饱和突变
限制
合成生物学
计算生物学
突变
定向进化
蛋白质工程
定向分子进化
生物
寡核苷酸
计算机科学
基因组文库
遗传学
突变
生物化学
基序列
基因
酶
工程类
突变体
机械工程
作者
David Öling,Lina Lawenius,W. M. Shaw,Sonya Clark,Ross Kettleborough,Tom Ellis,Niklas Larsson,Mark Wigglesworth
标识
DOI:10.1021/acssynbio.8b00118
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI