Literature DB >> 18714301

Kinetic flux profiling for quantitation of cellular metabolic fluxes.

Jie Yuan1, Bryson D Bennett, Joshua D Rabinowitz.   

Abstract

This protocol enables quantitation of metabolic fluxes in cultured cells. Measurements are based on the kinetics of cellular incorporation of stable isotope from nutrient into downstream metabolites. At multiple time points, after cells are rapidly switched from unlabeled to isotope-labeled nutrient, metabolism is quenched, metabolites are extracted and the extract is analyzed by chromatography-mass spectrometry. Resulting plots of unlabeled compound versus time follow variants of exponential decay, with the flux equal to the decay rate multiplied by the intracellular metabolite concentration. Because labeling is typically fast (t(1/2)<or=5 min for central metabolites in Escherichia coli), variations on this approach can effectively probe dynamically changing metabolic fluxes. This protocol is exemplified using E. coli and nitrogen labeling, for which quantitative flux data for approximately 15 metabolites can be obtained over 3 d of work. Applications to adherent mammalian cells are also discussed.

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Year:  2008        PMID: 18714301      PMCID: PMC2710581          DOI: 10.1038/nprot.2008.131

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  41 in total

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Authors:  Jochen Schaub; Carola Schiesling; Matthias Reuss; Michael Dauner
Journal:  Biotechnol Prog       Date:  2006 Sep-Oct

Review 2.  Absolute quantification of phosphorus metabolite concentrations in human muscle in vivo by 31P MRS: a quantitative review.

Authors:  Graham J Kemp; Martin Meyerspeer; Ewald Moser
Journal:  NMR Biomed       Date:  2007-10       Impact factor: 4.044

3.  Absolute quantitation of intracellular metabolite concentrations by an isotope ratio-based approach.

Authors:  Bryson D Bennett; Jie Yuan; Elizabeth H Kimball; Joshua D Rabinowitz
Journal:  Nat Protoc       Date:  2008       Impact factor: 13.491

4.  Kinetic flux profiling of nitrogen assimilation in Escherichia coli.

Authors:  Jie Yuan; William U Fowler; Elizabeth Kimball; Wenyun Lu; Joshua D Rabinowitz
Journal:  Nat Chem Biol       Date:  2006-08-27       Impact factor: 15.040

5.  Identifying decomposition products in extracts of cellular metabolites.

Authors:  Elizabeth Kimball; Joshua D Rabinowitz
Journal:  Anal Biochem       Date:  2006-08-14       Impact factor: 3.365

6.  In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data.

Authors:  J S Edwards; R U Ibarra; B O Palsson
Journal:  Nat Biotechnol       Date:  2001-02       Impact factor: 54.908

7.  Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS.

Authors:  Eliane Fischer; Uwe Sauer
Journal:  Eur J Biochem       Date:  2003-03

Review 8.  Nitrogen assimilation and global regulation in Escherichia coli.

Authors:  Larry Reitzer
Journal:  Annu Rev Microbiol       Date:  2003-05-01       Impact factor: 15.500

9.  Quantitative analysis of intermediary metabolism in rat hepatocytes incubated in the presence and absence of ethanol with a substrate mixture including ketoleucine.

Authors:  J M Baranyai; J J Blum
Journal:  Biochem J       Date:  1989-02-15       Impact factor: 3.857

Review 10.  Metabolic networks in motion: 13C-based flux analysis.

Authors:  Uwe Sauer
Journal:  Mol Syst Biol       Date:  2006-11-14       Impact factor: 11.429

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  109 in total

1.  Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation.

Authors:  Fangfang Ma; Lara J Jazmin; Jamey D Young; Doug K Allen
Journal:  Proc Natl Acad Sci U S A       Date:  2014-11-03       Impact factor: 11.205

Review 2.  Stable isotope-resolved metabolomics and applications for drug development.

Authors:  Teresa W-M Fan; Pawel K Lorkiewicz; Katherine Sellers; Hunter N B Moseley; Richard M Higashi; Andrew N Lane
Journal:  Pharmacol Ther       Date:  2011-12-23       Impact factor: 12.310

3.  Metabolomic analysis via reversed-phase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer.

Authors:  Wenyun Lu; Michelle F Clasquin; Eugene Melamud; Daniel Amador-Noguez; Amy A Caudy; Joshua D Rabinowitz
Journal:  Anal Chem       Date:  2010-04-15       Impact factor: 6.986

4.  Inference and Prediction of Metabolic Network Fluxes.

Authors:  Zoran Nikoloski; Richard Perez-Storey; Lee J Sweetlove
Journal:  Plant Physiol       Date:  2015-09-21       Impact factor: 8.340

5.  Liquid chromatography-high resolution mass spectrometry analysis of fatty acid metabolism.

Authors:  Jurre J Kamphorst; Jing Fan; Wenyun Lu; Eileen White; Joshua D Rabinowitz
Journal:  Anal Chem       Date:  2011-11-04       Impact factor: 6.986

6.  Human kinome profiling identifies a requirement for AMP-activated protein kinase during human cytomegalovirus infection.

Authors:  Laura J Terry; Livia Vastag; Joshua D Rabinowitz; Thomas Shenk
Journal:  Proc Natl Acad Sci U S A       Date:  2012-02-06       Impact factor: 11.205

7.  Quantitation of cellular metabolic fluxes of methionine.

Authors:  Tomer Shlomi; Jing Fan; Baiqing Tang; Warren D Kruger; Joshua D Rabinowitz
Journal:  Anal Chem       Date:  2014-01-16       Impact factor: 6.986

8.  Metabolomic profiling of the heart during acute ischemic preconditioning reveals a role for SIRT1 in rapid cardioprotective metabolic adaptation.

Authors:  Sergiy M Nadtochiy; William Urciuoli; Jimmy Zhang; Xenia Schafer; Joshua Munger; Paul S Brookes
Journal:  J Mol Cell Cardiol       Date:  2015-09-24       Impact factor: 5.000

Review 9.  Understanding metabolism with flux analysis: From theory to application.

Authors:  Ziwei Dai; Jason W Locasale
Journal:  Metab Eng       Date:  2016-09-22       Impact factor: 9.783

Review 10.  After the feature presentation: technologies bridging untargeted metabolomics and biology.

Authors:  Kevin Cho; Nathaniel G Mahieu; Stephen L Johnson; Gary J Patti
Journal:  Curr Opin Biotechnol       Date:  2014-05-06       Impact factor: 9.740

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