Literature DB >> 17526563

The thermodynamic meaning of metabolic exchange fluxes.

Wolfgang Wiechert1.   

Abstract

Metabolic flux analysis (MFA) deals with the experimental determination of steady-state fluxes in metabolic networks. An important feature of the (13)C MFA method is its capability to generate information on both directions of bidirectional reaction steps given by exchange fluxes. The biological interpretation of these exchange fluxes and their relation to thermodynamic properties of the respective reaction steps has never been systematically investigated. As a central result, it is shown here that for a general class of enzyme reaction mechanisms the quotients of net and exchange fluxes measured by (13)C MFA are coupled to Gibbs energies of the reaction steps. To establish this relation the concept of apparent flux ratios of enzymatic isotope-labeling networks is introduced and some computing rules for these flux ratios are given. Application of these rules reveals a conceptional pitfall of (13)C MFA, which is the inherent dependency of measured exchange fluxes on the chosen tracer atom. However, it is shown that this effect can be neglected for typical biochemical reaction steps under physiological conditions. In this situation, the central result can be formulated as a two-sided inequality relating fluxes, pool sizes, and standard Gibbs energies. This relation has far-reaching consequences for metabolic flux analysis, quantitative metabolomics, and network thermodynamics.

Mesh:

Substances:

Year:  2007        PMID: 17526563      PMCID: PMC1959540          DOI: 10.1529/biophysj.106.099895

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  34 in total

1.  Possible pitfalls of flux calculations based on (13)C-labeling.

Authors:  W van Winden; P Verheijen; S Heijnen
Journal:  Metab Eng       Date:  2001-04       Impact factor: 9.783

Review 2.  13C metabolic flux analysis.

Authors:  W Wiechert
Journal:  Metab Eng       Date:  2001-07       Impact factor: 9.783

3.  Metabolic isotopomer labeling systems. Part I: global dynamic behavior.

Authors:  W Wiechert; M Wurzel
Journal:  Math Biosci       Date:  2001-02       Impact factor: 2.144

Review 4.  Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era.

Authors:  C H Schilling; S Schuster; B O Palsson; R Heinrich
Journal:  Biotechnol Prog       Date:  1999 May-Jun

5.  Advances in flux balance analysis.

Authors:  Kenneth J Kauffman; Purusharth Prakash; Jeremy S Edwards
Journal:  Curr Opin Biotechnol       Date:  2003-10       Impact factor: 9.740

6.  Elementary metabolite units (EMU): a novel framework for modeling isotopic distributions.

Authors:  Maciek R Antoniewicz; Joanne K Kelleher; Gregory Stephanopoulos
Journal:  Metab Eng       Date:  2006-09-17       Impact factor: 9.783

7.  High-throughput metabolic flux analysis based on gas chromatography-mass spectrometry derived 13C constraints.

Authors:  Eliane Fischer; Nicola Zamboni; Uwe Sauer
Journal:  Anal Biochem       Date:  2004-02-15       Impact factor: 3.365

8.  Metabolic flux distributions in Corynebacterium glutamicum during growth and lysine overproduction.

Authors:  J J Vallino; G Stephanopoulos
Journal:  Biotechnol Bioeng       Date:  1993-03-15       Impact factor: 4.530

Review 9.  Metabolic networks in motion: 13C-based flux analysis.

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

10.  Relationship between thermodynamic driving force and one-way fluxes in reversible processes.

Authors:  Daniel A Beard; Hong Qian
Journal:  PLoS One       Date:  2007-01-03       Impact factor: 3.240

View more
  9 in total

1.  Thermodynamic calculations for biochemical transport and reaction processes in metabolic networks.

Authors:  Stefan J Jol; Anne Kümmel; Vassily Hatzimanikatis; Daniel A Beard; Matthias Heinemann
Journal:  Biophys J       Date:  2010-11-17       Impact factor: 4.033

2.  Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.

Authors:  R M T Fleming; I Thiele; G Provan; H P Nasheuer
Journal:  J Theor Biol       Date:  2010-03-15       Impact factor: 2.691

3.  Metabolic fluxes during strong carbon catabolite repression by malate in Bacillus subtilis.

Authors:  Roelco J Kleijn; Joerg M Buescher; Ludovic Le Chat; Matthieu Jules; Stephane Aymerich; Uwe Sauer
Journal:  J Biol Chem       Date:  2009-11-16       Impact factor: 5.157

4.  Cytosolic Aspartate Availability Determines Cell Survival When Glutamine Is Limiting.

Authors:  H Furkan Alkan; Katharina E Walter; Alba Luengo; Corina T Madreiter-Sokolowski; Sarah Stryeck; Allison N Lau; Wael Al-Zoughbi; Caroline A Lewis; Craig J Thomas; Gerald Hoefler; Wolfgang F Graier; Tobias Madl; Matthew G Vander Heiden; Juliane G Bogner-Strauss
Journal:  Cell Metab       Date:  2018-08-16       Impact factor: 31.373

5.  Fluxome study of Pseudomonas fluorescens reveals major reorganisation of carbon flux through central metabolic pathways in response to inactivation of the anti-sigma factor MucA.

Authors:  Stina K Lien; Sebastian Niedenführ; Håvard Sletta; Katharina Nöh; Per Bruheim
Journal:  BMC Syst Biol       Date:  2015-02-18

6.  Pool size measurements facilitate the determination of fluxes at branching points in non-stationary metabolic flux analysis: the case of Arabidopsis thaliana.

Authors:  Robert Heise; Alisdair R Fernie; Mark Stitt; Zoran Nikoloski
Journal:  Front Plant Sci       Date:  2015-06-02       Impact factor: 5.753

7.  Metabolite concentrations, fluxes and free energies imply efficient enzyme usage.

Authors:  Junyoung O Park; Sara A Rubin; Yi-Fan Xu; Daniel Amador-Noguez; Jing Fan; Tomer Shlomi; Joshua D Rabinowitz
Journal:  Nat Chem Biol       Date:  2016-05-02       Impact factor: 15.040

8.  The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis.

Authors:  Martin Beyß; Salah Azzouzi; Michael Weitzel; Wolfgang Wiechert; Katharina Nöh
Journal:  Front Microbiol       Date:  2019-05-24       Impact factor: 5.640

9.  Sulfate-dependent reversibility of intracellular reactions explains the opposing isotope effects in the anaerobic oxidation of methane.

Authors:  Gunter Wegener; Jonathan Gropp; Heidi Taubner; Itay Halevy; Marcus Elvert
Journal:  Sci Adv       Date:  2021-05-05       Impact factor: 14.136

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.