(333d) A Mammalian Synthetic Gene Circuit to Quantify Activation of the Ubiquitin Proteasome System

The ubiquitin proteasome system (UPS) is the main protein quality control system in eukaryotic cells that regulates degradation of damaged or misfolded proteins. Inefficient or defective UPS activity results in accumulation of misfolded proteins and aggregation, which are the hallmarks of a number of neurodegenerative diseases, including Parkinson’s and Alzheimer’s. Protein aggregates are also key impediments to the high expression of recombinant proteins and limit the high-yield production of proteins for research, diagnostic and industrial applications. We hypothesized that enhancing proteasomal degradation would facilitate intracellular clearance of misfolded proteins and prevent accumulation of protein aggregates. A number of proteasome inhibitors in the form of small molecules and peptides that bind to the catalytic sites of the proteasome have been reported. They have been widely used to characterize the role of the UPS in maintaining protein homeostasis and recently even transitioned to clinical therapeutics. On the other hand, pharmacologic agents that enhance UPS activity are rare and still largely unexplored. To fill this knowledge gap and generate a platform for high-throughput screening of proteasome activators, we developed a mammalian orthogonal genetic circuit that interfaces with cell’s natural proteasomal degradation pathways. In this synthetic circuit, increase of UPS activity is coupled with readily detectable fluorescence signal. The architecture of the genetic circuit is based on a transcriptional repressor engineered to function as a UPS model substrate. Guided by predictive modeling, we refined the circuit architecture to achieve a more robust and decisive response to modulation of proteasomal degradation. We report experimental evidence that self-activation of the repressor creates a positive feedback loop that results in enhanced sensitivity of the circuit to UPS activity and larger output signal window. This novel strategy overcomes limitations of current methods, which are based on detecting a decrease in concentration of a degradation-prone signal substrate and are prone to artifactual results.