Difference between revisions of "Team:ETH Zurich/Modeling/Single-cell Model"
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<p> In our system we want to reduce the amount the amount of<a href= “https://2015.igem.org/Team:ETH_Zurich/Practices/Medicine”> false positives </a>. That’s why cells displaying intermediary characteristics should not be detected by our system. We implemented the system to obtain an <b>AND GATE </b>. The system works as two sequential filtering step. <b> The sequential design </b> was used in order to limit the self-activation of the quorum sensing module .</b> Indeed as we have seen in the <a href="https://2015.igem.org/Team:ETH_Zurich/Modeling/AHL_Module">AHL module</a>, the difference between the two modules strongly depends on the amount of LuxR in the <i> E. coli </i>. This design has a disadvantage though, it requires fine-tuning in order to avoid that one signal prevails on the second one. In the scheme displayed below, we describe in which situation, the <i> E. coli </i> should display fluorescence. </p> | <p> In our system we want to reduce the amount the amount of<a href= “https://2015.igem.org/Team:ETH_Zurich/Practices/Medicine”> false positives </a>. That’s why cells displaying intermediary characteristics should not be detected by our system. We implemented the system to obtain an <b>AND GATE </b>. The system works as two sequential filtering step. <b> The sequential design </b> was used in order to limit the self-activation of the quorum sensing module .</b> Indeed as we have seen in the <a href="https://2015.igem.org/Team:ETH_Zurich/Modeling/AHL_Module">AHL module</a>, the difference between the two modules strongly depends on the amount of LuxR in the <i> E. coli </i>. This design has a disadvantage though, it requires fine-tuning in order to avoid that one signal prevails on the second one. In the scheme displayed below, we describe in which situation, the <i> E. coli </i> should display fluorescence. </p> | ||
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Revision as of 14:14, 17 September 2015
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Single-cell Model
Introduction
CAPTION TEXT
In our system we want to reduce the amount the amount of false positives . That’s why cells displaying intermediary characteristics should not be detected by our system. We implemented the system to obtain an AND GATE . The system works as two sequential filtering step. The sequential design was used in order to limit the self-activation of the quorum sensing module . Indeed as we have seen in the AHL module, the difference between the two modules strongly depends on the amount of LuxR in the E. coli . This design has a disadvantage though, it requires fine-tuning in order to avoid that one signal prevails on the second one. In the scheme displayed below, we describe in which situation, the E. coli should display fluorescence.
Description of the AND-GATE
In this section, we describe the behaviour of the combined model.
Combined Compartment Model
Overview
In this model we plan to simulate whether our system can work as an AND-GATE. Therefore we simulated the system using compartment to model the density of the E. coli as already explained in the AHL module.
First, we will simulate the model with no amplification of the lactate input to match our experimental results. In a second part, we will simulate the full model. As already done in the AHL module, we will compare three conditions:
- No degradation by AiiA, no riboregulator.
- Degradation of AHL by AiiA.
- Riboregulator controlling LuxI expression.
Results
