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

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                         <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>

Revision as of 11:51, 18 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
  • 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 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.