ABSTRACT

Manystrategies could be used by bacteria to coordinate temperature-dependent gene expression. A well-known class of biological temperature sensitive element is RNA-based thermosensor (RT), which is thermoregulatory RNA sequence in the 5'-untranslated region of mRNAs. RNA thermosensors could induce equilibrium shift between closed and open conformations of the translation initiation region under temperature variation, which influences the mRNA degradation or ribosome accessibility, thereby controlling translation efficiency.

However, natural RNA-based thermosensors have complex structure and narrow sensing temperature range, which become the biggest limitation on their potential application in many areas. To address this issue, based on free-energy method, we designed a series of synthetic RNA-based thermosensors (SynRTs), which have broader sensing range. Then, we predicted their theoretical sensing temperature through software, detected the practical threshold by experimenting setting temperature gradient, and used biophysical model to analyse their individual abilities to modulate gene expression, which include sensing temperature, expression intensity and sensitivity. Then we constructed evaluation model based on random forest, which we use to judge if the thermosensor is desirable.
After these systematic analytical works, we created a toolkit and matched search engine for potential users in numerous foundational and applied areas. We name this as SynRT toolkit, which have updated from version 3.0 to 1.0.