Literature DB >> 19519139

Noise-induced breakdown of the Michaelis-Menten equation in steady-state conditions.

R Grima1.   

Abstract

The Michaelis-Menten (MM) equation is the basic equation of enzyme kinetics; it is also a basic building block of many models of biological systems. We build a stochastic and microscopic model of enzyme kinetics inside a small subcellular compartment. Using both theory and simulations, we show that intrinsic noise induces a breakdown of the MM equation even if steady-state metabolic conditions are enforced. In particular, we show that (i) given a reaction velocity, deterministic rate equations can severely underestimate steady-state intracellular substrate concentrations and (ii) different reaction schemes which on a macroscopic level are indistinguishable because they are described by the same MM equation obey distinctly different equations in subcellular compartments.

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Year:  2009        PMID: 19519139     DOI: 10.1103/PhysRevLett.102.218103

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  15 in total

1.  Discreteness-induced concentration inversion in mesoscopic chemical systems.

Authors:  Rajesh Ramaswamy; Nélido González-Segredo; Ivo F Sbalzarini; Ramon Grima
Journal:  Nat Commun       Date:  2012-04-10       Impact factor: 14.919

2.  Note: Parameter-independent bounding of the stochastic Michaelis-Menten steady-state intrinsic noise variance.

Authors:  L A Widmer; J Stelling; F J Doyle
Journal:  J Chem Phys       Date:  2013-10-28       Impact factor: 3.488

3.  Accuracy of the Michaelis-Menten approximation when analysing effects of molecular noise.

Authors:  Michael J Lawson; Linda Petzold; Andreas Hellander
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

4.  GillesPy: A Python Package for Stochastic Model Building and Simulation.

Authors:  John H Abel; Brian Drawert; Andreas Hellander; Linda R Petzold
Journal:  IEEE Life Sci Lett       Date:  2016-09

5.  Modeling and simulation of biological systems from image data.

Authors:  Ivo F Sbalzarini
Journal:  Bioessays       Date:  2013-03-27       Impact factor: 4.345

6.  Noise-induced modulation of the relaxation kinetics around a non-equilibrium steady state of non-linear chemical reaction networks.

Authors:  Rajesh Ramaswamy; Ivo F Sbalzarini; Nélido González-Segredo
Journal:  PLoS One       Date:  2011-01-28       Impact factor: 3.240

7.  Intrinsic noise alters the frequency spectrum of mesoscopic oscillatory chemical reaction systems.

Authors:  Rajesh Ramaswamy; Ivo F Sbalzarini
Journal:  Sci Rep       Date:  2011-11-11       Impact factor: 4.379

8.  Intrinsic noise analyzer: a software package for the exploration of stochastic biochemical kinetics using the system size expansion.

Authors:  Philipp Thomas; Hannes Matuschek; Ramon Grima
Journal:  PLoS One       Date:  2012-06-12       Impact factor: 3.240

9.  Investigating the robustness of the classical enzyme kinetic equations in small intracellular compartments.

Authors:  Ramon Grima
Journal:  BMC Syst Biol       Date:  2009-10-08

10.  The slow-scale linear noise approximation: an accurate, reduced stochastic description of biochemical networks under timescale separation conditions.

Authors:  Philipp Thomas; Arthur V Straube; Ramon Grima
Journal:  BMC Syst Biol       Date:  2012-05-14
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