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Metabolic engineering--integrating methodologies of molecular breeding and bioprocess systems engineering
Authors:Shimizu Hiroshi
Affiliation:Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan. shimizu@bio.eng.osaka-u.ac.jp
Abstract:Metabolic engineering is an integrating methodology of analysis and synthesis for the improvement of flux distribution of metabolic pathways in complicated bioprocesses, which are highly multi-hierarchical systems to extend from macroscopic to microscopic levels. Recent progress in metabolic engineering methodologies to improve metabolic pathways in microorganisms was reviewed with many studies in this paper. Metabolic flux distribution was analyzed under different environmental conditions, using a metabolic reaction model. The physiological states of microorganisms were understood by interpreting metabolic flux analysis (MFA). This analysis was also used for development of process operation and control strategy. Cell capability to form a targeted product was analyzed with a metabolic reaction model and linear programming (LP). The use of a 13C-enriched carbon source and nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GCMS) analyses of intracellular and extracellular metabolites enabled determination of a metabolic flux distribution more accurately than the flux distribution determined only by the metabolic reaction model, which involves not only metabolite balances but also energy and redox balances. The comparison of metabolic flux distributions between before and after genetic modification of cells yielded information on the mechanism of regulation of metabolic flux in microorganisms. Finally, integration of bioinformatics and metabolic engineering is discussed, and cyclic modification of the complex bionetwork and process development were emphasized.
Keywords:metabolic flux distribution analysis (MFA)  metabolic control analysis (MCA)  on-line state recognition and process operation  13C-NMR  bioinformatics
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