A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae
| Autor: | Lindsey G Rey, Kathleen A. Curran, Amanda M. Lanza, Hal S. Alper |
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| Rok vydání: | 2014 |
| Předmět: |
Translational efficiency
Codon bias Systems biology Green Fluorescent Proteins Gene Expression Heterologous Context (language use) Saccharomyces cerevisiae Biology Synthetic biology Structural Biology Modelling and Simulation Databases Genetic Codon Molecular Biology Gene Genetics Methodology Article Applied Mathematics Codon optimization Catechol 1 2-Dioxygenase Computer Science Applications Metabolic Engineering Modeling and Simulation Codon usage bias Heterologous expression |
| Zdroj: | BMC Systems Biology |
| ISSN: | 1752-0509 |
| DOI: | 10.1186/1752-0509-8-33 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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