Öling David, Lawenius Lina, Shaw William, Clark Sonya, Kettleborough Ross, Ellis Tom, Larsson Niklas, Wigglesworth Mark
Discovery Biology, Discovery Sciences, Innovative Medicines and Early Development Biotech Unit , AstraZeneca R&D , 431 50 Mölndal , Sweden.
Department of Bioengineering , Imperial College London , London SW7 2AZ , U.K.
ACS Synth Biol. 2018 Sep 21;7(9):2317-2321. doi: 10.1021/acssynbio.8b00118. Epub 2018 Sep 12.
Site saturation mutagenesis (SSM) is a powerful mutagenesis strategy for protein engineering and directed evolution experiments. However, limiting factors using this method are either biased representation of variants, or limiting library size. To overcome these hurdles, we generated large scale targeted synthetic SSM libraries using massively parallel oligonucleotide synthesis and benchmarked this against an error-prone (epPCR) library. The yeast glucose activated GPCR-Gpr1 was chosen as a prototype to evolve novel glucose sensors. We demonstrate superior variant representation and several unique hits in the synthetic library compared to the PCR generated library. Application of this mutational approach further builds the possibilities of synthetic biology in tuning of a response to known ligands and in generating biosensors for novel ligands.
位点饱和诱变(SSM)是一种用于蛋白质工程和定向进化实验的强大诱变策略。然而,使用该方法的限制因素要么是变体的偏向性表征,要么是文库大小受限。为了克服这些障碍,我们使用大规模平行寡核苷酸合成生成了大规模靶向合成SSM文库,并将其与易错(epPCR)文库进行了比较。选择酵母葡萄糖激活的GPCR - Gpr1作为原型来进化新型葡萄糖传感器。与PCR生成的文库相比,我们证明了合成文库中具有更优异的变体表征和几个独特的命中结果。这种诱变方法的应用进一步拓展了合成生物学在调节对已知配体的反应以及生成新型配体生物传感器方面的可能性。