Abstract
The efficient redesign of bacteria for biotechnological purposes, such as biofuel production, waste disposal or specific biocatalytic functions, requires a quantitative systems-level understanding of energy supply, carbon, and redox metabolism. The measurement of transcript levels, metabolite concentrations and metabolic fluxes per se gives an incomplete picture. An appreciation of the interdependencies between the different measurement values is essential for systems-level understanding. Mathematical modeling has the potential to provide a coherent and quantitative description of the interplay between gene expression, metabolite concentrations, and metabolic fluxes. Escherichia coli undergoes major adaptations in central metabolism when the availability of oxygen changes. Thus, an integrated description of the oxygen response provides a benchmark of our understanding of carbon, energy, and redox metabolism. We present the first comprehensive model of the central metabolism of E. coli that describes steady-state metabolism at different levels of oxygen availability. Variables of the model are metabolite concentrations, gene expression levels, transcription factor activities, metabolic fluxes, and biomass concentration. We analyze the model with respect to the production capabilities of central metabolism of E. coli. In particular, we predict how precursor and biomass concentration are affected by product formation.
Highlights
Escherichia coli is able to utilize a variety of electron and carbon donors, such as glucose or glycerol, and electron acceptors, such as oxygen or nitrate
We present a mathematical model of the oxygen response of an E. coli population in a glucose-limited chemostat
The final model is able to provide an integrated description of metabolic fluxes and concentrations, gene expression levels and genetic regulation
Summary
Escherichia coli is able to utilize a variety of electron and carbon donors, such as glucose or glycerol, and electron acceptors, such as oxygen or nitrate. The analysis of measurement data of transcript levels, protein abundances, metabolite concentrations, and fluxes is a valuable tool to reveal bottlenecks of production pathways. A thorough analysis of manipulations of this network requires integration of measurement data of different types, in particular transcript and protein levels, metabolite concentrations, fluxes, and transcription factor activities, by analyzing their dependencies within the network structure. The goal of the modeling approach was to provide a physically consistent systems-level view of the central carbon and energy metabolism of E. coli and its regulation. We show how the model is able to explain the steady state response of Escherichia coli to oxygen by comparing model simulation and measurement data for different values of aerobiosis. We demonstrate the utility of the model by making predictions on the effect of biofuel production pathways on bacterial metabolism
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