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<p style="font-family: quicksand;font-size:150%;">Background </p> | <p style="font-family: quicksand;font-size:150%;">Background </p> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | According to Green <i>et al.</i> (2014) [1], the optimal length of RNA to be detected by a toehold switch is around 30 bp (complementary region at below figure). In other words, a target RNA with 1000 bp in length can have 970 possible switches with different performance, which is governed by their structures and thermodynamic parameters. We aim at providing a workflow and platform of modeling to help users design the switches by reducing the manual processing and increasing the hit-rate of finding a good switch. | + | According to Green <i>et al.</i> (2014) [1], the optimal length of RNA to be detected by a toehold switch is around 30 bp (complementary region at below figure). In other words, a target RNA with 1000 bp in length can have 970 possible switches with different performance, which is governed by their structures and thermodynamic parameters. <strong>We aim at providing a workflow and platform of modeling to help users design the switches by reducing the manual processing and increasing the hit-rate of finding a good switch.</strong> |
+ | |||
<br> | <br> | ||
<br> | <br> | ||
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<div class="column full_size"> | <div class="column full_size"> | ||
<p style="font-family: quicksand;font-size:150%;">RNA thermodynamic Modelling</p> | <p style="font-family: quicksand;font-size:150%;">RNA thermodynamic Modelling</p> | ||
+ | |||
+ | <center><img src="https://static.igem.org/mediawiki/2017/9/90/Toehold_Switch_Model.jpeg" width="100%" height="auto" class=" igem-logo"></center> | ||
+ | <p style="font-family: roboto;font-size:115%;"> | ||
+ | |||
<p style="font-family: roboto;font-size:125%;color:blue"><b>Assumption 1: Switch MFE (Minimum Free Energy) correlates with the expression leakage</p></b> | <p style="font-family: roboto;font-size:125%;color:blue"><b>Assumption 1: Switch MFE (Minimum Free Energy) correlates with the expression leakage</p></b> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
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<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
● ΔG<sub>RBS-Linker</sub> is the Gibbs free energy of the RNA sequence starting from the RBS to the linker in the switch-trigger duplex.<br> | ● ΔG<sub>RBS-Linker</sub> is the Gibbs free energy of the RNA sequence starting from the RBS to the linker in the switch-trigger duplex.<br> | ||
− | ● The duplex expression is the reporter expression of the switch-trigger | + | ● The duplex expression is the reporter expression of the switch-trigger duplex RNA. |
<br> | <br> | ||
− | After the switch RNA hairpin is unwound after binding to the trigger RNA, a switch-trigger | + | After the switch RNA hairpin is unwound after binding to the trigger RNA, a switch-trigger duplex RNA would be formed. The RBS-linker region of the MFE structure of this duplex RNA should have minimal base pairs. This makes it easier to unwind the RNA for this region, allowing ribosomes to bind to the RBS and move along the RNA for translation of the RFP reporter gene to occur. ΔG<sub>RBS-Linker</sub> reflects the difficulty for the unwinding process of the RBS-linker region. It is assumed that the more negative the ΔG<sub>RBS-Linker</sub> , the harder it is for the unwinding to take place, leading to lower translation rates. Thus, the duplex expression would be reduced. |
<br><br> | <br><br> | ||
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Since ΔMFE = –RTlnK, where: | Since ΔMFE = –RTlnK, where: | ||
<br> | <br> | ||
− | R= | + | R = Gas constant |
<br> | <br> | ||
− | T= | + | T = Temperature |
<br> | <br> | ||
− | K= | + | K = Equilibrium constant |
<br> | <br> | ||
Therefore, we assume that the more negative the MFE difference is, the higher the switch-trigger duplex RNA concentration compared to that of the switch RNA when in equilibrium. | Therefore, we assume that the more negative the MFE difference is, the higher the switch-trigger duplex RNA concentration compared to that of the switch RNA when in equilibrium. | ||
<br> | <br> | ||
− | <p style="font-family: roboto;font-size: | + | <p style="font-family: roboto;font-size:130%;"><center>Switch RNA + Trigger RNA ↔ Switch-Trigger Duplex</center></p> |
− | + | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
Consequently, increased equilibrium concentrations of the switch-trigger duplex RNA would provide an increased number of active mRNAs for the translation of the reporter RFP. | Consequently, increased equilibrium concentrations of the switch-trigger duplex RNA would provide an increased number of active mRNAs for the translation of the reporter RFP. | ||
