Snoek Tim, Romero-Suarez David, Zhang Jie, Ambri Francesca, Skjoedt Mette L, Sudarsan Suresh, Jensen Michael K, Keasling Jay D
Novo Nordisk Foundation Center for Biosustainability , Technical University of Denmark , 2800 Kgs. Lyngby , Denmark.
Joint BioEnergy Institute , Emeryville , California 94608 , United States.
ACS Synth Biol. 2018 Apr 20;7(4):995-1003. doi: 10.1021/acssynbio.7b00439. Epub 2018 Apr 5.
Microbes offer enormous potential for production of industrially relevant chemicals and therapeutics, yet the rapid identification of high-producing microbes from large genetic libraries is a major bottleneck in modern cell factory development. Here, we develop and apply a synthetic selection system in Saccharomyces cerevisiae that couples the concentration of muconic acid, a plastic precursor, to cell fitness by using the prokaryotic transcriptional regulator BenM driving an antibiotic resistance gene. We show that the sensor-selector does not affect production nor fitness, and find that tuning pH of the cultivation medium limits the rise of nonproducing cheaters. We apply the sensor-selector to selectively enrich for best-producing variants out of a large library of muconic acid production strains, and identify an isolate that produces more than 2 g/L muconic acid in a bioreactor. We expect that this sensor-selector can aid the development of other synthetic selection systems based on allosteric transcription factors.
微生物在生产工业相关化学品和治疗药物方面具有巨大潜力，但从大型基因文库中快速鉴定高产微生物是现代细胞工厂开发的主要瓶颈。在此，我们开发并应用了一种酿酒酵母中的合成选择系统，该系统通过使用驱动抗生素抗性基因的原核转录调节因子BenM，将塑料前体粘康酸的浓度与细胞适应性联系起来。我们表明，该传感器-选择器不影响产量和适应性，并发现调节培养基的pH值可限制非生产性作弊者的增加。我们应用该传感器-选择器从大量粘康酸生产菌株文库中选择性富集最佳生产变体，并鉴定出一株在生物反应器中产生超过2 g/L粘康酸的分离株。我们预计，这种传感器-选择器可有助于基于变构转录因子的其他合成选择系统的开发。
