Team:Tokyo Tech/Modeling/Incoherent Feed Forward Loop

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<p style="line-height:0em; text-indent:0em;">Incoherent Feed Forward Loop Modeling</p>
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<p style="line-height:0em; text-indent:0em;" name="top">Incoherent Feed Forward Loop Modeling</p>
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<h1>1. Introduction</h1>
<h1>1. Introduction</h1>
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<h2><p>In order to achieve the natural plants’ temporal pattern for producing plant hormones in <i>E. coli</i>, we introduced an incoherent feed forward loop, including new hybrid promoter part ([http://parts.igem.org/Part:BBa_K1139150 BBa_K1139150]).  
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<h2><p>In order to achieve the natural plants' temporal pattern for producing plant hormones in <i>E. coli</i>, we introduced an incoherent feed forward loop to our circuit, including a new hybrid promoter part ([http://parts.igem.org/Part:BBa_K1139150 BBa_K1139150]).  
</p>
</p>
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<p>The system of our designed incoherent feed forward loop is shown in Fig. 4-2-1.  We newly developed PRM/lac hybrid promoter, which is activated by CI and repressed by LacI (Fig. 4-2-2).  We plan to ligate a hormone synthase part downstream of this hybrid promoter.  While PRM/lac activation by CI is a single-step reaction, repression by LacI is a two-step reaction.  Thus, the activation of PRM/lac is faster than its repression.  This time lag between activation and repression is important for generating a temporal pattern of plant hormone production.
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<p>Our designed system with an incoherent feed forward loop is shown in Fig. 4-2-1.  We newly developed <i>RM/lac</i> hybrid promoter, which is activated by CI and repressed by LacI (Fig. 4-2-2).  We planned to ligate a plant hormone synthase part downstream of this hybrid promoter.  While the <i>RM/lac</i> hybrid promoter activation by CI is a single-step reaction, the repression by LacI is a two-step reaction.  Thus, the activation of <i>RM/lac</i> hybrid promoter is faster than the repression.  This time lag between the activation and the repression is important for generating a temporal pattern of plant hormone production.
</p></h2>
</p></h2>
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[[Image:Titech2013_IFFL_Fig_4-2-1_Our_designed_incoherent_feed_forward_loop.png|400px|thumb|left|Fig. 4-2-1. Our designed incoherent feed forward loop]]
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[[Image:Titech2013_IFFL_Fig_4-2-1_Our_designed_incoherent_feed_forward_loop.png|400px|thumb|left|Fig. 4-2-1. Our designed system with an incoherent feed forward loop]]
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[[Image:Titech2013_IFFL_Fig_4-2-2_Our new_designed_hybrid_promoter.png|400px|thumb|left|Fig. 4-2-2. Our new designed hybrid promoter]]
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[[Image:Titech2013_IFFL_Fig_4-2-2_Our new_designed_hybrid_promoter.png|400px|thumb|left|Fig. 4-2-2. Our newly designed hybrid promoter]]
<h2>
<h2>
<p>
<p>
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By following mathematical model, we predicted that we can achieve pulse-generation of cytokinin as output, using nitric acid (NO<sub>3</sub><sup>-</sup>) as input. In addition, we analyzed the relation between the waveform and the expression level of LacI.
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By the following mathematical model, we predicted that we can achieve pulse-generation of cytokinin as an output, using nitric acid (NO<sub>3</sub><sup>-</sup>) as an input. In addition, we analyzed the relation between the waveform and the expression level of LacI.
</p></h2>
</p></h2>
<h1>2. Dynamic behavior of our circuit</h1>
<h1>2. Dynamic behavior of our circuit</h1>
