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Revision as of 05:43, 14 October 2018
Overview
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余戎镇 正在编辑此页面
更新时间 Oct,14,2018 12:35PM
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SynRT Toolkit 1.0
This year, we aimed to develop a RNA-based thermosensor toolkit. Based on adding the stem-loop structure to 5'UTR, the thermosensors achieve the temperature sensing. And we construct the measurement device to characterize these thermosensors.
At elevated temperature, expression intensity of the reporter protein, sfGFP_optimism, increased sharply between 33 to 42℃, so we named this kind of thermosensor as Heat-inducible RNA-based thermosensor. After getting the measurement results of the first batch of heat-inducible RNA-based thermosensor. We showed the hopeful results to our users, including scientific researchers, medical practitioners, fermentation industry practitioners, etc. Through these human practice, we got many significant suggestions.
For example, by means of investigation in fermentation industry, the research engineer told us that for the potential users like them, the melting temperature of thermosensor should not be the only optional property, intensity and sensitivity should also be thought.
That really inspired us, we continued to design more and more thermosensors and measure them. Meanwhile, we also began to think, how to make users select a thermosensor conveniently? How to get the melting temperature, intensity and sensitivity of the thermosensor? To solving these problem, we decide to fit curve to reflect the relationship between the change of temperature and the expression intensity of thermosensors.
When we saw these different curve, there's a new question came up. Some of the thermosensor showed unsatisfactory result -- they don't have melting temperature or the melting temperature is too high or too low. So how to decrease the appearance of undesirable thermosensors? We decide to use random forest algorithm. We want to use machine to tell us whether the thermosensor is undesirable if we only provide the sequence. And we made it! This algorithm raised correct rate from 55% to 75% successfully.
After that, we continued to do experiments and got a lot of thermosensors. We chose 51 heat-inducible RNA-based thermosenors and added them to the parts registry. We also developed a search engine, we called SynRT Explorer. Until now, we have built the RNA-based thermosensor toolkit successfully!
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SynRT Toolkit 2.0
When we provided the SynRT toolkit to our potential users, we also got a meaningful suggestion. Except the heat-inducible RNA-based thermosensors, users also want a thermosensor that its intensity will decrease at elevated temperature. Based on this requirement, we update our SynRT to version 2.0. We designed heat-repressible RNA-based thermosensors, which based on the RNase E. We designed hundreds of heat repressible RNA-based thermosensors, measured them and selected 23 thermosensors in the toolkit.
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SynRT Toolkit 3.0
We definitely won't stop going, after getting these excited result, we still want to explore more. Can we expand our sensing temperature range? Can we design more different type of RNA thermosensors? Finally, we update the SynRT toolkit again. Now we call it SynRT 3.0, which contains four different types of RNA-based thermosensors. The cold-inducible RNA-based thermosensors and cold repressible RNA-based thermosensors were added to the SynRT toolkit. Cold-inducible RNA-based thermosensors based on the cspA 5'UTR mRNA, and cold-repressible RNA-based thermosensors based on the RNase III.
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Postscript
After getting these exciting results, we didn't want to stop going. We know there still are more things waiting for us to explore. The SynRT toolkit are still updating, we aim to provide users multiple thermosensor Biobricks to select.