Team:USTC-China/modeling
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<p>According to the Law of mass action, we can easily write down the equation approximations to reduce these equations.</p></br> | <p>According to the Law of mass action, we can easily write down the equation approximations to reduce these equations.</p></br> | ||
<p>First of all, we do quasi-steady state approximation for dimerization reactions</p> | <p>First of all, we do quasi-steady state approximation for dimerization reactions</p> | ||
- | + | <img src="https://static.igem.org/mediawiki/2012/1/15/2.jpg"> | |
- | + | ||
<p>where [cIT] and [croT] are the total concentration of cI and cro.</p> | <p>where [cIT] and [croT] are the total concentration of cI and cro.</p> | ||
<p>Besides, we decide to take the degradation into account in the very end step. So, considering the conservation of | <p>Besides, we decide to take the degradation into account in the very end step. So, considering the conservation of | ||
binding site</P> | binding site</P> | ||
- | + | <img src="https://static.igem.org/mediawiki/2012/7/79/3.jpg> | |
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<p>Where R is the total binding site number, we get</p> | <p>Where R is the total binding site number, we get</p> | ||
- | + | <img src="https://static.igem.org/mediawiki/2012/d/d0/4.jpg"> | |
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<p>The above equations give us the expression of [cro2 �OR3 ];[cI2 �OR1 ];[cI2 �OR1 �cI2 �OR2 ]. | <p>The above equations give us the expression of [cro2 �OR3 ];[cI2 �OR1 ];[cI2 �OR1 �cI2 �OR2 ]. | ||
- | The | + | The final step is to write down the evolution equations for [cI] and [cro]. |
- | + | <img src="https://static.igem.org/mediawiki/2012/0/03/5.jpg"> | |
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<p>where</p> | <p>where</p> | ||
- | + | <img src="https://static.igem.org/mediawiki/2012/1/18/6.jpg"> | |
<h2><a name="2">Toggle Switch with designed genetic route</a></h2> | <h2><a name="2">Toggle Switch with designed genetic route</a></h2> | ||
- | <p>There is a | + | <p>There is a difference if we add our designed genetic route:</p> |
- | + | <img src="https://static.igem.org/mediawiki/2012/f/fe/7.jpg"> | |
<p>where <img> �mcro refers to <img> �mcro.</p> | <p>where <img> �mcro refers to <img> �mcro.</p> | ||
<p>Three additional equation should be taken into account</p> | <p>Three additional equation should be taken into account</p> | ||
- | + | <img src="https://static.igem.org/mediawiki/2012/8/8c/8.jpg"> | |
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<p>The above gives us the expression for [img], which is a function of [img]. It is then straightforward to derive | <p>The above gives us the expression for [img], which is a function of [img]. It is then straightforward to derive | ||
[mcro] from the following</p> | [mcro] from the following</p> | ||
- | + | <img src="https://static.igem.org/mediawiki/2012/3/30/9.jpg"> | |
- | + | <p>Once obtained [mcro], substitute it into the following to get the final equation</p> | |
- | <p>Once obtained [mcro], substitute it into the following to get the | + | <img src="https://static.igem.org/mediawiki/2012/a/ae/10.jpg"> |
- | + | ||
<h2><a name="3">Result</a></h2> | <h2><a name="3">Result</a></h2> | ||
<p>We found that for the parameters in the value table, there is no real solution for both the two part in the following | <p>We found that for the parameters in the value table, there is no real solution for both the two part in the following |
Revision as of 16:57, 25 September 2012
MODELING
The function of the anticro is to repress the expression of cro. That means the anticro can strongly prevent the lambda phage from turning into lytic life cycle. It is the toggle switch in the genome of lambda phage that control the decision of lysogenic or lytic life cycle and it is the target of our anticro. So, we study the steady state property of two system, without and with our designed genetic circuit separately. Finally, we give the phase graphs to show the steady state property visibly and draw the vector diagram to simulate the fate of each point on the graph.
We study the steady state property of two system, without and with our designed genetic route separately.
I. Mathematical models
Toggle Switch without designed genetic route
The chemical reactions are:
According to the Law of mass action, we can easily write down the equation approximations to reduce these equations.
First of all, we do quasi-steady state approximation for dimerization reactions
where [cIT] and [croT] are the total concentration of cI and cro.
