Difference between revisions of "Team:ETH Zurich/Modeling/AHL Module"

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     <li>In this model we considered that <b> no AHL diffuses out of the cell</b>. </li>
 
     <li>In this model we considered that <b> no AHL diffuses out of the cell</b>. </li>
 
</ol>
 
</ol>
<h4>Simplified equations</h4>
+
<h4>Simplified equations including degradation by AiiA</h4>
 
\begin{align*}
 
\begin{align*}
 
[LuxRAHL]&= \frac{[AHL]\cdot LuxR_\mathrm{tot}}{K_{\mathrm{d,LuxRAHL}}+[AHL]}\\
 
[LuxRAHL]&= \frac{[AHL]\cdot LuxR_\mathrm{tot}}{K_{\mathrm{d,LuxRAHL}}+[AHL]}\\
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K_\mathrm{d,LuxRAHL} &= \frac{k_\mathrm{-LuxRAHL}}{k_\mathrm{LuxRAHL}}\\
 
K_\mathrm{d,LuxRAHL} &= \frac{k_\mathrm{-LuxRAHL}}{k_\mathrm{LuxRAHL}}\\
 
\end{align*}
 
\end{align*}
 +
<p> To see the parameters used, in this section of the model, <a href="https://2015.igem.org/Team:ETH_Zurich/Modeling/Parameters">click here</a>. </p>
  
 
<h3>Simulations</h3>
 
<h3>Simulations</h3>

Revision as of 18:42, 10 September 2015

"What I cannot create I do not understand."
- Richard Feynmann

AHL Module

Introduction and Goals

The present design is meant to respond to the colocalization of cells on the mammalian cell surface. The E. coli being denser on the mammalian cell surface will communicate via AHL signaling to produce GFP, whereas the E. coli localized in the bulk will be too far away to communicate in the case of normal cells. However, the dimensions of the chip in which the bacteria and the mammalian cells are located is really small (1 nL). We expect then the signaling molecule to diffuse almost instaneously in the well. Also, from previous years, we know that the LuxRAHL responsive operator is quite leaky in the presence of LuxR. This results in self-activation of all the bacteria, independently of their density. To address this problem, we studied two different ways to control the level of activation of the construct. During the first part of the project, we privileged integrating AiiA, an AHL degrading enzyme, into the final design. We thought it would be sufficient to prevent activation in unwanted situations. Our second approach consisted in replacing the LuxI controlling promoter by a riboregulated promoter. As shown by ETHZ 2014, the resulting promoter is not leaky. In the following we will describe the influence of the two approaches.

Description of the design

Figure 1: AHL sensor design

When AHL concentration is high enough due to high density of cells, the lux promoter is triggered, which produces more AHL via the synthesis of LuxI. When the threshold concentration of activated LuxR (LuxRAHL) is reached, GFP production starts. To see the reactions, jump to reactions!.

Goals

In the following, we present a single-cell model and a compartment model . The single cell model is meant to:

  1. As a sanity check for the equations.
  2. Study the influence of AiiA on the single cell.
  3. Study the influence of a riboswitch on the LuxI controlling promoter.

The compartment model will compare the behaviour of the E. coli in two different situations, when E. coli are highly concentrated around the mammalian cell and when they are spread in the bulk. Thanks to this model, we hope to know:

  1. Which approach riboswitch or AiiA degradation has the better chances of success to obtain the desired AND-gate.

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

Single Cell Model

The single cell model describes the basic chemical reactions and equations concerning the quorum sensing module. It also shows the basic behavior of the system.If it is too simple for you, jump to compartment model. In this model, we consider that LuxR is constitutively produced and constant. In the complete design, LuxR is however regulated by the lactate amplifier. Also, here, no AHL diffuses out of the cell. It is therefore not a realistic case in the context of our system.

Reactions

The Reactions depicted here are based on simple kinetics and Michaelis Menten kinetics. They describe the design provided above.

\begin{align*} \varnothing&\mathop{\xrightarrow{\hspace{4em}}}^{a_{\mathrm{LuxR}}} \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}\\ \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

The equations are based on mass action kinetics and basic rate laws such as Hill equation.

Assumptions

  1. As LuxR is constitutively produced in this model, we considered that LuxR was constant. We used then the conservation of mass to derive the equations
  2. On the other hand, the binding and unbinding of LuxR to AHL is fast compared to the synthesis of LuxI. We used the quasi steady state approximation (QSSA)
  3. In this model we considered that no AHL diffuses out of the cell.

