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<div class="col-sm-12 clearfix" style="padding: 0;padding-top:30px; | <div class="col-sm-12 clearfix" style="padding: 0;padding-top:30px; | ||
background: url(https://static.igem.org/mediawiki/2016/4/45/T--BIT-China--content_bg.jpg)"> | background: url(https://static.igem.org/mediawiki/2016/4/45/T--BIT-China--content_bg.jpg)"> | ||
− | + | <div class="content-right" style="float: left;width:100%;padding: 10px;"> | |
<img src="https://static.igem.org/mediawiki/2016/5/5c/T--BIT-China--content_decoration.png" | <img src="https://static.igem.org/mediawiki/2016/5/5c/T--BIT-China--content_decoration.png" | ||
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− | <div class="block-paragraph"> | + | <div class="block-paragraph" style="margin-top: 30px;margin-bottom: 10px"> |
<a data-toggle="collapse" href="#collapse0" | <a data-toggle="collapse" href="#collapse0" | ||
− | aria-expanded="true" aria-controls="collapse0"> | + | aria-expanded="true" aria-controls="collapse0" style="color: blue;text-decoration: underline"> |
<i class="fa fa-hand-o-right" aria-hidden="true"></i> | <i class="fa fa-hand-o-right" aria-hidden="true"></i> | ||
Experimental details <span>[Expand]</span> | Experimental details <span>[Expand]</span> | ||
</a> | </a> | ||
</div> | </div> | ||
− | <div id="collapse0" class="panel-collapse | + | <div id="collapse0" class="panel-collapse collapse " |
role="tabpanel" aria-labelledby="heading0"> | role="tabpanel" aria-labelledby="heading0"> | ||
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</div> | </div> | ||
<div> | <div> | ||
− | We used | + | We used P<sub>BAD</sub> promoters in all three circuits. All the circuits contain a B0034 and a B0015. <a href="http://parts.igem.org/Part:BBa_K2120303" style="color:blue;">[BBa_K2120303]</a><a href="http://parts.igem.org/Part:BBa_K2120304" style="color:blue;">[BBa_K2120304]</a><a href="http://parts.igem.org/Part:BBa_K2120304" style="color:blue;">[BBa_K2120304]</a> |
− | + | ||
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/b/bf/T--BIT-China--Project--Results--Threshold--fig1.png" | <img src="https://static.igem.org/mediawiki/2016/b/bf/T--BIT-China--Project--Results--Threshold--fig1.png" | ||
− | alt="fig1" style=" | + | alt="fig1" style="width:50%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | We used the red fluorescent protein to replace the killer gene and constructed three circuits [ | + | We used the red fluorescent protein to replace the killer gene and constructed three circuits <a href="http://parts.igem.org/Part:BBa_K2120301" style="color:blue;">[BBa_K2120301]</a> with different in-promoters (controlled by inhibitors). Two of them <a href="http://parts.igem.org/Part:BBa_I13521" style="color:blue;">[BBa_I13521]</a><a href="http://parts.igem.org/Part:BBa_I6031" style="color:blue;">[BBa_I6031]</a> comes from DNA Distribution kit. |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/a/ab/T--BIT-China--Project--Results--Threshold--fig2.png" | <img src="https://static.igem.org/mediawiki/2016/a/ab/T--BIT-China--Project--Results--Threshold--fig2.png" | ||
− | alt="fig2" style=" | + | alt="fig2" style="width:50%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/7/7d/T--BIT-China--Project--Results--Threshold--fig3.png" | <img src="https://static.igem.org/mediawiki/2016/7/7d/T--BIT-China--Project--Results--Threshold--fig3.png" | ||
− | alt="fig3" style=" | + | alt="fig3" style="width:100%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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<div class="block-paragraph"> | <div class="block-paragraph"> | ||
But when we added the arabinose, the RFP intensity increased, and it contradicted with expected results. We thought the terminator cannot completely isolate the two devices. | But when we added the arabinose, the RFP intensity increased, and it contradicted with expected results. We thought the terminator cannot completely isolate the two devices. | ||
− | <b>So we change the promoter direction and add another B0015 to optimize the circuits.</b> [ | + | <b>So we change the promoter direction and add another B0015 to optimize the circuits.</b> <a href="http://parts.igem.org/Part:BBa_K2120310" style="color:blue;">[BBa_K2120310]</a><a href="http://parts.igem.org/Part:BBa_K2120311" style="color:blue;">[BBa_K2120311]</a> |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/6/65/T--BIT-China--Project--Results--Threshold--fig4.png" | <img src="https://static.igem.org/mediawiki/2016/6/65/T--BIT-China--Project--Results--Threshold--fig4.png" | ||
− | alt="fig4" style=" | + | alt="fig4" style="width:100%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | Also in order to reflect the inhibitor concentration, we constructed the following circuit. [ | + | Also in order to reflect the inhibitor concentration, we constructed the following circuit. <a href="http://parts.igem.org/Part:BBa_K2120302" style="color:blue;">[BBa_K2120302]</a> |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/a/a5/T--BIT-China--Project--Results--Threshold--fig5.png" | <img src="https://static.igem.org/mediawiki/2016/a/a5/T--BIT-China--Project--Results--Threshold--fig5.png" | ||
− | alt="fig5" style=" | + | alt="fig5" style="width:70%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | We constructed 16 (4*2*2) devices [ | + | We constructed 16 (4*2*2) devices <a href="http://parts.igem.org/Part:BBa_K2120312" style="color:blue;">[BBa_K2120312]</a><a href="http://parts.igem.org/Part:BBa_K2120313" style="color:blue;">[BBa_K2120313]</a><a href="http://parts.igem.org/Part:BBa_K2120314" style="color:blue;">[BBa_K2120314]</a><a href="http://parts.igem.org/Part:BBa_K2120315" style="color:blue;">[BBa_K2120315]</a><a href="http://parts.igem.org/Part:BBa_K2120317" style="color:blue;">[BBa_K2120317]</a><a href="http://parts.igem.org/Part:BBa_K2120318" style="color:blue;">[BBa_K2120318]</a><a href="http://parts.igem.org/Part:BBa_K2120319" style="color:blue;">[BBa_K2120319]</a><a href="http://parts.igem.org/Part:BBa_K2120321" style="color:blue;">[BBa_K2120321]</a><a href="http://parts.igem.org/Part:BBa_K2120323" style="color:blue;">[BBa_K2120323]</a><a href="http://parts.igem.org/Part:BBa_K2120325" style="color:blue;">[BBa_K2120325]</a><a href="http://parts.igem.org/Part:BBa_K2120326" style="color:blue;">[BBa_K2120326]</a><a href="http://parts.igem.org/Part:BBa_K2120327" style="color:blue;">[BBa_K2120327]</a><a href="http://parts.igem.org/Part:BBa_K1480003" style="color:blue;">[BBa_K1480003]</a><a href="http://parts.igem.org/Part:BBa_K145201" style="color:blue;">[BBa_K145201]</a><a href="http://parts.igem.org/Part:BBa_K145113" style="color:blue;">[BBa_K145113]</a><a href="http://parts.igem.org/Part:BBa_K1480004" style="color:blue;">[BBa_K1480004]</a> with the alteration of constitutive promoters (4 kinds), RBS (2 kinds) and inhibitors (2 kinds). |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