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Our model is described by the following differential equations based on Hill equation.
Our model is described by the following differential equations based on Hill equation.
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</p>
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[[Image:Titech2013_IFFL_Fig_4-2-3_Equations_for_our_modeling.png|500px|thumb|center|Fig. 4-2-3. Our Equations for our modeling]]
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[[Image:Titech2013_IFFL_Fig_4-2-3_Equations_for_our_modeling.png|500px|thumb|center|Fig. 4-2-3. Equations for our modeling]]
<p>
<p>
We will explain each equation.
We will explain each equation.
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[[Image:Titech2013_IFFL_Fig_4-2-5_Equation_of_CI_and_LacI.png|500px|thumb|center|Fig. 4-2-5. Equations of CI and LacI]]
[[Image:Titech2013_IFFL_Fig_4-2-5_Equation_of_CI_and_LacI.png|500px|thumb|center|Fig. 4-2-5. Equations of CI and LacI]]
<p>
<p>
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Finally, behavior of PRM/lac hybrid promoter is shown as multiplication of activation by CI and repression by LacI. Therefore, the dynamics of cytokinin is described by equation (4).
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Finally, behavior of <i>RM/lac</i> hybrid promoter is shown as multiplication of the activation by CI and the repression by LacI. Therefore, the dynamics of cytokinin is described by equation (4).
</p>
</p>
[[Image:Titech2013_IFFL_Fig_4-2-6_Equation_of_cytokinin.png|500px|thumb|center|Fig. 4-2-6. Equation of cytokinin]]
[[Image:Titech2013_IFFL_Fig_4-2-6_Equation_of_cytokinin.png|500px|thumb|center|Fig. 4-2-6. Equation of cytokinin]]
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[[Image:Titech2013_IFFL_Fig_4-2-7_Descriptions_of_parameters.png|700px|thumb|center|Fig. 4-2-7. Descriptions of the parameters]]
[[Image:Titech2013_IFFL_Fig_4-2-7_Descriptions_of_parameters.png|700px|thumb|center|Fig. 4-2-7. Descriptions of the parameters]]
<p>
<p>
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The values of parameters are set as follows:
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The values of the parameters are set as follows:
</p>
</p>
[[Image:Titech2013_IFFL_Fig_4-2-8_Values_of_the_parameters.png|500px|thumb|center|Fig. 4-2-8. Values of the parameters]]
[[Image:Titech2013_IFFL_Fig_4-2-8_Values_of_the_parameters.png|500px|thumb|center|Fig. 4-2-8. Values of the parameters]]
</h2>
</h2>
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<h3>2-2. Simulation results of incoherent feed forward loop</h3>
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<h3>2-2. Simulation results of the incoherent feed forward loop</h3>
<h2><p>
<h2><p>
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Fig. 4-2-9 shows the simulation results about the relation between input (NO<sub>3</sub><sup>-</sup>) and output (cytokinin) in our circuit. The red line represent the concentration of NO<sub>3</sub><sup>-</sup>, the green line represents the concentration of cytokinin.
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Fig. 4-2-9 shows the simulation results about the relation between the input (NO<sub>3</sub><sup>-</sup>) and the output (cytokinin) in our circuit. The red line represents the concentration of NO<sub>3</sub><sup>-</sup>, the green line represents the concentration of cytokinin.
</p>
</p>
[[Image:Titech2013_IFFL_Fig_4-2-9_Time-dependent_change_of_the_concentrations_of_NO3-_and_cytokinin.png|500px|thumb|center|Fig. 4-2-9. Time-dependent change of the concentrations of NO<sub>3</sub><sup>-</sup> and cytokinin]]
[[Image:Titech2013_IFFL_Fig_4-2-9_Time-dependent_change_of_the_concentrations_of_NO3-_and_cytokinin.png|500px|thumb|center|Fig. 4-2-9. Time-dependent change of the concentrations of NO<sub>3</sub><sup>-</sup> and cytokinin]]
<p>
<p>
