Team:Jilin China/Measurement

MEASUREMENT


Devices Methods

Measurement

  • Overview

    After designing a large number of RNA thermosensors, we began to think 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 thermosensor, sfGFP and double terminator. We have added different types of measurement devices to the parts registry.

    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.

  • Measurement Device

    1. Promoter

    In the selection of promoters, we have done pre-experiments to select suitable promoter for different types of RNA thermosensors, in order for the valid expression intensity difference between different RNA thermosensors, and avoid the inaccurate results.

    2. RNA thermosensor

    RNA thermosensor is the temperature sensing element and involves the ribosome binding site(RBS). We have designed four different types of RNA thermosensor. For more information about the design of the RNA 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. Fluorescenct 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 at downstream sfGFP.

  • Methods

    Before we did experiment, we encountered a problem -- what methods did we use to accurately reflect the change in our RNA 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:

    As the figure shows that the intensity of expression of sfGFP by E.coli also increases at the elevated temperature. 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 part of the 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/OD600. 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: