http://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&feed=atom&action=historyTeam:KU Leuven/Project/Glucosemodel/MeS/Modelling - Revision history2024-03-28T15:16:50ZRevision history for this page on the wikiMediaWiki 1.16.5http://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=360451&oldid=prevFrederikM at 03:24, 29 October 20132013-10-29T03:24:23Z<p></p>
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</table>FrederikMhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=357730&oldid=prevSanderW at 01:48, 29 October 20132013-10-29T01:48:50Z<p></p>
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</table>SanderWhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=353130&oldid=prevVeerledewever at 22:23, 28 October 20132013-10-28T22:23:23Z<p></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><p align = "justify"> Due to the unforeseen circumstances with the qPCR we unfortunately were not able to <del class="diffchange diffchange-inline">get to know the real amount of mRNA molecules </del>for each protein in our system. <del class="diffchange diffchange-inline">(</del>More about this qPCR story can be read <a href="https://2013.igem.org/Team:KU_Leuven/Project/qPCR">here</a><del class="diffchange diffchange-inline">.) Since these amounts where the starting point of our model, we could not do any decent predictions or figure out the rate limiting step</del>.<del class="diffchange diffchange-inline"><br/></del><br/></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><p align = "justify"> <ins class="diffchange diffchange-inline">The limiting step (associated with the most uncertainty) in the kinetic parameter model is the transcription rate. We hoped to improve this aspect by using wetlab derived mRNA levels, obtained via qPCR studies. </ins>Due to the unforeseen circumstances with the qPCR we unfortunately were not able to <ins class="diffchange diffchange-inline">integrate these wet-lab data </ins>for each protein in our system. More about this qPCR story can be read <a href="https://2013.igem.org/Team:KU_Leuven/Project/qPCR">here</a>.<br/></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>Rather than running our model with unrealistic values (eg. <del class="diffchange diffchange-inline">The </del>formula described in section 1 <del class="diffchange diffchange-inline">for </del>the <del class="diffchange diffchange-inline">calculation of the transcription rate) which would result in inaccurate results</del>, we opted to not use this model <del class="diffchange diffchange-inline">for any predictions</del>. However we think that our extensive literature study has been very instructive, and hope that other iGEM teams could use this study (for example the RBS calculator) as a basis for their model. <b>We also want to emphasise the importance of the qPCR approach.</b> <del class="diffchange diffchange-inline">By using </del>the <del class="diffchange diffchange-inline">amount of transcripts as a starting point for your model</del>, <del class="diffchange diffchange-inline">you circumvent the most uncertain part of these kinds of models: </del>transcription. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">These amounts were meant to reduce the uncertainty in the model. </ins>Rather than running our model with unrealistic values (eg. <ins class="diffchange diffchange-inline">the transcription rate </ins>formula described in section 1<ins class="diffchange diffchange-inline">) and add uncertainty to </ins>the <ins class="diffchange diffchange-inline">data</ins>, we opted to not use this model <ins class="diffchange diffchange-inline">at this point</ins>.<ins class="diffchange diffchange-inline"><br/></ins></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div></p></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>However<ins class="diffchange diffchange-inline">, </ins>we think that our extensive literature study has been very instructive, and hope that other iGEM teams could use this study (for example the RBS calculator) as a basis for their model. <b>We also want to emphasise the importance of the qPCR approach.</b> <ins class="diffchange diffchange-inline">Providing we can circumvent </ins>the <ins class="diffchange diffchange-inline">problems associated with high copy number plasmids</ins>, <ins class="diffchange diffchange-inline">wetlab data will offer more realistic values than currently used, modelled </ins>transcription <ins class="diffchange diffchange-inline">values</ins>. </p></div></td></tr>
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</table>Veerledeweverhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=352959&oldid=prevVeerledewever at 22:13, 28 October 20132013-10-28T22:13:15Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><i>Table 1. Translation rates, as computed with the Penn State University RBS calculator, using the MIT 2006 BioBrick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>)</i>.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><i>Table 1. Translation rates, as computed with the Penn State University RBS calculator, using the MIT 2006 BioBrick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>)</i>.