Literature DB >> 17972325

Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary 13C labeling data.

Jochen Schaub1, Klaus Mauch, Matthias Reuss.   

Abstract

The novel concept of isotopic dynamic 13C metabolic flux analysis (ID-13C MFA) enables integrated analysis of isotopomer data from isotopic transient and/or isotopic stationary phase of a 13C labeling experiment, short-time experiments, and an extended range of applications of 13C MFA. In the presented work, an experimental and computational framework consisting of short-time 13C labeling, an integrated rapid sampling procedure, a LC-MS analytical method, numerical integration of the system of isotopomer differential equations, and estimation of metabolic fluxes was developed and applied to determine intracellular fluxes in glycolysis, pentose phosphate pathway (PPP), and citric acid cycle (TCA) in Escherichia coli grown in aerobic, glucose-limited chemostat culture at a dilution rate of D = 0.10 h(-1). Intracellular steady state concentrations were quantified for 12 metabolic intermediates. A total of 90 LC-MS mass isotopomers were quantified at sampling times t = 0, 91, 226, 346, 589 s and at isotopic stationary conditions. Isotopic stationarity was reached within 10 min in glycolytic and PPP metabolites. Consistent flux solutions were obtained by ID-13C MFA using isotopic dynamic and isotopic stationary 13C labeling data and by isotopic stationary 13C MFA (IS-13C MFA) using solely isotopic stationary data. It is demonstrated that integration of dynamic 13C labeling data increases the sensitivity of flux estimation, particularly at the glucose-6-phosphate branch point. The identified split ratio between glycolysis and PPP was 55%:44%. These results were confirmed by IS-13C MFA additionally using labeling data in proteinogenic amino acids (GC-MS) obtained after 5 h from sampled biomass.

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Year:  2008        PMID: 17972325     DOI: 10.1002/bit.21675

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  29 in total

Review 1.  Publishing 13C metabolic flux analysis studies: a review and future perspectives.

Authors:  Scott B Crown; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2013-09-08       Impact factor: 9.783

2.  (13)C-based metabolic flux analysis.

Authors:  Nicola Zamboni; Sarah-Maria Fendt; Martin Rühl; Uwe Sauer
Journal:  Nat Protoc       Date:  2009-05-21       Impact factor: 13.491

3.  Global transcription and metabolic flux analysis of Escherichia coli in glucose-limited fed-batch cultivations.

Authors:  K Lemuth; T Hardiman; S Winter; D Pfeiffer; M A Keller; S Lange; M Reuss; R D Schmid; M Siemann-Herzberg
Journal:  Appl Environ Microbiol       Date:  2008-09-19       Impact factor: 4.792

4.  Transient metabolic modeling of Escherichia coli MG1655 and MG1655 DeltaackA-pta, DeltapoxB Deltapppc ppc-p37 for recombinant beta-galactosidase production.

Authors:  Marjan De Mey; Gaspard J Lequeux; Joeri J Beauprez; Jo Maertens; Hendrik J Waegeman; Inge N Van Bogaert; Maria R Foulquié-Moreno; Daniel Charlier; Wim K Soetaert; Peter A Vanrolleghem; Erick J Vandamme
Journal:  J Ind Microbiol Biotechnol       Date:  2010-05-04       Impact factor: 3.346

5.  13C-flux analysis reveals NADPH-balancing transhydrogenation cycles in stationary phase of nitrogen-starving Bacillus subtilis.

Authors:  Martin Rühl; Dominique Le Coq; Stéphane Aymerich; Uwe Sauer
Journal:  J Biol Chem       Date:  2012-06-27       Impact factor: 5.157

6.  Isotopically nonstationary 13C flux analysis of Myc-induced metabolic reprogramming in B-cells.

Authors:  Taylor A Murphy; Chi V Dang; Jamey D Young
Journal:  Metab Eng       Date:  2012-08-08       Impact factor: 9.783

Review 7.  Recent advances in mapping environmental microbial metabolisms through 13C isotopic fingerprints.

Authors:  Joseph Kuo-Hsiang Tang; Le You; Robert E Blankenship; Yinjie J Tang
Journal:  J R Soc Interface       Date:  2012-08-15       Impact factor: 4.118

8.  Dynamic metabolic flux analysis demonstrated on cultures where the limiting substrate is changed from carbon to nitrogen and vice versa.

Authors:  Gaspard Lequeux; Joeri Beauprez; Jo Maertens; Ellen Van Horen; Wim Soetaert; Erick Vandamme; Peter A Vanrolleghem
Journal:  J Biomed Biotechnol       Date:  2010-08-23

9.  Optimization of cold methanol quenching for quantitative metabolomics of Penicillium chrysogenum.

Authors:  Lodewijk P de Jonge; Rutger D Douma; Joseph J Heijnen; Walter M van Gulik
Journal:  Metabolomics       Date:  2011-10-07       Impact factor: 4.290

Review 10.  Bidirectionality and compartmentation of metabolic fluxes are revealed in the dynamics of isotopomer networks.

Authors:  David W Schryer; Pearu Peterson; Toomas Paalme; Marko Vendelin
Journal:  Int J Mol Sci       Date:  2009-04-17       Impact factor: 6.208

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