%0 Journal Article
%T The role of codon selection in regulation of translation efficiency deduced from synthetic libraries
%A Sivan Navon
%A Yitzhak Pilpel
%J Genome Biology
%D 2011
%I BioMed Central
%R 10.1186/gb-2011-12-2-r12
%X We define the region in a gene that takes the longest time to translate as the bottleneck. We found that localization of the bottleneck at the beginning of a transcript promoted a high level of expression, especially if the computed dwell time of the ribosome within this region was sufficiently long. The location and translation time of the bottleneck were not correlated with the cost of expression, approximated by the fitness of the host cell, yet utilization of specific codons was. Particularly, enhanced usage of the codons UCA and CAU was correlated with increased cost of production, potentially due to sequestration of their corresponding rare tRNAs.The distribution of codons along the genes appears to affect translation efficiency, consistent with analysis of natural genes. This study demonstrates how synthetic biology complements bioinformatics by providing a set-up for well controlled experiments in biology.Understanding the mechanisms that control the efficiency of protein translation is a major challenge for proteomics, computational biology and biotechnology. Efficient translation of proteins, either in their natural biological context or in heterologous expression systems, amounts to maximizing production, while minimizing the costs of the process. Abundant genome sequence data now make it possible to decipher sequence design elements that govern the efficiency of translation. The codon adaptation index (CAI) [1] was the first measure to be introduced for gauging translation efficiency directly from nucleotide sequences of genes. This measure quantifies the extent to which the codon bias of a gene resembles that of highly expressed genes. The tRNA adaptation index (tAI) assesses the extent to which the codons of a gene are biased towards the more abundant tRNAs in the organism [2]. Despite several simplifying assumptions, both tAI and CAI are good measurements for predicting protein abundance from sequence [3,4]. Perhaps the most critical simplification of
%U http://genomebiology.com/2011/12/2/R12