Engineering Synthetic Oscillatory Gene Networks at the Population Level Duke University Genetically Engineered Machines 2006 Sagar Indurkhya, Nicholas Tang, Austen Heinz, and Lingchong You Durham, North Carolina 27708, U.S.A. Objectives and Approach To explore oscillating gene circuits at the population level for the purpose of developing methods and models for the engineering of more complex cellular behaviors Optimizing mathematical models In vitro characterization Computational characterization Artificial oscillating populations demonstrate the poten-tial for larger and more complex synchronized genetic circuits, which allow for drug delivery and integrated regulation of neuronal, metabolic, and cardiac systems. Characterization Computational Chemistry Analysis: Similar HOMO (highest occupied molecular orbital)/LUMO (lowest unoccupied molecular orbital) gap values indicate that degradation and hydrolysis of the molecule correspond to the various sites of excitability. These states also appear to correspond to the previously identified routes to inactivation of AHL, such as hydrolysis of the lactone ring, hydrolysis of the amide bond, and racemization. Using data from previous experimental characterization of degradation rates for the lux small molecule, we fit a power curve to approximate degradation rates for all four small molecules. These results provide predictive potential for degradation rates. Compression of digital logic with-in gene circuits using Ribosome Binding Site (RBS) Regulation Characterization of small molec-ule cross talk is necessary to pr-ovide gene circ-uit designers with solid found-ations. Abstract Engineered Genetic Machines can serve as effective gene delivery, drug production, and metabolic platforms, while shedding fundamental insight on natural biological systems. We have developed two novel gene circuits: a synthetic predator prey ecosystem and a multistage genetic oscillator using both new and novel strategies. Both circuits operate at the population level, synchronizing behavior through a biochemical process known as quorum sensing. To date they represent two of the most complex artificial biological systems ever attempted. Our work has given a detailed description of several natural processes while at the same time developed new biological parts and computational tools to further advance the rapidly developing field of synthetic biology. A Predator-Prey Ecosystem X-Verter Mathematical Modeling Assembly Analysis We have written a software package, Biobricks Manager, which autom-ates the assembly process in a customized Integrated Development Environment (IDE). Predator-Prey Handles multiple projects simultaneously (checking for reusable bricks) Automatically synchronizes information with the online Standard Parts Registry Automatically re-computes and optimizes the assembly process at each stage. Perform sequence analysis and automate the error detection process. Acknowledgements Duke University - Jingdong Tian Faisal Reza The North Carolina School of Science and Math - Myra Halpin - Bob Gotwals Conclusion We have found similarities between the pH degradation values of the different quorum sensing models through computational chemistry. We have developed and studied two different complex oscillating gene networks that both operate at the population level through quorum-sensing based synchronization. X-Verter