Efficient manipulations of synonymous mutations for controlling translation rate: an analytical approach.
Gene translation is a central process in all living organism with important ramifications to almost every biomedical field. Previous systems evolutionary studies in the field have demonstrated that in many organisms coding sequence features undergo selection to optimize this process. In the current study, we report for the first time analytical proofs related to the various aspects of this process and its optimality. Among our results we show that coding sequences with mono- tonic increasing profiles of translation efficiency (i.e., with slower codons near the 5'UTR), mathematically optimize ribosomal allocation by minimizing the number of ribosomes needed for translating a codon per time unit. Thus, the genomic translation efficiency profile reported in previous studies for many organisms is optimal in this sense. In addition, we show that improving translation efficiency of a codon in a gene may result in a decrease in the translation rate of other genes, demonstrating that the relation between codon bias and protein translation rate is less trivial than was assumed before. Based on these observations we describe an efficient heuristic for designing coding sequences with specific translation efficiency and minimal ribosomal allocation for heterologous gene expression. We demonstrate how this heuristic can be used in biotechnology for engineering a heterologous gene before expressing it in a new host.
The Iby and Aladar Fleischman Faculty of Engineering, Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.
Alexandra
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Dana
Tamir
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Tuller
D000465:Algorithms; D003062:Codon; D003198:Computer Simulation; D005815:Genetic Code; D006801:Humans; D007328:Insulin / Q000096:biosynthesis / Q000235:genetics; D007700:Kinetics; D008957:Models, Genetic; D009154:Mutation; D014176:Protein Biosynthesis; D011994:Recombinant Proteins / Q000096:biosynthesis / Q000235:genetics; D012270:Ribosomes / Q000378:metabolism; D012441:Saccharomyces cerevisiae / Q000235:genetics; D018709:Statistics, Nonparametric
D003062:Codon; D007328:Insulin; D011994:Recombinant Proteins