Document Type

Article

Publication Date

1-24-2017

Abstract

Ribosomal protein synthesis results in the genetically programmed incorporation of amino acids into a growing polypeptide chain. Faithful amino acid incorporation that accurately reflects the genetic code is critical to the structure and function of proteins as well as overall proteome integrity. Errors in protein synthesis are generally detrimental to cellular processes yet emerging evidence suggest that proteome diversity generated through mistranslation may be beneficial under certain conditions. Cumulative translational error rates have been determined at the organismal level, however codon specific error rates and the spectrum of misincorporation errors from system to system remain largely unexplored. In particular, until recently technical challenges have limited the ability to detect and quantify comparatively rare amino acid misincorporation events, which occur orders of magnitude less frequently than canonical amino acid incorporation events. We now describe a technique for the quantitative analysis of amino acid incorporation that provides the sensitivity necessary to detect mistranslation events during translation of a single codon at frequencies as low as 1 in 10,000 for all 20 proteinogenic amino acids, as well as non-proteinogenic and modified amino acids. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O’Donoghue.

Comments

NOTICE: this is the author’s version of a work that was accepted for publication in BBA General Subjects. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in BBA General Subjects, volume 1861, in 2017. https://doi.org/10.1016/j.bbagen.2017.01.025

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Copyright

Elsevier

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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