Over the last 17 years, scientists and engineers have developed synthetic gene circuits that can program the functionality, performance, and behavior of living cells. Analogous to integrated circuits that underlie myriad electronic products, engineered gene circuits can be used to generate defined dynamics, rewire endogenous networks, sense environmental stimuli, and produce valuable biomolecules.
These gene circuits hold great promise in medical and biotechnological applications, such as combating super bugs, producing advanced biofuels, and manufacturing functional materials.
To date, most circuits are constructed through a trial-and-error manner, which relies heavily on a designer’s intuition and is often inefficient, said University of Illinois Bioengineering Associate Professor Ting Lu. “With the increase of circuit complexity, the lack of predictive design guidelines has become a major challenge in realizing the potential of synthetic biology,” said Lu, who also is affiliated with the Carl R. Woese Institute for Genomic Biology and Physics Department at Illinois.
Researchers have turned to quantitative modeling to address this gene circuit design challenge. Typical models regard gene circuits as isolated entities that do not interact with their hosts and focus only on the biochemical processes within the circuits, noted Lu.
“Although highly valuable, the current modeling paradigm is often incapable of quantitatively, or even qualitatively sometimes, describing circuit behaviors,” he said. “Increasing experimental evidences have suggested that circuits and their biological host are intimately…