TY - JOUR T1 - Refactoring the Genetic Code for Increased Evolvability JF - bioRxiv DO - 10.1101/128058 SP - 128058 AU - Gur Pines AU - James D. Winkler AU - Assaf Pines AU - Ryan T. Gill Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/04/17/128058.abstract N2 - The standard genetic code is robust to mutations and base-pairing errors during transcription and translation. Point mutations are most likely to be synonymous or preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best performing mutant requires a replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyper-evolvable organism serving as an ideal platform for directed evolution experiments. We then conclude by evaluating potential applications for recoded organisms within the synthetic biology field.Significance Statement The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene using common error-prone methods. Here we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transition to a larger pool of amino acids and with a greater degree of chemical differences, using a single nucleotide replacement within the codon, thus increasing evolvability both at the single gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation and fitness maximization. ER -