(6ch) A Systems Biology Approach to Protein Translation

Translation, or protein synthesis, is a process that is central to cellular function and well conserved among all living organisms. Understanding the translation mechanism is important in many areas of medicine and biotechnology. Recent advances in genomics, microarray technology, and proteomics make possible the mapping between mRNA and protein expression levels in cells and have led to a wealth of information on protein synthesis at the systems, or genome wide, level. Mathematical modeling and computational studies are vital for integrating this vast information in order to characterize protein synthesis networks and predict how translational machinery responds under genetic or environmental perturbations.

Translation is essentially a polymerization process facilitated by the ribosome on an mRNA template consisting of initiation, elongation, and termination phases. Initiation occurs with binding of the ribosome to the ribosomal binding site near the 5' end of the mRNA. During elongation the ribosome facilitates assembly of the polypeptide chain with one amino acid added at each codon along the length of the mRNA. Amino acids are delivered to the ribosome by tRNAs that serve as adapter molecules between the amino acid and the codon occupying the ribosomal A site. Termination involves release of the completed peptide from the ribosome near the 3' end of the mRNA. Several ribosomes can simultaneously translate the same mRNA, forming a structure called a polysome.

We developed a gene sequence specific mechanistic model for the translation machinery which accounts for all the elementary steps of the translation mechanism. Specifically, our model includes all the elementary steps involved in the elongation cycle at every codon along the length of the mRNA. We performed a sensitivity analysis in order to determine the effects of kinetic parameters and concentrations of the translational components on protein synthesis rate. Utilizing our mathematical framework and sensitivity analysis, we investigated the translation kinetic properties of a single mRNA species in E. coli. We propose that translation rate at a given polysome size depends on the complex interplay between ribosomal occupancy of elongation phase intermediate states and ribosome distributions with respect to codon position along the length of the mRNA, and this interplay leads to polysome self-organization that drives translation rate to maximum levels.

We expanded our model to account for the non-specific binding of tRNAs to the ribosomal A site, and we find that the competitive, non-specific binding of the tRNAs is the rate limiting step in the elongation cycle for every codon. By introducing our model in terms of the Michaelis ? Menten kinetic framework, we determine that these results are due to the tRNAs that do not recognize the ribosomal A site codon acting as competitive inhibitors to the tRNAs that do recognize the ribosomal A site codon. We also expanded our sensitivity analysis to determine the contribution of elongation cycle kinetic parameters of each codon on the overall translation rate. Our sensitivity analysis predicts that different configurations of codons along the length of the mRNA control translation rate at different polysome sizes. We also observe that the relative position of codons along the mRNA determines the optimal protein synthesis rate and the rate limiting effect of the individual codons.

We applied our expanded mechanistic framework and sensitivity analysis to the translation of every protein in E. coli in order to determine the translational efficiency of each gene. Because of the important role codons play in translation kinetics, codon usage patterns have been correlated with gene characteristics such as expression level, intragenic position, and length. However, codons have varying elongation kinetics due to different tRNA availabilities, codon ? anticodon compatibilities, and the multiple elementary steps and translational components involved in the elongation cycle at every codon. Hence, applying our mechanistic framework to E. coli genes aids in understanding the complex, nonlinear interplay between codon usage and protein synthesis properties, and characterizing how these properties relate to patterns such as gene expression levels and function in cells. Our results have implications in design of rational protein production systems, wherein quantitative knowledge of responses of protein expression to genetic or environmental perturbations can be used to optimize a cellular system towards the production of a protein of interest.