SynRT toolkit version 1.0 is the first generation thermosensors collection we provide to users. It contains 48 heat-inducible RNA-based thermosensors.
·Activities of thermosensors increase at elevated temperature
We measured the activities of these thermosensors at six different temperatures: 29, 31, 35, 37, 39 and 42℃, and then fitted curve. Through the curve fitting, we discarded some thermosensors, which have low fitting goodness or have illogical melting temperature. Upon screening, we selected 48 heat-inducible RNA-based thermosensors out of the 150 members. And figure 1 shows the 48 thermosensors' activity. The positive control we designed won't form stem-loop structure with SD sequence by software prediction, and the experimental characterization is described in Measurement page. In order to choose a method to accurately reflect the activity change of our RNA-based thermosensor with temperature, we decided to use normalized fluorescence by positive control. We find that all of these thermosensors' expression level increase at elevated temperature, and the extent of increase relative to temperature is different.
Figure I. Experimental measurement of the heat-inducible RNA-based thermosensors show a variety of responses. (A) Rows represent activity levels of different thermosensors. These values are normalized using the fluorescence/Abs600 of pos.control. (B) Replotting of data from (A). Each set of six bars represents the activity level of a different thermosensor. The bar colors purple, aquamarine, light green, orange, red and brown represent the temperature 29, 31 ,35, 37, 39 and 42℃.
To quantify different features of this library, we computed the fold-change of the response in the given temperature range. As the figure shows, from 29 to 37℃, the fold change ranges from 2.26 fold to 7.17 fold. And from 37 to 42℃, the fold change ranges from 1.40 fold to 3.01 fold. These fold-changes were higher than positive control. These results show that there is a diverse set of heat-inducible RNA-based thermosensors in toolkit.
Conclusion: as these results show, the heat-inducible RNA-based thermosensor we designed can work. The fluorescence value increases with temperature elevated. Besides, the difference in fluorescence intensity and the rate of increase points to the diversity in thermosensor response. We think the sequence change in stem length, loop size, and mismatches or bulges in the stem give rise to the diversity in thermosensor response.
·Thermosensors' features can be computed by fitting curve
Combined with our human practice work we have mentioned in the Overview page. We also have built switching behavior fitting model to describe the continuous switching behavior of thermosensors.
>For more details about our model, you can visit Model page.<
From the fitted curve, we can get the melting temperature, relative intensity and sensitivity of each thermosensors.
You can see the individual result as follows:
BBa_K2541001 (Click one above to change.)
Figure 3. (A) Experiment measurement of the individual heat-inducible RNA-based thermosensor. The height of the bars represent the normalized fluorescence, which is the mean of three replication. The bar colors purple, aquamarine, light green, orange, red and brown represent the temperature 29, 31, 35, 37, 39 and 42℃. (B) The fitted curve of individual thermosensor, the black dash line is the tangent line at the melting temperature. The intersection of the upper gray dash line and curve represents the stem-loop structures are all destroyed. The intersection of the medial gray dash line and curve represents a 50% switch in expression occurs. The intersection of the lower gray dash line and curve represents the stem-loop structures all exist. (C) The features of thermosensors computed through the fitted curve. Melting tempurature is the temperature at which a 50% switch in expression occurs. Sensitivity is defined as the value of derivative at melting temperature. Relative intensity is the predicted intensity when all of the stem-loop structure in thermosensor mRNA were destroyed.
Conclusion: Through the fitting curve, we can compute the features of our thermosensors. Based on these features, we conclude that thermosensors have different sensing range, most of them are from 35 to 37℃. Additionally, they also have some difference in activity and sensitivity. Since we have these diverse set of heat-inducible RNA-based thermosensors, we classified them by melting temperature, relative intensity and sensitivity. Based on these datas, we classified these thermosensors, and develop a search engine -- SynRT Explorer. You can visit our Search Engine page to use it.
This is the results of SynRT toolkit 1.0. Click here to see the results of version 2.0.