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As shown in Fig. 4-2-9, we verified the pulse-generation of cytokinin as the output with an input of nitric acid NO<sub>3</sub><sup>-</sup>. We will discuss the process of the pulse-generation by looking at the expression level of each substance.
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As shown in Fig. 4-2-9, we verified the pulse-generation of cytokinin as the output. We will discuss the process of the pulse-generation by looking at the expression level of each substance.
</p>
</p>
<p>
<p>
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First, NO<sub>3</sub><sup>-</sup> as an input activates CI. CI continues to increase until the input is completely degraded because the expression level of CI depends on the volume of the input (Fig. 4-2-10.).
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First, NO<sub>3</sub><sup>-</sup> as an input activates CI. CI continues to increase until the input is completely degraded because the expression level of CI depends on the volume of the input (Fig. 4-2-10).
</p>
</p>
[[Image:Titech2013_IFFL_Fig_4-2-10_Time-dependent_change_of_the_concentrations_of_NO3-_and_CI.png|500px|thumb|center|Fig. 4-2-10. Time-dependent change of the concentrations of NO<sub>3</sub><sup>-</sup> and CI]]
[[Image:Titech2013_IFFL_Fig_4-2-10_Time-dependent_change_of_the_concentrations_of_NO3-_and_CI.png|500px|thumb|center|Fig. 4-2-10. Time-dependent change of the concentrations of NO<sub>3</sub><sup>-</sup> and CI]]
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Next, Fig. 4-2-11 shows that LacI and cytokinin are activated by CI. Also, in Fig. 4-2-12, which shows the enlarged view of Fig. 4-2-11 around 0 min., LacI is expressed after the expression of CI.
Next, Fig. 4-2-11 shows that LacI and cytokinin are activated by CI. Also, in Fig. 4-2-12, which shows the enlarged view of Fig. 4-2-11 around 0 min., LacI is expressed after the expression of CI.
</p>
</p>
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[[Image:Titech2013_IFFL_Fig_4-2-11_Time-dependent_change_of_the_concentrations_of_CI%2C_LacI%2C_cytokinin.png|500px|thumb|center|Fig. 4-2-11. Time-dependent change of the concentrations of CI, LacI, cytokinin]]
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[[Image:Titech2013_IFFL_Fig_4-2-11_Time-dependent_change_of_the_concentrations_of_CI%2C_LacI%2C_cytokinin.png|500px|thumb|center|Fig. 4-2-11. Time-dependent change of the concentrations of CI, LacI and cytokinin]]
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[[Image:Titech2013_IFFL_Fig_4-2-12_Enlarged_view_of_Fig.2.2.3.png|500px|thumb|center|Fig. 4-2-12. Enlarged view of Fig. 4-2-11.]]
[[Image:Titech2013_IFFL_Fig_4-2-12_Enlarged_view_of_Fig.2.2.3.png|500px|thumb|center|Fig. 4-2-12. Enlarged view of Fig. 4-2-11.]]
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Finally, Fig. 4-2-11 also shows that cytokinin is repressed by LacI after it is activated by CI. Cytokinin is expressed during this time lag between the activation and the repression.  
Finally, Fig. 4-2-11 also shows that cytokinin is repressed by LacI after it is activated by CI. Cytokinin is expressed during this time lag between the activation and the repression.  
</p></h2>
</p></h2>
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<h3>2-3. Relation between the waveform and the maximum level of LacI expression</h3>
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<h3>2-3. Relation between the waveform and the maximum level <br><div align="right">of the LacI expression</div></h3>
<h2>
<h2>
<p>
<p>
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In 2-2, we confirmed that the expression of LacI is deeply concerned with the expression of cytokinin. Here, we analyze the waveform of cytokinin output by changing the maximum level of LacI expression (alpha2).  
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In 2-2, we confirmed that the expression of LacI is deeply concerned with the expression of cytokinin. Here, we analyzed the waveform of the cytokinin output by changing the maximum level of the LacI expression (α2).  