Besides, we decide to take the degradation into account in the very end step. So, considering the conservation of binding site
The above equations give us the expression of [cro2 �OR3 ];[cI2 �OR1 ];[cI2 �OR1 �cI2 �OR2 ]. The final step is to write down the evolution equations for [cI] and [cro].
where
Toggle Switch with designed genetic route
There is a difference if we add our designed genetic route:
where �mcro refers to �mcro.
Three additional equation should be taken into account
The above gives us the expression for [img], which is a function of [img]. It is then straightforward to derive [mcro] from the following
Once obtained [mcro], substitute it into the following to get the final equation
Result
We found that for the parameters in the value table, there is no real solution for both the two part in the following equation The reason of this problem probably stems from the[img] arameters|�1 ;�2 di�ers too much wich �3 ;�4 ;�5 , thus it is impossible for the equation to have real solution. We lot the stream diagram for [cIT] and [croT]:
After adding our designed route, the stream flow diagram is
We can see that after adding our designed part, the system goes through double steady state to single steady state.
II. computer simulations
In order to show the visible process of our engineered bacteria defending against the bacteriophage, we write a JAVA program to simulate the evolution of the colony which is invaded by the bacteriophage. The program interface is showed below:
【img】Here is the description of our JAVA program: (if you want to operate the program skipping the description, please click here.)
The blue box: presents the lysogenies
The red box: presents the phage in the host is in lytic life cycle
The grey box: presents the normal bacterium
The amount of this three kinds of bacteria have been set as three changeable parameters in our program. The other three changeable parameters are:
P1: The newly infected cells turn into lytic life cycle at possibility of P1 and turn into lysogenic life cycle at possibility 1-P1.
P2: The lysogen suicides at possibility of P2.
P3: At the grids marked as competence states, the lysogenic marks win the occupancy of these grids in the competence at possibility of P3. Thus, the marks represent competence states transform into lysogenic marks at possibility of P3 and transform into normal marks at possibility of 1-P3.
Model:
Grid model of solid LB medium
1. The cell can only reproduce new cells when there are empty grids around it.
2. The newly assembled and emitted phages will only infect the cells in the grids around its host.
3. The step length of time for this JAVA applet to operate is the time of a cell cycle.
4. The basic level of expression of the lysis gene and the quorum sensing among cells are ignored.
5. We adopt the Monte-Carlo simulation to deal with the process of competence among cells
Description of the algorithm
The process of infection:
1. When the host is lysed by the newly reproduced phages, the cells in the grids around it will be infected by the emitted phages and the grid the host occupied will return to be empty.
2. The newly infected cells turn into lytic life cycle at possibility of P1 and turn into lysogenic life cycle at possibility 1-P1.
The process of growth of the cell:
1. The normal cell can only reproduce new cells when there are empty grids around it.
2. The lysogen suicides at possibility of P2 and reproduce a new lysogen at empty grid around it.
3. If a empty grid abut both a normal cell and a lysogen and both the two cell will reproduce new cell, the offspring of the lysogen win the empty grid at possibility of P3.
Procedures of the algorithm
1. Arrange three kinds of cells(grey: the normal cell, red: the host in which the phage is at lytic life cycle, blue: the lysogen) at the screen according to the parameters at random.
2. The red cell is lysed and releases the grid it occupied. All the cells in the grids abut the lysed host will be infected.
3. Scan the screen again. The newly infected cells turn into lytic life cycle at possibility of P1 and turn into lysogenic life cycle at possibility 1-P1.
4. The normal cell sets marks represent the reproduction of normal cells (called the normal marks) in the grids around it.
5. The lysogen suicides at possibility of P2. Otherwise, it sets marks represent the reproduction of lysogens (called the lysogenic marks) in the grids around it. If some of these grids around the lysogen have been marked as reproduction of normal cells, then the lysogen marks these grids as competence states.
6. At the grids marked as competence states, the lysogenic marks win the occupancy of these grids in the competence at possibility of P3. Thus, the marks represent competence states transform into lysogenic marks at possibility of P3 and transform into normal marks at possibility of 1-P3.
7. Those grids with normal mark are occupied by the newly reproduced normal cells and those grids with lysogenic mark are occupied by the lysogenies.