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<div class="column full_size"> | <div class="column full_size"> | ||
− | <p style="font-family: quicksand;font-size:150%;"> | + | <p style="font-family: quicksand;font-size:150%;">Initial screening using our software</p> |
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | To minimize the manpower on screening of the switches, we constructed an online toehold switch design program. Apart from basic thermodynamic parameters, it also screens for other factors(please visit our <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Software"> software page </a>. Ultimately, the program generated a list of possible toehold switch sequences according to many different free energy parameters using the <a href="http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/barriers.cgi">ViennaRNA package</a>[2]. The graph below shows 394 possible H5 toehold switches generated by our software. The assumptions motioned earlier stated 3 very important parameters for the selection of switch candidates with the greatest possible performances: Switch MFE, ΔG<sub>RBS-linker</sub>, and ΔMFE. We applied these parameters to our switch selection process: We first chose the switches that with the highest ΔG<sub>RBS-linker</sub> (-3.8 kcal/mol). Among those switches, we chose the 3 switches with the lowest switch MFE and the highest ΔMFE. | + | To minimize the manpower on screening of the switches, we constructed an online toehold switch design program. Apart from basic thermodynamic parameters, it also screens for other factors(please visit our <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Software"> software page</a>. Ultimately, the program generated a list of possible toehold switch sequences according to many different free energy parameters using the <a href="http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/barriers.cgi">ViennaRNA package</a> [2]. The graph below shows 394 possible H5 toehold switches generated by our software. The assumptions motioned earlier stated 3 very important parameters for the selection of switch candidates with the greatest possible performances: Switch MFE, ΔG<sub>RBS-linker</sub>, and ΔMFE. We applied these parameters to our switch selection process: We first chose the switches that with the highest ΔG<sub>RBS-linker</sub> (-3.8 kcal/mol). Among those switches, we chose the 3 switches with the lowest switch MFE and the highest ΔMFE. |
</p> | </p> | ||
− | |||
− | <p><center><img src="https://static.igem.org/mediawiki/2017/7/78/CUHK_softwarecandidate.jpg" width=" | + | <p><center><img src="https://static.igem.org/mediawiki/2017/7/78/CUHK_softwarecandidate.jpg" width="40%" height="auto" ></center></p> |
<br><br><br> | <br><br><br> | ||
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<td>H5-3</td> | <td>H5-3</td> | ||
<td>-3.8</td> | <td>-3.8</td> | ||
− | <td>-24</td> | + | <td>-24.0</td> |
<td>+37.9</td> | <td>+37.9</td> | ||
</tr> | </tr> | ||
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<td>-3.8</td> | <td>-3.8</td> | ||
<td>-17.1</td> | <td>-17.1</td> | ||
− | <td>+24</td> | + | <td>+24.0</td> |
</tr> | </tr> | ||
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<td>-3.8</td> | <td>-3.8</td> | ||
<td>-21.6</td> | <td>-21.6</td> | ||
− | <td>+27</td> | + | <td>+27.0</td> |
</tr> | </tr> | ||
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<td>-3.8</td> | <td>-3.8</td> | ||
<td>-24.7</td> | <td>-24.7</td> | ||
− | <td>+38</td> | + | <td>+38.0</td> |
</tr> | </tr> | ||
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<td>PB2-3</td> | <td>PB2-3</td> | ||
<td>-3.8</td> | <td>-3.8</td> | ||
− | <td>-16</td> | + | <td>-16.0</td> |
<td>+28.2</td> | <td>+28.2</td> | ||
</tr> | </tr> | ||
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<div class="column full_size"> | <div class="column full_size"> | ||
<p style="font-family: quicksand;font-size:150%;">Suboptimal Structure Modelling</p> | <p style="font-family: quicksand;font-size:150%;">Suboptimal Structure Modelling</p> | ||
− | <p style="font-family: roboto;font-size:125%;" | + | <p style="font-family: roboto;font-size:125%;color:blue"><b>Assumption 4: Accessibility of toehold domain correlates with the performance of switch</p></u> |
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | ● The toehold domain (first 15 | + | ● The toehold domain (first 15 nts) of the switch RNA is crucial for the binding of the trigger RNA to the switch RNA to initiate the switch-unwinding process: |
− | |||
− | |||
