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

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.

Design, Engineering, and Characterization of Prokaryotic Ligand-Binding Transcriptional Activators as Biosensors in Yeast.

In cell factory development, screening procedures, often relying on low-throughput analytical methods, are lagging far behind diversity generation methods. This renders the identification and selection of the best cell factory designs tiresome and costly, conclusively hindering the manufacturing process. In the yeast Saccharomyces cerevisiae, implementation of allosterically regulated transcription factors from prokaryotes as metabolite biosensors has proven a valuable strategy to alleviate this screening bottleneck. Here, we present a protocol to select and incorporate prokaryotic transcriptional activators as metabolite biosensors in S. cerevisiae. As an example, we outline the engineering and characterization of the LysR-type transcriptional regulator (LTTR) family member BenM from Acetinobacter sp. ADP1 for monitoring accumulation of cis,cis-muconic acid, a bioplast precursor, in yeast by means of flow cytometry.

Engineering prokaryotic transcriptional activators as metabolite biosensors in yeast.

Whole-cell biocatalysts have proven a tractable path toward sustainable production of bulk and fine chemicals. Yet the screening of libraries of cellular designs to identify best-performing biocatalysts is most often a low-throughput endeavor. For this reason, the development of biosensors enabling real-time monitoring of production has attracted attention. Here we applied systematic engineering of multiple parameters to search for a general biosensor design in the budding yeast Saccharomyces cerevisiae based on small-molecule binding transcriptional activators from the prokaryote superfamily of LysR-type transcriptional regulators (LTTRs). We identified a design supporting LTTR-dependent activation of reporter gene expression in the presence of cognate small-molecule inducers. As proof of principle, we applied the biosensors for in vivo screening of cells producing naringenin or cis,cis-muconic acid at different levels, and found that reporter gene output correlated with production. The transplantation of prokaryotic transcriptional activators into the eukaryotic chassis illustrates the potential of a hitherto untapped biosensor resource useful for biotechnological applications.