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Synonymous Genes Explore Different Evolutionary Landscapes
The evolutionary potential of a gene is constrained not only by the amino acid sequence of its product, but by its DNA sequence as well. The topology of the genetic code is such that half of the amino acids exhibit synonymous codons that can reach different subsets of amino acids from each other thr...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2575237/ https://www.ncbi.nlm.nih.gov/pubmed/19008944 http://dx.doi.org/10.1371/journal.pgen.1000256 |
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author | Cambray, Guillaume Mazel, Didier |
author_facet | Cambray, Guillaume Mazel, Didier |
author_sort | Cambray, Guillaume |
collection | PubMed |
description | The evolutionary potential of a gene is constrained not only by the amino acid sequence of its product, but by its DNA sequence as well. The topology of the genetic code is such that half of the amino acids exhibit synonymous codons that can reach different subsets of amino acids from each other through single mutation. Thus, synonymous DNA sequences should access different regions of the protein sequence space through a limited number of mutations, and this may deeply influence the evolution of natural proteins. Here, we demonstrate that this feature can be of value for manipulating protein evolvability. We designed an algorithm that, starting from an input gene, constructs a synonymous sequence that systematically includes the codons with the most different evolutionary perspectives; i.e., codons that maximize accessibility to amino acids previously unreachable from the template by point mutation. A synonymous version of a bacterial antibiotic resistance gene was computed and synthesized. When concurrently submitted to identical directed evolution protocols, both the wild type and the recoded sequence led to the isolation of specific, advantageous phenotypic variants. Simulations based on a mutation isolated only from the synthetic gene libraries were conducted to assess the impact of sub-functional selective constraints, such as codon usage, on natural adaptation. Our data demonstrate that rational design of synonymous synthetic genes stands as an affordable improvement to any directed evolution protocol. We show that using two synonymous DNA sequences improves the overall yield of the procedure by increasing the diversity of mutants generated. These results provide conclusive evidence that synonymous coding sequences do experience different areas of the corresponding protein adaptive landscape, and that a sequence's codon usage effectively constrains the evolution of the encoded protein. |
format | Text |
id | pubmed-2575237 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25752372008-11-14 Synonymous Genes Explore Different Evolutionary Landscapes Cambray, Guillaume Mazel, Didier PLoS Genet Research Article The evolutionary potential of a gene is constrained not only by the amino acid sequence of its product, but by its DNA sequence as well. The topology of the genetic code is such that half of the amino acids exhibit synonymous codons that can reach different subsets of amino acids from each other through single mutation. Thus, synonymous DNA sequences should access different regions of the protein sequence space through a limited number of mutations, and this may deeply influence the evolution of natural proteins. Here, we demonstrate that this feature can be of value for manipulating protein evolvability. We designed an algorithm that, starting from an input gene, constructs a synonymous sequence that systematically includes the codons with the most different evolutionary perspectives; i.e., codons that maximize accessibility to amino acids previously unreachable from the template by point mutation. A synonymous version of a bacterial antibiotic resistance gene was computed and synthesized. When concurrently submitted to identical directed evolution protocols, both the wild type and the recoded sequence led to the isolation of specific, advantageous phenotypic variants. Simulations based on a mutation isolated only from the synthetic gene libraries were conducted to assess the impact of sub-functional selective constraints, such as codon usage, on natural adaptation. Our data demonstrate that rational design of synonymous synthetic genes stands as an affordable improvement to any directed evolution protocol. We show that using two synonymous DNA sequences improves the overall yield of the procedure by increasing the diversity of mutants generated. These results provide conclusive evidence that synonymous coding sequences do experience different areas of the corresponding protein adaptive landscape, and that a sequence's codon usage effectively constrains the evolution of the encoded protein. Public Library of Science 2008-11-14 /pmc/articles/PMC2575237/ /pubmed/19008944 http://dx.doi.org/10.1371/journal.pgen.1000256 Text en Cambray, Mazel. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Cambray, Guillaume Mazel, Didier Synonymous Genes Explore Different Evolutionary Landscapes |
title | Synonymous Genes Explore Different Evolutionary Landscapes |
title_full | Synonymous Genes Explore Different Evolutionary Landscapes |
title_fullStr | Synonymous Genes Explore Different Evolutionary Landscapes |
title_full_unstemmed | Synonymous Genes Explore Different Evolutionary Landscapes |
title_short | Synonymous Genes Explore Different Evolutionary Landscapes |
title_sort | synonymous genes explore different evolutionary landscapes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2575237/ https://www.ncbi.nlm.nih.gov/pubmed/19008944 http://dx.doi.org/10.1371/journal.pgen.1000256 |
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