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Metabolites. 2012 Nov 12;2(4):844-71. doi: 10.3390/metabo2040844.

Analysis and Design of Stimulus Response Curves of E. coli.

Author information

1
Systems Biotechnology, Technische Universität München, Boltzmannstr. 15, Garching b. München, Germany. a.kremling@tum.de.
2
University Osnabrück, Barbarastrasse 11, Osnabrück, Germany. anna.goehler@gmx.de.
3
University Osnabrück, Barbarastrasse 11, Osnabrück, Germany. knut.jahreis@biologie.uni-osnabrueck.de.
4
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. markus.nees@mpi-magdeburg.mpg.de.
5
Systems Biotechnology, Technische Universität München, Boltzmannstr. 15, Garching b. München, Germany. auerbach@web.de.
6
Hans Knoell Institute, Beutenbergstrasse 11a, Jena, Germany. wolgang.schmidt-heck@hki-jena.de.
7
Helmholtz Center for Infection Research, Inhoffenstr. 7, Braunschweig, Germany. koekpinar@iftc.uni-hannover.de.
8
Helmholtz Center for Infection Research, Inhoffenstr. 7, Braunschweig, Germany. Robert.Geffers@helmholtz-hzi.de.
9
Helmholtz Center for Infection Research, Inhoffenstr. 7, Braunschweig, Germany. Ursula.Rinas@helmholtz-hzi.de.
10
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. katja.bettenbrock@mpi-magdeburg.mpg.de.

Abstract

Metabolism and signalling are tightly coupled in bacteria. Combining several theoretical approaches, a core model is presented that describes transcriptional and allosteric control of glycolysis in Escherichia coli. Experimental data based on microarrays, signalling components and extracellular metabolites are used to estimate kinetic parameters. A newly designed strain was used that adjusts the incoming glucose flux into the system and allows a kinetic analysis. Based on the results, prediction for intracelluar metabolite concentrations over a broad range of the growth rate could be performed and compared with data from literature.

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