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> When MIT produced their MeS brick <a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a> in 2006, it was meant to convert salicylate to methylsalicylate and produce a wintergreen scent in the process. However, the scent could only be detected when salicylate was added to the medium, proving that the BSMT1 equation functions yet the PchA and PchB equations may not function. Initially, it was thought that the RBS problems discussed above could be the cause but we could show this is most likely not the case : we entered the MIT brick sequence in the operon specific tool and obtained satisfactory data. Thus, at least <I>in silico</I> the pchBA operon could function, suggesting the lack of salicylate is caused by a different reason. For further elaboration on this topic we refer you to the <a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab">methyl salicylate wetlab page</a>. </p></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> When MIT produced their MeS brick <a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a> in 2006, it was meant to convert salicylate to methylsalicylate and produce a wintergreen scent in the process. However, the scent could only be detected when salicylate was added to the medium, proving that the BSMT1 equation functions yet the PchA and PchB equations may not function. Initially, it was thought that the RBS problems discussed above could be the cause but we could show this is most likely not the case : we entered the MIT brick sequence in the operon specific tool and obtained satisfactory data. Thus, at least <I>in silico</I> the pchBA operon could function, suggesting the lack of salicylate is caused by a different reason. For further elaboration on this topic we refer you to the <a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab">methyl salicylate wetlab page</a>. </p></div></td></tr>
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</table>Veerledeweverhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=352938&oldid=prevVeerledewever at 22:12, 28 October 20132013-10-28T22:12:00Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A first run through the tool yielded adequate results for both PchB and BSMT1, however the output for PchA was unrealistically low. We realised the RBS for PchA was part of PchB, causing the low output. After communication with dr. Salis himself we settle on a different tool from his website, especially designed for operon structures. </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A first run through the tool yielded adequate results for both PchB and BSMT1, however the output for PchA was unrealistically low. We realised the RBS for PchA was part of PchB, causing the low output. After communication with dr. Salis himself we settle on a different tool from his website, especially designed for operon structures. </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>This was indeed the appropriate tool to quantify the translation initiation of the operon pchBA : the output now showed a satisfactory translation rate for each of the proteins in <i>E. coli</i>. We obtained results for the lac operon (as a control) and for the genes we want to clone into <i>E. coli</i> (<a href="https://salis.psu.edu/software/">https://salis.psu.edu/software/</a>). They are listed in Table 1. The third column of this table shows the values of the translation initiation rate that are computed using the literature value from the lac operon.</p></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>This was indeed the appropriate tool to quantify the translation initiation of the operon pchBA : the output now showed a satisfactory translation rate for each of the proteins in <i>E. coli</i>. We obtained results for the lac operon (as a control) and for the genes we want to clone into <i>E. coli</i> (<a href="https://salis.psu.edu/software/">https://salis.psu.edu/software/</a>). They are listed in Table 1. The third column of this table shows the values of the translation initiation rate that are computed using the literature value from the lac operon.</p></div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><tr ><th><b>Gene</b></th><th><b>Translation initiation rate according to the RBS calculator (a.u.)</b></th><th><b>Translation initiation rate (initiations/(s.mRNA))</b></th></tr></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><tr ><th><b>Gene</b></th><th><b>Translation initiation rate according to the RBS calculator (a.u.)</b></th><th><b>Translation initiation rate (initiations/(s.mRNA))</b></th></tr></div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><i>Table 1. Translation rates, as computed with the Penn State University RBS calculator, using the MIT 2006 BioBrick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>)</i>.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><i>Table 1. Translation rates, as computed with the Penn State University RBS calculator, using the MIT 2006 BioBrick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>)</i>.</div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline"><br/></ins></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><p> <del class="diffchange diffchange-inline">A malfunctioning translation step could explain the lack of wintergreen scent when using the </del>MIT <del class="diffchange diffchange-inline">2006 </del>brick <del class="diffchange diffchange-inline">(</del><a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a><del class="diffchange diffchange-inline">)</del>. <del class="diffchange diffchange-inline">Of this brick only </del>the <del class="diffchange diffchange-inline">BSMT1 step </del>was <del class="diffchange diffchange-inline">proven </del>to <del class="diffchange diffchange-inline">function and not </del>the PchA and <del class="diffchange diffchange-inline">the </del>PchB <del class="diffchange diffchange-inline">step</del>. <del class="diffchange diffchange-inline">This buried the hypothesis </del>that the <del class="diffchange diffchange-inline">low translation rate </del>is <del class="diffchange diffchange-inline">responsible for </del>the <del class="diffchange diffchange-inline">lack of occurrence of salycic acid while using </del>the brick, <del class="diffchange diffchange-inline">for </del>further elaboration on this topic we refer you to the <a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab">methyl salicylate wetlab page</a>. </p></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><p <ins class="diffchange