Model of the pH-induced metabolic shift in phosphate-limited continuous cultures of C. acetobutylicum assuming a phenotypic switch Version 1
This model assumes a phenotypic switch between an acid- and solvent-forming population caused by the changing pH levels. The two phenotypes differ in their transcriptomic, proteomic, and ,thus, their metabolomic profile. Because the growth rates of these phenotypes depends on the extracellular pH, the initiation of the pH-shift results in a significant decline of the acidogenic population. Simultaneously, the solvent-forming population rises and establishes an new steady state.
The model is build in Matlab and consists of several functions which define the model, parameters, initial values, and graphical output. Furthermore, the used data are joint using the parameters for the decline of the pH. The population dynamics is estimated from optical density data. The latter two functions are available as independent files.
This model refines our previous model published by Haus et al., BMC Syst. Biol. 5,10 (2011)
Model image: No image specified
Views: 1904 Downloads: 0
Created: 6th Jan 2013 at 16:20
Last updated: 6th Jan 2013 at 17:25
Last used: 21st Oct 2019 at 18:54
I am a mathematical modeller concerned primarily with applications in biology,
Tools: data modelling, Dynamic modelling, Computational Systems Biology, Stochastic models, C programming, differential algebraic equations, Mathematica, Matlab, ODE, Computational and theoretical biology
Modelling of cellular signalling, Dynamic Motifs and Feedback, Quantitative Measures, Theoretical Aspects of Modelling Biological Systems
Institutions: University of Rostock
Tools: quantitative western blot analysis, Stochastic models, quantitative western blot analyses, differential algebraic equations, stimulus response experiments, Mathematica, Matlab, ODE, Computational and theoretical biology
Date Published: 3rd May 2013
Journal: Appl. Microbiol. Biotechnol.
PubMed ID: 23640360
Date Published: 1st Mar 2012
Journal: Journal of Biotechnology
Date Published: 6th Jan 2011
Journal: J. Mol. Microbiol. Biotechnol.
PubMed ID: 21212688
Date Published: 2011
Journal: BMC Syst Biol
Date Published: 1st Aug 2010
Journal: Appl Microbiol Biotechnol