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− | We first assumed that both genes encoding RT and Cre are placed together under a lac operon (Fig 2a). The repressor protein LacI is stably expressed in the cell, 2 molecules of LacI will form a dimer which binds to LacO DNA fragment and represses the expression of RT and Cre. When IPTG is added and transported into the cell, IPTG molecules will bind with LacI and inhibit its binding to LacO. In this way, RT and Cre can be rescued from suppression (<a href="#Ref1"><u> | + | We first assumed that both genes encoding RT and Cre are placed together under a lac operon (Fig 2a). The repressor protein LacI is stably expressed in the cell, 2 molecules of LacI will form a dimer which binds to LacO DNA fragment and represses the expression of RT and Cre. When IPTG is added and transported into the cell, IPTG molecules will bind with LacI and inhibit its binding to LacO. In this way, RT and Cre can be rescued from suppression (<a href="#Ref1"><u>Stamatakis et al.</u></a>). The ordinary differential equations (ODEs) describing these processes are shown as follows. Details of the substance names, parameter names and chemical equations can be found in the <a href="#App"><u>appendix</u></a>.<br /><br /> |
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As a result of the impreciseness of the basic assumption of the models in part I, we only gave a qualitative conclusion that the amount of RT and Cre should be different. Here we need to quantify how Cre degradation rate and steady-state concentration affects the yield of recombined P<sub>target</sub>. That’s why we employed deterministic model here to combine the separate steps together into one and better simulate real intracellular circumstances.<br /><br /> | As a result of the impreciseness of the basic assumption of the models in part I, we only gave a qualitative conclusion that the amount of RT and Cre should be different. Here we need to quantify how Cre degradation rate and steady-state concentration affects the yield of recombined P<sub>target</sub>. That’s why we employed deterministic model here to combine the separate steps together into one and better simulate real intracellular circumstances.<br /><br /> | ||
By combining the models that have been talked above, we revealed the reason why the degradation tag with a moderate degradation rate, which can’t be too high or too low, should be selected (Fig 6b): under appropriate inducer concentration (20~22uM), when the degradation rate is relatively low (below 0.1 min<sup>-1</sup>), the yield of recombined P<sub>target</sub> will increase according to the increase of Cre degradation rate, but when that rate is sufficiently high (above 0.1 min<sup>-1</sup>), the increase of Cre degradation rate will do harm to the yield of recombined P<sub>target</sub>.<br /><br /> | By combining the models that have been talked above, we revealed the reason why the degradation tag with a moderate degradation rate, which can’t be too high or too low, should be selected (Fig 6b): under appropriate inducer concentration (20~22uM), when the degradation rate is relatively low (below 0.1 min<sup>-1</sup>), the yield of recombined P<sub>target</sub> will increase according to the increase of Cre degradation rate, but when that rate is sufficiently high (above 0.1 min<sup>-1</sup>), the increase of Cre degradation rate will do harm to the yield of recombined P<sub>target</sub>.<br /><br /> | ||
− | The average degradation rate acquired from literature is 0.2 min<sup>-1</sup>(<a href="#Ref1"><u> | + | The average degradation rate acquired from literature is 0.2 min<sup>-1</sup>(<a href="#Ref1"><u>Stamatakis et al.</u></a>) and the degradation rate of Cre when tagged with the most efficient degradation tag is 0.69 min<sup>-1</sup>. Within this range of degradation rate, the maximum yield of recombined P<sub>target</sub> will decrease according to the increase of Cre degradation efficiency (Fig 6c). So we decided to use the least efficient degradation tag.<br /><br /> |
