An Orthogonal and pH-Tunable Sensor-Selector for Muconic Acid Biosynthesis in Yeast

Tim Snoek, David Romero-Suarez, Jie Zhang, Francesca Ambri, Mette L. Skjoedt, Suresh Sudarsan, Michael K. Jensen, Jay D. Keasling

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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.
Original languageEnglish
JournalA C S Synthetic Biology
Issue number4
Pages (from-to)995-1003
Publication statusPublished - 2018


  • Biosensor
  • Evolution
  • Metabolic engineering
  • Sustainability
  • Transcriptional activator
  • Yeast

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