Prototyping Diverse Synthetic Biological Circuits in a Cell-Free Transcription-Translation System

Synthetic biological circuits are the foundation for the ultimate goals of controlling cells and building artificial cells from the ground up. To get closer to these goals in a more efficient way, we utilize a cell-free transcription-translation system to help perfect biological circuits for the simplicity, freedom, and convenience that the system offers. In this thesis, we demonstrate three distinct aspects of biological circuits in a cell-free transcription-translation system: circuit dynamics, phosphorylation, and membrane proteins. We start with a simple feedforward circuit, which shows dynamic responses to the input. We first prototype the feedforward circuit in the cell-free system with the aid of mathematical modeling. Then, based on the knowledge learned from prototyping, we successfully implement the circuit in cells. Not only do we show that a circuit with dynamics can be prototyped in the cell- free system, but we also test a more complicated circuit involving a phosphorylation cycle. The phosphorylation-based insulator circuit is prototyped and then a model created for the circuit is shown to be identifiable in the cell-free system. To further expand the capability of the cell-free system, we demonstrate that biologically active membrane proteins can be generated in the cell-free system with engineering, suggesting that even biological circuits requiring membrane proteins can be prototyped in the system. These results help advance our knowledge of both biological circuits and the cell-free transcription-translation system, and bring us one step closer to our ultimate goals of implementing control theory in synthetic biology

Retroactivity to the input in complex gene transcription networks

Synthetic biology is a bottom-up engineering discipline: biological modules are systematically designed with predefined behavior and then combined to build up larger circuits. Although the modules produce the desired behavior in isolation, they fail to operate properly when they are connected due to retroactivity, an effect which extends the notion of impedance to biomolecular systems. Despite playing a central role, retroactivity is not yet characterized in complex gene transcription networks. In this paper, we mathematically describe and quantify this effect. This result is obtained by applying singular perturbation on the finite time interval. We identify the biomolecular counterpart of impedance and introduce the effective retroactivity to the input of a gene. Furthermore, we provide a theorem describing how modules affect each other when connected. We restore modular composition of synthetic circuits by extending the characterization of modules with internal and input retroactivities. We illustrate the implications of the results by investigating crosstalk in a simple genetic system