Literature DB >> 11744196

Full-scale model of glycolysis in Saccharomyces cerevisiae.

F Hynne1, S Danø, P G Sørensen.   

Abstract

We present a powerful, general method of fitting a model of a biochemical pathway to experimental substrate concentrations and dynamical properties measured at a stationary state, when the mechanism is largely known but kinetic parameters are lacking. Rate constants and maximum velocities are calculated from the experimental data by simple algebra without integration of kinetic equations. Using this direct approach, we fit a comprehensive model of glycolysis and glycolytic oscillations in intact yeast cells to data measured on a suspension of living cells of Saccharomyces cerevisiae near a Hopf bifurcation, and to a large set of stationary concentrations and other data estimated from comparable batch experiments. The resulting model agrees with almost all experimentally known stationary concentrations and metabolic fluxes, with the frequency of oscillation and with the majority of other experimentally known kinetic and dynamical variables. The functional forms of the rate equations have not been optimized.

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Year:  2001        PMID: 11744196     DOI: 10.1016/s0301-4622(01)00229-0

Source DB:  PubMed          Journal:  Biophys Chem        ISSN: 0301-4622            Impact factor:   2.352


  53 in total

1.  Cell population modelling of yeast glycolytic oscillations.

Authors:  Michael A Henson; Dirk Müller; Matthias Reuss
Journal:  Biochem J       Date:  2002-12-01       Impact factor: 3.857

2.  Modeling diauxic glycolytic oscillations in yeast.

Authors:  Bjørn Olav Hald; Preben G Sørensen
Journal:  Biophys J       Date:  2010-11-17       Impact factor: 4.033

Review 3.  Systems biology from micro-organisms to human metabolic diseases: the role of detailed kinetic models.

Authors:  Barbara M Bakker; Karen van Eunen; Jeroen A L Jeneson; Natal A W van Riel; Frank J Bruggeman; Bas Teusink
Journal:  Biochem Soc Trans       Date:  2010-10       Impact factor: 5.407

4.  Structural kinetic modeling of metabolic networks.

Authors:  Ralf Steuer; Thilo Gross; Joachim Selbig; Bernd Blasius
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-31       Impact factor: 11.205

5.  Elevated glucose concentrations promote receptor-independent activation of adherent human neutrophils: an experimental and computational approach.

Authors:  Ursula Kummer; Jürgen Zobeley; Jens Christian Brasen; Ryan Fahmy; Andrei L Kindzelskii; Aaron R Petty; Andrea J Clark; Howard R Petty
Journal:  Biophys J       Date:  2007-01-19       Impact factor: 4.033

6.  An equation-free approach to analyzing heterogeneous cell population dynamics.

Authors:  Katherine A Bold; Yu Zou; Ioannis G Kevrekidis; Michael A Henson
Journal:  J Math Biol       Date:  2007-04-11       Impact factor: 2.259

Review 7.  Towards the engineering of in vitro systems.

Authors:  Christoph Hold; Sven Panke
Journal:  J R Soc Interface       Date:  2009-05-27       Impact factor: 4.118

Review 8.  Rethinking glycolysis: on the biochemical logic of metabolic pathways.

Authors:  Arren Bar-Even; Avi Flamholz; Elad Noor; Ron Milo
Journal:  Nat Chem Biol       Date:  2012-05-17       Impact factor: 15.040

9.  Approaches to biosimulation of cellular processes.

Authors:  F J Bruggeman; H V Westerhoff
Journal:  J Biol Phys       Date:  2006-11-11       Impact factor: 1.365

10.  TIde: a software for the systematic scanning of drug targets in kinetic network models.

Authors:  Marvin Schulz; Barbara M Bakker; Edda Klipp
Journal:  BMC Bioinformatics       Date:  2009-10-19       Impact factor: 3.169

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