Rapid advances in the forward engineering of complex genetic circuits in living cells proved that the young discipline of Synthetic Biology has the potential to transform modern biotechnology. A predictive understanding of living systems is a prerequisite for designed manipulation in bioengineering and informed intervention in medicine. Such an understanding requires quantitative measurements, mathematical analysis, and theoretical abstraction. The advent of powerful measurement technologies and computing capacity has positioned biology to drive the next scientific revolution. Synthetic Biology provides a natural platform for the development and testing of models and general network principles using quantitative data from engineered genetic circuits. One of the major fundamental problems of Synthetic Biology is the propensity of synthetic circuits to evolve and obliterate their intended functionality. Thus, it is important to develop a quantitative approach to make genetic networks more robust and stable which also will make them more useful in therapeutic applications. The overall goal of this project to explore the challenges and exploit the opportunities that accompany the inevitable selective pressure that arises in synthetic biology through a combination of cutting-edge experimental and computational tools. Successful accomplishment of this project will lead to significant advances in understanding the interaction between synthetic circuits and host genome in the evolutionary context. This project will provide ample opportunities for cross-disciplinary training of the new generation of quantitative biologists. Furthermore, to broaden the impact of this project beyond academia, its participants will expand a highly successful elementary school science program that that foster collaboration between researchers and teachers at partner elementary schools to improve hands-on science education.
To reach the overall goal of the project, the recently developed "synchronized lysis circuit" will be used as the major focus. This synthetic gene circuit functions by triggering death of around 90% of the bacteria at a threshold population density, leaving the remaining 10% of the cells to grow back to threshold and restart the cycle. This generates a distinct phenotype characterized by population cycling that can be monitored across a wide range of length scales using micro- and bench-top chemostats. It also introduces a strong selective pressure that can lead to rapid evolution. The investigators will develop quantitative measurement technology and computational modeling that will lead to a quantitative statistical characterization of the circuit-host evolution process. Sequencing of the circuit and mutated sections of the host genome along the time course of the experiments will be used to reconstruct the evolutionary path the systems have taken. Mathematical modeling will guide experiments and help extract key parameters characterizing evolutionary dynamics of the synchronized lysis circuit. Using the gained knowledge, the researchers will engineer a "lysis circuit stabilizer" module that kills mutant bacteria losing lysis efficiency, and explore ways to use lysis circuit as a tool in directed evolution of synthetic circuits.
This award was co-funded by the Systems and Synthetic Biology (SSB) program in the Molecular and Cellular Biosciences (MCB) Division in the Biological Sciences Directorate and the Biotechnology and Biochemical Engineering (BBE) program of the Division of Chemical, Bioengineering, Environmental and Transport Systems (CBET) in the Engineering Directorate.
