title: An improved kinetic model for the acetone-butanol-ethanol pathway of Clostridium acetobutylicum and model-based perturbation analysis.
abstract: BACKGROUND
  Comprehensive kinetic models of microbial metabolism can enhance the understanding of system dynamics and regulatory mechanisms, which is helpful in optimizing microbial production of industrial chemicals. Clostridium acetobutylicum produces solvents (acetone-butanol-ethanol, ABE) through the ABE pathway. To systematically assess the potential of increased production of solvents, kinetic modeling has been applied to analyze the dynamics of this pathway and make predictive simulations. Up to date, only one kinetic model for C. acetobutylicum supported by experiment has been reported as far as we know. But this model did not integrate the metabolic regulatory effects of transcriptional control and other complex factors. It also left out the information of some key intermediates (e.g. butyryl-phosphate).
  
  
  RESULTS
  We have developed an improved kinetic model featured with the incorporation of butyryl-phosphate, inclusion of net effects of complex metabolic regulations, and quantification of endogenous enzyme activity variations caused by these regulations. The simulation results of our model are more consistent with published experimental data than the previous model, especially in terms of reflecting the kinetics of butyryl-phosphate and butyrate. Through parameter perturbation analysis, it was found that butyrate kinase has large and positive influence on butanol production while CoA transferase has negative effect on butanol production, suggesting that butyrate kinase has more efficiency in converting butyrate to butanol than CoA transferase.
  
  
  CONCLUSIONS
  Our improved kinetic model of the ABE process has more capacity in approaching real circumstances, providing much more insight in the regulatory mechanisms and potential key points for optimization of solvent productions. Moreover, the modeling strategy can be extended to other biological processes.
authors.affiliation: Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
authors.forename: Ru-Dong
authors.initials: RD
authors.lastname: Li
authors.forename: Yuan-Yuan
authors.initials: YY
authors.lastname: Li
authors.forename: Ling-Yi
authors.initials: LY
authors.lastname: Lu
authors.forename: Cong
authors.initials: C
authors.lastname: Ren
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
authors.forename: Lei
authors.initials: L
authors.lastname: Liu
mesh_terms: D000096:Acetone / Q000378:metabolism*; D000440:Butanols / Q000378:metabolism*; D046969:Clostridium acetobutylicum / Q000235:genetics / Q000378:metabolism*; D000431:Ethanol / Q000378:metabolism*; D005818:Genetic Engineering; D007700:Kinetics; D008954:Models, Biological; D012997:Solvents / Q000378:metabolism
chemical_list: D000440:Butanols; D012997:Solvents; D000096:Acetone; D000431:Ethanol