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A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae
BACKGROUND: Heterologous gene expression is an important tool for synthetic biology that enables metabolic engineering and the production of non-natural biologics in a variety of host organisms. The translational efficiency of heterologous genes can often be improved by optimizing synonymous codon u...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4004289/ https://www.ncbi.nlm.nih.gov/pubmed/24636000 http://dx.doi.org/10.1186/1752-0509-8-33 |
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author | Lanza, Amanda M Curran, Kathleen A Rey, Lindsey G Alper, Hal S |
author_facet | Lanza, Amanda M Curran, Kathleen A Rey, Lindsey G Alper, Hal S |
author_sort | Lanza, Amanda M |
collection | PubMed |
description | BACKGROUND: Heterologous gene expression is an important tool for synthetic biology that enables metabolic engineering and the production of non-natural biologics in a variety of host organisms. The translational efficiency of heterologous genes can often be improved by optimizing synonymous codon usage to better match the host organism. However, traditional approaches for optimization neglect to take into account many factors known to influence synonymous codon distributions. RESULTS: Here we define an alternative approach for codon optimization that utilizes systems level information and codon context for the condition under which heterologous genes are being expressed. Furthermore, we utilize a probabilistic algorithm to generate multiple variants of a given gene. We demonstrate improved translational efficiency using this condition-specific codon optimization approach with two heterologous genes, the fluorescent protein-encoding eGFP and the catechol 1,2-dioxygenase gene CatA, expressed in S. cerevisiae. For the latter case, optimization for stationary phase production resulted in nearly 2.9-fold improvements over commercial gene optimization algorithms. CONCLUSIONS: Codon optimization is now often a standard tool for protein expression, and while a variety of tools and approaches have been developed, they do not guarantee improved performance for all hosts of applications. Here, we suggest an alternative method for condition-specific codon optimization and demonstrate its utility in Saccharomyces cerevisiae as a proof of concept. However, this technique should be applicable to any organism for which gene expression data can be generated and is thus of potential interest for a variety of applications in metabolic and cellular engineering. |
format | Online Article Text |
id | pubmed-4004289 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40042892014-05-19 A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae Lanza, Amanda M Curran, Kathleen A Rey, Lindsey G Alper, Hal S BMC Syst Biol Methodology Article BACKGROUND: Heterologous gene expression is an important tool for synthetic biology that enables metabolic engineering and the production of non-natural biologics in a variety of host organisms. The translational efficiency of heterologous genes can often be improved by optimizing synonymous codon usage to better match the host organism. However, traditional approaches for optimization neglect to take into account many factors known to influence synonymous codon distributions. RESULTS: Here we define an alternative approach for codon optimization that utilizes systems level information and codon context for the condition under which heterologous genes are being expressed. Furthermore, we utilize a probabilistic algorithm to generate multiple variants of a given gene. We demonstrate improved translational efficiency using this condition-specific codon optimization approach with two heterologous genes, the fluorescent protein-encoding eGFP and the catechol 1,2-dioxygenase gene CatA, expressed in S. cerevisiae. For the latter case, optimization for stationary phase production resulted in nearly 2.9-fold improvements over commercial gene optimization algorithms. CONCLUSIONS: Codon optimization is now often a standard tool for protein expression, and while a variety of tools and approaches have been developed, they do not guarantee improved performance for all hosts of applications. Here, we suggest an alternative method for condition-specific codon optimization and demonstrate its utility in Saccharomyces cerevisiae as a proof of concept. However, this technique should be applicable to any organism for which gene expression data can be generated and is thus of potential interest for a variety of applications in metabolic and cellular engineering. BioMed Central 2014-03-17 /pmc/articles/PMC4004289/ /pubmed/24636000 http://dx.doi.org/10.1186/1752-0509-8-33 Text en Copyright © 2014 Lanza et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Lanza, Amanda M Curran, Kathleen A Rey, Lindsey G Alper, Hal S A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae |
title | A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae |
title_full | A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae |
title_fullStr | A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae |
title_full_unstemmed | A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae |
title_short | A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae |
title_sort | condition-specific codon optimization approach for improved heterologous gene expression in saccharomyces cerevisiae |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4004289/ https://www.ncbi.nlm.nih.gov/pubmed/24636000 http://dx.doi.org/10.1186/1752-0509-8-33 |
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