Toehold domain must have minimal paired bases in the switch RNA to ensure the successful binding of this domain with the complementary sequence in the trigger RNA, which allows the unwinding of the switch RNA and permits translation of the reporter protein, RFP, to occur. </p> | Toehold domain must have minimal paired bases in the switch RNA to ensure the successful binding of this domain with the complementary sequence in the trigger RNA, which allows the unwinding of the switch RNA and permits translation of the reporter protein, RFP, to occur. </p> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | Our program can only calculate the minimal free energy | + | Our program can only calculate the structure with the minimal free energy (MFE) for each target RNA region to reduce calculation workload. In reality, different conformations of RNAs with the same sequence co-exist in solution, and the concentrations of those populations are determined by their structures and free energy. Therefore, we manually checked the predicted structures and equilibrium concentrations of the ten suboptimal structures of each influenza switches with the lowest MFEs on the web tool developed by <a href="http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/barriers.cgi">ViennaRNA package</a> [2]. Then we predicted the performance of each influenza switches and compared with the experimental results.</p> |
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
The table below shows the different suboptimal structures of each switch RNA sequence:</p> | The table below shows the different suboptimal structures of each switch RNA sequence:</p> | ||
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<td>H5-1</td> | <td>H5-1</td> | ||
<td><font color="red">1, 6, 7,</font> <font color="green">2</font></td> | <td><font color="red">1, 6, 7,</font> <font color="green">2</font></td> | ||
− | <td> | + | <td>Low</td> |
− | <td>11.676366 ( | + | <td>11.676366 (Low)</td> |
− | <td> | + | <td>True Negative</td> |
</tr> | </tr> | ||
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<td>H5-2</td> | <td>H5-2</td> | ||
<td><font color="red">1, 2, 3, 4,</font> <font color="green">5</font></td> | <td><font color="red">1, 2, 3, 4,</font> <font color="green">5</font></td> | ||
− | <td> | + | <td>Low</td> |
− | <td>38.24207 ( | + | <td>38.24207 (Low)</td> |
− | <td> | + | <td>True Negative</td> |
</tr> | </tr> | ||
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− | <td> | + | <td>Low</td> |
<td>13.34770467 (low)</td> | <td>13.34770467 (low)</td> | ||
− | <td> | + | <td>True Negative</td> |
</tr> | </tr> | ||
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<td>H7-1</td> | <td>H7-1</td> | ||
<td><font color="red">1, 2, 3, 4</font> <font color="green"></font></td> | <td><font color="red">1, 2, 3, 4</font> <font color="green"></font></td> | ||
− | <td> | + | <td>Low</td> |
− | <td>10.82038167 ( | + | <td>10.82038167 (Low)</td> |
− | <td> | + | <td>True Negative</td> |
</tr> | </tr> | ||
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<td>H7-2</td> | <td>H7-2</td> | ||
<td><font color="red">1, 3,</font> <font color="green">2, 7</font></td> | <td><font color="red">1, 3,</font> <font color="green">2, 7</font></td> | ||
− | <td> | + | <td>Low</td> |
− | <td>8.577606333 ( | + | <td>8.577606333 (Low)</td> |
− | <td> | + | <td>True Negative</td> |
</tr> | </tr> | ||
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<td>H7-3</td> | <td>H7-3</td> | ||
<td><font color="red"></font> <font color="green">1, 2</font></td> | <td><font color="red"></font> <font color="green">1, 2</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>637.066 ( | + | <td>637.066 (High)</td> |
− | <td> | + | <td>True Positive</td> |
</tr> | </tr> | ||
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<td>N1-1</td> | <td>N1-1</td> | ||
<td><font color="red"></font> <font color="green">1, 2</font></td> | <td><font color="red"></font> <font color="green">1, 2</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>204.7757333 ( | + | <td>204.7757333 (High)</td> |
− | <td> | + | <td>True Positive</td> |
</tr> | </tr> | ||
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<td>N1-2</td> | <td>N1-2</td> | ||
<td><font color="red">1, 2</font> <font color="green"></font></td> | <td><font color="red">1, 2</font> <font color="green"></font></td> | ||
− | <td> | + | <td>Low</td> |
− | <td>9.325934 ( | + | <td>9.325934 (Low)</td> |
− | <td> | + | <td>True Negative</td> |
</tr> | </tr> | ||
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<td>N1-3</td> | <td>N1-3</td> | ||
<td><font color="red"></font> <font color="green">1, 2</font></td> | <td><font color="red"></font> <font color="green">1, 2</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>9.148810667 ( | + | <td>9.148810667 (Low)</td> |
− | <td> | + | <td><em>False Positive</em></td> |
</tr> | </tr> | ||
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<td>N9-1</td> | <td>N9-1</td> | ||
<td><font color="red"></font> <font color="green">1, 2, 3</font></td> | <td><font color="red"></font> <font color="green">1, 2, 3</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>166.49639 ( | + | <td>166.49639 (High)</td> |
− | <td> | + | <td>True Positive</td> |
</tr> | </tr> | ||
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<td>N9-2</td> | <td>N9-2</td> | ||
