Team:Michigan/Modeling

From 2009.igem.org

(Difference between revisions)
Line 14: Line 14:
==<B><font size=3>Cell Growth/Death</font></B>  ==
==<B><font size=3>Cell Growth/Death</font></B>  ==
-
Cell Lysis happens when holin creates pores in the cell membrane, allowing lysozyme to attack the cell wall.
+
* Cell Lysis happens when holin creates pores in the cell membrane, allowing lysozyme to attack the cell wall.
-
Assume rate of cell death [holin](# cells), rate of cell growth in exponential phase
+
* Assuming rate of cell death is proportional to [holin](# cells), rate of cell growth in exponential phase is:
[[Image:Equation1.jpg]]
[[Image:Equation1.jpg]]
Line 23: Line 23:
[[Image:Equation2.jpg]]
[[Image:Equation2.jpg]]
-
𝑓([𝑇]) is a function of toluene concentration
 
-
Use Hill Equation to describe binding affinity of toluene to Pu promoter.
+
f([T]) is a function of toluene concentration
 +
 
 +
* Use the Hill Equation to describe binding affinity of toluene to the Pu promoter:
[[Image:Equation3.jpg]]
[[Image:Equation3.jpg]]
==<B><font size=3>Transcription of Lysozyme and Holin:</font></B>==
==<B><font size=3>Transcription of Lysozyme and Holin:</font></B>==
-
Assume transcription rate is proportional to # of free operator sites (which should be the same for both lysozyme and holin, since they are downstream of the same promoter)
+
* Assume the transcription rate is proportional to the number of free operator sites (which should be the same for both lysozyme and holin, since they are downstream of the same promoter).
[[Image:Equation4.jpg]]
[[Image:Equation4.jpg]]
-
Assume transcription rates for H and L are the same
+
* Assume transcription rates for H and L are the same.
==<B><font size=3>Repression of Lysozyme and Holin Transcription </font></B>  ==
==<B><font size=3>Repression of Lysozyme and Holin Transcription </font></B>  ==
-
Repressor binds with free operator site, preventing transcription of lysozyme and holin.
+
* Repressor binds with free operator site, preventing transcription of lysozyme and holin.
-
Use a model invoking law of mass action.
+
* Invoking law of mass action:
[[Image:Equation5.jpg]]
[[Image:Equation5.jpg]]
Line 47: Line 48:
==<B><font size=3>Production of Repressor </font></B>  ==
==<B><font size=3>Production of Repressor </font></B>  ==
-
Using the translation rate for R and taking into consideration the binding of R with fops,
+
* Using the translation rate for R and taking into consideration the binding of R with fops:
[[Image:Equation6.jpg]]
[[Image:Equation6.jpg]]
Line 53: Line 54:
==<B><font size=3>Production of Proteins </font></B>  ==
==<B><font size=3>Production of Proteins </font></B>  ==
-
Production of antiholin, under constitutive promoter, is at a constant rate γA, which depends on the promoter that is used
+
* Production of antiholin, under constitutive promoter, is at a constant rate γA, which depends on the promoter that is used.
''Dimerization:''
''Dimerization:''
-
Since holin and antiholin form a complex
+
* Since holin and antiholin form a complex--
[[Image:Equation7.jpg]]
[[Image:Equation7.jpg]]
-
Using the translation rates and incorporating dimerization using the law of mass action,
+
--and using the translation rates and incorporating dimerization using the law of mass action:
[[Image:Equation8.jpg]]
[[Image:Equation8.jpg]]
Line 66: Line 67:
==<B><font size=3>Assumptions</font></B>  ==
==<B><font size=3>Assumptions</font></B>  ==
-
Can set γA equal to rate of production of holin in the case that all operating sites are free
+
* We can set γA equal to rate of production of holin in the case that all operating sites are free.
 +
** This is in order to balance antiholin and holin levels without repression
 +
** ''This can be tuned so that timing of cell death works out''
 +
** Set antiholin production rate to that of holin in the absence of repression
 +
** Put this through the transcription and translation equations to obtain production rate
-
<ul>
 
-
<li> This is in order to balance antiholin and holin levels without repression </li>
 
-
<li> ''This can be tuned so that timing of cell death works out'' </li>
 
-
<li> Set antiholin production rate to that of holin in the absence of repression </li>
 
-
<li> Put this through the transcription and translation equations to obtain production rate </li>
 
-
</ul>
 
-
Assume degradation rates of all mRNAs are the same
+
* We assume degradation rates of all mRNAs are the same.
 +
** Can use half life to calculate rate [[Image:Equation9.jpg]]
-
<ul>
 
-
<li>Can directly search for these rates in literature </li>
 
-
<li>Can use half life to calculate rate [[Image:Equation9.jpg]]</li>
 
-
</ul>
 
For protein degradation rate:
For protein degradation rate:
-
''Case 1: Proteins are stable:''
+
* ''Case 1: Proteins are stable:''
 +
** Degradation rates equal reproduction rate of cell
 +
** This is due to dilution of proteins across daughter cells
-
<ul>
+
* ''Case 2: Proteins are unstable''
-
<li>Degradation rates equal reproduction rate of cell </li>
+
-
<li>This is due to dilution of proteins across daughter cells </li>
+
-
</ul>
+
-
''Case 2: Proteins are unstable''
 
-
<ul>
 
-
<li>If not other degradation rate information is provided, can possibly assume that the degradation rates are a few orders of magnitude above the reproduction rate of cell</li>
 
