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Open Access Highly Accessed Methodology article

Computational codon optimization of synthetic gene for protein expression

Bevan Kai-Sheng Chung123 and Dong-Yup Lee123*

Author affiliations

1 Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore, 117576, Singapore

2 NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, 28 Medical Drive, #05-01, Singapore, 117456, Singapore

3 Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), 20 Biopolis Way, #06-01 Centros, Singapore, 138668, Singapore

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Citation and License

BMC Systems Biology 2012, 6:134  doi:10.1186/1752-0509-6-134

Published: 20 October 2012

Abstract

Background

The construction of customized nucleic acid sequences allows us to have greater flexibility in gene design for recombinant protein expression. Among the various parameters considered for such DNA sequence design, individual codon usage (ICU) has been implicated as one of the most crucial factors affecting mRNA translational efficiency. However, previous works have also reported the significant influence of codon pair usage, also known as codon context (CC), on the level of protein expression.

Results

In this study, we have developed novel computational procedures for evaluating the relative importance of optimizing ICU and CC for enhancing protein expression. By formulating appropriate mathematical expressions to quantify the ICU and CC fitness of a coding sequence, optimization procedures based on genetic algorithm were employed to maximize its ICU and/or CC fitness. Surprisingly, the in silico validation of the resultant optimized DNA sequences for Escherichia coli, Lactococcus lactis, Pichia pastoris and Saccharomyces cerevisiae suggests that CC is a more relevant design criterion than the commonly considered ICU.

Conclusions

The proposed CC optimization framework can complement and enhance the capabilities of current gene design tools, with potential applications to heterologous protein production and even vaccine development in synthetic biotechnology.