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Team:St Andrews/project/RBS
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We decided to design RBS sequences with different translation rate for GFPmut3b as it is the most popular fluorescent protein by using the RBS calculator. Therefore two RBS sequence was designed by the Forward engineering program with the specific rate. In addition the rate of one of the Anderson RBS catalog was measured by the Reverse engineering program. | We decided to design RBS sequences with different translation rate for GFPmut3b as it is the most popular fluorescent protein by using the RBS calculator. Therefore two RBS sequence was designed by the Forward engineering program with the specific rate. In addition the rate of one of the Anderson RBS catalog was measured by the Reverse engineering program. | ||
We designed an experiment to measure the rate of protein expression by using these three RBS. The next step was ordering a sequence and then following the lab work for ligating these RBS with a promoter and GFP protein. After a successful ligation, the rate of protein expression of each biobrick was measured by flow cytometry and the negative control was I13401. | We designed an experiment to measure the rate of protein expression by using these three RBS. The next step was ordering a sequence and then following the lab work for ligating these RBS with a promoter and GFP protein. After a successful ligation, the rate of protein expression of each biobrick was measured by flow cytometry and the negative control was I13401. | ||
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This the result of our experiment: | This the result of our experiment: | ||
Revision as of 12:09, 27 October 2010
Contents |
Motivation
One of the major problems that we have observed from the past teams it was not having fine control over protein expression. Since the Ribosome Binding Site sequence play a key role on rate of protein expression, here we face this problem by using a bioinformatic tool able to design the RBS sequence for a specific coding sequence with the wanted translation rate.
Ribosome Binding Site
The Ribosome Binding Site (RBS) is a sequence on the messenger RNA to which the ribosome can bind and initiate protein translation. In bacteria, the initiation of the translation requires a RBS sequence and a start codon. Ribosome binding sites can control the translation initiation rate and thereby protein expression [1]. Regulating the level of protein expression is required to connect genetic circuits [1] and control the energy flux through a metabolic pathway [2].
The RBS affects the translation rate of an open reading frame (ORF) in two main ways [3]. First, the rate at which ribosomes are attached to the mRNA and initiate translation is dependent on the RBS sequence. Second, the RBS influences the level of protein synthesis by modifying mRNA stability. The stability of the mRNA has impact on the steady state level of mRNA; for example, two mRNAs are being produced at the same rate but the stable one, the one with longer life, would produce more protein than the less stable one. Since the primary sequence and the secondary structure of an RBS (for example, the RBS could introduce a RNase site) can affect the stability of the mRNA, the RBS can affect the amount of mRNA translated and thus, the level of protein expression.
Translation in Bacteria involves four steps: initiation, elongation, termination and ribosome turnover [4]. Translation initiation is the rate-limiting step. Its rate is determined by molecular interactions, such as hybridization of the 16S rRNA to the RBS sequence, the binding site of tRNA-fMET to the start codon, the distance between the 16S rRNA binding site and the start codon (spacing) and the presence of RNA secondary structures that occlude either the 16S rRNA binding site or the standby site [1]. A thermodynamic model takes into account the strength of molecular interaction between an mRNA and the 30S ribosome complex to predict the translation initiation rate [1]. The model is based on two separated reversible transition states. The initial state is the folded mRNA and the free 30S complex and the final state is the assembled 30S complex on an mRNA. The difference in Gibbs free energy between these two states (ΔGtot) relies on the mRNA sequence surrounding a start codon (AUG or GUG). ΔGtot is more negative when there is an attractive interaction between ribosome and mRNA and ΔGtot is more positive when there is exclusive secondary structure [1].
How we can measure and regulate protein expression
The RBS Calculator is a piece of software programmed to design synthetic ribosome binding sites, facilitating a rational control of protein expression. The software has two parts: forward engineering and reverse engineering. Forward engineering incorporates a thermodynamic model into an optimizing algorithm for designing a ribosome binding site sequence which is predicted to drive protein translation at a particular rate. Reverse engineering predicts the relative translation rate of an existing RBS sequence with regard to upstream protein coding sequence.
[http://voigtlab.ucsf.edu/software/ RBS Calculator]
Experiment and RBS Characterizing
We decided to design RBS sequences with different translation rate for GFPmut3b as it is the most popular fluorescent protein by using the RBS calculator. Therefore two RBS sequence was designed by the Forward engineering program with the specific rate. In addition the rate of one of the Anderson RBS catalog was measured by the Reverse engineering program. We designed an experiment to measure the rate of protein expression by using these three RBS. The next step was ordering a sequence and then following the lab work for ligating these RBS with a promoter and GFP protein. After a successful ligation, the rate of protein expression of each biobrick was measured by flow cytometry and the negative control was I13401. This the result of our experiment:
Reference
1. Voigt, C., Mirsky, E., Salis, H. Automated desing of sysnthetic ribosome binding sites to control protein expression. Nature Biotechnology ,946-950 (2009)
2. Dueber, J.E. et al. Synthetic protein scaffolds provide modular control over metabolic flux. Nature. Biotechnolgy. 27, 753–759 (2009)
3. Bernstein, JA., Khodursky, AB., Lin, PH., Lin-Chao, S., Cohsen, SN., Global analysis of mRNA decay and abundance in Escherichia coli at single-gene resolution using two-color fluorescent DNA microarrays.