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<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/7/77/T--BIT-China--Project--Results--Threshold--table1.png" | <img src="https://static.igem.org/mediawiki/2016/7/77/T--BIT-China--Project--Results--Threshold--table1.png" | ||
− | alt="table1" style=" | + | alt="table1" style="width:80%;" class="center-block"> |
</div> | </div> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/5/5c/T--BIT-China--Project--Results--Threshold--fig6.png" | <img src="https://static.igem.org/mediawiki/2016/5/5c/T--BIT-China--Project--Results--Threshold--fig6.png" | ||
− | alt="fig6" style=" | + | alt="fig6" style="width:80%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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</div> | </div> | ||
<div> | <div> | ||
− | After constructing the circuits with different constitutive promoters to express the inhibitor, we change the constitutive promoter direction and add corresponding in-promoter. [ | + | After constructing the circuits with different constitutive promoters to express the inhibitor, we change the constitutive promoter direction and add corresponding in-promoter. <a href="http://parts.igem.org/Part:BBa_K2120416" style="color:blue;">[BBa_K2120416]</a><a href="http://parts.igem.org/Part:BBa_K2120418" style="color:blue;">[BBa_K2120418]</a><a href="http://parts.igem.org/Part:BBa_K2120419" style="color:blue;">[BBa_K2120419]</a><a href="http://parts.igem.org/Part:BBa_K2120420" style="color:blue;">[BBa_K2120420]</a><a href="http://parts.igem.org/Part:BBa_K2120421" style="color:blue;">[BBa_K2120421]</a><a href="http://parts.igem.org/Part:BBa_K2120423" style="color:blue;">[BBa_K2120423]</a><a href="http://parts.igem.org/Part:BBa_K2120424" style="color:blue;">[BBa_K2120424]</a><a href="http://parts.igem.org/Part:BBa_K2120425" style="color:blue;">[BBa_K2120425]</a> |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/8/80/T--BIT-China--Modeling--hfig1.png" | <img src="https://static.igem.org/mediawiki/2016/8/80/T--BIT-China--Modeling--hfig1.png" | ||
− | alt="fig7" style=" | + | alt="fig7" style="width:80%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/b/be/T--BIT-China--Project--Results--Threshold--table2.png" | <img src="https://static.igem.org/mediawiki/2016/b/be/T--BIT-China--Project--Results--Threshold--table2.png" | ||
− | alt="table2" style=" | + | alt="table2" style="width:40%" class="center-block"> |
</div> | </div> | ||
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | The fragments containing the constitutive promoter (Fig. | + | The fragments containing the constitutive promoter (Fig.8) are linked with and cloned into three types of plasmids individually. |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/9/90/T--BIT-China--Project--Results--Threshold--fig8.png" | <img src="https://static.igem.org/mediawiki/2016/9/90/T--BIT-China--Project--Results--Threshold--fig8.png" | ||
− | alt="fig8" style=" | + | alt="fig8" style="width:50%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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<div class="block-content-header"> | <div class="block-content-header"> | ||
− | 1. Simulated the production of inhibitors with different | + | 1. Simulated the production of inhibitors with different concentrations by adding different concentration of arabinose |
</div> | </div> | ||
<div> | <div> | ||
− | In order to construct the environment with different concentrations of inhibitor and find the threshold, we use the PBAD promoter to achieve this. In the wet lab, we chose the CI-PR circuit like the picture to do this experiments. | + | In order to construct the environment with different concentrations of inhibitor and find the threshold, we use the PBAD promoter to achieve this. In the wet lab, we chose the CI-PR circuit like the picture (Fig. 1) to do this experiments. |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/e/e5/T--BIT-China--Project--Results--Threshold--2fig1.png" | <img src="https://static.igem.org/mediawiki/2016/e/e5/T--BIT-China--Project--Results--Threshold--2fig1.png" | ||
− | alt="2fig1" style=" | + | alt="2fig1" style="width:100%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/6/6e/T--BIT-China--Project--Results--Threshold--2fig2.png" | <img src="https://static.igem.org/mediawiki/2016/6/6e/T--BIT-China--Project--Results--Threshold--2fig2.png" | ||
− | alt="2fig2" style=" | + | alt="2fig2" style="width:100%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
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<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/5/51/T--BIT-China--Project--Results--Threshold--2table1.png" | <img src="https://static.igem.org/mediawiki/2016/5/51/T--BIT-China--Project--Results--Threshold--2table1.png" | ||
− | alt="2table1" style=" | + | alt="2table1" style="width:80%;" class="center-block"> |
</div> | </div> | ||
</div> | </div> | ||
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<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/5/5e/T--BIT-China--Project--Results--Threshold--2fig3.png" | <img src="https://static.igem.org/mediawiki/2016/5/5e/T--BIT-China--Project--Results--Threshold--2fig3.png" | ||
− | alt="2fig3" style=" | + | alt="2fig3" style="width:80%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | |||
</div> | </div> | ||
</div> | </div> | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | And then we draw the diagram about RFP intensity/OD600 and time under different concentrations of arabinose (Fig. | + | And then we draw the diagram about RFP intensity/OD600 and time under different concentrations of arabinose (Fig. 3). |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/b/bc/T--BIT-China--Project--Results--Threshold--2fig4.png" | <img src="https://static.igem.org/mediawiki/2016/b/bc/T--BIT-China--Project--Results--Threshold--2fig4.png" | ||
− | alt="2fig4" style=" | + | alt="2fig4" style="width:100%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 3</b> the diagram of the about RFP intensity/OD600 and time under different concentrations of arabinose |
</div> | </div> | ||
</div> | </div> | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | Then we collect the data after passing 17.5 hours from Fig. 3 to draw the diagram about the relationship between RFP intensity/OD600 and arabinose concentration (Fig. | + | Then we collect the data after passing 17.5 hours from Fig. 3 to draw the diagram about the relationship between RFP intensity/OD600 and arabinose concentration (Fig. 4). |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/f/f4/T--BIT-China--Project--Results--Threshold--2fig5.png" | <img src="https://static.igem.org/mediawiki/2016/f/f4/T--BIT-China--Project--Results--Threshold--2fig5.png" | ||
− | alt="2fig5" style=" | + | alt="2fig5" style="width:100%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 4</b> the diagram of the about RFP intensity/OD600 and arabinose concentration |
</div> | </div> | ||