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Fig 4-2-13 shows the change in the waveforms of cytokinin depending on the maximum level of LacI expression.
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Fig. 4-2-13 shows the change in the waveforms of cytokinin depending on the maximum level of LacI expression.
</p>
</p>
[[Image:Titech2013_IFFL_Fig_4-2-13_Waveforms_of_cytokinin_depending_on_the_maximum_level_of_LacI_expression.png|500px|thumb|center|Fig. 4-2-13. Waveforms of cytokinin depending on the maximum level of LacI expression]]
[[Image:Titech2013_IFFL_Fig_4-2-13_Waveforms_of_cytokinin_depending_on_the_maximum_level_of_LacI_expression.png|500px|thumb|center|Fig. 4-2-13. Waveforms of cytokinin depending on the maximum level of LacI expression]]
<p>
<p>
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We see that the waveform of cytokinin output changes depending on the maximum level of LacI expression. In considering the application of this system, we predict that we can adapt the output waveforms to the circumstances of plants.  
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We see that the waveform of the cytokinin output changes depending on the maximum level of the LacI expression. In considering the application of this system, we predict that we can adapt the output waveforms to the circumstances of plants.  
</p>
</p>
</h2>
</h2>
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<h2>
<h2>
<p>
<p>
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Here, we will predict the activity of LacI by considering IPTG, which represses LacI. Decreasing of LacI activity is described by equation (5).  
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Here, we will predict the activity of LacI by considering the volume of IPTG, which represses LacI. Decrease in LacI activity is described by equation (5) (γ denotes the decay rate constant.).
</p>
</p>
[[Image:Titech2013_IFFL_Fig_4-2-14_Equation_of_decreasing_LacI_activity.png|500px|thumb|center|Fig. 4-2-14. Equation of decreasing LacI activity]]
[[Image:Titech2013_IFFL_Fig_4-2-14_Equation_of_decreasing_LacI_activity.png|500px|thumb|center|Fig. 4-2-14. Equation of decreasing LacI activity]]
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[[Image:Titech2013_IFFL_Fig_4-2-15_Equation_of_cytokinin_led_from_equation_(4)_and_(5).png|500px|thumb|center|Fig. 4-2-15. Equation of cytokinin led from equation (4) and (5)]]
[[Image:Titech2013_IFFL_Fig_4-2-15_Equation_of_cytokinin_led_from_equation_(4)_and_(5).png|500px|thumb|center|Fig. 4-2-15. Equation of cytokinin led from equation (4) and (5)]]
<p>
<p>
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Shown in equation (6), pulse width of the cytokinin expression can be controlled by external IPTG. In simulation by changing the value of gamma, we obtained the result shown in Fig. 4-2-16.
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Shown in equation (6), the pulse width of the cytokinin expression can be controlled by external IPTG. In the simulation by changing the value of γ, we obtained the result shown in Fig. 4-2-16.
</p>
</p>
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[[Image:Titech2013_IFFL_Fig_4-2-16_Changes_of_cytokinin_expression_time_controlled_by_IPTG.png|500px|thumb|center|Fig. 4-2-16. Changes of cytokinin expression time controlled by IPTG]]
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[[Image:Titech2013_IFFL_Fig_4-2-16_Changes_of_cytokinin_expression_time_controlled_by_IPTG.png|500px|thumb|center|Fig. 4-2-16. Changes of the cytokinin expression time controlled by IPTG]]
<p>
<p>
Therefore, we confirmed that the pulse width of the cytokinin expression can be controlled by the volume of IPTG.
Therefore, we confirmed that the pulse width of the cytokinin expression can be controlled by the volume of IPTG.
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Latest revision as of 10:49, 28 October 2013


