PT - JOURNAL ARTICLE AU - Tim Snoek AU - David Romero-Suarez AU - Jie Zhang AU - Mette L. Skjoedt AU - Suresh Sudarsan AU - Michael K. Jensen AU - Jay D. Keasling TI - An orthogonal and pH-tunable sensor-selector for muconic acid biosynthesis in yeast AID - 10.1101/229922 DP - 2017 Jan 01 TA - bioRxiv PG - 229922 4099 - http://biorxiv.org/content/early/2017/12/06/229922.short 4100 - http://biorxiv.org/content/early/2017/12/06/229922.full AB - 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 the sensor-selector does not affect production, and find that tuning pH of the cultivation medium limits the rise of non-producing 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 produced 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.