabolites from replicate analysis of different Arabidopsis accessions was merged to form an integrative dataset allowing both classification of different genotypes and the unbiased analysis of the hierarchical organization of proteins and metabolites within a real biochemical network.

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Year:  2004        PMID: 14730673     DOI: 10.1002/pmic.200200500

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  126 in total

1.  Differential metabolic networks unravel the effects of silent plant phenotypes.

Authors:  Wolfram Weckwerth; Marcelo Ehlers Loureiro; Kathrin Wenzel; Oliver Fiehn
Journal:  Proc Natl Acad Sci U S A       Date:  2004-05-10       Impact factor: 11.205

2.  Association analysis of phenotypic and metabolomic changes in Arabidopsis accessions and their F1 hybrids affected by different photoperiod and sucrose supply.

Authors:  Quynh Thi Ngoc Le; Naoya Sugi; Jun Furukawa; Makoto Kobayashi; Kazuki Saito; Miyako Kusano; Hiroshi Shiba
Journal:  Plant Biotechnol (Tokyo)       Date:  2019-09-25       Impact factor: 1.133

Review 3.  Metabolomics and its role in understanding cellular responses in plants.

Authors:  Ritu Bhalla; Kothandaraman Narasimhan; Sanjay Swarup
Journal:  Plant Cell Rep       Date:  2005-11-16       Impact factor: 4.570

Review 4.  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

5.  Metabolomics and transcriptomics identify pathway differences between visceral and subcutaneous adipose tissue in colorectal cancer patients: the ColoCare study.

Authors:  David B Liesenfeld; Dmitry Grapov; Johannes F Fahrmann; Mariam Salou; Dominique Scherer; Reka Toth; Nina Habermann; Jürgen Böhm; Petra Schrotz-King; Biljana Gigic; Martin Schneider; Alexis Ulrich; Esther Herpel; Peter Schirmacher; Oliver Fiehn; Johanna W Lampe; Cornelia M Ulrich
Journal:  Am J Clin Nutr       Date:  2015-07-08       Impact factor: 7.045

6.  Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry.

Authors:  Oliver Fiehn
Journal:  Trends Analyt Chem       Date:  2008-03       Impact factor: 12.296

7.  The contribution of SERF1 to root-to-shoot signaling during salinity stress in rice.

Authors:  Romy Schmidt; Camila Caldana; Bernd Mueller-Roeber; Jos H M Schippers
Journal:  Plant Signal Behav       Date:  2014-01-21

8.  Pilot study investigating the ability of an herbal composite to alleviate clinical signs of respiratory dysfunction in horses with recurrent airway obstruction.

Authors:  Wendy Pearson; Armen Charch; Dyanne Brewer; Andrew F Clarke
Journal:  Can J Vet Res       Date:  2007-04       Impact factor: 1.310

9.  A prominent role for the CBF cold response pathway in configuring the low-temperature metabolome of Arabidopsis.

Authors:  Daniel Cook; Sarah Fowler; Oliver Fiehn; Michael F Thomashow
Journal:  Proc Natl Acad Sci U S A       Date:  2004-09-21       Impact factor: 11.205

10.  Ethanol production and maximum cell growth are highly correlated with membrane lipid composition during fermentation as determined by lipidomic analysis of 22 Saccharomyces cerevisiae strains.

Authors:  Clark M Henderson; Michelle Lozada-Contreras; Vladimir Jiranek; Marjorie L Longo; David E Block
Journal:  Appl Environ Microbiol       Date:  2012-10-12       Impact factor: 4.792

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