Team:Northwestern/Project/Modeling
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| Chitin || [[Image:P1.jpg|400px]] || [[Image:P2.jpg|400px]] | | Chitin || [[Image:P1.jpg|400px]] || [[Image:P2.jpg|400px]] | ||
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==='''Future Concerns'''=== | ==='''Future Concerns'''=== | ||
- | + | Overall, the model, though logical, is not yet fit for application, mostly due to the lack of empirical data to which the model could be fit and/or tested. Once fit, the rate constant values and initial concentration values will be much more accurate. The following concerns deal primarily with problems that could possibly not be corrected even with empirical data. | |
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+ | *Currently the model predicts the final product expression level between the top layer and bottom layer of a gradient-induced system as only about 0.00001%. Determine if this is primarily due to model inaccuracy or the inefficacy of diffusion-based layer differential induction method. | ||
+ | *Currently the model only predicts only a 10% increase in product when induced by what is suspected to be a significant concentration of inducer. This could be due to a model design problem. | ||
+ | *The model assumes constant substrate; this assumption may or may not be accurate. | ||
+ | *The model assumes all components are in first order; this assumption may or may not be sufficient. | ||
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+ | ==='''Future Work'''=== | ||
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+ | Aside from being generally accurate, the model should perform the following functions: | ||
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+ | *Differentiate protein production between the top and bottom layer of the biofilm based on a diffusion-gradient inducer. | ||
+ | *Differentiate protein production between expression vectors with different repressor production levels. | ||
+ | *Differentiate protein production between expression vectors with different IPTG Induction levels. | ||
+ | *Differentiate protein production between expression vectors with different Promoters (k-transcribe). | ||
+ | *Differentiate protein production between expression vectors with different Ribosome Binding Sites (k-translate). | ||
+ | *Differentiate protein production between expression vectors with different Copy Number Plasmids. | ||
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=='''References'''== | =='''References'''== |
Revision as of 04:33, 27 October 2010
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ObjectiveThe main purpose of modeling was to characterize the topography of the kinetics behind foreign protein/product production in recombinant E.Coli biofilm with a diffusing inducer, and the effect on the various species involved by primarily the following factors:
ModelingOverall ModelUsing enzyme kinetics equations, we elected to mathematically simulate the following model:
Variables
EquationsThe differential of the variables were found as follows:
IPTG DiffusionFirst, Fick's Law of Diffusion was modeled through MATLAB. The diffusion constant used was 220um^2/s.[4] IPTG was sprayed at the top of the colony, which then diffuses as according to Fick's law. The spatially different local IPTG concentration will then differentially induce downstream processes. This distinction was necessary in our project in order to establish a Chitin layer on the top of the biofilm. Semi-Empirical Variable/Constant DeterminationStatus: Under Development The initial plan was to use lacI-constitutive expression / lac-operon (CP-LacpI) part with Green Fluorescent Protein to acquire empirical data. By testing various combinations of CP/LacpI, RBS, and IPTG concentrations, the acquisition of a broad range of expression level (GFP fluorescence) over time could be acquired through a plate reader. This data would be used to determine many of the rate constants as well as initial concentration values, thus generating a more accurate semi-empirical kinetics model. However, at the time of the wiki-freeze, data acquisition is incomplete. Current ModelThe plots of the non-induced and the induced system are as follows:
Future ConcernsOverall, the model, though logical, is not yet fit for application, mostly due to the lack of empirical data to which the model could be fit and/or tested. Once fit, the rate constant values and initial concentration values will be much more accurate. The following concerns deal primarily with problems that could possibly not be corrected even with empirical data.
Future WorkAside from being generally accurate, the model should perform the following functions:
References1. A novel structured kinetic modeling approach for the analysis of plasmid instability in recombinant bacterial cultures William E. Bentley, Dhinakar S. Kompala Article first published online: 18 FEB 2004 DOI: 10.1002/bit.260330108 http://onlinelibrary.wiley.com/doi/10.1002/bit.260330108/pdf
Jongdae Lee, W. Fred Ramirez Article first published online: 19 FEB 2004 DOI: 10.1002/bit.260390608 http://onlinelibrary.wiley.com/doi/10.1002/bit.260390608/pdf
DOMINIQUE MENGIN-LECREULX, BERNARD FLOURET, AND JEAN VAN HEIJENOORT* E.R. 245 du C.N.R.S., Institut de Biochimie, Universit' Paris-Sud, Orsay, 91405, France Received 9 February 1983/Accepted 15 March 1983 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC217602/pdf/jbacter00247-0262.pdf
Philip S. Stewart Center for Biofilm Engineering and Department of Chemical Engineering, Montana State University–Bozeman, Bozeman, Montana, 59717-3980 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC148055/pdf/0965.pdf
PATRICIA L. EDELMANN' AND GORDON EDLIN Department of Genetics, University of California, Davis, California 95616 Received for publication 21 March 1974 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC245824/pdf/jbacter00335-0105.pdf
MATLAB file provided upon request. |