Team:UT-Tokyo/Sudoku modeling

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In addition, we changed many parameters, especially,l0,v(whose values are unclear) and p(leakiness of terminator) ,  to see whether the device is able to operate within a large part of parameter space.
In addition, we changed many parameters, especially,l0,v(whose values are unclear) and p(leakiness of terminator) ,  to see whether the device is able to operate within a large part of parameter space.
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As a result, the circuit can function correctly within the range of </html><math> 0.001< p < 0.1, 0.001 < v <1.0, 0.01 < l0 < 1.0</math><html> , demonstrating its robustness.
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As a result, the circuit can function correctly within the range of <math> 0.001< p < 0.1, 0.001 < v <1.0, 0.01 < l0 < 1.0</math><html> , demonstrating its robustness.
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This robustness may come from the assumption that DNA recombination is irreversible, which is supported by our design of the system.
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This robustness may come from the assumption that DNA recombination is irreversible, which is supported by our design of the system.<math>\frac{2}{2}</math>
==='''conclusion'''===
==='''conclusion'''===

Revision as of 17:56, 27 October 2010

UT-Tokyo

Sudoku

Introduction System Modeling Experiment Perspective Reference

4C3leak switch

We modeled our 4C3 leak switch as deterministic ODE system.


Modelling

Assumption

1.We treated DNA as continuous variabl, since there could be hundreds of plasmid in one E.coli (multicopy plasmid). There are 32 kinds of variables that stand for DNA concentration corresponding to their different internal states.

2.We assumed that cre recombinase operate as tetramer, and other recombinase as dimer (but this seems not to be relevant).

3.We assumed that association and dissociation of DNA recombinase to DNA is sufficiently fast so that equilibrate in the timescale of the whole switch.

4.We ignored the reverse reaction of DNA recombinase because we used irreversible sequence (lox66, lox71 etc).

Variable

Basically, "pn" denotes for protein concentration and "rn" denotes for mRNA concentration

p1,p2,p3,p4 : concentration of 4 recombinase protein

r1,r2,r3,r4 : concentration of 4 recombinass mRNA

u1,u2,u3,u4 : concentration of input mRNA

pc,rc : concentration of cre recombinase protein and mRNA

ps,rs : concentration of SP6 polymerase protein and mRNA


Parameters

k0 : mRNA translation rate

k1 : protein degradation rate

k2 : mRNA translation rate

k3 : cre protein degradation rate

l0 : transcription speed per unit concentration of RNA polymearase

l1 : mRNA degradation rate

l2 : cre mRNA degradation rate

K : recombinase binding constant

v : recombinase reaction rate

pT7 : concentration o T7 polymerase

p : terminator leak probability


Equations

Methods

We used our original python program (4 th order explicit Runge-Kutta algorithm) to solve thess equations.


Results

We input signal 1,2,4 and simulated the time evolution of the system.

The time course of DNA concentration

Sim res.JPG

The time course of mRNA concentration. Note that the output of this system is not protein but mRNA.

Rna.JPG

Discussion

It is confirmed that the system works as expected with a certain combination of parameters.

In addition, we changed many parameters, especially,l0,v(whose values are unclear) and p(leakiness of terminator) , to see whether the device is able to operate within a large part of parameter space.

As a result, the circuit can function correctly within the range of <math> 0.001< p < 0.1, 0.001 < v <1.0, 0.01 < l0 < 1.0</math> , demonstrating its robustness. This robustness may come from the assumption that DNA recombination is irreversible, which is supported by our design of the system.\frac{2}{2} ==='''conclusion'''=== The correct operation of the switch was confirmed. By changing parameter exponentially, the robustness of the system was shown. =='''MS2 phage infection'''== ===='''Modeling'''==== '''Variable''' U: uninfected coli I: coli which got '1' signal Io1: other once infected coli I2: coli which got '1''2' signal Io2: other second infected coli I3: coli which got '1''2''3' signal Io3: other third infected coli B4: '4' coli which began phage making Bo: other coli which began phage making P4: free phage of '4' Po: other free phage '''Parameters''' g: growth rate of coli k1: rate of infection k2: death rate of uninfected k3: lysis rate of infected k4: rate of phage producing k5: phage death rate k6: terminator leak rate '''Equations''' We assume that cell lysis caused by MS2 phage is sufficiently rapid than coli death rate. ===='''Method'''==== We used original matlab program. We set conditions as following. -when t = 10(min), signal of number '1' comes.(step input) -when t = 30(min), signal of number '2' comes.(step input) -when t = 50(min), signal of number '3' comes.(step input) ===='''Results'''==== Image:MS2-0.5,0.6,0.png ===='''Discussion'''==== '''conclusion''' =='''Whole system'''== [[Image:What_Sudoku_99.png|200px|thumb|What's Sudoku?]] {{UT-Tokyo_Foot}}