Semester of Graduation

May 2022


Master of Chemical Engineering (MChE)


Gordon A. and Mary Cain Department of Chemical Engineering

Document Type



A longstanding goal in synthetic biology has been to build synthetic gene circuits with the ability to harness nature’s capability of precise gene expression regulation. Advancements in RNA technology have established RNA-based regulators with distinct advantages over traditional protein-based regulators such as faster signal propagation, versatile programmability, and low cellular burden, which has created an interest in the field to construct innovative synthetic gene circuits using de novo RNA- based regulators. However, our understanding of the behavior and kinetics of RNA-RNA interactions for the construction of gene circuits is incomplete. This thesis proposes a model-guided design framework that integrates mechanistic modeling and statistical analysis with experimental efforts to overcome this challenge. The proposed framework features: first, define the application of gene circuit; second, select the circuit's architecture and relevant gene regulatory components based on desired dynamics; third, develop a mathematical model to describe the involved biomolecular reaction in the system and identify relevant kinetic information from literature; fourth, perform in vivo or in vitro experimental construction and validation of the circuit.

The feasibility of the framework is first demonstrated by assessing the viability of an RNA-only I1-FFL gene circuit. The proposed design is evaluated using a combined experimental and mathematical approach to elucidate the kinetics of RNA-RNA interactions for timescale critical circuit architectures. The framework is then extended to evaluate the relationship between regulation level (transcription or translation) and circuit dynamics using four design variations of the I1-FFL circuit. The performance of each circuit is compared using mechanistic modeling, statistical analysis, and standard control theory concepts, which provide a quantitative way to reveal the effect of regulation level and circuit behavior. The major contributions of this thesis include: (1) it demonstrates the utility of modeling to troubleshoot and debug circuit design (2) it reveals the importance of regulation level in designing synthetic circuits. Together, the findings presented in this thesis aim to facilitate the design and implementation of gene circuits with increased complexity and functionality.

Committee Chair

Xun Tang