How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering

Abstract

Genetic code engineering aims to produce organisms that translate genetic information in a different way from that prescribed by the standard genetic code. This endeavor could eventually lead to genetic isolation, where an organism that operates under a different genetic code will not be able to transfer functional genes with other living species, thereby standing behind a genetic firewall. It is not clear however, how distinct the code should be, or how to measure the distance. We have developed a metric (Δcode) where we assigned polarity indices (clog D7) to amino acids to calculate the distances between pairs of genetic codes. We then calculated the distance between a set of 204 genetic codes, including the 24 known distinct natural codes, 11 extreme‐distance codes created computationally, nine theoretical special purpose codes from literature and 160 codes in which canonical amino acids were replaced by noncanonical chemical analogues. The metric can be used for building strategies towards creating semantically alienated organisms, and testing the strength of genetic firewalls. This metric provides the basis for a map of the genetic codes that could guide future efforts towards novel biochemical worlds, biosafety and deep barcoding applications.

Genetically engineered bacteria: a new frontier in targeted drug delivery

“…This is where biological containment strategies, or “genetic firewall” mechanisms, come into play. 156,157 These strategies are designed to make GEB dependent on specific conditions or nutrients that are not available outside of the laboratory or their intended application environment. For instance, an ‘auxotrophic’ containment strategy could be used, where GEB are engineered to be unable to synthesize a certain vital nutrient and therefore cannot survive without supplementation.…”

Refactored genetic codes enable bidirectional genetic isolation

“…The functional orthogonality of genes in cells with altered decoders will depend on the frequency of reassigned codons and the functional consequences of codon reassignments. The consequences of amino acid substitutionsa result of codon reassignment-may globally and crudely correlate with differences in amino acid polarity and hydrophobicity (6,25). The consequences of amino acid substitutions at particular sites in proteins may be predicted by using computational approaches that leverage evolutionary sequence-and/or structural information (26)(27)(28)(29).…”

Bottlenecks and opportunities for synthetic biology biosafety standards

“…Searching peer-reviewed publications in Pubmed (keywords: containment, biosafety, synthetic biology, genetic engineering, CRISPR, gene flow, safeguard, kill switch, genetic code engineering, auxotrophy, cell free, chromosome free), we found 53 biosafety and biocontainment proto-standards with a potential to be applied in synthetic biology. Thematically the proto-standards are quite diverse, ranging from physical containment 16 to synthetic auxotrophy 17 – 19 , kill switches 20 , 21 , semantic biocontainment such as genetic code engineering 22 – 25 , CRISPR safeguards such as gene drives 26 , 27 , DNA barcoding 15 , 28 , and chromosome free systems 29 . Underlying all of these is an implied reliance on relevant metrics: what do we measure to assure the proto-standards are working as described, and what metrics are required to know when a proto-standard can become a standard?…”