<td><font color="red"></font> <font color="green">1, 2, 6</font></td> | <td><font color="red"></font> <font color="green">1, 2, 6</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>604.2225333 ( | + | <td>604.2225333 (High)</td> |
− | <td> | + | <td>True Positive</td> |
</tr> | </tr> | ||
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<td>N9-3</td> | <td>N9-3</td> | ||
<td><font color="red"></font> <font color="green">1</font></td> | <td><font color="red"></font> <font color="green">1</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>10.587811 ( | + | <td>10.587811 (Low)</td> |
− | <td> | + | <td><em>False Positive</em></td> |
</tr> | </tr> | ||
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<td>PB2-1</td> | <td>PB2-1</td> | ||
<td><font color="red"></font> <font color="green">1, 2</font></td> | <td><font color="red"></font> <font color="green">1, 2</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>8.756591333 ( | + | <td>8.756591333 (Low)</td> |
− | <td> | + | <td><em>False Positive</em></td> |
</tr> | </tr> | ||
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<td>PB2-2</td> | <td>PB2-2</td> | ||
<td><font color="red">1, 3</font> <font color="green"></font></td> | <td><font color="red">1, 3</font> <font color="green"></font></td> | ||
− | <td> | + | <td>Low</td> |
− | <td>24.68932333 ( | + | <td>24.68932333 (Low)</td> |
− | <td> | + | <td>True Negative</td> |
</tr> | </tr> | ||
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<td>PB2-3</td> | <td>PB2-3</td> | ||
<td><font color="red"></font> <font color="green">1, 2, 3, 5</font></td> | <td><font color="red"></font> <font color="green">1, 2, 3, 5</font></td> | ||
− | <td> | + | <td>High</td> |
− | <td>368.0475667 ( | + | <td>368.0475667 (High)</td> |
− | <td> | + | <td>True Positive</td> |
</tr> | </tr> | ||
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<br> | <br> | ||
<br> | <br> | ||
− | In the table, each suboptimal structure is labelled by numbers 1 to 10, where structure 1 has the lowest free energy(the MFE structure), and structure 10 has the highest free energy. In the "Suboptimal structures" column, only suboptimal structures with non-negligible equilibrium concentrations are considered and shown. The equilibrium concentrations were calculated by the ViennaRNA | + | In the table, each suboptimal structure is labelled by numbers 1 to 10, where <em>structure 1 has the lowest free energy (the MFE structure)</em>, and <em>structure 10 has the highest </em> free energy. In the "Suboptimal structures" column, only suboptimal structures with non-negligible equilibrium concentrations are considered and shown. The equilibrium concentrations were calculated by the ViennaRNA web server [2]. |
<br> | <br> | ||
For example, for H5-3 switch: | For example, for H5-3 switch: | ||
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<br> | <br> | ||
− | We checked the status of the toehold domain for each suboptimal structure from the ViennaRNA | + | We checked the status of the toehold domain for each suboptimal structure from the ViennaRNA web server output [2] to see if it was open or closed. In the table, the structures with an open toehold domain are shown in <font color="green">green</font>, and ones with a closed toehold domain are shown in <font color="red">red</font>. |
<br> | <br> | ||
For example, for H5-3 switch: | For example, for H5-3 switch: | ||
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</p> | </p> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | The expected fluorescence(determined by the ratio of suboptimal structures with open/closed toehold domains) exhibited by E. coli | + | The expected fluorescence(determined by the ratio of suboptimal structures with open/closed toehold domains) exhibited by <i>E. coli</i> co-transformed with the switch and trigger RNA after 12 hours was compared with the actual observed fluorescence during the experiment.</p> |
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | From the table above, we observed that only 3 out of 15 of our predictions were incorrect, showing promising accuracy of this prediction method. None of the 3 incorrect predictions were false negatives, indicating that the suboptimal structure prediction method should be mostly applied to filtering out switch sequences with low predicted performances.</p> | + | From the table above, we observed that only <em>3 out of 15 of</em> our predictions were incorrect, showing promising accuracy of this prediction method. None of the 3 incorrect predictions were false negatives, indicating that <strong>the suboptimal structure prediction method should be mostly applied to filtering out switch sequences with low predicted performances</strong>.</p> |
<br> | <br> | ||
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<div class="column full_size"> | <div class="column full_size"> | ||
