Team:ETH Zurich/Modeling/Switch Circuit

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Revision as of 09:05, 28 October 2008

Switch Circuit

Detailed Model

diffusion of IPTG

In order to switch on the sircuit, we induce with IPTG. When we add the IPTG into the medium diffuses reversibly between the medium and the cells, where it is slowly degraded. In a chemostat extracellular IPTG is washed away.
Grafik

diffusion of tet

The second inducer which is used in our system is tet. This also diffuses into the cell when it is added into the medium and degrades slowly.
Grafik

binding of tetR to LacI-promotor and LacIIs-promotor

binding of LacI and LacIIs to GFP-promotor

binding of tet to tetR

binding of IPTG to LacI

transcription and translation of LacI

transcription and translation of LacIIs

transcription and translation of tetR

transcription and translation of GFP

dimerization of tetR

dimerization and tetramerization of LacI and LacIIs

Implementation and Simulation

The model of the switch circuit has been implemented using the Simbiology Toolbox in MATLAB.

For the sake of simplicity, the effects of dimerization and dimerization/tetramerization of tetR and LacI/LacIIs have been neglected. So we did with the additional steps involving the RNApolymerase in the transcription of proteins and the ribosomes in the translation of proteins.

diagram view of the model

Results and Discussion

Parameters

In this section you can find all the parameters used in the simulation.

#	Parameter name	Value	Units
1	k_assoc(IPTG_LacI)	5.0	X
2	k_assoc(LacI)	5.0	X
3	k_assoc(LacIs)	5.0	X
4	k_assoc(tet)	5.0	X
5	k_assoc(tetR)	5.0	X
6	k_dec(IPTG)	0.002	X
7	k_dec(IPTG_ext)	0.005	X
8	k_dec(LacI)	5.0	X
9	k_dec(LacIs)	5.0	X
10	k_dec(gfp)	1.0	X
11	k_dec(mRNA_LacI)	0.1	X
12	k_dec(mRNA_LacIs)	0.1	X
13	k_dec(mRNA_gfp)	0.2	X
14	k_dec(mRNA_tetR)	0.05	X
15	k_dec(tetR)	0.05	X
16	k_dec(tet)	0.002	X
17	k_dec(tet_ext)	0.005	X
18	k_diff(IPTG)	0.1	X
19	k_diff(tet)	0.1	X
20	k_dissoc(IPTG_LacI)	1.0	X
21	k_dissoc(LacI)	1.0	X
22	k_dissoc(LacIs)	1.0	X
23	k_dissoc(tet)	1.0	X
24	k_dissoc(tetR)	1.0	X
25	k_tl(LacI)	10.0	X
26	k_tl(LacIs)	10.0	X
27	k_tl(gfp)	10.0	X
28	k_tl(tetR)	10.0	X
29	k_tr(LacI)	2.0	X
30	k_tr(LacIs)	2.0	X
31	k_tr(gfp)	2.0	X
32	k_tr(tetR)	2.0	X

References

(1) "Spatiotemporal control of gene expression with pulse-generating networks", Basu et al., PNAS, 2004

(2) "Genetic circuit building blocks for cellular computation, communications, and signal processing", Weiss et al., Natural Computing, 2003

(3) "Predicting stochastic gene expression dynamics in single cells", Mettetal et al., PNAS, 2006

(4) "Engineered gene circuits", Hasty et al., Nature, 2002

@@ Line 73: / Line 73: @@
 [[Image:model.PNG|thumb|center|600px|diagram view of the model]]
-== Simulation ==
-In order to get some useful results out of this model, we ran deterministic and stochastic simulations using Mass-Action-Kinetics. The stochastic simulations turned out to be computationally very demanding and yielded no additional results compared to the deterministic ones.
 == Results and Discussion ==