Enhancing the translational capacity of E. coli by resolving the codon bias
Zoltán LipinszkiiD, Viktor VernyikiD, Nóra FaragóiD, Tobias Sari, László Géza PuskásiD, Frederick R. Blattner, György PósfaiiD, Zsuzsanna GyörfyiD
Abstract
Escherichia coli is a well-established, and popular host for heterologous expression of proteins. The preference in the choice of synonymous codons (codon bias), however, might differ for the host and the original source of the recombinant protein, constituting a potential bottleneck in production. Codon choice affects the efficiency of translation by a complex and poorly understood mechanism. The availability of certain tRNA species is one of the factors that may curtail the capacity of translation.\n\nHere we provide a tRNA-overexpressing strategy that allows the resolution of the codon bias, and boosts the translational capacity of the popular host BL21(DE3) when rare codons are encountered. In BL21(DE3)-derived strain, called SixPack, copies of the genes corresponding to the six least abundant tRNA species have been assembled in a synthetic fragment and inserted into a ribosomal RNA operon. This arrangement, while not interfering with the growth properties of the new strain, allows dynamic control of the transcription of the extra tRNA genes, providing significantly elevated levels of the rare tRNAs in exponential growth phase.\n\nResults from expression assays of a panel of heterologous proteins of diverse origin and codon composition showed that the performance of SixPack surpassed that of the parental BL21(DE3) or a related strain equipped with a rare tRNA-expressing plasmid.\n\nImportanceCodon composition not fitting the codon bias of the expression host frequently compromises the efficient production of foreign proteins in E. coli. Various attempts to remedy the problem (codon optimization by gene synthesis, expression of rare tRNAs from a plasmid) proved to be unsatisfying. Our new approach, adjusting the tRNA pool by co-expressing extra copies of rare tRNA genes with ribosomal RNA genes, does not affect normal cell physiology, and seems to be a superior solution in terms of simplicity, cost, and yield.
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