Modelling ribosome kinetics and translational control on dynamic mRNA

Abstract

The control of protein synthesis and the overall levels of various proteins in the cell is critical for achieving homoeostasis. Regulation of protein levels can occur at the transcriptional level, where the total number of messenger RNAs in the overall transcriptome are controlled, or at the translational level, where interactions of proteins and ribosomes with the messenger RNA determine protein translational efficiency. Although transcriptional control of mRNA levels is the most commonly used regulatory control mechanism in cells, positive-sense single-stranded RNA viruses often utilise translational control mechanisms to regulate their proteins in the host cell. Here I detail a computational method for stochastically simulating protein synthesis on a dynamic messenger RNA using the Gillespie algorithm, where the mRNA is allowed to co-translationally fold in response to ribosome movement. Applying the model to the test case of the bacteriophage MS2 virus, I show that the models ability to accurately reproduce experimental measurements of coat protein production and translational repression of the viral RNA dependant RNA polymerase at high coat protein concentrations. The computational techniques reported here open up the potential to examine the infection dynamics of a ssRNA virus in a host cell at the level of the genomic RNA, as well as examine general translation control mechanisms present in polycistronic mRNAs.

Design of a self-regulating mRNA gene circuit

“…Here I have demonstrated as a proof of concept that such artificial gene regulatory mRNAs can be constructed. Moreover, I have also shown that a stochastic computational model that takes into account detailed steps of ribosome kinetics 17 , can be utilised simulate translational coupling/repression, predict protein synthesis rates, and design mutations which enhance protein expression.…”

“…Second, the mutated sequence is folded for t = 1 second of time kinetically using KFOLD 21 starting from a single-stranded state. Finally, the mutated sequence is tested for its ability to return the NLuc ribosome binding site back to its original structure during co-translational folding in the presence of ribosomes using my ribosome/folding kinetics model which simulates mRNA co-translational folding kinetics due to ribosome movement over the mRNA 17 . Satisfying these three tests insures that; (a) kinetic folding of the sequence is "funnelled" into the thermodynamic minimum free energy structure and, (b) that co-translational folding of the sequence does not trap any structures (particularly the ribosome binding site) into mis-folded states.…”

“…While each of these can provide estimation of gene expression in a prokaryotic system, they are not capable of predicting gene experssion on mRNAs containing the two key features of interest in this study, specifically translational coupling and repression. For this reason, computational prediction of coat protein and nano luciferase expression of the CTNano-cnt and CTnano mRNAs where simulated using my ribosome/folding kinetics model 17 . This model is capable of predicting gene experssion in mRNAs with translational coupling/repression since it simulates the movement of ribosomes and the resulting co-translational folding of the mRNA of interest in addition to simulating the entire translational process that would be occurring in the cellular 'background' of an exponentially growing E. Coli cell.…”

“…Modelling this competition is critical to correctly calculating when the Nano-luc gene will be fully repressed and will be dependent on how the concentration of coat protein increases over time. Further details on the parameter settings, the number of cellular mRNAs, and the cell growth rate, can be found in 17 .…”

“…The resulting polycistronic mRNA contains separate genes for the coat and NLuc proteins, with the NLuc protein being translationally coupled and repressed by the MS2 coat protein. Through the use of my computational tool which simulates the kinetics of ribosome translation and mRNA co-translation folding due to ribosome movements on the mRNA 17 , I am able to propose a series of mutations which enhance overall protein expression and the ability of MS2 coat protein to repress expression of NLuc via the binding of coat protein to a TR hairpin. Interestingly, the results also reveal the importance of alternative RNA secondary structures in the RBS and how these can kinetically compete to alter gene expression, providing important insights into the impact of RNA secondary structure on translation efficiency.…”