− | <p style="font-family: quicksand;font-size:150%;"> | + | <p style="font-family: quicksand;font-size:150%;">Experimental verification of the thermodynamic mode</p> |
<p style="font-family: roboto;font-size:125%;"><u><b> Correlation of switch MFE (Minimum Free Energy) and expression leakage </p></b></u> | <p style="font-family: roboto;font-size:125%;"><u><b> Correlation of switch MFE (Minimum Free Energy) and expression leakage </p></b></u> | ||
<img src="https://static.igem.org/mediawiki/2017/1/1e/CUHK_SMFE.jpg" width="40%" height="auto" class=" igem-logo"> | <img src="https://static.igem.org/mediawiki/2017/1/1e/CUHK_SMFE.jpg" width="40%" height="auto" class=" igem-logo"> | ||
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<img src="https://static.igem.org/mediawiki/2017/d/d9/CUHK_ScMFE2.jpg" width="40%" height="auto" class=" igem-logo"> | <img src="https://static.igem.org/mediawiki/2017/d/d9/CUHK_ScMFE2.jpg" width="40%" height="auto" class=" igem-logo"> | ||
<br> | <br> | ||
− | Although the switch MFE correlates with the expression leakage, this plot showed that the switches with lower MFE also have lower RFP signal in the presence of trigger. This suggests that a low MFE | + | Although the switch MFE correlates with the expression leakage, this plot showed that the switches with lower MFE also have lower RFP signal in the presence of trigger. This suggests that a low switch MFE could also be a hindrance to detection that it increases the energy input to the system (activation energy), so it takes more energy for switch-trigger duplex formation to occur. This could lower the expression level of the switch-trigger duplex. |
<br> | <br> | ||
<br> | <br> | ||
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<img src="https://static.igem.org/mediawiki/2017/c/c1/CUHK_MFED.jpg" width="40%" height="auto" class=" igem-logo"> | <img src="https://static.igem.org/mediawiki/2017/c/c1/CUHK_MFED.jpg" width="40%" height="auto" class=" igem-logo"> | ||
<br> | <br> | ||
− | We initially thought that the larger the MFE difference between the sum of the MFE of switch and trigger and that of the switch-trigger duplex, the more favourable the duplex structure will be. However, there seems to be a weak positive correlation between the expression level of the switch | + | We initially thought that the larger the MFE difference between the sum of the MFE of switch and trigger and that of the switch-trigger duplex, the more favourable the duplex structure will be. However, there seems to be a weak positive correlation between the expression level of the switch-trigger duplex and the MFE difference of a switch. This could be because that a low MFE difference could indicate a more similar conformation of the switch/trigger RNA to the switch-trigger duplex RNA. This could lead to less conformational changes in the duplex formation process, making the process faster. Thus, a small MFE difference could lead to an increased expression level of the switch-trigger duplex. |
<br> | <br> | ||
<br> | <br> | ||
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<img src="https://static.igem.org/mediawiki/2017/3/33/CUHK_bp.jpg" width="40%" height="auto" class=" igem-logo"> | <img src="https://static.igem.org/mediawiki/2017/3/33/CUHK_bp.jpg" width="40%" height="auto" class=" igem-logo"> | ||
<br> | <br> | ||
− | The plot shows some kind of negative correlation between RFP signal in the presence of trigger and the number of base pairs in the toehold domain. Some exceptions were observed, they are N1-3, N9-3, N9-1. H5-3 and N1-2. This supports the | + | The plot shows some kind of negative correlation between RFP signal in the presence of trigger and the number of base pairs in the toehold domain. Some exceptions were observed, they are N1-3, N9-3, N9-1. H5-3 and N1-2. This supports the assumption in the suboptimal structure modelling that an increasing number of unpaired bases in the toehold domain promotes initial binding of a trigger RNA to the corresponding switch RNA. |
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<br> | <br> | ||
<br>References: | <br>References: | ||
− | <br>[1] Green AA, Silver PA, Collins JJ, Yin P. Toehold switches: De-novo-designed regulators of gene expression. Cell. 2014;159(4):925–39. | + | <br>[1] Green AA, Silver PA, Collins JJ, Yin P. Toehold switches: De-novo-designed regulators of gene expression. <i>Cell.</i> 2014;159(4):925–39. |
− | <br>[2] Hofacker IL. RNA secondary structure analysis using the Vienna RNA package. Curr Protoc Bioinformatics [Internet]. 2009;Chapter 12:Unit12.2. Available from: | + | <br>[2] Hofacker IL. RNA secondary structure analysis using the Vienna RNA package. <i>Curr Protoc Bioinformatics [Internet]</i>. 2009;Chapter 12:Unit12.2. Available from: |
http://www.ncbi.nlm.nih.gov/pubmed/19496057 | http://www.ncbi.nlm.nih.gov/pubmed/19496057 | ||
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</section> | </section> |
Latest revision as of 04:01, 2 November 2017