(236f) Development of Modular Tunable Biosensors for Gene Regulation and Autonomous Pathway Optimization | AIChE

(236f) Development of Modular Tunable Biosensors for Gene Regulation and Autonomous Pathway Optimization

Authors 

Solomon, K. V. - Presenter, Purdue University
Microbial chemical factories increasingly rely on biosynthetic pathways incorporating toxic intermediates that inhibit cellular growth and product formation. A promising strategy to overcome this challenge is dynamic regulation of production pathways to limit toxic intermediate accumulation, and maintain cells at optimal health for increased production. While dynamic control may be implemented with natural transcription factors as sensors that recognize and respond to a given metabolite, sensors for many intermediates are largely unknown. However, many valuable toxic intermediates and value-added products disrupt cellular pH homeostasis, generating a universal carrier signal for cellular stress. In my lab, we develop modular transcriptional regulators whose sensitivity to this pH and their transcriptional response can be independently tuned for programmable autonomous feedback. Our transcriptional regulators consist of an elastin-like polypeptide (ELP) biosensor fused to a transcription factor to directly respond to general indicators of cellular stress for dynamic control of any biosynthetic pathway. ELPs are engineered proteins that reversibly self-assemble at a critical temperature, pH, and/or ionic strength programmed by their tunable primary sequence. When fused to transcription factors such as orthogonal sigma factors, ELP self-assembly sequesters fused transcription factor, altering gene transcription at targeted promoters in a reversible switch-like fashion. Constructs in E. coli demonstrate a 4-fold dynamic range in response to changes in temperature. Similarly, we demonstrate that these sensors respond to small variations in intracellular pH that precede significant cellular damage. The tunable responsive nature of these synthetic regulators make them ideal regulators for pathway optimization, with potentially broad utility across organisms with appropriate transcription factor design