Estimation of metabolic fluxes, expression levels and metabolite dynamics of a secondary metabolic pathway in potato using label pulse-feeding experiments combined with kinetic network modelling and simulation.
In this paper we present a method that allows dynamic flux analysis without a priori kinetic knowledge. This method was developed and validated using the pulse-feeding experimental data obtained in our previous study (Matsuda et al., 2005), in which incorporation of exogenously applied l-phenylalanine-d(5) into seven phenylpropanoid metabolites in potato tubers was determined. After identification of the topology of the metabolic network of these biosynthetic pathways, the system was described by dynamic mass balances in combination with power-law kinetics. After the first simulations, some reactions were removed from the network because they were not contributing significantly to network behaviour. As a next step, the exponents of the power-law kinetics were identified and then kept at fixed values during further analysis. The model was tested for statistical reliability using Monte Carlo simulations. Most fluxes could be identified with high accuracy. The two test cases, control and after elicitation, were clearly distinguished, and with elicitation fluxes to N-p-coumaroyloctopamine (pCO) and N-p-coumaroyltyramine (pCT) increased significantly, whereas those for chlorogenic acid (CGA) and p-coumaroylshikimate decreased significantly. According to the model, increases in the first two fluxes were caused by induction/derepression mechanisms. The decreases in the latter two fluxes were caused by decreased concentrations of their substrates, which in turn were caused by increased activity of the pCO- and pCT-producing enzymes. Flux-control analysis showed that, in most cases, flux control was changed after application of elicitor. Thus the results revealed potential targets for improving actions against tissue wounding and pathogen attack.
Heinzle
Elmar
E
Biochemical Engineering Institute, Saarland University, D-66123 Saarbrücken, Germany. e.heinzle@mx.uni-saarland.de
Matsuda
Fumio
F
Miyagawa
Hisashi
H
Wakasa
Kyo
K
Nishioka
Takaaki
T
D000465:Algorithms; D003198:Computer Simulation; D007700:Kinetics; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D008962:Models, Theoretical; D011198:Solanum tuberosum / Q000378:metabolism*