Simplified equations including degradation by AiiA

\begin{align*} [LuxRAHL]&= \frac{[AHL]\cdot LuxR_\mathrm{tot}}{K_{\mathrm{d,LuxRAHL}}+[AHL]}\\ \frac{d[LuxI]}{dt}&=a_{\mathrm{LuxI}}k_{\mathrm{leaky}}(LuxR_\mathrm{tot}-[LuxRAHL])+\frac{a_{\mathrm{LuxI}}(\frac{[LuxRAHL]}{K_{\mathrm{a,LuxRAHL}}})^{n_{lux}}}{1+(\frac{[LuxRAHL]}{K_{\mathrm{a,LuxRAHL}}})^{n_{lux}}}-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_\mathrm{tot}-[LuxRAHL])+\frac{a_\mathrm{GFP}(\frac{[LuxRAHL]}{K_{\mathrm{a,LuxRAHL}}})^{n_{lux}}}{1+(\frac{[LuxRAHL]}{K_{\mathrm{a,LuxRAHL}}})^{n_{lux}}}-d_{\mathrm{GFP}}[GFP]\\ K_\mathrm{d,LuxRAHL} &= \frac{k_\mathrm{-LuxRAHL}}{k_\mathrm{LuxRAHL}}\\ \end{align*}

To see the parameters used, in this section of the model, click here.

Simulations

We decided to simulate the single cell model in order to check the influence of AHL degradation by AiiA, and to confirm the sequential design.

Figure 1: AHL sensor output with and without AiiA degradation

Observations

We can observe that AiiA degradation has no influence on GFP output. It is because of LuxI accumulation in the cell. Indeed, AiiA acts on AHL level, but because of the leakiness of the promoter, AiiA is unable to counteract production of AHL level by LuxI.

Single cell model with riboregulated LuxR responsive promoter

Adding a riboregulator

Figure 1: AHL sensor design with riboregulator

We wanted to check the influence of a riboregulator on GFP output. Looking at the characterization from ETHZ 2014, we saw that riboswitches were able to reduce the leakiness by 65 fold. However, as well as reducing the leakiness, riboswitches reduce the final expression levels by 10 fold. As we have two different promoters controlling the expression of LuxI and GFP. We decided to use one riboswitch only for LuxI, to prevent LuxI accumulation in the cell.

Simplified equations

\begin{align*} [LuxRAHL]&= \frac{[AHL]\cdot LuxR_\mathrm{tot}}{K_{\mathrm{d,LuxRAHL}}+[AHL]}\\ \frac{d[LuxI]}{dt}&=L_{Lux,ribo}+\frac{a_{\mathrm{LuxI,ribo}}(\frac{[LuxRAHL]}{K_{\mathrm{LuxRAHL,ribo}}})^{n_{lux}}}{1+(\frac{[LuxRAHL]}{K_{\mathrm{LuxRAHL,ribo}}})^{n_{lux}}}-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_\mathrm{tot}-[LuxRAHL])+\frac{a_\mathrm{GFP}(\frac{[LuxRAHL]}{K_{\mathrm{a,LuxRAHL}}})^{n_{lux}}}{1+(\frac{[LuxRAHL]}{K_{\mathrm{a,LuxRAHL}}})^{n_{lux}}}-d_{\mathrm{GFP}}[GFP]\\ K_\mathrm{d,LuxRAHL} &= \frac{k_\mathrm{-LuxRAHL}}{k_\mathrm{LuxRAHL}}\\ \end{align*}

Simulation

Figure 1: AHL sensor output with and without AiiA degradation

Observations

We can see that: The activation time is delayed compared to the case with no riboregulator. Also, AiiA has a much stronger influence on GFP levels.

Expected limitations and Conclusion

Our system should respond to the colocalization of the e-coli cells on the mammalian cell surface. The different concentrations of e-coli in the bulk and around the mammalian cells will determine the response of the sensor. However, we anticipate the following problems:

  1. If the concentration of the protein LuxR is too high, the leakiness of the promoter might self activate the sensor too quickly.
  2. If AHL diffuses in the nano well plate too fast, the fluctuations in the concentration of e coli cells might not be detected by the quorum sensing module.

The reaction-diffusion model is meant to answer these questions. Click here for reaction diffusion models