Motivation: Codon optimisation, the process of adapting the codon composition of a coding sequence, is often used in synthetic biology to increase expression of a heterologous protein. Recently, a number of synthetic biology approaches that allow synthetic constructs to be deployed in multiple organisms have been published. However, so far, design tools for codon optimisation have not been updated to reflect these new approaches. Approach: We designed an evolutionary algorithm (EA) to design coding sequences (CDSs) that encode a target protein for one or more target organisms, based on the Chimera average repetitive substring (ARS) metric -- a correlate of gene expression. A parameter scan was then used to find optimal parameter sets. Using the optimal parameter sets, three heterologous proteins were repeatedly optimised Bacillus subtilis 168 and Escherichia coli MG1655. The ARS scores of the resulting sequences were compared to the ARS scores of coding sequences that had been optimised for each organism individually (using Chimera Map). Results: We demonstrate that an EA is a valid approach to optimising a coding sequence for multiple organisms at once; both crossover and mutation operators were shown to be necessary for the best performance. In some scenarios, the EA generated CDSs that had higher ARS scores than CDSs optimised for the individual organisms, suggesting that the EA exploits the CDS design space in a way that Chimera Map does not. Availability and implementation: The implementation of the EA, with instructions, is available on GitHub: https://github.com/intbio-ncl/chimera_evolve.

中文翻译：

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密码子优化，可在多种物种和微生物群落中最大化基因表达

动机：密码子优化是适应编码序列密码子组成的过程，通常用于合成生物学中以增加异源蛋白的表达。最近，已经公开了许多合成生物学方法，其允许合成构建体被部署在多种生物中。但是，到目前为止，用于密码子优化的设计工具尚未更新以反映这些新方法。方法：我们设计了一种进化算法（EA），以基于嵌合体平均重复亚串（ARS）指标（一种与基因表达相关的指标）来设计编码一种或多种靶生物的靶蛋白的编码序列（CDS）。然后使用参数扫描来找到最佳参数集。使用最佳参数集，反复优化了三种异源蛋白枯草芽孢杆菌168和大肠杆菌MG1655。将所得序列的ARS分数与已针对每种生物体分别优化的编码序列的ARS分数进行比较（使用Chimera Map）。结果：我们证明了EA是一次针对多种生物优化编码序列的有效方法；交叉和变异算子均被证明是获得最佳性能所必需的。在某些情况下，EA生成的CDS具有比针对单个生物体优化的CDS更高的ARS分数，这表明EA以Chimera Map所没有的方式利用CDS设计空间。可用性和实施​​：可以在GitHub上获得具有说明的EA实施：https：//github.com/intbio-ncl/chimera_evolve。