Codon optimisation for maximising gene expression in multiple species and microbial consortia
Codon optimisation for maximising gene expression in multiple species and microbial consortia
复制标题
密码子优化以最大化多个物种和微生物群落中的基因表达
DOI：
10.1101/2020.06.30.177766
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Skelton D
中科院分区：
文献类型：
--
作者：
Skelton D
运动密码子优化，即调整编码序列的密码子组成的过程，通常用于合成生物学以增加异源蛋白质的表达。最近，一些合成生物学方法已经发表，这些方法允许在多个生物体中部署合成结构。然而，到目前为止，用于密码子优化的设计工具还没有更新来反映这些新的方法。方法我们设计了一个进化算法(EA)来设计编码序列(CDS)，以编码一个或多个目标生物的目标蛋白质，基于嵌合体平均重复亚串(ARS)度量-基因表达的关联。然后使用参数扫描来寻找最优参数集。利用优化后的参数集，对枯草芽孢杆菌168和大肠杆菌MG1655这三个异源蛋白进行了反复优化。将得到的序列的ARS分数与针对每个生物体单独优化的编码序列的ARS分数进行比较。结果表明，进化算法是一种同时优化多个生物的编码序列的有效方法；交叉和变异算子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以嵌合体地图无法利用CDS设计空间的方式使用CDS设计空间。可用性和实现EA的实现及其说明可在GitHub上找到：https://github.com/intbio-ncl/chimera_evolve.
MotivationCodon 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.ApproachWe 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 optimisedBacillus subtilis168 andEscherichia coliMG1655. 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).ResultsWe 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 implementationThe implementation of the EA, with instructions, is available on GitHub: https://github.com/intbio-ncl/chimera_evolve.
影响因子：
5.8
作者：
Diament, Alon;Weiner, Iddo;Tuller, Tamir
通讯作者：
Tuller, Tamir
影响因子：
14.9
作者：
SHARP, PM;LI, WH
通讯作者：
LI, WH