</div> | </div> | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | After we use the | + | After we use the P<sub>BAD</sub> promoter to construct the environment with different concentrations of inhibitor, we have successfully proved that the in-promoter will respond to the different concentrations of inhibitor differently and found the threshold of inhibitor’s concentration that the P<sub>BAD</sub> promoter expressed under the 0.003% arabinose concentration. |
</div> | </div> | ||
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</div> | </div> | ||
<div> | <div> | ||
− | In order to know the exact concentration of inhibitor under the different concentrations of arabinose. In E.coli Top10, we used the RFP to replace the inhibitor gene, so we can use RFP to reflect the inhibitor when we added the same concentration of arabinose. | + | In order to know the exact concentration of inhibitor under the different concentrations of arabinose. In E.coli Top10, we used the RFP to replace the inhibitor gene (Fig. 5), so we can use RFP to reflect the inhibitor when we added the same concentration of arabinose. |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/a/a5/T--BIT-China--Project--Results--Threshold--fig5.png" | <img src="https://static.igem.org/mediawiki/2016/a/a5/T--BIT-China--Project--Results--Threshold--fig5.png" | ||
− | alt="2fig6" style=" | + | alt="2fig6" style="width:60%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig.5</b> The circuit constructed to measure the inhibitor concentration, inhibitor is replaced by RFP. |
</div> | </div> | ||
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | At first, we also use the modeling to simulate this circuit get the curve about relationship between the arabinose added and protein intensity. We got the curve below (Fig. | + | At first, we also use the modeling to simulate this circuit get the curve about relationship between the arabinose added and protein intensity. We got the curve below (Fig. 6): |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/0/07/T--BIT-China--Project--Results--Threshold--2fig7.png" | <img src="https://static.igem.org/mediawiki/2016/0/07/T--BIT-China--Project--Results--Threshold--2fig7.png" | ||
− | alt="2fig7" style=" | + | alt="2fig7" style="width:100%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 6</b> The concentration of inhibitor expressed by PBAD changes with different concentrations of inducer. |
</div> | </div> | ||
</div> | </div> | ||
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<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/b/b8/T--BIT-China--Project--Results--Threshold--2table2.png" | <img src="https://static.igem.org/mediawiki/2016/b/b8/T--BIT-China--Project--Results--Threshold--2table2.png" | ||
− | alt="2table2" style=" | + | alt="2table2" style="width:70%" class="center-block"> |
</div> | </div> | ||
</div> | </div> | ||
Line 472: | Line 471: | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/5/5e/T--BIT-China--Project--Results--Threshold--2fig3.png" | <img src="https://static.igem.org/mediawiki/2016/5/5e/T--BIT-China--Project--Results--Threshold--2fig3.png" | ||
− | alt="2fig3_copy" style=" | + | alt="2fig3_copy" style="width:80%" class="center-block"> |
</div> | </div> | ||
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | We draw the diagram about RFP intensity/OD600 and time under different concentrations of arabinose (Fig. | + | We draw the diagram about RFP intensity/OD600 and time under different concentrations of arabinose (Fig. 7). |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/4/48/T--BIT-China--Project--Results--Threshold--2fig8.png" | <img src="https://static.igem.org/mediawiki/2016/4/48/T--BIT-China--Project--Results--Threshold--2fig8.png" | ||
− | alt="2fig8" style=" | + | alt="2fig8" style="width:100%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 7</b> The relationship between the fluorescence/OD600 and time |
</div> | </div> | ||
</div> | </div> | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | Then we collect the data after passing 11.3 hours from Fig. 8 to draw the diagram about the relationship between RFP intensity/OD600 and arabinose concentration (Fig. | + | Then we collect the data after passing 11.3 hours from Fig. 8 to draw the diagram about the relationship between RFP intensity/OD600 and arabinose concentration (Fig. 8). |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/7/7b/T--BIT-China--Project--Results--Threshold--2fig9.png" | <img src="https://static.igem.org/mediawiki/2016/7/7b/T--BIT-China--Project--Results--Threshold--2fig9.png" | ||
− | alt="2fig9" style=" | + | alt="2fig9" style="width:100%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 8</b> The relationship between the fluorescence/OD600 and the concentration of arabinose |
</div> | </div> | ||
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | From this diagram, we can get the conclusion that | + | From this diagram, we can get the conclusion that the concentration of arabinose have a positive correlation with RFP intensity/OD600. |
</div> | </div> | ||
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<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Table | + | <b>Table 3.</b> The copy numbers of different plasmids. |
</div> | </div> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/b/be/T--BIT-China--Project--Results--Threshold--table2.png" | <img src="https://static.igem.org/mediawiki/2016/b/be/T--BIT-China--Project--Results--Threshold--table2.png" | ||
− | alt="3table1" style=" | + | alt="3table1" style="width:40%;" class="center-block"> |
</div> | </div> | ||
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | The fragments below (Fig. | + | The fragments below (Fig. 9) containing constitutive promoter to express inhibitor. |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/d/d1/T--BIT-China--Project--Results--Threshold--3fig1.png" | <img src="https://static.igem.org/mediawiki/2016/d/d1/T--BIT-China--Project--Results--Threshold--3fig1.png" | ||
− | alt="3fig1" style=" | + | alt="3fig1" style="width:100%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig.9</b> The circuit constructed to detect the inhibitor protein and the strengths of different promoters. |
</div> | </div> | ||
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | In order to detect the inhibitor protein more easily, we replace the inhibitor with RFP like circuits below (Fig. | + | In order to detect the inhibitor protein more easily, we replace the inhibitor with RFP like circuits below (Fig. 10) |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/5/55/T--BIT-China--Project--Results--Threshold--3fig2.png" | <img src="https://static.igem.org/mediawiki/2016/5/55/T--BIT-China--Project--Results--Threshold--3fig2.png" | ||
− | alt="3fig2" style=" | + | alt="3fig2" style="width:50%;" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 10</b> The fragments constructed on different plasmids |
</div> | </div> | ||
</div> | </div> | ||
