African Journal of
Biotechnology

  • Abbreviation: Afr. J. Biotechnol.
  • Language: English
  • ISSN: 1684-5315
  • DOI: 10.5897/AJB
  • Start Year: 2002
  • Published Articles: 12481

Full Length Research Paper

Metabolic flux distribution and mathematical models for dynamic simulation of carbon metabolism in Escherichia coli

Md. Aminul Hoque1,4,5,*,  Kotb Attia2, Omar Alattas3 and Amir Feisal Merican1  
  1Centre of Research in Computational Sciences and Informaticsin Biology, Biodiversity, Environment, Agriculture and Healthcare (CRYSTAL), Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur-50603, Malaysia. 2Graduate School of Science and Technology, Niigata University, Ikarashi-2, Niigata, Japan. 3Centre of Excellence in Biotechnology Research, King Saud University, Riyadh 11451, Kingdom of Saudi Arabia. 4Graduate School of Medicine, Niigata University, Asahimachi 1-754, Niigata, Japan. 5Department of Statistics, Rashahi University, Rajshahi-6205, Bangladesh.
Email: [email protected]

  •  Accepted: 14 September 2009
  •  Published: 21 March 2011

Abstract

 

A simple model was build for the metabolic flux determination based on published articles. A method for metabolic flux determination by carbon labeling experiments was described and developed here in the first part of this study that allows mathematical description relating the measured quantities and the intracellular fluxes. The described method was used to investigate the central carbon metabolism of Escherichia coli. In the second part of this study, computer simulation was made to study the dynamics of the intracellular metabolite concentrations in E. coli in particular for the glycolysis and pentose-phosphate pathway based on the kinetic rate equations. The model successfully simulates the main features of the time course without alteration of the experimentally determined parameters. After simulation starts, the intracellular concentrations of ATP, PEP, PYR, G6P, F6P, NAD and 3PG decreased while FDP, 6PG, S7P, E4P AMP, GAP, ADP, NADH and NADPH increased for wild E. coli. These simulation results were also partly verified by experimental results.

 

Key words: Metabolic flux, metabolite concentration, computer simulation, optimization technique, parameters.