Incoherent Feed Forward Loop Modeling

Contents

1. Introduction

In order to achieve the natural plants' temporal pattern for producing plant hormones in E. coli, we introduced an incoherent feed forward loop to our circuit, including a new hybrid promoter part ([http://parts.igem.org/Part:BBa_K1139150 BBa_K1139150]).

Our designed system with an incoherent feed forward loop is shown in Fig. 4-2-1. We newly developed RM/lac hybrid promoter, which is activated by CI and repressed by LacI (Fig. 4-2-2). We planned to ligate a plant hormone synthase part downstream of this hybrid promoter. While the RM/lac hybrid promoter activation by CI is a single-step reaction, the repression by LacI is a two-step reaction. Thus, the activation of RM/lac hybrid promoter is faster than the repression. This time lag between the activation and the repression is important for generating a temporal pattern of plant hormone production.

Fig. 4-2-1. Our designed system with an incoherent feed forward loop
Fig. 4-2-2. Our newly designed hybrid promoter

By the following mathematical model, we predicted that we can achieve pulse-generation of cytokinin as an output, using nitric acid (NO3-) as an input. In addition, we analyzed the relation between the waveform and the expression level of LacI.

2. Dynamic behavior of our circuit

2-1. Building a mathematical model

Our model is described by the following differential equations based on Hill equation.

Fig. 4-2-3. Equations for our modeling

We will explain each equation.

As for NO3-, we only take the degradation into consideration, assuming that NO3- act directly on nitrate promoter.

Fig. 4-2-4. Equation of NO3-

CI is activated by NO3-, LacI is activated by CI. Behaviors of CI and LacI are described by equation (2) and (3).

Fig. 4-2-5. Equations of CI and LacI

Finally, behavior of RM/lac hybrid promoter is shown as multiplication of the activation by CI and the repression by LacI. Therefore, the dynamics of cytokinin is described by equation (4).

Fig. 4-2-6. Equation of cytokinin

We set the parameters as follows:

Fig. 4-2-7. Descriptions of the parameters

The values of the parameters are set as follows:

Fig. 4-2-8. Values of the parameters

2-2. Simulation results of the incoherent feed forward loop

Fig. 4-2-9 shows the simulation results about the relation between the input (NO3-) and the output (cytokinin) in our circuit. The red line represents the concentration of NO3-, the green line represents the concentration of cytokinin.

Fig. 4-2-9. Time-dependent change of the concentrations of NO3- and cytokinin

As shown in Fig. 4-2-9, we verified the pulse-generation of cytokinin as the output. We will discuss the process of the pulse-generation by looking at the expression level of each substance.

First, NO3- as an input activates CI. CI continues to increase until the input is completely degraded because the expression level of CI depends on the volume of the input (Fig. 4-2-10).

Fig. 4-2-10. Time-dependent change of the concentrations of NO3- and CI

Next, Fig. 4-2-11 shows that LacI and cytokinin are activated by CI. Also, in Fig. 4-2-12, which shows the enlarged view of Fig. 4-2-11 around 0 min., LacI is expressed after the expression of CI.

Fig. 4-2-11. Time-dependent change of the concentrations of CI, LacI and cytokinin


Fig. 4-2-12. Enlarged view of Fig. 4-2-11.

Finally, Fig. 4-2-11 also shows that cytokinin is repressed by LacI after it is activated by CI. Cytokinin is expressed during this time lag between the activation and the repression.

2-3. Relation between the waveform and the maximum level
of the LacI expression

In 2-2, we confirmed that the expression of LacI is deeply concerned with the expression of cytokinin. Here, we analyzed the waveform of the cytokinin output by changing the maximum level of the LacI expression (α2). Fig. 4-2-13 shows the change in the waveforms of cytokinin depending on the maximum level of LacI expression.

Fig. 4-2-13. Waveforms of cytokinin depending on the maximum level of LacI expression

We see that the waveform of the cytokinin output changes depending on the maximum level of the LacI expression. In considering the application of this system, we predict that we can adapt the output waveforms to the circumstances of plants.

2-4. Relation between the output waveform and IPTG

Here, we will predict the activity of LacI by considering the volume of IPTG, which represses LacI. Decrease in LacI activity is described by equation (5) (γ denotes the decay rate constant.).

Fig. 4-2-14. Equation of decreasing LacI activity

Substituting equation (5) for equation (4), we obtain equation (6).

Fig. 4-2-15. Equation of cytokinin led from equation (4) and (5)

Shown in equation (6), the pulse width of the cytokinin expression can be controlled by external IPTG. In the simulation by changing the value of γ, we obtained the result shown in Fig. 4-2-16.

Fig. 4-2-16. Changes of the cytokinin expression time controlled by IPTG

Therefore, we confirmed that the pulse width of the cytokinin expression can be controlled by the volume of IPTG.