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<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | At first, because it’s hard to control the number of plasmids, we use the model to simulate the relationship between the plasmids number and inhibitor protein. | + | At first, because it’s hard to control the number of plasmids, we use the model to simulate the relationship between the plasmids number and inhibitor protein (Fig. 11). |
</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/7/71/T--BIT-China--Project--Results--Threshold--3fig3.png" | <img src="https://static.igem.org/mediawiki/2016/7/71/T--BIT-China--Project--Results--Threshold--3fig3.png" | ||
− | alt="3fig3" style=" | + | alt="3fig3" style="width:80%" class="center-block"> |
</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 11</b> The relationship between the protein intensity and the number of plasmids. |
</div> | </div> | ||
</div> | </div> | ||
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<div class="block-paragraph"> | <div class="block-paragraph"> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Table.</b> | + | <b>Table. 4</b> The form about experimental set up. |
</div> | </div> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/c/cb/T--BIT-China--Project--Results--Threshold--3table2.png" | <img src="https://static.igem.org/mediawiki/2016/c/cb/T--BIT-China--Project--Results--Threshold--3table2.png" | ||
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− | <b>Table | + | <b>Table. 5</b>.The RFP intensity of different circuits on different plasmids |
</div> | </div> | ||
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/c/c2/T--BIT-China--Project--Results--Threshold--3table3.png" | <img src="https://static.igem.org/mediawiki/2016/c/c2/T--BIT-China--Project--Results--Threshold--3table3.png" | ||
− | alt="3table3" style=" | + | alt="3table3" style="width:100%" class="center-block"> |
</div> | </div> | ||
</div> | </div> | ||
− | + | <div class="block-paragraph"> | |
+ | From the table. 5, we can know that different plasmids copy numbers will lead to different RFP intensity. More plasmids copies, more RFP expressed. | ||
+ | </div> | ||
+ | <div class="block-paragraph"> | ||
+ | At the same time, we constructed the constitutive promoter with in-promoter (Fig. 12) on the plasmids with different copy numbers to see the express of the RFP started by in-promoter. | ||
+ | </div> | ||
+ | <div class="block-paragraph"> | ||
+ | <div><img src="https://static.igem.org/mediawiki/2016/8/80/T--BIT-China--Modeling--hfig1.png" style="width:100%" class="center-block" /></div> | ||
+ | <div class="pic_info"><b>Fig. 12</b> the circuit constructed on different plasmids.</div> | ||
+ | </div> | ||
<div class="block-content-header"> | <div class="block-content-header"> | ||
4. Employed different RBS and promoters with different strengths to change the inhibitor | 4. Employed different RBS and promoters with different strengths to change the inhibitor | ||
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</div> | </div> | ||
<div class="block-paragraph"> | <div class="block-paragraph"> | ||
− | + | <div class="pic_info"> | |
− | + | <b>Table 6.</b> The strengths and efficiencies of different promoters and RBS | |
− | + | </div> | |
<div> | <div> | ||
<img src="https://static.igem.org/mediawiki/2016/7/77/T--BIT-China--Project--Results--Threshold--table1.png" | <img src="https://static.igem.org/mediawiki/2016/7/77/T--BIT-China--Project--Results--Threshold--table1.png" | ||
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<img src="https://static.igem.org/mediawiki/2016/1/13/T--BIT-China--Project--Results--Threshold--4fig1.png" | <img src="https://static.igem.org/mediawiki/2016/1/13/T--BIT-China--Project--Results--Threshold--4fig1.png" | ||
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</div> | </div> | ||
<div class="pic_info"> | <div class="pic_info"> | ||
− | <b>Fig. | + | <b>Fig. 13</b> Constitutive circuits to reappear the threshold concentration of inhibitors. Only few will be selected and used to prove the concept of plasmid sensing. |
</div> | </div> | ||
</div> | </div> | ||
− | <div> | + | <div class="block-paragraph"> |
− | + | <b> | |
+ | By now, we can give you a summary. By combining with our modeling part, we have successfully proved that: | ||
+ | </b> | ||
+ | </div> | ||
+ | <div class="block-paragraph-padding"> | ||
+ | (1) The plasmid copies can affect the concentration of inhibitor in the constitutive circuit. | ||
+ | <br>(2) The concentration of inhibitor can affect the in-promoter’s activity and affect the expression of killer gene in the end. | ||
+ | <br>(3) Our system can help the cell sense the number of plasmids. | ||
+ | <br>(4) The number of plasmids can affect the expression of killer gene. | ||
+ | </div> | ||
+ | <div class="block-paragraph"> | ||
+ | When the plasmid number is above its threshold, the concentration of inhibitor being high enough, the killer gene can be repressed completely. | ||
+ | </div> | ||
+ | <div class="block-paragraph"> | ||
+ | When the plasmid number is below the threshold, the inhibitor won’t work anymore, the killer can get the chance. | ||
</div> | </div> | ||
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+ | |||
+ | <!--分界线--> | ||
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− | <br>The cells were diluted | + | <br>The cells were diluted 10<sup>2</sup>–10<sup>4</sup> fold and plated onto agar plates containing <span class="italic">AmpR</span> and <span class="italic">CmR</span>. The results showed that the control group with no induction was growing better than the testing group when both of them were diluted 10<sup>3</sup> fold, which means the DSB did have the lethal effect and can be used as a candidate for killer device. |
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<b>Fig.1</b> Double plasmids to meet different requirements for each element. Equip the high copy number plasmid <span class="italic">pUC19</span> with sgRNA targeting site on genome and donor fragment with homologous arms. The low copy number plasmid are equipped with expression cassette of Cas9 protein and λ-Red recombinase | <b>Fig.1</b> Double plasmids to meet different requirements for each element. Equip the high copy number plasmid <span class="italic">pUC19</span> with sgRNA targeting site on genome and donor fragment with homologous arms. The low copy number plasmid are equipped with expression cassette of Cas9 protein and λ-Red recombinase | ||
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− | Fig. | + | <b>Fig.2</b>Four testing circuits used as our donor fragment |
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Latest revision as of 16:35, 9 November 2016
Threshold device
In the threshold device, we need to prove that the in-promoter will have different responses corresponding to different plasmid numbers. In our project, we use the inhibitor protein as the signal. We combined the wet experiment results and the mathematical model to prove our system can work in order. We divided it into two main goals:
(1) To prove that inhibitor’s concentration can regulate the expression of the killer gene by affecting its in-promoter.
