| Autor: |
Ederer M; Institute for System Dynamics, University of Stuttgart Stuttgart, Germany., Steinsiek S; Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Germany., Stagge S; Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Germany., Rolfe MD; Department of Molecular Biology and Biotechnology, The University of Sheffield Sheffield, UK., Ter Beek A; Molecular Microbial Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands., Knies D; Institute for System Dynamics, University of Stuttgart Stuttgart, Germany., Teixeira de Mattos MJ; Molecular Microbial Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands., Sauter T; Life Sciences Research Unit, Université du Luxembourg Luxembourg, Luxembourg., Green J; Department of Molecular Biology and Biotechnology, The University of Sheffield Sheffield, UK., Poole RK; Department of Molecular Biology and Biotechnology, The University of Sheffield Sheffield, UK., Bettenbrock K; Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Germany., Sawodny O; Institute for System Dynamics, University of Stuttgart Stuttgart, Germany. |
| Abstrakt: |
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. |