These equations are the integration of both modules in one compartment model.
Assumptions
Here we will assume that .
Equations
Single cell model
Overview
The single cell model is provided here to simulate the combined model.
Chemical species
Name | Description |
---|---|
AHL | Signaling protein, Acyl homoserine lactone (30C6-HSL) |
LuxR | Regulator protein, that can bind to AHL to form a complex |
LuxRAHL | Complex of LuxR and AHL, activates transcription of LuxI |
LuxI | Autoinducer synthase |
Aiia | AHL-lactonase, N-Acyl Homoserine Lactone Lactonase |
Lact | Lactate |
LacI | Lac operon repressor, DNA-binding protein, acts as a protein |
IPTG | Isopropyl β-D-1-thiogalactopyranoside, prevents LacI from repressing the gene of interest |
IL | Dimer formed between LacI and IPTG |
Reactions
\begin{align*} &\mathop{\xrightarrow{\hspace{4em}}}_{a_{LacI},K_{A,appLact}}^{\displaystyle\mathop{\downarrow}^{\text{Lact}}} \text{LacI}\\ \text{IPTG} + \text{LacI} &\mathop{\mathop{\xrightarrow{\hspace{4em}}}^{\xleftarrow{\hspace{4em}}}}_{k_{\mathrm{IL}}}^{k_{\mathrm{-IL}}} \text{IL}\\ &\mathop{\xrightarrow{\hspace{4em}}}_{a_{LuxR},K_{A,appLact}}^{\displaystyle\mathop{\downarrow}^{\text{Lact}}} \text{LuxR}\\ &\mathop{\xrightarrow{\hspace{4em}}}_{a_{LuxR},K_{R,LacI}}^{\displaystyle\mathop{\bot}^{\text{LacI}}} \text{LuxR}\\ \text{AHL} + \text{LuxR} &\mathop{\mathop{\xrightarrow{\hspace{4em}}}^{\xleftarrow{\hspace{4em}}}}_{k_{\mathrm{LuxRAHL}}}^{k_{\mathrm{-LuxRAHL}}} \text{LuxRAHL}\\ &\mathop{\xrightarrow{\hspace{4em}}}_{a_\mathrm{LuxI},K_{\mathrm{a,LuxRAHL}}}^{\displaystyle\mathop{\downarrow}^{\text{LuxRAHL}}} \text{LuxI}\\ &\mathop{\xrightarrow{\hspace{4em}}}_{a_\mathrm{GFP},K_{\mathrm{a,LuxRAHL}}}^{\displaystyle\mathop{\downarrow}^{\text{LuxRAHL}}} \text{GFP}\\ \end{align*} | \begin{align*} \text{LuxI}&\mathop{\xrightarrow{\hspace{4em}}}^{a_{\mathrm{AHL}}}\text{AHL}+\text{LuxI}\\ \text{LuxR}&\mathop{\xrightarrow{\hspace{4em}}}^{d_{\mathrm{LuxR}}}\varnothing\\ \text{AHL}&\mathop{\xrightarrow{\hspace{4em}}}^{d_{\mathrm{AHL}}}\varnothing\\ \text{LuxRAHL}&\mathop{\xrightarrow{\hspace{4em}}}^{d_{\mathrm{LuxRAHL}}}\varnothing\\ \text{LuxI}&\mathop{\xrightarrow{\hspace{4em}}}^{d_{\mathrm{LuxI}}}\varnothing\\ \text{Aiia}+\text{AHL}&\mathop{\xrightarrow{\hspace{4em}}}^{K_{\mathrm{M}},v_{\mathrm{Aiia}}}\text{Aiia}\\ \end{align*} |
Equations
Combining all of the equations from the two different modules, it yields the following system:
\begin{align*} \frac{d[LacI]}{dt}&=\frac{a_\mathrm{LacI} \cdot (\frac{[Lact]}{K_\mathrm{A,appLact}})^{n_1}}{1+(\frac{[Lact]}{K_\mathrm{A,appLact}})^{n_1}}-d_{\mathrm{LacI}}[LacI]\\ \frac{d[LuxR]}{dt}&=\frac{a_\mathrm{LuxR} \cdot (\frac{[Lact]}{K_\mathrm{A,appLact}})^{n_1}}{1+(\frac{[Lact]}{K_\mathrm{A,appLact}})^{n_1}} \cdot \frac{1}{1+(\frac{[LacI]}{K_{\mathrm{R,LacI}}\cdot (\gamma_2+1)})^{n_\mathrm{2}}}-d_{\mathrm{LuxR}}[LuxR]\\ [LuxRAHL]&= \frac{[AHL]\cdot [LuxR]}{K_{\mathrm{d,LuxRAHL}}+[AHL]}\\ \frac{d[LuxI]}{dt}&=a_{\mathrm{LuxI}}k_{\mathrm{leaky}}([LuxR]-[LuxRAHL])+\frac{a_{\mathrm{LuxI}}(\frac{[LuxRAHL]}{K_{\mathrm{A,LuxRAHL}}})^2}{1+(\frac{[LuxRAHL]}{K_{\mathrm{A,LuxRAHL}}})^2}-d_{\mathrm{LuxI}}[LuxI]\\ \frac{d[AHL]}{dt}&=a_{\mathrm{AHL}}[LuxI]-d_{\mathrm{AHL}}[AHL]-\frac{v_\mathrm{Aiia}\cdot [AHL]}{K_{\mathrm{M,AiiA}}+[AHL]}\\ \frac{d[GFP]}{dt}&=a_\mathrm{GFP}k_{\mathrm{leaky}}([LuxR]-[LuxRAHL])+\frac{a_\mathrm{GFP}(\frac{[LuxRAHL]}{K_{\mathrm{A,LuxRAHL}}})^2}{1+(\frac{[LuxRAHL]}{K_{\mathrm{A,LuxRAHL}}})^2}-d_{\mathrm{GFP}}[GFP]\\ K_\mathrm{d,LuxRAHL} &= \frac{k_\mathrm{-LuxRAHL}}{k_\mathrm{LuxRAHL}}\\ \gamma_2 &= \frac{IPTG_{tot}}{K_{IL}} \end{align*}