(2) To prove that plasmid numbers will influence the inhibitor concentration
(2) To prove that plasmid numbers will influence the inhibitor concentration
Results:
1. Simulated the production of inhibitors with different concentrations by adding different concentrations of arabinose
2. Found out the concentrations of inhibitor under different concentrations of arabinose and used the results to derive the threshold of plasmids number in the constitutive circuit.
3. Employed plasmids with different copy numbers and simulated the concentrations of plasmids losing on different levels
4. Employed different RBS and promoters with different strengths to change the inhibitor concentration
2. Found out the concentrations of inhibitor under different concentrations of arabinose and used the results to derive the threshold of plasmids number in the constitutive circuit.
3. Employed plasmids with different copy numbers and simulated the concentrations of plasmids losing on different levels
4. Employed different RBS and promoters with different strengths to change the inhibitor concentration
Build result
1. Constructing the circuits.
We used PBAD promoters in all three circuits. All the circuits contain a B0034 and a B0015. [BBa_K2120303][BBa_K2120304][BBa_K2120304]
Fig. 1 Arabinose induced expression cassette of three kinds of inhibitors
We used the red fluorescent protein to replace the killer gene and constructed three circuits [BBa_K2120301] with different in-promoters (controlled by inhibitors). Two of them [BBa_I13521][BBa_I6031] comes from DNA Distribution kit.
Fig. 2 In-promoter controlled expression cassette of RFP. RFP is used to replace killer gene.
And we separately assembled the two devices.
Fig. 3 Assembly of inhibitor and in-promoter. They can be used to test the minimum arabinose concentration which can totally repress the expression of RFP.
But when we added the arabinose, the RFP intensity increased, and it contradicted with expected results. We thought the terminator cannot completely isolate the two devices.
So we change the promoter direction and add another B0015 to optimize the circuits. [BBa_K2120310][BBa_K2120311]
Fig. 4 Optimized circuits after changing the direction of promoter pBAD and adding another terminator B0015.
Also in order to reflect the inhibitor concentration, we constructed the following circuit. [BBa_K2120302]
Fig. 5 RFP is used to replace the inhibitor gene.
We constructed 16 (4*2*2) devices [BBa_K2120312][BBa_K2120313][BBa_K2120314][BBa_K2120315][BBa_K2120317][BBa_K2120318][BBa_K2120319][BBa_K2120321][BBa_K2120323][BBa_K2120325][BBa_K2120326][BBa_K2120327][BBa_K1480003][BBa_K145201][BBa_K145113][BBa_K1480004] with the alteration of constitutive promoters (4 kinds), RBS (2 kinds) and inhibitors (2 kinds).
Table 1. The strengths and efficiencies of different promoters and RBS
Fig. 6 Constitutive circuits to reappear the threshold concentration of inhibitors. Only few will be selected and used to prove the concept of plasmid sensing.
2. We construct the constitutive promoter with the corresponding in-promoter in the one plasmids.
After constructing the circuits with different constitutive promoters to express the inhibitor, we change the constitutive promoter direction and add corresponding in-promoter. [BBa_K2120416][BBa_K2120418][BBa_K2120419][BBa_K2120420][BBa_K2120421][BBa_K2120423][BBa_K2120424][BBa_K2120425]
Fig.7 The constitutive promoter express inhibitor protein and repress the downstream in-promoter. The constitutive promoter include J23119, J23106, J23116, J23109; inhibitor include CI and tetR and in-promoter include ptet and pR.
3. We choose plasmids with different copy numbers to simulate the situation of different plasmid losing rates.
Since it’s hard to control the intracellular plasmid numbers, we choose plasmids with different copy numbers to prove our system. Three kinds of plasmids are listed below.
Table 2. The copy numbers of different plasmids.
The fragments containing the constitutive promoter (Fig.8) are linked with and cloned into three types of plasmids individually.
Fig.8 The circuit constructed with constitutive promoter to simulate the situation of different plasmid losing rates.
Test result
1. Simulated the production of inhibitors with different concentrations by adding different concentration of arabinose
In order to construct the environment with different concentrations of inhibitor and find the threshold, we use the PBAD promoter to achieve this. In the wet lab, we chose the CI-PR circuit like the picture (Fig. 1) to do this experiments.
Fig.1 the circuit constructed to measure
When we added enough arabinose, the CI inhibitor could repress the pR promoter fully, so the RFP can’t be tested. Also when the inhibitor was not enough, the promoter will express RFP which stands the killer gene’s expression..
Firstly, we use the model to simulate the relationship between the arabinose added and RFP intensity. We got the curve below (Fig. 2):
Fig. 2 this curve is about the corresponding RFP intensity under the different concentration of the arabinose.
This curve describes the in-promoter activity have a relationship with the different concentrations of the arabinose. That means when we add different concentrations of arabinose, the in-promoter’s activity will be different. We regarded the concentration of arabinose 0.003% as a threshold, the corresponding in-promoter is thought just be repressed regarded as the threshold. Thus we can say the in-promoter can have different responses to the inhibitor.
After the simulation, we added different concentrations of arabinose to construct different concentrations of intracellular inhibitor in the wet lab.
After the pre-experiment, the arabinose concentrations we chose are listed in table.1. The negative control is the strain containing the empty pSB1K3 and the positive control is the strain containing the device in Fig.1 on pSB1K3 without adding the arabinose.
Table. 1 the arabinose concentration used in pre-experiment
The strain we used is E.coli Top10.
Firstly, the two strains containing empty pSB1K3 and containing the device in Fig.1 on pSB1K3 separately overnight (12 h) growth in the LB medium. Then the overnight culture was diluted 1:100 into new LB medium while add the certain concentration of the arabinose.