diffchange-inline">align="justify"</ins>> <ins class="diffchange diffchange-inline">When </ins>MIT <ins class="diffchange diffchange-inline">produced their MeS </ins>brick <a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a> <ins class="diffchange diffchange-inline">in 2006, it was meant to convert salicylate to methylsalicylate and produce a wintergreen scent in the process</ins>. <ins class="diffchange diffchange-inline">However, </ins>the <ins class="diffchange diffchange-inline">scent could only be detected when salicylate </ins>was <ins class="diffchange diffchange-inline">added </ins>to <ins class="diffchange diffchange-inline">the medium, proving that the BSMT1 equation functions yet </ins>the PchA and PchB <ins class="diffchange diffchange-inline">equations may not function</ins>. <ins class="diffchange diffchange-inline">Initially, it was thought </ins>that the <ins class="diffchange diffchange-inline">RBS problems discussed above could be the cause but we could show this </ins>is <ins class="diffchange diffchange-inline">most likely not </ins>the <ins class="diffchange diffchange-inline">case : we entered </ins>the <ins class="diffchange diffchange-inline">MIT </ins>brick <ins class="diffchange diffchange-inline">sequence in the operon specific tool and obtained satisfactory data. Thus</ins>, <ins class="diffchange diffchange-inline">at least <I>in silico</I> the pchBA operon could function, suggesting the lack of salicylate is caused by a different reason. For </ins>further elaboration on this topic we refer you to the <a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab">methyl salicylate wetlab page</a>. </p></div></td></tr>
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</table>Veerledeweverhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=352619&oldid=prevVeerledewever at 21:53, 28 October 20132013-10-28T21:53:47Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A first run through the tool yielded adequate results for both PchB and BSMT1, however the output for PchA was unrealistically low. We realised the RBS for PchA was part of PchB, causing the low output. After communication with dr. Salis himself we settle on a different tool from his website, especially designed for operon structures. </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A first run through the tool yielded adequate results for both PchB and BSMT1, however the output for PchA was unrealistically low. We realised the RBS for PchA was part of PchB, causing the low output. After communication with dr. Salis himself we settle on a different tool from his website, especially designed for operon structures. </div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>This was indeed the appropriate tool to quantify the translation initiation of the operon pchBA : the output now showed a satisfactory translation rate for each of the proteins in <i>E. coli</i>. We obtained results for the lac operon (as a control) and for the genes we want to clone into <i>E. coli</i> (<a href="https://salis.psu.edu/software/">https://salis.psu.edu/software/</a>). They are listed in Table 1. The third column of this table shows the values of the translation initiation rate that are computed using the literature value from the lac operon.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>This was indeed the appropriate tool to quantify the translation initiation of the operon pchBA : the output now showed a satisfactory translation rate for each of the proteins in <i>E. coli</i>. We obtained results for the lac operon (as a control) and for the genes we want to clone into <i>E. coli</i> (<a href="https://salis.psu.edu/software/">https://salis.psu.edu/software/</a>). They are listed in Table 1. The third column of this table shows the values of the translation initiation rate that are computed using the literature value from the lac operon.<ins class="diffchange diffchange-inline"></p></ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del style="color: red; font-weight: bold; text-decoration: none;">A malfunctioning translation step could explain the lack of wintergreen scent when using the MIT 2006 brick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>). Of this brick only the BSMT1 step was proven to function and not the PchA and the PchB step. This buried the hypothesis that the low translation rate is responsible for the lack of occurrence of salycic acid while using the brick, for further elaboration on this topic we refer you to the <a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab">methyl salicylate wetlab page</a>. </p></del></div></td><td colspan="2"> </td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><tr ><th><b>Gene</b></th><th><b>Translation initiation rate according to the RBS calculator (a.u.)</b></th><th><b>Translation initiation rate (initiations/(s.mRNA))</b></th></tr></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><tr ><th><b>Gene</b></th><th><b>Translation initiation rate according to the RBS calculator (a.u.)</b></th><th><b>Translation initiation rate (initiations/(s.mRNA))</b></th></tr></div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><i>Table 1. Translation rates, as computed with the Penn State University RBS calculator, using the MIT 2006 BioBrick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>)</i>.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><i>Table 1. Translation rates, as computed with the Penn State University RBS calculator, using the MIT 2006 BioBrick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>)</i>.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"><p> A malfunctioning translation step could explain the lack of wintergreen scent when using the MIT 2006 brick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>). Of this brick only the BSMT1 step was proven to function and not the PchA and the PchB step. This buried the hypothesis that the low translation rate is responsible for the lack of occurrence of salycic acid while using the brick, for further elaboration on this topic we refer you to the <a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab">methyl salicylate wetlab page</a>. </p></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins style="color: red; font-weight: bold; text-decoration: none;"><br></ins></div></td></tr>
