Team:Slovenia/ModelingMutualRepressorSwitchStochastic

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Here:
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    <li>Pro1 is construct 1 promoter (i.e. promoter 1 - constitutive);</li>
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    <li>Pro2 is construct 2 promoter (i.e. promoter 2 - constitutive);</li>
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    <li>Pro3 s construct 3 promoter (i.e. promoter 3 - constitutive);</li> 
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    <li>Pro4 is construct 4 promoter (i.e. promoter 4 - constitutive);</li>       
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    <li>Pro5 is construct 5 promoter (i.e. promoter 5 - constitutive);</li>
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    <li>Ind1 Is inducer 1 (i.e. signal 1), used to induce stable state 1;</li>
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    <li>Ind2 is inducer 2 (i.e. signal 2), used to induce stable state 2.</li>
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[multi] is a variable, equal to a degree of multimerization and is used to model cooperativity. Normal gene expression means constitutive gene expression, occuring when no repressor is bound.
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When inducer 1 is present, it binds PIP:KRAB and forms a complex, denoted as Ind1.PIP:KRAB. This complex is referred to as inactive PIP:KRAB, meaning PIP:KRAB that cannot bind to the promoter 3. When inducer 2 is present, it binds E:KRAB and forms a complex, denoted as Ind2.E:KRAB. This complex is referred to as inactive E:KRAB, meaning E:KRAB that cannot bind to the promoter 4.
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<h2><a name="results">Simulation results</a></h2>
 
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<h2><a name="results">Simulation results</a></h2>
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Simulation results are shown as concentrations of reporter for different states (BFP, mCitrine) indicating one of the two states as a function of time. No specific units were used, hence no absolute interpretation of the results' values in terms of units is in place. Switching between states was achieved using two signals (inducers) that were introduced into the system at appropriate time. The signals were modeled as a high number of molecules that triggered state induction and were removed at an appropriate time.
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Revision as of 22:37, 25 September 2012


Modeling - mutual repressor switch

  1. Deterministic model
  2. Stochastic model
  3. C#Sim model

Stochastic model of the mutual repressor switch

Stochastic simulation revealed that the mutual repressor switch exhibited bistability only as long as there was no leaky expression present. Otherwise, cooperativity higher than 1 was required. Higher cooperativity improved leaky expression tolerance, but only to a certain threshold. Higher leaky expression resulted in lower stable-state levels.

Bistable behavior of the switch became inconsistent when a delay between transcription and translation was taken into account.

The model

The basis for the stochastic simulation of the mutual repressor switch was the following set of reactions that describe the dynamics of the switch:

Here:

  • Pro1 is construct 1 promoter (i.e. promoter 1 - constitutive);
  • Pro2 is construct 2 promoter (i.e. promoter 2 - constitutive);
  • Pro3 s construct 3 promoter (i.e. promoter 3 - constitutive);
  • Pro4 is construct 4 promoter (i.e. promoter 4 - constitutive);
  • Pro5 is construct 5 promoter (i.e. promoter 5 - constitutive);
  • Ind1 Is inducer 1 (i.e. signal 1), used to induce stable state 1;
  • Ind2 is inducer 2 (i.e. signal 2), used to induce stable state 2.

[multi] is a variable, equal to a degree of multimerization and is used to model cooperativity. Normal gene expression means constitutive gene expression, occuring when no repressor is bound.

When inducer 1 is present, it binds PIP:KRAB and forms a complex, denoted as Ind1.PIP:KRAB. This complex is referred to as inactive PIP:KRAB, meaning PIP:KRAB that cannot bind to the promoter 3. When inducer 2 is present, it binds E:KRAB and forms a complex, denoted as Ind2.E:KRAB. This complex is referred to as inactive E:KRAB, meaning E:KRAB that cannot bind to the promoter 4.

Simulation results

Simulation results are shown as concentrations of reporter for different states (BFP, mCitrine) indicating one of the two states as a function of time. No specific units were used, hence no absolute interpretation of the results' values in terms of units is in place. Switching between states was achieved using two signals (inducers) that were introduced into the system at appropriate time. The signals were modeled as a high number of molecules that triggered state induction and were removed at an appropriate time.


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