Difference between revisions of "Team:Jilin China/Measurement"
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<p>For more information about the improvement of sfGFP, you can visit the Improve page. <b><a href="https://2018.igem.org/Team:Jilin_China/Improve">Click Here!</a></b></p> | <p>For more information about the improvement of sfGFP, you can visit the Improve page. <b><a href="https://2018.igem.org/Team:Jilin_China/Improve">Click Here!</a></b></p> | ||
<h3>4. Double terminator</h3> | <h3>4. Double terminator</h3> | ||
| − | <p>In order to prevent the leakage of the gene, we decided to add two terminators at downstream sfGFP.</p> | + | <p>In order to prevent the leakage of the gene, we decided to add two terminators(BBa_B0010 and BBa_B0012) at downstream sfGFP.</p> |
</div> | </div> | ||
</li> | </li> | ||
| Line 100: | Line 100: | ||
<div> | <div> | ||
<h2>Methods</h2> | <h2>Methods</h2> | ||
| − | <p>Before we did | + | <p>Before we did experiments, we encountered a problem -- what methods did we use to accurately reflect the change in our RNA-based thermosensor with temperature?</p> |
<p>Before solving this problem, we must determine how the expression system of the chassis organism <i>E.coli</i> DH5α is affected by temperature. In order to solve this problem, we have designed positive control devices with different intensities. Their RBS sequence predicted by the software will not form a stem-loop structure.</p> | <p>Before solving this problem, we must determine how the expression system of the chassis organism <i>E.coli</i> DH5α is affected by temperature. In order to solve this problem, we have designed positive control devices with different intensities. Their RBS sequence predicted by the software will not form a stem-loop structure.</p> | ||
<p>Fudan_China team helped us to measure some of the positive controls and plotted sfGFP expression intensity curve with temperature and got the following results:</p> | <p>Fudan_China team helped us to measure some of the positive controls and plotted sfGFP expression intensity curve with temperature and got the following results:</p> | ||
Revision as of 20:38, 17 October 2018
Measurement
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Overview
After designing a large number of RNA-based thermosensors, we began to consider about how to measure these thermosensors to get their melting temperature, intensity and sensitivity. After reading a large amount of relevant literature, we designed the following measurement device, which consists of a promoter, RNA-based thermosensor, sfGFP and double terminator. We have added different types of measurement devices to the Parts Registry.
Figure 1. Diagram of the measurement device.
The measurement protocol has been added to the Protocol page, you can click here to read. And for more information about the results, you can visit our results page.
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Measurement Device
1. Promoter
In the selection of promoters, we have done pre-experiments to select suitable promoter for different types of RNA-based thermosensors, in order to get the valid expression intensity between different RNA-based thermosensors and avoid the inaccurate results.
2. RNA-based thermosensor
RNA-based thermosensor is the temperature sensing element, which involves the Shine-Dalgarno （SD） sequence. We have designed four different types of RNA-based thermosensors. For more information about the design of the RNA-based thermosensor, you can visit our Design page. Click Here!
3. sfGFP
sfGFP, superfolder Green Fluorescence Protein，is the reporter protein of measurement device. It develops fluorescence about 3 fold faster than mut3 GFP and reaches 4 fold higher absolute fluorescence levels. Fluorescent colonies can be identified with the naked eyes even without UV or blue light illumination. Additionally it is more stable in vitro and refolds faster after in vitro denaturation with respect to mut3 GFP.
Since we used the Golden Gate assembly this year, the sfGFP from iGEM parts registry cannot be used because it contains the commonly used IIS restriction enzyme site. In order to solve this problem, we designed BbsI free site-directed mutagenesis sfGFP for Golden Gate and prokaryotic codon-optimism sfGFP_optimism. We compared these two parts with sfGFP and added them to the registry. As can be seen from the data, sfGFP_optimism has a strong fluorescence intensity, so we finally apply sfGFP_optimism in the construction device.
For more information about the Golden Gate assembly, you can visit the Construction page. Click Here!
For more information about the improvement of sfGFP, you can visit the Improve page. Click Here!
4. Double terminator
In order to prevent the leakage of the gene, we decided to add two terminators(BBa_B0010 and BBa_B0012) at downstream sfGFP.
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Methods
Before we did experiments, we encountered a problem -- what methods did we use to accurately reflect the change in our RNA-based thermosensor with temperature?
Before solving this problem, we must determine how the expression system of the chassis organism E.coli DH5α is affected by temperature. In order to solve this problem, we have designed positive control devices with different intensities. Their RBS sequence predicted by the software will not form a stem-loop structure.
Fudan_China team helped us to measure some of the positive controls and plotted sfGFP expression intensity curve with temperature and got the following results:
Figure 2. Fluorescence expression of positive control at different temperatures at 8 hrs. The figure’s horizontal axis represents the temperature range (28℃ to 42℃), and the vertical axis represents fluorescence intensity of sfGFP. (A) represents positive control-1, (B) represents positive control-2.
As the figure shows that the expression intensity of sfGFP by E.coli also increases with elevated temperatures. So we came to the following conclusions:
1. E.coli DH5α protein expression system will be affected by temperature.
2. The change of temperature and the expression level of sfGFP are approximately linear.
We are very grateful to Fudan_China for helping us in this experiment. Other cooperation about us will be recorded on the Collaboration page, you can Click Here!
After obtaining such a conclusion, it is important to eliminate the influence of temperature to the bacterial expression system. Therefore, as for the data processing, we mainly reflect the sfGFP intensity expressed by bacteria at a unit concentration by Fluorescence/Abs600. And the Normalized Fluorescence is used to reflect the change of expression intensity with different temperature in the experimental group compared with the control group. Their calculation methods are as follows:
