Does quantitative tRNA adaptation to codon content in mRNA optimize the ribosomal translation efficiency? Proposal for a translation system model.

Neither a dynamic nor an energetic approach of the translation process has taken into account that intracellular levels of iso-tRNA species are adapted or adjusted to the codon frequency of mRNA being decoded (Bombyx mori silk gland, rabbit reticulocyte). A critical study of available experimental data suggests that the average elongation rate of a protein is maximized in the presence of an adapted tRNA population, usually an homologous tRNA. In addition, the amount of synthesized protein parallels that of corresponding mRNA. Other evidences--including in vitro and in vivo elongation assays with fibroin mRNA--show that individual elongation rates are not uniform. Pauses occur at certain sites of the mRNA chain. The relative lifetime of these pauses depends on the tRNA pool used. Finally, it appears that translation accuracy also depends on the balanced tRNA population. We propose to explain these different effects by using a codon-anticodon recognition model, called "trial and error system" based on a stochastic processing of the ribosome. Accordingly, various acylated tRNA species which surround a ribosome randomly encounter the receptor A site. Every trapped tRNA species is tested for a proper pairing with the codon to be recognized at the level of a comparator or discriminator function. If the pairing is correct, transpeptidation becomes irreversible. If not, the aminoacyl-tRNA is rejected and another randomly trapped tRNA is processed in turn. Mathematical analysis of this model shows that the mean number of trials used for translating the whole sequence of a mRNA is minimized when the proportion of different iso-tRNA species is correlated with the square root of codon frequency. Quantitations of reticulocyte tRNA support such a parabolic relation. Our translation system model brings some light into the role of tRNA adaptation for optimizing translation efficiency, i.e. maximizing both speed and accuracy. Some consequences of the model are discussed.