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</table>Veerledeweverhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=352559&oldid=prevVeerledewever at 21:50, 28 October 20132013-10-28T21:50:23Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Transcription:</h3></p></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Transcription:</h3></p></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> </div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>An extensive literature survey revealed that it is difficult to predict transcription rate, particularly combined with the proper promoter dependence. It is even near impossible <del class="diffchange diffchange-inline">with </del>without good wet-lab data.<br/></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>An extensive literature survey revealed that it is difficult to predict transcription rate, particularly combined with the proper promoter dependence. It is even near impossible without good wet-lab data.<br/></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A recent review by Shiue and Prather (2012) describes this problem in the following way: “<i>due to the large sequence space and relative lack of understanding regarding polymerase-promoter interactions, the development of such predictive models remains a daunting task</i>”. Also recent discussions on stochastic gene expression suggest that reliable, quantitative predictions of mRNA production are a daunting task.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>A recent review by Shiue and Prather (2012) describes this problem in the following way: “<i>due to the large sequence space and relative lack of understanding regarding polymerase-promoter interactions, the development of such predictive models remains a daunting task</i>”. Also recent discussions on stochastic gene expression suggest that reliable, quantitative predictions of mRNA production are a daunting task.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Translation:</h3></p></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Translation:</h3></p></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> </div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>Initiation is usually the most important rate-determining step of the translation process (McCarthy and Gualerzi, 1990). Combined with the fact that there is a negligible chance for premature disassembly of the ribosome and mRNA, <b> only the rate of translation initiation has to be known <del class="diffchange diffchange-inline">in order </del>to determine the rate of translation </b>.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>Initiation is usually the most important rate-determining step of the translation process (McCarthy and Gualerzi, 1990). Combined with the fact that there is a negligible chance for premature disassembly of the ribosome and mRNA, <b> only the rate of translation initiation has to be known to determine the rate of translation </b>.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>The initiation codon, the Shine-Dalgarno sequence, the identity of the base at position -3 and the occurrence of alternative ATGs (that do not serve as an initiation codon) are features known to be important for translation initiation (Barrick <i>et al.</i>, 1994). When those are known it should be possible to make an estimation of the translation rate<del class="diffchange diffchange-inline">. It is however necessary to mention another feature that can be of particular importance for the initiation of translation: the occurrence of a secondary structure in the ribosome binding site. This can be regarded as an outlier tough, since evolution tuned the ribosome binding sites as such that they only rarely show this behavior. When it would occur there would be a much lower rate of translation, since initiation requires the RBS to be unfolded (De Smit and van Duin, 1990)</del>.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>The initiation codon, the Shine-Dalgarno sequence, the identity of the base at position -3 and the occurrence of alternative ATGs (that do not serve as an initiation codon) are features known to be important for translation initiation (Barrick <i>et al.</i>, 1994). When those are known it should be possible to make an estimation of the translation rate.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>Pennsylvania State University was able to quantify the different relevant features and created a tool (Salis <i>et al.</i>, 2009) (Salis, 2011) that predicts the translation rate when the mRNA sequence is known. Even within a range of five orders of magnitude the tool should not differ from the reality with a factor higher than 2.3 (Salis <i>et al.</i>, 2009). The RBS determines the translation initiation rate, however this is relative to all other translated coding sequences (Salis, 2011). Since the RBS calculator uses the same scale for every calculation, the relative translation initiation rate of each <del class="diffchange diffchange-inline">of the proteins </del>can thus be determined. <del class="diffchange diffchange-inline">To extract absolute rates it suffices to have an </del>absolute translation initiation rate for only one gene<del class="diffchange diffchange-inline">. In order </del>to model this properly we would require a translation initiation rate of one of <del class="diffchange diffchange-inline">our </del>genes from our construct. <del class="diffchange diffchange-inline">These </del>values are not available <del class="diffchange diffchange-inline">at this moment</del>, but values from literature should give a reasonable result. We have found that the initiation rate of translation for the <i>lacZ</i> gene in the <i>lac</i> operon is approximately 0.31 initiations per second per mRNA copy (Kennell and Riezman, 1977), which we consequently used as a standard. