(497f) A Genome-Scale Analysis Of The Translational Efficiencies Of E. Coli Genes

Translation is a central cellular process and the sheer complexity of its mechanism necessitates mathematical frameworks to better understand system properties and make quantitative predictions for many problems in medicine and biotechnology. Central to the translation mechanism is the elongation phase, during which 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.

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, in order to better understand the relationship between codon usage patterns and protein synthesis properties, we have developed a gene sequence specific mechanistic model for translation which accounts for all the elementary steps of translation elongation.

We apply our mechanistic framework to the translation of every protein in E. coli in order to determine the translational efficiency of each gene. We also perform a sensitivity analysis to determine the contribution of elongation kinetic parameters of each codon on the overall protein synthesis rate of each gene. We observe that the relative position of codons along the mRNA determines the rate limiting effect of the individual codons and the optimal protein synthesis rate. Applying our mechanistic framework to E. coli genes aids in understanding the complex, nonlinear interplay between codon usage and protein synthesis properties, and in characterizing how these properties relate to patterns such as gene expression levels and function in cells. Based on these studies we propose some principles for the design of vectors for optimal protein production.