Please use this identifier to cite or link to this item: https://doi.org/10.1186/1752-0509-6-134
Title: Computational codon optimization of synthetic gene for protein expression
Authors: Chung, B.K.-S.
Lee, D.-Y. 
Issue Date: 20-Oct-2012
Citation: Chung, B.K.-S., Lee, D.-Y. (2012-10-20). Computational codon optimization of synthetic gene for protein expression. BMC Systems Biology 6 : -. ScholarBank@NUS Repository. https://doi.org/10.1186/1752-0509-6-134
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. © 2012 Chung and Lee; licensee BioMed Central Ltd.
Source Title: BMC Systems Biology
URI: http://scholarbank.nus.edu.sg/handle/10635/63624
ISSN: 17520509
DOI: 10.1186/1752-0509-6-134
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
2012-computational_codon_optimization-published.pdf1.49 MBAdobe PDF

OPEN

PublishedView/Download

SCOPUSTM   
Citations

37
checked on Oct 16, 2018

WEB OF SCIENCETM
Citations

33
checked on Oct 8, 2018

Page view(s)

47
checked on Oct 13, 2018

Download(s)

7
checked on Oct 13, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.