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>Pennsylvania State University was able to quantify the different relevant features and created a tool (Salis <i>et al.</i>, 2009) (Salis, 2011) that predicts the translation rate when the mRNA sequence is known. Even within a range of five orders of magnitude the tool should not differ from the reality with a factor higher than 2.3 (Salis <i>et al.</i>, 2009). The RBS determines the translation initiation rate, however<ins class="diffchange diffchange-inline">, </ins>this is relative to all other translated coding sequences (Salis, 2011). Since the RBS calculator uses the same scale for every calculation, the relative translation initiation rate of each <ins class="diffchange diffchange-inline">protein </ins>can thus be determined. <ins class="diffchange diffchange-inline">An </ins>absolute translation initiation rate for only one gene <ins class="diffchange diffchange-inline">suffices </ins>to <ins class="diffchange diffchange-inline">extract absolute rates. To </ins>model this properly<ins class="diffchange diffchange-inline">, </ins>we would require a translation initiation rate of one of <ins class="diffchange diffchange-inline">the </ins>genes from our construct. <ins class="diffchange diffchange-inline">At this moment, these </ins>values are not available <ins class="diffchange diffchange-inline">from the wetlab</ins>, but values from literature should give a reasonable result. We have found that the initiation rate of translation for the <i>lacZ</i> gene in the <i>lac</i> operon is approximately 0.31 initiations per second per mRNA copy (Kennell and Riezman, 1977), which we consequently used as a standard. </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>A first run through the tool yielded adequate results for both PchB and BSMT1, however the output for PchA was <del class="diffchange diffchange-inline">not satisfactory</del>. <del class="diffchange diffchange-inline">A malfunctioning translation step could explain </del>the <del class="diffchange diffchange-inline">lack </del>of <del class="diffchange diffchange-inline">wintergreen scent when using </del>the <del class="diffchange diffchange-inline">MIT 2006 brick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>). Of this brick only the BSMT1 step was proven to function and not the PchA and the PchB step</del>. After communication with dr. Salis himself we <del class="diffchange diffchange-inline">used </del>a different tool <del class="diffchange diffchange-inline">on the </del>website, designed for operon structures. This was indeed the appropriate tool to quantify the translation initiation of pchBA<del class="diffchange diffchange-inline">, since </del>the <del class="diffchange diffchange-inline">RBS of pchA is in the end of the coding sequence of pchB. The </del>output now showed a satisfactory translation rate for each of the proteins in <i>E. coli</i>. <del class="diffchange diffchange-inline">This buried the hypothesis that the low translation rate is responsible </del>for the <del class="diffchange diffchange-inline">lack of occurrence of salycic acid while using </del>the <del class="diffchange diffchange-inline">brick, for further elaboration on this topic </del>we <del class="diffchange diffchange-inline">refer you </del>to <del class="diffchange diffchange-inline">the </del><<del class="diffchange diffchange-inline">a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab"</del>><del class="diffchange diffchange-inline">methyl salicylate wetlab page</del></<del class="diffchange diffchange-inline">a</del>><del class="diffchange diffchange-inline">. The results from using the above-mentioned tool </del>(<a href="https://salis.psu.edu/software/">https://salis.psu.edu/software/</a>) <del class="diffchange diffchange-inline">for the lac operon and for the genes we want to clone into <i>E</del>. <del class="diffchange diffchange-inline">coli</i>, </del>are listed in Table 1. The third column of this table shows the values of the translation initiation rate that are computed using the literature value from the lac operon.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>A first run through the tool yielded adequate results for both PchB and BSMT1, however the output for PchA was <ins class="diffchange diffchange-inline">unrealistically low</ins>. <ins class="diffchange diffchange-inline">We realised </ins>the <ins class="diffchange diffchange-inline">RBS for PchA was part </ins>of <ins class="diffchange diffchange-inline">PchB, causing </ins>the <ins class="diffchange diffchange-inline">low output</ins>. After communication with dr. Salis himself we <ins class="diffchange diffchange-inline">settle on </ins>a different tool <ins class="diffchange diffchange-inline">from his </ins>website, <ins class="diffchange diffchange-inline">especially </ins>designed for operon structures. </div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div></p></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>This was indeed the appropriate tool to quantify the translation initiation of <ins class="diffchange diffchange-inline">the operon </ins>pchBA <ins class="diffchange diffchange-inline">: </ins>the output now showed a satisfactory translation rate for each of the proteins in <i>E. coli</i>. <ins class="diffchange diffchange-inline">We obtained results </ins>for the <ins class="diffchange diffchange-inline">lac operon (as a control) and for </ins>the <ins class="diffchange diffchange-inline">genes </ins>we <ins class="diffchange diffchange-inline">want </ins>to <ins class="diffchange diffchange-inline">clone into </ins><<ins class="diffchange diffchange-inline">i</ins>><ins class="diffchange diffchange-inline">E. coli</ins></<ins class="diffchange diffchange-inline">i</ins>> (<a href="https://salis.psu.edu/software/">https://salis.psu.edu/software/</a>). <ins class="diffchange diffchange-inline">They </ins>are listed in Table 1. The third column of this table shows the values of the translation initiation rate that are computed using the literature value from the lac operon.