4.5 Article

Control of the threonine-synthesis pathway in Escherichia coli:: a theoretical and experimental approach

Journal

BIOCHEMICAL JOURNAL
Volume 356, Issue -, Pages 433-444

Publisher

PORTLAND PRESS LTD
DOI: 10.1042/0264-6021:3560433

Keywords

amino acid; biosynthetic pathway modelling; computer simulation; metabolic control analysis; metabolic engineering

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A computer simulation of the threonine-synthesis pathway in Escherichia coli Tir-8 has been developed based on our previous measurements of the kinetics of the pathway enzymes under near-physiological conditions. The model successfully simulates the main features of the time courses of threonine synthesis previously observed in a cell-free extract without alteration of the experimentally determined parameters, although improved quantitative fits can be obtained with small parameter adjustments. At the concentrations of enzymes, precursors and products present in cells, the model predicts a threonine-synthesis flux close to that required to support cell growth. Furthermore, the first two enzymes operate close to equilibrium, providing an example of a near-equilibrium feedback-inhibited enzyme. The predicted flux control coefficients of the pathway enzymes under physiological conditions show that the control of flux is shared between the first three enzymes: aspartate kinase, aspartate semialdehyde dehydrogenase and homoserine dehydrogenase, with no single activity dominating the control. The response of the model to the external metabolites shows that the sharing of control between the three enzymes holds across a wide range of conditions, but that the pathway flux is sensitive to the aspartate concentration. When the model was embedded in a larger model to simulate the variable demands for threonine at different growth rates, it showed the accumulation of free threonine that is typical of the Tir-8 strain at low growth rates. At low growth rates, the control of threonine flux remains largely with the pathway enzymes. As an example of the predictive power of the model, we studied the consequences of over-expressing different enzymes in the pathway.

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