At first, the overnight culture’s OD600 and red fluorescence intensity are measured. And then we measure the OD600 and red fluorescence intensity every 1-2 hours.
And then we draw the diagram about RFP intensity/OD600 and time under different concentrations of arabinose (Fig. 3).
Fig. 3 the diagram of the about RFP intensity/OD600 and time under different concentrations of arabinose
From this diagram, we can clearly know more arabinose added, less RFP expressed. When the arabinose concentration is 0.003%, the RFP intensity have been very low. So we think when the arabinose concentration is above 0.003%, the in-promoter will be fully repressed that means the killer will not express to kill the bacteria.
Then we collect the data after passing 17.5 hours from Fig. 3 to draw the diagram about the relationship between RFP intensity/OD600 and arabinose concentration (Fig. 4).
Fig. 4 the diagram of the about RFP intensity/OD600 and arabinose concentration
From this curve, we can directly to see the relationship between RFP intensity/OD600 and arabinose’s concentration: The arabinose’s concentration have a negative correlation with RFP intensity/OD600. We regard that the in-promoter have been repressed fully when the concentration of arabinose between 0.003% and 0.004%. So we think when the concentration of arabinose is 0.003%, the in-promoter’s activity is very low, and the killer gene wouldn’t kill the bacteria. So we regard that 0.003% is threshold of arabinose concentration which also is fit in with our modeling part.
After we use the PBAD promoter to construct the environment with different concentrations of inhibitor, we have successfully proved that the in-promoter will respond to the different concentrations of inhibitor differently and found the threshold of inhibitor’s concentration that the PBAD promoter expressed under the 0.003% arabinose concentration.
2. Found out the concentrations of inhibitor under different concentrations of arabinose and used the results to derive the threshold of plasmids number in the constitutive circuit.
In order to know the exact concentration of inhibitor under the different concentrations of arabinose. In E.coli Top10, we used the RFP to replace the inhibitor gene (Fig. 5), so we can use RFP to reflect the inhibitor when we added the same concentration of arabinose.
Fig.5 The circuit constructed to measure the inhibitor concentration, inhibitor is replaced by RFP.
At first, we also use the modeling to simulate this circuit get the curve about relationship between the arabinose added and protein intensity. We got the curve below (Fig. 6):
Fig. 6 The concentration of inhibitor expressed by PBAD changes with different concentrations of inducer.
From this curve, we can clearly see the concentration of arabinose have positive relationship with protein intensity in a proper range. Before we have achieve the threshold of the inhibitor concentration under the 0.003%concentration of arabinose. The point of inducer’s concentration (0.003%) can cast on protein intensity coordinate axis, and the corresponding intensity is about 24.42 units.
In the wet lab, after the pre-experiment, the arabinose concentrations we chose are listed in table.2. The negative control is the strain containing the empty pSB1C3 and the positive control is the strain containing the device in Fig.6 on pSB1C3 without adding the arabinose.
Table. 2 the arabinose concentration used in pre-experiment
Firstly, the two strains containing empty pSB1C3 and the device in Fig.6 separately overnight (12 h) growth in the LB medium. Then the overnight culture was diluted 1:100 into new LB medium while add the certain concentration of the arabinose.
At first, the overnight culture’s OD600 and red fluorescence intensity were measured. And then we measured the OD600 and red fluorescence intensity every 1-2 hours.
We draw the diagram about RFP intensity/OD600 and time under different concentrations of arabinose (Fig. 7).
Fig. 7 The relationship between the fluorescence/OD600 and time
From this diagram we can see that the concentration of inducer will affect the expression of downstream RFP, more inducer added, more RFP will be expressed.
Then we collect the data after passing 11.3 hours from Fig. 8 to draw the diagram about the relationship between RFP intensity/OD600 and arabinose concentration (Fig. 8).
Fig. 8 The relationship between the fluorescence/OD600 and the concentration of arabinose
From this diagram, we can get the conclusion that the concentration of arabinose have a positive correlation with RFP intensity/OD600.
3. Employed plasmids with different copy numbers and simulated the concentration of plasmids losing on different levels.
In order to know the concentration of inhibitor changing with number of plasmids, we chose three types of plasmids with different copy numbers to achieve this.
Three kinds of plasmids are listed below.
Table 3. The copy numbers of different plasmids.
The fragments below (Fig. 9) containing constitutive promoter to express inhibitor.
Fig.9 The circuit constructed to detect the inhibitor protein and the strengths of different promoters.
In order to detect the inhibitor protein more easily, we replace the inhibitor with RFP like circuits below (Fig. 10)
Fig. 10 The fragments constructed on different plasmids
Then we construct two fragments in the Fig. 11 on different plasmids with different copy numbers.
At first, because it’s hard to control the number of plasmids, we use the model to simulate the relationship between the plasmids number and inhibitor protein (Fig. 11).
Fig. 11 The relationship between the protein intensity and the number of plasmids.
From this curve, we can clearly know that the relationship between number of plasmids and protein intensity. The concentration of arabinose have a positive relationship with protein intensity in a proper range. In the previous section, we think when protein intensity above the 24.42 units, the in-promoter will be repressed fully, so the threshold of the number of plasmids is calculated to be 210 copies.
In the wet lab, the strains containing different plasmids copy numbers separately overnight (16 h) growth in the LB medium.
Table. 4 The form about experimental set up.
After 16h growth in the LB medium, we measure the RFP intensity of seven groups. Then we calculate the relative RFP intensity by subtracting the negative control
Table. 5.The RFP intensity of different circuits on different plasmids
From the table. 5, we can know that different plasmids copy numbers will lead to different RFP intensity. More plasmids copies, more RFP expressed.
At the same time, we constructed the constitutive promoter with in-promoter (Fig. 12) on the plasmids with different copy numbers to see the express of the RFP started by in-promoter.
Fig. 12 the circuit constructed on different plasmids.
4. Employed different RBS and promoters with different strengths to change the inhibitor
In order to achieve the goal of regulating the threshold of plasmid number and finally control its number to meet different needs, we decided to set up different groups consist of different RBS and promoters with different strength
Table 6. The strengths and efficiencies of different promoters and RBS
Fig. 13 Constitutive circuits to reappear the threshold concentration of inhibitors. Only few will be selected and used to prove the concept of plasmid sensing.
By now, we can give you a summary. By combining with our modeling part, we have successfully proved that:
(1) The plasmid copies can affect the concentration of inhibitor in the constitutive circuit.
