Part:BBa_K2541201
Cold-repressible RNA-based thermosensor-1
A RNA-based thermosensor that can be used for temperature sensitive post-transcriptional regulation which is based on the change of RNA sencondary structure. The cold-repressible RNA-based thermosensors can repress translation of downstream genes at low temperatures.
1. Usage and Biology
RNA-based temperature sensing is common in bacteria that live in fluctuating environments. Most naturally occurring RNA thermosensors have long sequences and complicated sencondary structure and function by sequestering the Shine–Dalgarno (SD) sequence in a stem-loop structure at lower temperatures.
Here, we designed short, cold-repressible RNA thermosensors, which will form a stem-loop upstream Shine–Dalgarno (SD) sequence. These thermosensors contain a double-strand RNA cleavage site for RNase III, an enzyme native to Escherichia coli and many other organisms. At low temperatures, the mRNA stem-loop is stable to expose the RNase III cleavage site and the transcript will be degraded. At elevated temperatures, the stem-loop will unfold and translation will occur unhindered.
These short, modular cold-repressible RNA thermosensors can be applied to the construction of complex genetic circuits, facilitating rational reprogramming of cellular processes for synthetic biology applications.
2. Design
The RNase III recognition site is a distal box (db) sequence ad its cleavage site is proximal box (pb) sequence. We keep the db and pb sequence conserved which is necessary for RNase III to cleave. And we change their adjacent base pairs to increase or decrease the stem length to design cold-repressible RNA-based thermosensors with different melting temperatures, intensity and sensitivity. Moreover, changing adjacent base pairs may also influence RNase III catalytic efficiency.
Adding stem length can optimize cold-repressible RNA-based thermosensors to more high temperature, while decreasing stem length has the opposite effect. The stem length is X base paring in K2541201. After designing, the theromsensor sequence is predicted by computational methods mFOLD to get its minimum free energy and secondary structure (figure 2).
Figure 2. Design of synthetic cold-repressible RNA-based thermosensor. (A) The RNA secondary structure is predictred by mFOLD. (B) Thermosensor sequence, △G and Tm are in the table.
3.Characterization
The thermosensor sequence is constructed on the pSB1C3 vector by GoldenGate assembly. The measurement device is composed of Anderson promotor (BBa_J23106), thermosensor (BBa_K2541201), sfGFP_optimism (BBa_K2541400) and terminator (BBa_B0015). We select a medium constitutive Anderson promoter J23106 as a suitable promoter by pre-experiment. The sfGFP_optimism has faster folding speed and higher fluorescence intensity. The B0015 is a double terminator that can reduce leakge (Figure 3). We characterized RNA-based thermosensors in E.coli DH5a.
On the left side of the figure 4 is K2541201. On the right of figure 4 is positive control. K2415029, K2514013, K2514037 are three heat-inducible RNA-based thermosensors with different intensity. As shown in the figure 4, the thermosensor K2541001 ‘off’ from 29°C to 37°C. Its intensity is about equal to K2541037.
Figure 4. Characteristics of synthetic heat-repressible RNA-based thermosensors. Each set of three bars represents the activity level of a different thermosensor. The bar colors purple, yellow and red represent the temperatures 29, 37 and 42°C, respectively. The height of the bars corresponds to the normalized fluorescence.
This year, our project is to design a collection of RNA-based thermosensors with different melting temperatures, intensity and sensitivity. We used a combination of experimental measurements and computations of RNA secondary structures to achieve this objective. We studied a set of measured synthetic RNA-based thermosensors, finding consistency with measured results and among our experimental and computational analyses.
Figure 5. Temperature response of the heat-repressible RNA-based thermosensor. The red solid line represents the activity of the RNA-based thermosensor as a function of temperature. Key quantitative features of the response such as Tm, intensity, threshold and sensitivity are emphasized.
Figure 6. Experimental measurements of the collection of heat-repressible RNA-based thermosensors show a variety of responses. (A) Rows represent activity levels of different thermosensors. (B) Each set of three bars represents the activity level of a different thermosensor. The bar colors purple, yellow and red represent the temperatures 29, 37 and 42°C, respectively. The height of the bars corresponds to the normalized fluorescence.
4. Conclusion
Our data show that efficient RNA-based thermosensors with different melting temperatures, intensity and sensitivity can be built from a single small RNA stem-loop structure, thus providing useful RNA-based toolkit for the regulation of gene expression.
Sequence and Features
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