Difference between revisions of "Team:HUST-China/Model/model-euk"

 
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                         <li class="dropdown1"><a class="down-scroll active" href="https://2016.igem.org/Team:HUST-China/Model">MODELING</a>
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                    <li><a href="https://2016.igem.org/Team:HUST-China/Model">Overview</a></li>
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                                <li><a href="https://2016.igem.org/Team:HUST-China/Model">Overview</a></li>
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                    <li><a href="https://2016.igem.org/Team:HUST-China/Model/model-pro">Prokaryotic circuit</a></li>
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                    <li><a href="https://2016.igem.org/Team:HUST-China/Model/model-euk">Eukaryotic circuit</a></li>
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                                <li><a href="https://2016.igem.org/Team:HUST-China/Model/model-euk">Eukaryotic circuit</a></li>
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                    <li><a href="https://2016.igem.org/Team:HUST-China/Model/model-app">Application circuit</a></li>
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                         <!-- <h3>Web Lab</h3> -->
 
                         <!-- <h3>Web Lab</h3> -->
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<table class="tableizer-table" style="margin: 0 auto;">
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<thead><tr class="tableizer-firstrow"><th>Parameter</th><th>Description </th></tr></thead><tbody>
 +
<tr><td>trc pulseoff</td><td>rate of pulseoff transcription </td></tr>
 +
<tr><td>trc pulseon</td><td>rate of pulseon transcription</td></tr>
 +
<tr><td>copynum</td><td>copy number of plasmid</td></tr>
 +
<tr><td>trc 1</td><td>rate of ABF2 transcription</td></tr>
 +
<tr><td>trl pp2cs</td><td>rate of pp2cs translation </td></tr>
 +
<tr><td>trl snRk</td><td>rate of snRk translation </td></tr>
 +
<tr><td>trl ABF2</td><td>rate of ABF2 translation </td></tr>
 +
<tr><td>trl Gene</td><td>rate of Gene_of_interset translation </td></tr>
 +
<tr><td>deg mPP2Cs</td><td>rate of mPP2C degradation </td></tr>
 +
<tr><td>deg mSnRk2.2 </td><td>rate of mSnRk2.2  degradation </td></tr>
 +
<tr><td>deg mABF2</td><td>rate of mABF2 degradation </td></tr>
 +
<tr><td>deg mGene</td><td>rate of mGene_of_interset degradation </td></tr>
 +
<tr><td>deg pp2cs</td><td>rate of pp2cs degradation </td></tr>
 +
<tr><td>deg snRk</td><td>rate of snRk degradation </td></tr>
 +
<tr><td>deg ABF2</td><td>rate of ABF2 degradation </td></tr>
 +
<tr><td>deg Gene</td><td>rate of Gene_of_interset degradation </td></tr>
 +
<tr><td>Vmax mSnRk2.2 </td><td>maximum transcription rate of promoter RD29A</td></tr>
 +
<tr><td>Vmax mgene</td><td>maximum transcription rate of promoter RD29A</td></tr>
 +
<tr><td>KmABF2</td><td>apparent association constant for ABF2 binding with RD29A</td></tr>
 +
<tr><td>Vmax ABF2</td><td>maxinum rate of Phosphorylation</td></tr>
 +
<tr><td>Vmax PP2C</td><td>maxinum rate of Dephosphorylation</td></tr>
 +
<tr><td>KmSnRK</td><td>Michaelis-Menten constant of Phosphorylation</td></tr>
 +
<tr><td>KmPP2C</td><td>Michaelis-Menten constant of Dephosphorylation</td></tr>
 +
</tbody></table></p>
 +
<p><a href="https://static.igem.org/mediawiki/2016/5/50/T--HUST-China--model-program-eukaryotic.xlsx" style="text-decoration:none"><button type="button" class="btn btn-info center-block"> Click to download our parameter </button></a></p>
 
                     </div>
 
                     </div>
 
                     <li>
 
                     <li>
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                 <p>We have only on/off states of the eukaryotic system, so the complexity of this model will be lower, but it probably means that the system can have a better stability and robustness, for that reason, we will focus on the sensitivity analysis of parameters, meanwhile, validate the designed functions work out or not.</p>
 
                 <p>We have only on/off states of the eukaryotic system, so the complexity of this model will be lower, but it probably means that the system can have a better stability and robustness, for that reason, we will focus on the sensitivity analysis of parameters, meanwhile, validate the designed functions work out or not.</p>
 
                 <ul>
 
                 <ul>
 +
<li>
 +
                        <h3>Test of switch function </h3>
 +
                        <p>Before we begin to do the test, we need to find out whether our design has reached the expected goal. So we changed the signal intensity ratio of pulse on and pulse off and do the statistics of the steady-state concentration of protein under different ratio.</p>
 +
                        <img src="https://static.igem.org/mediawiki/2016/6/6a/T--HUST-China--modeling-eukaryotic-switch.png" alt="">
 +
                        <p>It is clear that there exists a distinct boundary between opened state and closed state. It can be regarded as the turning point of the system when the ratio is about 1.
 +
</p>
 +
                    </li>
 
                     <li>
 
                     <li>
 
                         <h3>Test of filter function</h3>
 
                         <h3>Test of filter function</h3>
 
                         <p>We adopted a simple sine function as input to verify the filtering performance.* (The input signal in the figure is to show the result more clearly so that we have moved the graph. The actual strength is 0.1sin（t）)</p>
 
                         <p>We adopted a simple sine function as input to verify the filtering performance.* (The input signal in the figure is to show the result more clearly so that we have moved the graph. The actual strength is 0.1sin（t）)</p>
 
                         <img src="https://static.igem.org/mediawiki/2016/4/46/T--HUST-China--modeling-eukaryotic-filtering.png" alt="">
 
                         <img src="https://static.igem.org/mediawiki/2016/4/46/T--HUST-China--modeling-eukaryotic-filtering.png" alt="">
−
                         <p>We can see that the output signal, which does not contain obvious waveform, is still stable. And the ABF2 phosphorylation/dephosphorylation of the system have played the role as the "capacity" as we analyzed before, so as to improve the filtering effect of the system.</p>
+
                         <p>We can see that the output signal, which does not contain obvious waveform, is still stable. And the ABF2 phosphorylation/dephosphorization of the system has played the role as the "capacity" as we analyzed before, so as to improve the filtering effect of the system.</p>
 
                     </li>
 
                     </li>
 
                     <li>
 
                     <li>
 
                         <h3>Parameter sensitivity analysis/robustness evaluation</h3>
 
                         <h3>Parameter sensitivity analysis/robustness evaluation</h3>
−
                         <p>The main approximate treatment in this circuit should be substrate disaggregation coefficient correction, when SnRK2.2 / PP2Cs concentration is low and supersaturated by the substrate, meanwhile, part of the substrate cannot be catalytic in time. So we mainly analyzed the velocity of substrate（mABF2） producing rate for testing the sensitivity of the parameters, which is named trc1.
</p>
+
                         <p>The main approximate treatment in this circuit should be substrate disaggregation coefficient correction, when SnRK2.2 / PP2Cs concentration is low and supersaturated by the substrate, meanwhile, part of the substrate cannot be catalytic in time. So we mainly analyzed the velocity of substrate producing rate for testing the sensitivity of the parameters, which is named trc1.
</p>
 
                         <p>Similarly, we keep pathways in the condition of open and choose to change the ratio of signal strength to find out the final expression level and the response time for analyzing.</p>
 
                         <p>Similarly, we keep pathways in the condition of open and choose to change the ratio of signal strength to find out the final expression level and the response time for analyzing.</p>
 
                         <img src="https://static.igem.org/mediawiki/2016/4/4f/T--HUST-China--modeling-eukaryotic-trc1_EX.png" alt="">
 
                         <img src="https://static.igem.org/mediawiki/2016/4/4f/T--HUST-China--modeling-eukaryotic-trc1_EX.png" alt="">
−
                         <p>The expresion level of the final production varies with the changing of trc1, but it still maintains itself in a high expresion level, which has a minor influence on our switching or the filting function. </p>
+
                         <p>The expression level of the final production varies with the changing of trc1, but it still maintains itself in a high expression level, which has a minor influence on our switching or the filtering function. </p>
 
                         <img src="https://static.igem.org/mediawiki/2016/0/04/T--HUST-China--modeling-eukaryotic-trc1.png" alt="">
 
                         <img src="https://static.igem.org/mediawiki/2016/0/04/T--HUST-China--modeling-eukaryotic-trc1.png" alt="">
−
                         <p>Even though there exist some twists in the responsing time, all the floating range is still in 10%. And our circuit shows a great stability after we enlarged the numerical value of trc1.</p>
+
                         <p>Even though there exist some twists in the responding time, all the floating range is still in 10%. And our circuit shows a great stability after we enlarged the numerical value of trc1.</p>
 
                     </li>
 
                     </li>
 
                 </ul>
 
                 </ul>
 
                 <h2>Summary</h2>
 
                 <h2>Summary</h2>
−
                 <p>Our eukaryotic pathway can be worked out as a filter and a swich in a steady way. And the analyzement of sensitivity of parameters also shows that we should use the promoter, which has much bigger velocity of transcription, to help maintain a great robustness.</p>
+
                 <p>Our eukaryotic pathway can be worked out as a filter and a swich in a steady way. And the analyze of sensitivity of parameters also shows that we should use the promoter, which has much bigger velocity of transcription, to help maintain a great robustness.</p>
 
             </article>
 
             </article>
 
         </div>
 
         </div>

Latest revision as of 17:56, 19 October 2016

Modeling

Eukaryote

This pathway has two inputs, but only has two states: the target gene expressed or not. If “Pulse on” input signal is higher than “pulse off”, it will lead to the expression of gene of interest. Otherwise, it will not lead to expression.

In order to expand our scope of the filter, we also design the eukaryotic pathway which has the function of corresponding filter/switch. Meanwhile, we also need to understand its working condition clearly.

Modeling

In this pathway, the time of spreading of the substance or each combination/response reaction, compared to the whole time scales (protein), is negligible, so we adopted simplified differential equation to simulate the pathway this time.

  • Parameter details

    more details

    • ParameterDescription
    trc pulseoffrate of pulseoff transcription
    trc pulseonrate of pulseon transcription
    copynumcopy number of plasmid
    trc 1rate of ABF2 transcription
    trl pp2csrate of pp2cs translation
    trl snRkrate of snRk translation
    trl ABF2rate of ABF2 translation
    trl Generate of Gene_of_interset translation
    deg mPP2Csrate of mPP2C degradation
    deg mSnRk2.2 rate of mSnRk2.2 degradation
    deg mABF2rate of mABF2 degradation
    deg mGenerate of mGene_of_interset degradation
    deg pp2csrate of pp2cs degradation
    deg snRkrate of snRk degradation
    deg ABF2rate of ABF2 degradation
    deg Generate of Gene_of_interset degradation
    Vmax mSnRk2.2 maximum transcription rate of promoter RD29A
    Vmax mgenemaximum transcription rate of promoter RD29A
    KmABF2apparent association constant for ABF2 binding with RD29A
    Vmax ABF2maxinum rate of Phosphorylation
    Vmax PP2Cmaxinum rate of Dephosphorylation
    KmSnRKMichaelis-Menten constant of Phosphorylation
    KmPP2CMichaelis-Menten constant of Dephosphorylation

  • Fomular

    more details

Analysis

We have only on/off states of the eukaryotic system, so the complexity of this model will be lower, but it probably means that the system can have a better stability and robustness, for that reason, we will focus on the sensitivity analysis of parameters, meanwhile, validate the designed functions work out or not.

  • Test of switch function

    Before we begin to do the test, we need to find out whether our design has reached the expected goal. So we changed the signal intensity ratio of pulse on and pulse off and do the statistics of the steady-state concentration of protein under different ratio.

    It is clear that there exists a distinct boundary between opened state and closed state. It can be regarded as the turning point of the system when the ratio is about 1.

  • Test of filter function

    We adopted a simple sine function as input to verify the filtering performance.* (The input signal in the figure is to show the result more clearly so that we have moved the graph. The actual strength is 0.1sin（t）)

    We can see that the output signal, which does not contain obvious waveform, is still stable. And the ABF2 phosphorylation/dephosphorization of the system has played the role as the "capacity" as we analyzed before, so as to improve the filtering effect of the system.

  • Parameter sensitivity analysis/robustness evaluation

    The main approximate treatment in this circuit should be substrate disaggregation coefficient correction, when SnRK2.2 / PP2Cs concentration is low and supersaturated by the substrate, meanwhile, part of the substrate cannot be catalytic in time. So we mainly analyzed the velocity of substrate producing rate for testing the sensitivity of the parameters, which is named trc1.


    Similarly, we keep pathways in the condition of open and choose to change the ratio of signal strength to find out the final expression level and the response time for analyzing.

    The expression level of the final production varies with the changing of trc1, but it still maintains itself in a high expression level, which has a minor influence on our switching or the filtering function.

    Even though there exist some twists in the responding time, all the floating range is still in 10%. And our circuit shows a great stability after we enlarged the numerical value of trc1.

Summary

Our eukaryotic pathway can be worked out as a filter and a swich in a steady way. And the analyze of sensitivity of parameters also shows that we should use the promoter, which has much bigger velocity of transcription, to help maintain a great robustness.