Abstract
| Original language | English |
|---|---|
| Journal | A C S Synthetic Biology |
| Volume | 7 |
| Issue number | 4 |
| Pages (from-to) | 995-1003 |
| ISSN | 2161-5063 |
| DOIs | |
| Publication status | Published - 2018 |
Keywords
- Biosensor
- Evolution
- Metabolic engineering
- Sustainability
- Transcriptional activator
- Yeast
Cite this
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An Orthogonal and pH-Tunable Sensor-Selector for Muconic Acid Biosynthesis in Yeast. / Snoek, Tim; Romero-Suarez, David; Zhang, Jie; Ambri, Francesca; Skjoedt, Mette L.; Sudarsan, Suresh; Jensen, Michael K.; Keasling, Jay D.
In: A C S Synthetic Biology, Vol. 7, No. 4, 2018, p. 995-1003.Research output: Contribution to journal › Letter › Research › peer-review
TY - JOUR
T1 - An Orthogonal and pH-Tunable Sensor-Selector for Muconic Acid Biosynthesis in Yeast
AU - Snoek, Tim
AU - Romero-Suarez, David
AU - Zhang, Jie
AU - Ambri, Francesca
AU - Skjoedt, Mette L.
AU - Sudarsan, Suresh
AU - Jensen, Michael K.
AU - Keasling, Jay D.
PY - 2018
Y1 - 2018
N2 - 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.
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 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.
KW - Biosensor
KW - Evolution
KW - Metabolic engineering
KW - Sustainability
KW - Transcriptional activator
KW - Yeast
U2 - 10.1021/acssynbio.7b00439
DO - 10.1021/acssynbio.7b00439
M3 - Letter
VL - 7
SP - 995
EP - 1003
JO - A C S Synthetic Biology
JF - A C S Synthetic Biology
SN - 2161-5063
IS - 4
ER -