Date of Award
Doctor of Philosophy (PhD)
Microbial production of chemicals has provided an attractive alternative to chemical synthesis. A key to make this technology economically viable is to improve titers, productivities, and strain robustness. However, pathway productivities and yields are often limited by metabolic imbalances that inhibit cell growth and chemical production. In contrast, natural metabolic pathways are dynamically regulated according to cellular metabolic status. Dynamic regulation allows cells to adjust metabolite concentrations to optimal levels and avoid wasting carbon and energy. Inspired by nature, synthetic regulatory circuits have shown great promise in improving titers and productivities, because they can balance the metabolism by dynamically adjusting enzyme expression levels according to cellular metabolic status.
To engineer synthetic regulatory circuits to improve production, we must design and tune metabolite biosensors, and also understand the metabolic dynamics to identify the optimal regulatory architecture. The research presented here addresses both these key aspects and demonstrates an application of genetic circuits to improve pathway production. Specifically, we develop theories that predict and experimentally validate a coupling between dynamic range and response threshold in transcription factor-based biosensors, and provide design guidelines to orthogonally control the biosensor output and its sensitivity. Next, we develop a malonyl-CoA sensor-actuator and demonstrate its application to engineering a negative feedback circuit to improve fatty acid production. Finally, genetic circuits with various architectures are constructed to study metabolic dynamics, which reveal that negative feedback circuits can dramatically accelerate metabolic dynamics.
The findings of this dissertation provide rational design principles for transcription factor-based metabolite biosensors and a systematic understanding of metabolic dynamics under various regulation architectures. They provide valuable tools and knowledge to engineer metabolic circuits to regulate various metabolic pathways, increasing titers, productivities, and yields.
Gautam Dantas, Bradley Evans, Tae Seok Moon, Himadri Pakrasi,