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">A malfunctioning translation step could explain the lack of wintergreen scent when using the MIT 2006 brick (<a href="http://parts.igem.org/Part:BBa_J45700">BBa_J45700</a>). Of this brick only the BSMT1 step was proven to function and not the PchA and the PchB step. This buried the hypothesis that the low translation rate is responsible for the lack of occurrence of salycic acid while using the brick, for further elaboration on this topic we refer you to the <a href="https://2013.igem.org/Team:KU_Leuven/Project/MeSa/wetlab">methyl salicylate wetlab page</a>. </ins></p></div></td></tr>
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</table>Veerledeweverhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=352185&oldid=prevVeerledewever at 21:24, 28 October 20132013-10-28T21:24:40Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Copy number:</h3></p></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Copy number:</h3></p></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> </div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align="justify"> </div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><del class="diffchange diffchange-inline">The first step in our model is the determination of </del>the number of genes <del class="diffchange diffchange-inline">which can be </del>transcribed. <del class="diffchange diffchange-inline">In our system we </del>start with 2 genes (<i>pchBA</i> operon and <i>bsmt1</i>). They are not on the same plasmid but both carry a pMB1 origin of replication. This ORI has a copy number of 100 to 300 plasmids per cell. Therefore we <del class="diffchange diffchange-inline">will </del>assume 200 copies <del class="diffchange diffchange-inline">of genes </del>per cell.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">First we determine </ins>the number of genes transcribed <ins class="diffchange diffchange-inline">in our model</ins>. <ins class="diffchange diffchange-inline">We </ins>start with 2 genes (<i>pchBA</i> operon and <i>bsmt1</i>). They are not on the same plasmid but both carry a pMB1 origin of replication. This ORI has a copy number of 100 to 300 plasmids per cell. Therefore we assume <ins class="diffchange diffchange-inline">an average of </ins>200 <ins class="diffchange diffchange-inline">gene </ins>copies per cell.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Transcription:</h3></p></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div> <p align = "justify"><h3>Transcription:</h3></p></div></td></tr>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>An extensive literature survey revealed that <del class="diffchange diffchange-inline">prediction of </del>transcription rate, <del class="diffchange diffchange-inline">and its </del>promoter dependence<del class="diffchange diffchange-inline">, </del>is <del class="diffchange diffchange-inline">very hard and </del>even impossible <del class="diffchange diffchange-inline">to do </del>without <del class="diffchange diffchange-inline">any </del>good data. <del class="diffchange diffchange-inline">The </del>review <del class="diffchange diffchange-inline">article </del>by Shiue and Prather (2012) describes this problem the following way: “<i>due to the large sequence space and relative lack of understanding regarding polymerase-promoter interactions, the development of such predictive models remains a daunting task</i>”. Also <del class="diffchange diffchange-inline">the </del>recent discussions <del class="diffchange diffchange-inline">about </del>stochastic gene expression <del class="diffchange diffchange-inline">make it as good as impossible to do </del>quantitative predictions of mRNA production.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>An extensive literature survey revealed that <ins class="diffchange diffchange-inline">it is difficult to predict </ins>transcription rate, <ins class="diffchange diffchange-inline">particularly combined with the proper </ins>promoter dependence<ins class="diffchange diffchange-inline">. It </ins>is even <ins class="diffchange diffchange-inline">near </ins>impossible <ins class="diffchange diffchange-inline">with </ins>without good <ins class="diffchange diffchange-inline">wet-lab </ins>data.<ins class="diffchange diffchange-inline"><br/></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ins class="diffchange diffchange-inline">A recent </ins>review by Shiue and Prather (2012) describes this problem <ins class="diffchange diffchange-inline">in </ins>the following way: “<i>due to the large sequence space and relative lack of understanding regarding polymerase-promoter interactions, the development of such predictive models remains a daunting task</i>”. Also recent discussions <ins class="diffchange diffchange-inline">on </ins>stochastic gene expression <ins class="diffchange diffchange-inline">suggest that reliable, </ins>quantitative predictions of mRNA production <ins class="diffchange diffchange-inline">are a daunting task</ins>.