Sunday, May 3, 2009
2-70

Design of transcription factor-based in vivo biosensors for improved butanol production in E. coli

Jeffrey A. Dietrich1, David L. Shih2, Aurora Chan2, and Jay D. Keasling3. (1) Department of Bioengineering, UC-Berkeley; Joint BioEnergy Institute, EmeryStationEast, 5885 Hollis St, 4th floor, Emeryville, CA 94608, (2) Joint BioEnergy Institute, EmeryStationEast, 5885 Hollis St, 4th floor, Emeryville, CA 94608, (3) Departments of Chemical Engineering and Bioengineering, UC-Berkeley and Lawrence Berkeley National Laboratory, EmeryStationEast, 5885 Hollis St, 4th floor, Emeryville, CA 94608

The Pseuodomonads are well recognized for their ability to rapidly evolve σ54-transcriptional activators to detect synthetic compounds in their environment, many of which are of high interest for replacement using microbial production processes.  Here we present a facile strategy for the in vivo detection and quantification of structurally-diverse, industrially-important metabolites on the single cell level.  We constructed an in vivo biosensor responding to C2-C8 linear alcohols from a rationally-designed library of chimeric Pseudomonad σ54-transcriptional activators.  We focused on a putative alcohol-responsive transcription factor from Pseudomonas butanovora, BmoR, and XylR, a well characterized toluene-responsive transcription factor from Pseudomonas putida.  When transformed into Escherichia coli the biosensor yielded a linear response to exogenously added n-butanol up to 0.5% v/v; above which butanol-induced growth inhibition was observed.  In butanol production strains of E. coli the biosensor demonstrated accurate quantification of butanol titers as compared to gas chromatography-mass spectrometry measurements.  We then employed the biosensor for directed evolution of Escherichia coli for improved n-butanol production, targeting modifications to the E. coli genome and a heterologous n-butanol pathway from Clostridium acetobutylicum.  This work demonstrates a versatile strategy for rapid design of high-throughput screens and selections targeting for intracellular metabolites.  Further, we gained increased insight into possible mechanisms through which the nature is able to evolve the ability to detect and respond to synthetic compounds in the environment.