Cargando…
How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering
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 tra...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049029/ https://www.ncbi.nlm.nih.gov/pubmed/33231343 http://dx.doi.org/10.1002/cbic.202000758 |
_version_ | 1783679350308077568 |
---|---|
author | Schmidt, Markus Kubyshkin, Vladimir |
author_facet | Schmidt, Markus Kubyshkin, Vladimir |
author_sort | Schmidt, Markus |
collection | PubMed |
description | 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 (Δ(code)) where we assigned polarity indices (clog D (7)) 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. |
format | Online Article Text |
id | pubmed-8049029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80490292021-04-20 How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering Schmidt, Markus Kubyshkin, Vladimir Chembiochem Full Papers 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 (Δ(code)) where we assigned polarity indices (clog D (7)) 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. John Wiley and Sons Inc. 2020-12-30 2021-04-06 /pmc/articles/PMC8049029/ /pubmed/33231343 http://dx.doi.org/10.1002/cbic.202000758 Text en © 2020 The Authors. ChemBioChem published by Wiley-VCH GmbH https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Full Papers Schmidt, Markus Kubyshkin, Vladimir How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering |
title | How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering |
title_full | How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering |
title_fullStr | How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering |
title_full_unstemmed | How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering |
title_short | How To Quantify a Genetic Firewall? A Polarity‐Based Metric for Genetic Code Engineering |
title_sort | how to quantify a genetic firewall? a polarity‐based metric for genetic code engineering |
topic | Full Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049029/ https://www.ncbi.nlm.nih.gov/pubmed/33231343 http://dx.doi.org/10.1002/cbic.202000758 |
work_keys_str_mv | AT schmidtmarkus howtoquantifyageneticfirewallapolaritybasedmetricforgeneticcodeengineering AT kubyshkinvladimir howtoquantifyageneticfirewallapolaritybasedmetricforgeneticcodeengineering |