(2) The concentration of inhibitor can affect the in-promoter’s activity and affect the expression of killer gene in the end.
(3) Our system can help the cell sense the number of plasmids.
(4) The number of plasmids can affect the expression of killer gene.
(2) The concentration of inhibitor can affect the in-promoter’s activity and affect the expression of killer gene in the end.
(3) Our system can help the cell sense the number of plasmids.
(4) The number of plasmids can affect the expression of killer gene.
When the plasmid number is above its threshold, the concentration of inhibitor being high enough, the killer gene can be repressed completely.
When the plasmid number is below the threshold, the inhibitor won’t work anymore, the killer can get the chance.
Killer device
Since the lethal efficiency of killer genes will decide the capacity of general circuit, so we have to:
1. Prove that the toxin protein we selected can successfully express and the
lethal effect is obvious
2. Adjust the translation efficiency of toxin proteins through replace ribosome binding site (RBS), thus to adjust the threshold
3. Construct gene circuits connecting killer device and inhibitor device
4. Find another possible way to produce the lethal effect
2. Adjust the translation efficiency of toxin proteins through replace ribosome binding site (RBS), thus to adjust the threshold
3. Construct gene circuits connecting killer device and inhibitor device
4. Find another possible way to produce the lethal effect
Results:
1. Successfully constructed the testing circuits of toxin proteins [Part:
BBa_K2120002 and Part:
BBa_K2120003]
2. After transformation, we measured the OD600 to draw the growth curve and observed the function of toxin protein.
3. In addition to B0032, we selected a stronger RBS B0034 and a weaker one B0031. Through measuring OD600, we demonstrated that we can adjust the lethal efficiency through replacing RBS.
4. Successfully constructed the testing circuit of toxin proteins according to two kinds of inhibitors. [For example, Part: BBa_K2120400]
5. Tested the lethal effect of producing DSB through coupling sgRNA and Cas9
2. After transformation, we measured the OD600 to draw the growth curve and observed the function of toxin protein.
3. In addition to B0032, we selected a stronger RBS B0034 and a weaker one B0031. Through measuring OD600, we demonstrated that we can adjust the lethal efficiency through replacing RBS.
4. Successfully constructed the testing circuit of toxin proteins according to two kinds of inhibitors. [For example, Part: BBa_K2120400]
5. Tested the lethal effect of producing DSB through coupling sgRNA and Cas9
1. Constructing the testing circuits
The DNA Agarose Gel electrophoresis showed that the whole length of the first circuit is about 1500bp, the second circuit is about 1400bp.
Fig.1 DNA Agarose Gel electrophoresis results of mazF
Fig.2 DNA Agarose Gel electrophoresis results of hokD
2. Testing the lethal effect of toxin proteins MazF and HokD by measuring the growth curve.
The testing groups are the two circuits above (mazF and hokD), while the control is the empty vector. Add arabinose or not, there is another comparison. We used 0.01% arabinose to induce the PBAD promoter when the OD600 is 0.6. We measured the OD600 every hour until the bacteria reached the flat stage.
Fig.3 Compared with the negative control (the empty pSB1C3 vector), OD600 of the two circuits containing toxin proteins are obviously lower, and the difference is evident as time going on. No obvious difference observed among the three groups with no induction. It showed that toxin proteins didn’t leak out.
Through the growth curve, we concluded that toxin protein HokD and MazF have different lethal efficiency. Depending on different situations, we can choose either of them.
3. Replacement of the RBS to adjust the lethal effect as well as the threshold
Through one-step mutation, we have separately replaced the B0032 (33.96%) with B0031 (12.64%) and B0034 (100%). Here are the sequencing results.
Fig.4 The successful sequencing results of 4 mutations: B0031+mazF; B0034+mazF; B0031+hokD; B0034+hokD
We used 0.01% arabinose to induce the PBAD promoter when the OD600 is 0.6. We measured the OD600 every hour until the bacteria reached the flat stage.
Fig.5 For the toxin protein MazF, we concluded that the influence of strong RBS is more evident.
Fig.6 For the toxin protein HokD, the replacement of RBS will influence the expression of hokD. The weaker RBS B0031 leads to lower expression of toxin protein HokD.
We tested the lethal efficiency of HokD and MazF under different RBS. Compared with the positive control (pSB1C3 empty vector), the three experimental groups showed obvious difference. For MazF, the strong RBS B0034 was proved to have highest lethal efficiency. For HokD, the weak RBS B0031 was proved to have the lowest lethal efficiency.
4. sgRNA targeting genome of strains with no NHEJ repair system
To test the effects of Cas9 and targeting sgRNA, we separately constructed two plasmids containing sgRNA and Cas9 protein. We co-transformed the two plasmids into E.coli TOP10, and added 10mM arabinose to induce the expression of Cas9. In order to validate the effect of Cas9 and sgRNA, we did quantitative analysis of colony formation after induction to confirm CRISPR/Cas9-Mediated DSB in E.coli TOP10.
Fig.7 experimental procedure
The cells were diluted 102–104 fold and plated onto agar plates containing AmpR and CmR. The results showed that the control group with no induction was growing better than the testing group when both of them were diluted 103 fold, which means the DSB did have the lethal effect and can be used as a candidate for killer device.
Fig.8 Confirmation of CRISPR/Cas9-Mediated DSB in E.coli TOP10
Recombination
Aim
Considering the factor of the potential deficiency of executor killer due to the completely lost of plasmids and the number of "in-promoters" will affect our system, we decide to integrate the killer device into the genome. This group mainly provided a tool for genome integration. The insertion fragment is our testing device, including the expression cassette of rfp and killer gene. With this recombination system, we can get the upgraded type of our P-SLACKiller.
Results
1. Coupled CRISPR/Cas9 system with λ-Red recombineering to integrate the donor fragments, but we haven’t finished the second plasmid construction
2. Tried the traditional lambda Red recombination and successfully inserted four testing devices into the genome, locus of LacI.
2. Tried the traditional lambda Red recombination and successfully inserted four testing devices into the genome, locus of LacI.
Coupling CRISPR/Cas9 system with λ-Red recombineering
1. Plasmid construction
We designed a two-plasmid system applied for it. There was a low-copy plasmid pSTV29 for Cas9 and λ-Red expression from the arabinose-inducible promoter PBAD respectively and a high-copy plasmid pUC19 for sgRNA expression from a constitutive promoter J23119.