-
<li>Will have to look into this further</li>
 
-
</ul>
 
==<B><font size=3>Variables and Parameters</font></B>  ==
==<B><font size=3>Variables and Parameters</font></B>  ==
Line 102: Line 92:
==<B><font size=3>Further Work</font></B>  ==
==<B><font size=3>Further Work</font></B>  ==
-
We plan to run simulations of this model using MATLAB, focusing on the relationship between cell count and toluene concentration.  Before this is done, we must find/estimate values for the parameters listed above.  Initial simulations will be tailored to fine-tuning parameters to satisfy the primary needs of the modeling: at high toluene concentrations, the cells will survive; at low toluene concentrations, the cells will die.  After that, we will look at low-to-high and high-to-low transitions in toluene concentrations and look for equilibria that arise as a result.  This will help us understand how responsive the system is to toluene levels (including initial concentrations).
+
We plan to run simulations of this model using MATLAB, focusing on the relationship between cell count and toluene concentration.  Before this is done, we must find or estimate values for the parameters listed above.  Initial simulations will be tailored to fine-tuning parameters to satisfy the primary needs of the modeling: at high toluene concentrations, the cells will survive; at low toluene concentrations, the cells will die.  After that, we will look at low-to-high and high-to-low transitions in toluene concentrations and look for equilibria that arise as a result.  This will help us understand how responsive the system is to toluene levels (including initial concentrations).
-
Lastly, a future version of this model will couple the kill switch mechanism with the degradation mechanism.  One of the major effects that this will have on the kill switch modeling is that toluene levels will be reduced by the degradation pathway.  To understand coupling effect is one of the major goals down the road, as it will help us gain a deeper understanding of the overall dynamics of our proposed project (i.e. to see the "big picture").
+
Lastly, a future version of this model will couple the kill switch mechanism with the degradation mechanism.  One of the major effects that this will have on the kill switch modeling is that toluene levels will be reduced by the degradation pathway.  To understand coupling effect is one of the major goals down the road, as it will help us gain a deeper understanding of the overall dynamics of our proposed project.

Revision as of 23:57, 21 October 2009


UMheaderlogo.jpg
HOME THE TEAM THE PROJECT MODELING REGISTRY PARTS NOTEBOOK SAFETY

The Toluene Terminator Model

Overview :

The following mathematical model examines the dynamics of the Suicide Mechanism with Tunable Repression (see Project Page). As outlined in the project description, the Pu promoter is placed in front of a repressor system that would inhibit the production of holin and lysozyme, while a constitutive promoter is placed in front of the gene for antiholin. In the presence of toluene, the Pu promoter would be activated, leading to repression of holin/lysozyme production and therefore cell survival. In the absence of toluene, the Pu promoter would not be activated, and as a result holin and lysozyme would be produced, leading to cell death.

Kill switch topology for modeling.jpg


Cell Growth/Death

  • Cell Lysis happens when holin creates pores in the cell membrane, allowing lysozyme to attack the cell wall.
  • Assuming rate of cell death is proportional to [holin](# cells), rate of cell growth in exponential phase is:

Equation1.jpg

Transcription of Repressor :

Equation2.jpg

f([T]) is a function of toluene concentration

  • Use the Hill Equation to describe binding affinity of toluene to the Pu promoter:

Equation3.jpg

Transcription of Lysozyme and Holin:

  • Assume the transcription rate is proportional to the number of free operator sites (which should be the same for both lysozyme and holin, since they are downstream of the same promoter).

Equation4.jpg

  • Assume transcription rates for H and L are the same.

Repression of Lysozyme and Holin Transcription

  • Repressor binds with free operator site, preventing transcription of lysozyme and holin.
  • Invoking law of mass action:

Equation5.jpg

Assuming that fops and Rfops do not undergo spontaneous degradation.

Production of Repressor

  • Using the translation rate for R and taking into consideration the binding of R with fops:

Equation6.jpg

Production of Proteins

  • Production of antiholin, under constitutive promoter, is at a constant rate γA, which depends on the promoter that is used.

Dimerization:

  • Since holin and antiholin form a complex--

Equation7.jpg

--and using the translation rates and incorporating dimerization using the law of mass action:

Equation8.jpg

Assumptions

  • We can set γA equal to rate of production of holin in the case that all operating sites are free.
    • This is in order to balance antiholin and holin levels without repression
    • This can be tuned so that timing of cell death works out
    • Set antiholin production rate to that of holin in the absence of repression
    • Put this through the transcription and translation equations to obtain production rate


  • We assume degradation rates of all mRNAs are the same.
    • Can use half life to calculate rate Equation9.jpg


For protein degradation rate:

  • Case 1: Proteins are stable:
    • Degradation rates equal reproduction rate of cell
    • This is due to dilution of proteins across daughter cells
  • Case 2: Proteins are unstable


Variables and Parameters

Variables and Parameters.jpg

Further Work

We plan to run simulations of this model using MATLAB, focusing on the relationship between cell count and toluene concentration. Before this is done, we must find or estimate values for the parameters listed above. Initial simulations will be tailored to fine-tuning parameters to satisfy the primary needs of the modeling: at high toluene concentrations, the cells will survive; at low toluene concentrations, the cells will die. After that, we will look at low-to-high and high-to-low transitions in toluene concentrations and look for equilibria that arise as a result. This will help us understand how responsive the system is to toluene levels (including initial concentrations).

Lastly, a future version of this model will couple the kill switch mechanism with the degradation mechanism. One of the major effects that this will have on the kill switch modeling is that toluene levels will be reduced by the degradation pathway. To understand coupling effect is one of the major goals down the road, as it will help us gain a deeper understanding of the overall dynamics of our proposed project.