</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align = "justify"><img src="https://static.igem.org/mediawiki/2013/0/08/NTU-Signapore-Transcription-Formula.png"></p></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align = "justify"><img src="https://static.igem.org/mediawiki/2013/0/08/NTU-Signapore-Transcription-Formula.png"></p></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align = "justify"></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><p align = "justify"></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>We <del class="diffchange diffchange-inline">believe </del>that this formula <del class="diffchange diffchange-inline">does </del>not <del class="diffchange diffchange-inline">represent the </del>transcription rate <del class="diffchange diffchange-inline">on </del>a <del class="diffchange diffchange-inline">correct way because</del>:</p></div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>We <ins class="diffchange diffchange-inline">fear </ins>that this formula <ins class="diffchange diffchange-inline">is </ins>not <ins class="diffchange diffchange-inline">a proper representation of </ins>transcription rate <ins class="diffchange diffchange-inline">for </ins>a <ins class="diffchange diffchange-inline">number of reasons </ins>:</p></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><ol><li>The reference <del class="diffchange diffchange-inline">that says that the </del>average transcription speed <del class="diffchange diffchange-inline">is </del>70 nt/s <del class="diffchange diffchange-inline">does not exist anymore</del>. We tried to search for an <b>average transcription rate</b> ourselves and we can’t seem to find <del class="diffchange diffchange-inline">any decent value</del>.</li><li><del class="diffchange diffchange-inline">In this </del>formula <del class="diffchange diffchange-inline">there is no single association with the </del>promoter strength. This is remarkable, because the strength of a promoter is a measure for how many times a transcript is initiated. (Molecular Biology of the Gene, 7th edition). <b>The stronger your promoter, the more transcripts are initiated, the more the gene is transcribed in time and thus the higher transcription rate</b>.</li><li><del class="diffchange diffchange-inline">The </del>number of nucleotides could <del class="diffchange diffchange-inline">indeed have some </del>influence <del class="diffchange diffchange-inline">on the rate of </del>transcription. <b>The longer the gene, the <del class="diffchange diffchange-inline">bigger </del>the chance that the polymerase <del class="diffchange diffchange-inline">does not properly finish </del>the <del class="diffchange diffchange-inline">transcript</del>.</b> <del class="diffchange diffchange-inline">But in literature we </del>did not find any reference <del class="diffchange diffchange-inline">that uses the </del>gene length as <del class="diffchange diffchange-inline">one of the </del>important <del class="diffchange diffchange-inline">parameters for determining the </del>rate <del class="diffchange diffchange-inline">of transcription</del>.</li></ol> </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><ol><li>The reference <ins class="diffchange diffchange-inline">claiming an </ins>average transcription speed <ins class="diffchange diffchange-inline">of </ins>70 nt/s <ins class="diffchange diffchange-inline">is no longer available</ins>. We tried to search for an <b>average transcription rate</b> ourselves and we can’t seem to find <ins class="diffchange diffchange-inline">realistic values</ins>.</li><li><ins class="diffchange diffchange-inline">This </ins>formula <ins class="diffchange diffchange-inline">does not take into account </ins>promoter strength. This is remarkable, because the strength of a promoter is a measure for how many times a transcript is initiated. (<ins class="diffchange diffchange-inline">Watson et al., </ins>Molecular Biology of the Gene, 7th edition). <b>The stronger your promoter, the more transcripts are initiated, the more the gene is transcribed in time and thus the higher transcription rate</b>.</li><li><ins class="diffchange diffchange-inline">Gene length, aka the </ins>number of nucleotides <ins class="diffchange diffchange-inline">involved, </ins>could influence transcription <ins class="diffchange diffchange-inline">rate</ins>. <b>The longer the gene, the <ins class="diffchange diffchange-inline">higher </ins>the chance that the polymerase <ins class="diffchange diffchange-inline">starts proofreading, slowing down </ins>the <ins class="diffchange diffchange-inline">transcription rate</ins>.</b> <ins class="diffchange diffchange-inline">We </ins>did not find any reference <ins class="diffchange diffchange-inline">in literature incorporating </ins>gene length as <ins class="diffchange diffchange-inline">an </ins>important <ins class="diffchange diffchange-inline">transcription </ins>rate <ins class="diffchange diffchange-inline">parameter</ins>.</li></ol> </div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div><p align = "justify"><del class="diffchange diffchange-inline">We hope that </del>other iGEM teams <del class="diffchange diffchange-inline">in the future will </del>refrain from using this formula, because it is not a realistic representation of the transcription rate.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div><p align = "justify"><ins class="diffchange diffchange-inline">Summarized, we would strongly suggest to </ins>other iGEM teams <ins class="diffchange diffchange-inline">to </ins>refrain from using this formula, because it is not a realistic representation of the transcription rate.