Genetic code engineering aims to produce organisms that translate genetic information in a different way from that prescribed by the standard genetic code, which can eventually lead to organisms that operate under different genetic codes. And, if two organisms operate under different genetic codes, how likely is it that they can still correctly interpret each other’s genes?
In this work, a versatile metric (Δcode) is introduced to quantify the distance (dissimilarity) between different genetic codes (a genetic firewall), and it can be applied with the 20 canonical but also noncanonical amino acids.
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.
Read the full article here.