title: Metabolic flux analysis of Escherichia coli K12 grown on 13C-labeled acetate and glucose using GC-MS and powerful flux calculation method.
abstract: A new algorithm was developed for the estimation of the metabolic flux distribution based on GC-MS data of proteinogenic amino acids. By using a sensitive GC-MS protocol as well as by combining the global search algorithm such as the genetic algorithm with the local search algorithm such as the Levenberg-Marquardt algorithm, not only the distribution of the net fluxes in the entire network, but also certain exchange fluxes which contribute significantly to the isotopomer distribution could be quantified. This mass isotopomer analysis could identify the biochemical changes involved in the regulation where acetate or glucose was used as a main carbon source. The metabolic flux analysis clearly revealed that when the specific growth rate increased, only a slight change in flux distribution was observed for acetate metabolism, indicating that subtle regulation mechanism exists in certain key junctions of this network system. Different from acetate metabolism, when glucose was used as a carbon source, as the growth rate increased, a significant increase in relative pentose phosphate pathway (PPP) flux was observed for Escherichia coli K12 at the expense of the citric acid cycle, suggesting that when growing on glucose, the flux catalyzed by isocitrate dehydrogenase could not fully fulfill the NADPH demand for cell growth, causing the oxidative PPP to be utilized to a larger extent so as to complement the NADPH demand. The GC-MS protocol as well as the new algorithm demonstrated here proved to be a powerful tool for characterizing metabolic regulation and can be utilized for strain improvement and bioprocess optimization.
authors.affiliation: Institute for Advanced Biosciences, Keio University, Yamagata 997-0017, Japan.
authors.forename: Jiao
authors.initials: J
authors.lastname: Zhao
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Shimizu
mesh_terms: D000085:Acetates / Q000378:metabolism*; D000465:Algorithms; D002244:Carbon / Q000378:metabolism; D002247:Carbon Isotopes; D002478:Cells, Cultured; D003198:Computer Simulation; D004734:Energy Metabolism / Q000502:physiology; D004926:Escherichia coli / Q000145:classification / Q000378:metabolism*; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D005947:Glucose / Q000378:metabolism*; D007553:Isotope Labeling / Q000379:methods; D008954:Models, Biological; D009097:Multienzyme Complexes / Q000378:metabolism; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013045:Species Specificity
chemical_list: D000085:Acetates; D002247:Carbon Isotopes; D009097:Multienzyme Complexes; D002244:Carbon; D005947:Glucose