Line 1,984: | Line 1,984: | ||
<div class="row para1"> | <div class="row para1"> | ||
<div class="col"> | <div class="col"> | ||
− | We first assumed that both genes encoding RT and Cre are placed together under a lac operon (<a href="#Fig2">Fig 2a</a>). 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">Nikos et al.</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 < | + | We first assumed that both genes encoding RT and Cre are placed together under a lac operon (<a href="#Fig2">Fig 2a</a>). 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">Nikos et al.</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">appendix</a>.<br /><br /> |
</div> | </div> | ||
</div> | </div> | ||
Line 2,049: | Line 2,049: | ||
<div class="col"> | <div class="col"> | ||
From the first model, the concentration of both RT and Cre are acquired. The concentration of RT serves as input to the reverse transcription model. As the schematic diagram depicts (<a href="#Fig3">Fig. 3a</a>), tRNA primer first binds with reverse transcriptase. When this complex binds with a certain fragment on the target sequence, which is called primer binding site (PBS), the reverse transcription will start and cDNA will be synthesized.<br /><br /> | From the first model, the concentration of both RT and Cre are acquired. The concentration of RT serves as input to the reverse transcription model. As the schematic diagram depicts (<a href="#Fig3">Fig. 3a</a>), tRNA primer first binds with reverse transcriptase. When this complex binds with a certain fragment on the target sequence, which is called primer binding site (PBS), the reverse transcription will start and cDNA will be synthesized.<br /><br /> | ||
− | Although a more elaborate model of reverse transcription has been proposed by <a href="#Ref2">Kulpa et al.</a>, it includes many reactions whose kinetic properties are not well characterized. As a result, we simplified that model and came up with our own. The ODEs describing these processes are shown as follows. Details of the substance names, parameter names and chemical equations we used can be found in the < | + | Although a more elaborate model of reverse transcription has been proposed by <a href="#Ref2">Kulpa et al.</a>, it includes many reactions whose kinetic properties are not well characterized. As a result, we simplified that model and came up with our own. The ODEs describing these processes are shown as follows. Details of the substance names, parameter names and chemical equations we used can be found in the <a href="#App">appendix</a>.<br /><br /> |
</div> | </div> | ||
</div> | </div> | ||
Line 2,100: | Line 2,100: | ||
<div class="row para1"> | <div class="row para1"> | ||
<div class="col"> | <div class="col"> | ||
− | Our first assumption is that the genes encoding RT and Cre are both placed under lac operon and thus be expressed in the same amount. So now we are about to compute the yield of our desired product to identify whether this experimental setup is feasible. The model of the recombination process has been clearly described by <a href="#Ref3">Ehrilich et al</a>. We made some changes to it according to our own experimental design. The schematic diagram is shown in <a href="#Fig4">Fig. 4a</a>. The ODEs describing these processes are shown as follows. Details of the substance names, parameter names and chemical equations can be found in the < | + | Our first assumption is that the genes encoding RT and Cre are both placed under lac operon and thus be expressed in the same amount. So now we are about to compute the yield of our desired product to identify whether this experimental setup is feasible. The model of the recombination process has been clearly described by <a href="#Ref3">Ehrilich et al</a>. We made some changes to it according to our own experimental design. The schematic diagram is shown in <a href="#Fig4">Fig. 4a</a>. The 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">appendix</a>.<br /><br /> |
</div> | </div> | ||
</div> | </div> | ||
Line 2,227: | Line 2,227: | ||
<div class="col"> | <div class="col"> | ||
To ensure the evolved protein is encoded by the mutated GOI sequence that is recombined into P<sub>target</sub>, we decided to use degradation tag to accelerate the degradation process of Cre. This design would make Cre only function when inducer is in the system, thus allowing stringent control of the protein. However, we then face the problem of how to select the optimal degradation tag. Empirically, to minimize the duration of recombination, we tend to choose degradation tags with higher efficiency, but extremely high degradation rate will also reduce the yield of recombined P<sub>target</sub>, leading to decreased library size. Also, it is impractical for researchers to do experiments to test these degradation tags one by one. For these reasons, we are going to use models to find out the optimal degradation tag that should be added to Cre based on the average yield of recombined P<sub>target</sub> at the end of R-Evolution functioning period (8 hours).<br /><br /> | To ensure the evolved protein is encoded by the mutated GOI sequence that is recombined into P<sub>target</sub>, we decided to use degradation tag to accelerate the degradation process of Cre. This design would make Cre only function when inducer is in the system, thus allowing stringent control of the protein. However, we then face the problem of how to select the optimal degradation tag. Empirically, to minimize the duration of recombination, we tend to choose degradation tags with higher efficiency, but extremely high degradation rate will also reduce the yield of recombined P<sub>target</sub>, leading to decreased library size. Also, it is impractical for researchers to do experiments to test these degradation tags one by one. For these reasons, we are going to use models to find out the optimal degradation tag that should be added to Cre based on the average yield of recombined P<sub>target</sub> at the end of R-Evolution functioning period (8 hours).<br /><br /> | ||
− | We intend to use the models described in Part I, combined with aTc induction model proposed by <a href="#Ref5">Steel et al</a>. to compute the yield of recombined P<sub>target</sub> under different degradation rate of Cre (the reason why Tet operon is used has been elaborated in Part I; the schematic diagram of this process is shown in <a href="#Fig6">Fig 6a</a>. The ODEs describing these processes are shown as follows. Details of the substance names, parameter names and chemical equations we used can be found in the < | + | We intend to use the models described in Part I, combined with aTc induction model proposed by <a href="#Ref5">Steel et al</a>. to compute the yield of recombined P<sub>target</sub> under different degradation rate of Cre (the reason why Tet operon is used has been elaborated in Part I; the schematic diagram of this process is shown in <a href="#Fig6">Fig 6a</a>. The ODEs describing these processes are shown as follows. Details of the substance names, parameter names and chemical equations we used can be found in the <a href="#App">appendix</a>. |
</div> | </div> | ||
</div> | </div> | ||
Line 2,272: | Line 2,272: | ||
<div class="col"> | <div class="col"> | ||
Please consult the appendix file for a clearer understanding of the formulation of the model.<br /><br /> | Please consult the appendix file for a clearer understanding of the formulation of the model.<br /><br /> | ||
− | <embed src="https://static.igem.org/mediawiki/2019/8/8c/T--Fudan-TSI--ModelApp.pdf" width="100%" height="1000" type="application/pdf"> | + | <a name="App"><embed src="https://static.igem.org/mediawiki/2019/8/8c/T--Fudan-TSI--ModelApp.pdf" width="100%" height="1000" type="application/pdf"></a> |
</div> | </div> | ||
</div> | </div> |
Revision as of 18:37, 20 October 2019