Stoichiometric model of Escherichia coli metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements.

Research paper by J J Pramanik, J D JD Keasling

Indexed on: 22 Jul '08Published on: 22 Jul '08Published in: Biotechnology and Bioengineering


A stoichiometric model of metabolism was developed to describe the balance of metabolic reactions during steady-state growth of Escherichia coli on glucose (or metabolic intermediates) and mineral salts. The model incorporates 153 reversible and 147 irreversible reactions and 289 metabolites from several metabolic data bases for the biosynthesis of the macromolecular precursors, coenzymes, and prosthetic groups necessary for synthesis of all cellular macromolecules. Correlations describing how the cellular composition changes with growth rate were developed from experimental data and were used to calculate the drain of precursors to macromolecules, coenzymes, and prosthetic groups from the metabolic network for the synthesis of those macromolecules at a specific growth rate. Energy requirements for macromolecular polymerization and proofreading, transport of metabolites, and maintenance of transmembrane gradients were included in the model rather than a lumped maintenance energy term. The underdetermined set of equations was solved using the Simplex algorithm, employing realistic objective functions and constraints; the drain of precursors, coenzymes, and prosthetic groups and the energy requirements for the synthesis of macromolecules served as the primary set of constraints. The model accurately predicted experimentally determined metabolic fluxes for aerobic growth on acetate or acetate plus glucose. In addition, the model predicted the genetic and metabolic regulation that must occur for growth under different conditions, such as the opening of the glyoxylate shunt during growth on acetate and the branching of the tricarboxylic acid cycle under anaerobic growth. Sensitivity analyses were performed to determine the flexibility of pathways and the effects of different rates and growth conditions on the distribution of fluxes. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 56: 398-421, 1997.