We also revealed the dynamic change of the recombined P<sub>target</sub>. It will continuously accumulate within Cre function period (Fig 6d). However, the concentration remains to be low within that period, due to Cre degradation (Fig 6e).<br /><br /> | We also revealed the dynamic change of the recombined P<sub>target</sub>. It will continuously accumulate within Cre function period (Fig 6d). However, the concentration remains to be low within that period, due to Cre degradation (Fig 6e).<br /><br /> | ||
Finally, there is another interesting phenomenon that is worth mentioning. From Fig 6b and Fig 6c, we can find that for each degradation tag rate greater than 0.2 min<sup>-1</sup>, there exits a range of aTc dosage that can make the yield of recombined relatively big. Also, decreased degradation efficiency enlarges that range. This discovery provides us with another reason for using less efficient degradation tag in that it can increase the robustness of our mutagenesis system by decreasing its sensitivity to the change of inducer dosage. | Finally, there is another interesting phenomenon that is worth mentioning. From Fig 6b and Fig 6c, we can find that for each degradation tag rate greater than 0.2 min<sup>-1</sup>, there exits a range of aTc dosage that can make the yield of recombined relatively big. Also, decreased degradation efficiency enlarges that range. This discovery provides us with another reason for using less efficient degradation tag in that it can increase the robustness of our mutagenesis system by decreasing its sensitivity to the change of inducer dosage. | ||
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<ul class="paraUl" style="list-style:none;"> | <ul class="paraUl" style="list-style:none;"> | ||
− | <li | + | <li>[1] Stamatakis M, Mantzaris N V. <a href="https://www.ncbi.nlm.nih.gov/pubmed/19186128" target="_blank" name="Ref1">Comparison of Deterministic and Stochastic Models of the lac Operon Genetic Network.</a> <i>Biophys. J.</i> 96, 887–906 (2009).</li> |
− | <li | + | <li>[2] Kulpa, D. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1169686/" target="_blank" name="Ref2">Determination of the site of first strand transfer during Moloney murine leukemia virus reverse transcription and identification of strand transfer-associated reverse transcriptase errors</a> <i>EMBO J.</i> 16, 856–865 (1997).</li> |
− | <li | + | <li>[3] Ringrose, L. et al.<a href="https://www.ncbi.nlm.nih.gov/pubmed/9813124" target="_blank" name="Ref3">Comparative kinetic analysis of FLP and cre recombinases: mathematical models for DNA binding and recombination</a> <i>J. Mol. Biol.</i> 284, 363–384 (1998).</li> |
− | <li | + | <li>[4] Wilkinson, Darren J. <a name="Ref4">Stochastic modeling for Systems Biology</a>, Second Edition. <a>Crc Press</a>, 2011.</li> |
− | <li | + | <li>[5] Harris A W K, Kelly C L, Steel H, et al. <a href="https://ieeexplore.ieee.org/document/8263882" target="_blank" name="Ref5">The autorepressor: A case study of the importance of model selection</a> <i>2017 IEEE 56th Annual Conference on Decision and Control (CDC)</i> 1622–1627 (2017).</li> |
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<ul> | <ul> | ||
<li><a href="/Team:Fudan-TSI/Public_Engagement">Education & Public engagement</a></li> | <li><a href="/Team:Fudan-TSI/Public_Engagement">Education & Public engagement</a></li> | ||
− | <li><a href="/Team:Fudan-TSI/ | + | <li><a href="/Team:Fudan-TSI/Human_Practices">Integrated human practice</a></li> |
<li><a href="/Team:Fudan-TSI/Collaborations">Collaborations</a></li> | <li><a href="/Team:Fudan-TSI/Collaborations">Collaborations</a></li> | ||
<li><a href="/Team:Fudan-TSI/Safety">Safety</a></li> | <li><a href="/Team:Fudan-TSI/Safety">Safety</a></li> | ||
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<li><a href="/Team:Fudan-TSI/Team">Members</a></li> | <li><a href="/Team:Fudan-TSI/Team">Members</a></li> | ||
<li><a href="/Team:Fudan-TSI/Attributions">Attributions</a></li> | <li><a href="/Team:Fudan-TSI/Attributions">Attributions</a></li> | ||
− | |||
<li><a href="/Team:Fudan-TSI">© 2019</a></li> | <li><a href="/Team:Fudan-TSI">© 2019</a></li> | ||
</ul> | </ul> |
Revision as of 02:40, 22 October 2019