※. To whom correspondence should be addressed, SHI Binbin, ltbyshi@gmail.com; DING Hongxu, poulainding@163.com.
Abstract The first software that can design temperature-sensing regulatory RNA – RNAThermo is presented in this article. Parameters were set and several temperature-sensing regulatory RNA sequences were given by the RNAThermo. The designed RNAs are verified both on the structural and functional aspects. At the end of the article, RNAThermo’s potential application in fermentation industry is discussed.
Keywords: RNA Thermometer, computer, design
Introduction
Besides exploration, explanation and prediction, the ultimate goal of science is creation. In the field of life science, enthusiasm towards creation originates the synthetic biology. During the last decade, numerous artificial biological networks had been made. However, no nodes within these networks are artificially made thus such networks cannot be recognized as ‘created’. Recently, the creation of nodes inside biological networks emerges as a hotspot. Because of its structural simplicity and manipulation convenience, RNATs become an ideal model for conducting such researches.
RNA Thermometer (RNAT)
Resides in the 5’ untranslated region (5’UTR) of the whole mRNA, RNA thermometer (RNAT) is a kind of temperature-sensing sequence. As the environmental temperature changes, the RNAT can fold into a series of different secondary structure. Some of the structures can block ribosomes’ access to the mRNA thus hinder translation (referred to as unmelted structure). Other structures can cause ribosomes’ binding to the mRNA and the initiation of translation (referred to as melted structure). By shifting from the two kinds of structures, the RNAT regulate gene expression in the level of translation (1).
The software RNAThermo can design RNATs that meet the given parameters
Based on biological and physical principle, adapting computer algorithms, RNAThermo designs RNATs that meet the given parameters. What the user should tell the software are the regulation temperature, the structure (both unmelted structure and melted structure) of the RNAT and the SD sequence position of the RNAT. RNAThermo gives the sequences of RNATs that fulfill these requirements.
The design of RNATs based on biological principle
The principle behind the RNATs’ response to temperature is simple: At low temperatures, sequence that binds to ribosome will be trapped in a hairpin structure. Increasing temperature destabilizes the structure such that the trapped sequence becomes accessible, allowing translation to be initiated. The following (Figure 1) is the schematic diagram (2):
Figure 1. Structural change of RNAT’s according to the environmental temperature. The SD stands for Shine-Dalgarno sequence, which is recognized and bind by ribosome to initiate translation. The AUG stands for start codon, from where the translation begins.
One example for this mechanism is the regulation of E.Coli’s rpoH gene (Figure 2). Responded to environmental temperature change, rpoH gene regulates the expression of the heat shock protein. Low temperatures (30 °C) induces a bend in the ribosome-binding site (RBS)-associated downstream box (DB) region, thereby interfering with ribosome binding. High temperature (42 °C) disrupt the bend and initiate the process of translation (3).
Figure 2. a. Formation of stem III in the rpoH transcript at low temperatures (30 °C) induces a bend in the ribosome-binding site (RBS)-associated downstream box (DB) region, thereby interfering with ribosome binding. b. A rise in temperature to 42 °C opens stem III and stem I of the rpoH mRNA, liberates the AUG start codon and DB region, facilitates ribosome binding.
Inspired by such mechanism, our group designed a series of RNATs whose SD sequence will have trap-release structural change according to the environmental temperature. The following is the schematic diagram of the RNATs we designed (Figure 3):
Figure 3. Schematic diagram of the RNATs we designed. The red box indicates the SD sequence.
The design of RNATs based on physical principle
To give RNAT sequences that meet the given parameters, the central problem is to predict RNATs’ secondary structure at a given temperature. Two methods are adapted according to the computer algorithm’s requirement (More details will be articulated in ‘The design of RNATs adapting computer algorithms’).
One principle adapted in predicting RNA secondary structure is free energy minimization (4). Secondary structure with the least free energy is considered to be the optimal solution (5).
Another principle adapted here is partition function method (6). Rather than give one definite structure as the free energy minimization method, partition function tells the probability of each secondary structure’s appearance. In the following equation, Q stands for partition function and P (structure) stands for the probability of one specific structure’s appearance.
The design of RNATs adapting computer algorithms
This part is included in another page of our wiki.
Verification of the designed RNATs’ secondary structure
The first step in verification the in silico design is testifying the designed structure in vitro. In-line probing method is adapted to measure the RNATs’ structure (10). The results are as shown in Figure 5.
Figure 5
Verification of the designed RNATs’ temperature-sensing regulatory function
Then, rectification of the temperature-response regulatory function in vivo should be taken in verification of the in silico design. GFP is adapted as reporter gene in measuring the RNATs’ temperature-response regulatory function. The results are shown in Figure 6.
Figure 6
Potential Application in Fermentation Industry
Computer aided RNAT design provides a new method for achieving controlled expression of products in fermentation industry. Engineered microorganisms sense a temperature signal and initiate the regulation. The results are shown in Figure 7.
Figure 7
Reference
(1). Jens Kortmann and Franz Narberhaus. Bacterial RNA thermometers: molecular zippers and switches. NATURE REVIEWS MICROBIOLOGY, VOLUME 10, 265, APRIL 2012
(2). Birgit Klinkert and Franz Narberhaus. Microbial thermosensors. Cell. Mol. Life Sci. (2009) 66:2661–2676
(3). Miyo Terao Morita, Yoshiyuki Tanaka, Takashi S. Kodama, Yoshimasa Kyogoku,
Hideki Yanagi and Takashi Yura. Translational induction of heat shock transcription factor sigma32: evidence for a built-in RNA thermosensor.. Genes Dev. 1999 13: 655-665
(4). David H. Mathews. Revolutions in RNA Secondary Structure Prediction. J. Mol. Biol. (2006) 359, 526–532
(5). David H Mathews and Douglas H Turner. Prediction of RNA secondary structure by free energy minimization. Current Opinion in Structural Biology 2006, 16:270–278
(6). J. S. McCASKlLL. The Equilibrium Partition Function and Base Pair Binding Probabilities for RNA Secondary Structure. Biopolymers, Vol. 29,1105-1119 (1990)
(7). http://www.tbi.univie.ac.at/~ivo/RNA/
(8). http://www.tbi.univie.ac.at/~ivo/RNA/man/RNAfold.html
(9). L. Hofacker, W. Fontan. Fast folding and comparison of RNA secondary structures. Monatshefte fur Chemie , 125, 167-188.
(10). In-Line Probing Analysis of Riboswitches.Elizabeth E. Regulski and Ronald R. Breaker. NATURE PROTOCOL EXCHANGE http://www.nature.com/protocolexchange/protocols/1889
Acknowledgement
Thank Prof. CHEN Guoqiang, Prof. SUN Zhirong and Prof. DAI Junbiao for devoting guidance in the project. Thank Prof. Tom Kelie for his careful revision of the PPT and the report. Thanks Dr. YIN Ping and Dr. QU Peng for his kind help in the RNA experiments. Thanks FU Xiaozhi and LI Teng for their generous help in the molecular biology experiment.
Supporting online materials
1. PDF version of the article
2. A demo of RNAThermo
3. Algorithm of RNAThermo
4. RNAThermo download
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