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/><br/></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>In our case we <del class="diffchange diffchange-inline">decided that we would bypass </del>the mRNA production <del class="diffchange diffchange-inline">step as it is responsible for a large part of the uncertainty in our prediction</del>. <del class="diffchange diffchange-inline">In order </del>to <del class="diffchange diffchange-inline">attain our goal without </del>the <del class="diffchange diffchange-inline">use of transcription rates </del>we tried to determine <del class="diffchange diffchange-inline">the </del><i>in vivo</i> mRNA concentrations using qPCR. This means that we will drop formulas [1.A] and [1.B]. If you want to know more on how we tackled the qPCR, please go to our <a href="https://2013.igem.org/Team:KU_Leuven/Project/qPCR">WETLAB part</a>. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>In our case<ins class="diffchange diffchange-inline">, </ins>we <ins class="diffchange diffchange-inline">observed most uncertainty in </ins>the <ins class="diffchange diffchange-inline">transition from transcription to </ins>mRNA production. <ins class="diffchange diffchange-inline">As an alternative </ins>to the <ins class="diffchange diffchange-inline">modelled mRNA production step, </ins>we tried to determine <i>in vivo</i> mRNA concentrations using qPCR. This means that we will drop formulas [1.A] and [1.B]. If you want to know more on how we tackled the qPCR, please go to our <a href="https://2013.igem.org/Team:KU_Leuven/Project/qPCR">WETLAB part</a>. </div></td></tr>
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</table>Veerledeweverhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=351873&oldid=prevVeerledewever at 20:58, 28 October 20132013-10-28T20:58:26Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>At first, our intention was to model the entire pathway from the implemented DNA sequence to the resulting production rate. This could be very useful to approximate the resulting production rate and to figure out the rate-limiting step. To achieve this we need a mathematical representation of all the relevant biological processes, including transcription rate, mRNA degradation rate, translation rate, protein degradation rate and enzyme kinetics.</div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div>At first, our intention was to model the entire pathway from the implemented DNA sequence to the resulting production rate. This could be very useful to approximate the resulting production rate and to figure out the rate-limiting step. To achieve this we need a mathematical representation of all the relevant biological processes, including transcription rate, mRNA degradation rate, translation rate, protein degradation rate and enzyme kinetics.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/> <br/></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/> <br/></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>We created a set of <b>ordinary differential equations (ODEs)to represent every step in our pathway</b>: transcription, translation and the chemical activity of the protein. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>We created a set of <b>ordinary differential equations (ODEs) to represent every step in our pathway</b>: transcription, translation and the chemical activity of the protein. </div></td></tr>
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</table>Veerledeweverhttp://2013.igem.org/wiki/index.php?title=Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling&diff=351848&oldid=prevVeerledewever at 20:57, 28 October 20132013-10-28T20:57:00Z<p></p>
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<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>At first, our intention was to model the entire pathway from the implemented DNA sequence to the resulting production rate. This could be very useful <del class="diffchange diffchange-inline">in order </del>to <del class="diffchange diffchange-inline">have an approximation of </del>the resulting production rate and to figure out the rate-limiting step. To achieve this we need a mathematical representation of all <del class="diffchange diffchange-inline">of our </del>biological processes, <del class="diffchange diffchange-inline">the </del>transcription rate, <del class="diffchange diffchange-inline">the </del>mRNA degradation rate, <del class="diffchange diffchange-inline">the </del>translation rate, <del class="diffchange diffchange-inline">the </del>protein degradation rate and <del class="diffchange diffchange-inline">the </del>enzyme kinetics.</div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>At first, our intention was to model the entire pathway from the implemented DNA sequence to the resulting production rate. This could be very useful to <ins class="diffchange diffchange-inline">approximate </ins>the resulting production rate and to figure out the rate-limiting step. To achieve this we need a mathematical representation of all <ins class="diffchange diffchange-inline">the relevant </ins>biological processes, <ins class="diffchange diffchange-inline">including </ins>transcription rate, mRNA degradation rate, translation rate, protein degradation rate and enzyme kinetics.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/> <br/></div></td><td class='diff-marker'> </td><td style="background: #eee; color:black; font-size: smaller;"><div><br/> <br/></div></td></tr>
<tr><td class='diff-marker'>-</td><td style="background: #ffa; color:black; font-size: smaller;"><div>We created a set of <b>ordinary differential equations (ODEs)<del class="diffchange diffchange-inline">, which </del>represent every step in our pathway</b>: transcription, translation and the chemical activity of the protein. </div></td><td class='diff-marker'>+</td><td style="background: #cfc; color:black; font-size: smaller;"><div>We created a set of <b>ordinary differential equations (ODEs)<ins class="diffchange diffchange-inline">to </ins>represent every step in our pathway</b>: transcription, translation and the chemical activity of the protein. </div></td></tr>
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</table>Veerledewever