This project is a multi-institutional collaboration in which we plan to investigate a new soft-logic approach for creating ?designer gene? circuits. Genetic circuits are crafted in the laboratory using genomic building blocks, and are used to control specific behaviors in engineered bacteria. A major research challenge for genetic circuits is that there is a high level of randomness in the cell?s internal environment. Belief networks provide a well-defined solution for handling the effects of randomness in genetic systems. We propose to study how belief networks can be applied to control and even exploit randomness to achieve new and useful genetic behaviors. Our research results will be used to improve a software application for genetic design called iBioSim.
There are many anticipated benefits for synthetic genetic circuits, including industrial, environmental, and medical applications. For example, bacteria can theoretically be engineered to clean oil spills, kill tumors, and deliver medicines, but only if we can precisely control when and how the bacteria perform their functions. Our investigation will illuminate the unique challenges involved in controlling highly random bacterial systems and will provide the community with rigorous theory and practicable techniques that resolve these challenges.
This project was a collaboration of computer scientists, electrical engineers, and biological engineers to create computer-aided design (CAD) solutions for the emerging field of synthetic biology, which concerns the creation of artificial genetic circuits that are inserted into living organisms (usually bacteria). We explored new techniques for specifying the desired function of fuzzy biological systems; for simulating their behavior including random behavioral aspects; and for verifying statistically correct behaviors. We accomplished these goals by developing a custom CAD product called iBioSim, which is freely available to the public from our web page at: http://www.async.ece.utah.edu/iBioSim/ Intellectual Merit: Our objectives were to increase the speed of genetic design, to improve the success rate of laboratory experiments, and to expand the space of possibilities for new genetic circuits. To meet these objectives, we developed several new "incremental stochastic simulation" algorithms (which we call iSSA methods) that assist in statistical exploration of genetic circuit behavior at the level of molecular reactions. We also developed a new "stochastic model checking" methodology for describing desired statistical behaviors in biochemical systems. Our iBioSim tool uses the model checking methodology to detect violations of desired properties in genetic circuit designs. In addition to improved molecular simulations, we developed new ways to model and simulate complex cellular interactions in populations of engineered cells. These populations can be described and simulated using iBioSim, and their collective behavior can be inspected using a new visual interface. Our students competed in the international Genetically Engineered Machines (iGEM) competition. iGEM is the premiere Synthetic Biology student competition and the largest Synthetic Biology conference in the world. The USU iGEM team's project, titled "CyanoBricks", expanded the available building blocks for synthetic biology by synthesizing several different DNA promoters and ribosome binding sites for use in cyanobacteria. Synthetic biology research has been limited to a small range of target organisms, most commonly E. coli. This new part collection expands the range of biological possibilities. These BioBrick parts are now freely available to the scientific community. The team won a gold medal for their efforts. We also discovered some ways to improve traditional electronic design by borrowing ideas from genetic circuits, which will aid in producing devices that last longer and operate more reliably in harsh environments. Our new method, called "restorative feedback" is based on a natural bacterial signalling mechanism known as "quorum sensing," in which a population of cells exchange signals to help coordinate their behavior. Restorative feedback uses an electronic version of this process to suppress the occurrence of random logic errors in a computing circuit. A harsh environment may include high-temperature or high-radiation scenarios, which occur in many industrial and scientific settings ranging from mining operations to space exploration. Broader Impacts: The chief impact of our work is the development and free distribution of the iBioSim software, which is being used by researchers to advance the possibilities of synthetic biology. There are numerous potential applications for synthetic biology, including medical treatments, pharmaceutical manufacturing, production of biofuels and bioplastics, among others. Our work provides new tools to accelerate the progress of research in this young field.
