In silico Derivation of a Reduced Kinetic Model for Stationary or Oscillating Glycolysis in Escherichia coli Bacterium

G. Maria

Abstract
Modelling bacteria glycolysis is a classical subject but still of high interest. Glycolysis, together with the phosphotransferase (PTS)-system for glucose transport into the cell, the pentose-phosphate pathway (PPP), and tricarboxylic acid cycle (TCA) characterize the central carbon metabolism. Such a model usually serves as the foundation for developing modular simulation platforms used for consistent analysis of the control regulation of target metabolite synthesis. The present study is focused on analyzing the advantage and limitations of using a simplified but versatile ‘core’ model of mTRM) of glycolysis when incomplete experimental information is available. Exemplification is made for a reduced glycolysis model from literature for Escherichia coli cells, by performing a few modifications (17 identifiable parameters) to increase its agreement with simulated data generated by using an extended model (127 parameters) over a large operating domain of an experimental bioreactor. With the expense of ca. 8–13 % increase in the relative model error vs. extended simulation models, derivation of reduced kinetic structures to describe some parts of the core metabolism is worth the associated identification effort, due to the considerable reduction in model parameterization (e.g. 17 parameters in mTRM vs. 127 in the extendedChassM model of Chassagnole et al.), while preserving a fair adequacy over a wide experimental domain generated in-silico by using the valuable extended ChassM. The reduced model flexibility is tested by reproducing stationary or oscillatory glycolysis conditions. The reduced mTRM model includes enough information to reproduce not only the cell energy-related potential through the total A(MDT)P level, but also the role played by ATP/ADP ratio as a glycolysis driving force. The model can also reproduce the oscillatory behaviour occurrence conditions, as well as situations when homeostatic conditions are not fulfilled.

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Keywords
dynamic model, glycolysis, Escherichia coli, reduced model identification, oscillations