Fig.1 Double plasmids to meet different requirements for each element. Equip the high copy number plasmid pUC19 with sgRNA targeting site on genome and donor fragment with homologous arms. The low copy number plasmid are equipped with expression cassette of Cas9 protein and λ-Red recombinase
We mainly used Gibson assembly to construct these two plasmids. The pUC19 plasmid containing sgRNA and donor fragment was successfully constructed. Separately, we successfully constructed the lambda Red protein and Cas9 protein on pSTV29.
However, we didn’t finish the second plasmid construction due to the limit of time. Instead, we decided to employ the traditional lambda Red recombination system to carry out the integration process since we received the plasmid pKD46 from Dr. Bo Lv.
Lambda red recombination
For facile blue and white colony screening, the target site we chose is the 5 ’end of LacZ gene encoding the active site of β-galactosidase. At first, we used strain TOP10 as our host. To test the experiment conditions which is optimal for transformation, we did the pre-experiment and used the resistance Kana gene as the donor fragment to target the gene locus of LacZ. We have tried several times, but failed.
Considering that the complementary sequence between donor fragment and target site is one of the most important factors deciding the successful rate of recombination, we re-designed our experiment. The whole sequence of TOP10 is not open access and the specific sequence for LacZ has been modified and we couldn’t confirm the modified one. So we decided to replace the host to DH5α.
1. Transformed the plasmid pKD46 into host and made it competent cell after induced by L-arabinose
We transformed the pKD46 into competent cell DH5α, and added arabinose to induce the expression of recombinase. When the OD600 is about 0.6 which means the bacteria is at the log phase, we made it competent for electroporation transformation.
2. Preparation of donor fragment
We designed homologous arms with the length of 50bp and 500 bp. The short one was designed on the primer, while the long arm was constructed through over-lap extension PCR
(OE-PCR).
After several times of try-error, we confirmed the comparatively optimal condition for lambda Red recombination. The target site is LacI and the host is DH5α. The homologous arm of 50 bp is enough for recombination.
Using the pKD3 as template, we added the cat expression cassette behind the testing parts, the whole donor fragment was sandwiched by 50bp left and right homologous arm.
Fig.2Four testing circuits used as our donor fragment
Fig.3 DNA Agarose Gel electrophoresis of donor fragments
3. Transformed the donor fragment through electroporation into the competent cell we prepared before
After transformation, we observed clones on the chloramphenicol plates. We selected the positives clones through colony PCR.
Fig.4 Recombination model and the sites of verifying primers
According to our design, the donor fragment is about 2000 bp, while the substituted fragment on genome is 1083bp, which means the successful integration will result in over 1000 bp increasing of length on the locus of LacI. We used the verifying primers to test whether we have successfully integrated these donor fragments.
Fig.5 The positive clones are 1~7, separately indicating the testing circuits above, and 8 is the negative control whose template is the original genome without any integration.
Compared with the negative control with no integration occurred, the colony PCR showed that we have successfully integrated the four circuits into the LacI locus of genome.
Site-directed promoter mutation
We have two combinations of inhibitor and "in-promoter": TetR-PTet, CI-PR. The strength of "in-promoter" will decide the expression level of killer gene. Directly applied these two combinations, we got the initial threshold. In order to adjust the threshold, we planned to mutate the "in-promoter" and got mutants with various strengths. We chose PTet as our target promoter. Through literature research, we chose the -35 region as our mutation region. We mainly used RFP to indicate the promoter strength in our wet experiment.
Results
1. Tried to use one-step mutation, but because of the secondary structure of promoters, we didn’t get positive results
2. Built a library of mutated PTet promoters and characterized the promoter activity through measuring the red fluorescence intensity
3. Selected 4 mutants and got the successful sequencing results
2. Built a library of mutated PTet promoters and characterized the promoter activity through measuring the red fluorescence intensity
3. Selected 4 mutants and got the successful sequencing results
1. One step mutation--plan A
At first, we used “Quickchange”, using the methylated plasmid as a template, which was extracted from E.coli, and we designed a pair of 25pb primers containing the desired mutation to amplify the DNA through PCR, and we got the demethylated plasmids. Finally, we treated the products with Dpn1, which was specific for methylated DNA and was used to digest the parental DNA template and selected for mutation-containing synthesized DNA. And we used the method of thermal stimulation to transform it into E.coli.
But we didn’t we get the positive clone of the plasmid. And we thought as a result of the characteristics of the promoter structure, viewing it from the secondary structure, there appears a cervical-loop structure. Also a mutation site just appears in the loop, which results in primers having a comparatively long homologous region. So the complementary pairing occurs between upstream and downstream primer, forming primer dimer, which lead PCR amplification to failure.
2. Digestion and ligation—plan B
To avoid forming the cervical-loop structure, we gave up the one-step mutation approach. Instead, we designed the mutation on the primers and planned to construct the testing circuit through the traditional digestion and ligation.
We designed random primers containing NNNNNN in -35 region.
Through PCR amplification, we purified the PCR product. We used DpnI to digest the template. Constructed the fragment on the vector pSB1C3, we transformed the ligation product into E.coli TOP10. After incubation at 37℃for 16h, we observed the formation of single clone.
Through colony PCR, we selected the clone on the plate and had successfully got the positive clones. To facilitate the characterization of promoter strength, we constructed circuits containing rfp. The whole length is 923bp, counting the region between VF and VR, the positive length should be over 1000. Results shown in Fig.1.
Fig.1 positive clones of mutated promoters containing RFP
Then we selected the positive clones, incubated it at the tube, and measured the RFP intensity. Under the same condition, the fluorescence intensity of original promoter was 5000, and the PTet-1, PTet-2 and PTet-3 were about 200, while the selected No.25 was about 500.
Fig.2 RFP intensity measurement results. The original PTet has highest activity, while the strength of mutant PTet-25 is about 1/10 of the original one. Other mutants has considerably low activity.
Compared with the original promoter, the promoter activity after mutation was sharply decreased while the difference was obvious between the testing group (data over 200) and the negative control (data below 100). Since we employed PTet to control the expression of toxin proteins, it’s better that we can reduce the background expression as much as possible. The sequencing results confirmed the successful mutation of four mutants.
Fig.3 The sequencing results. Mutation occurred only in -35 region.
Through measuring the RFP intensity, we selected four mutants. They can be used to control the expression of toxin proteins.