Debugging Platform for Iterative Design of Model-Based Synthetic Genomes

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Kevin Tsai, Chuan-Hsiung Chang

Academia Sinica, United States

Scientists have leveraged similarities between synthetic biology and engineering in order to apply engineering techniques to genome design. One of such techniques, called iterative design, has enabled scientists to generate viable synthetic organisms by conducting iterations of design, prototyping, and evaluation. However, the tools used during evaluation can still lead to uncertainties on how to correct undesirable behavior. The synthetic biology community needs better platforms to debug the mechanics of synthetic organisms both in silico and in vivo in order to avoid wasted effort and resources used during wet lab implementation. In order to address these issues we have constructed a software platform that can perform the first formalized debugging method for synthetic and systems biology. The method allows users to refine their models by translating a model to a biological instruction set and perform debugging techniques similar to that seen in integrated development environments for software engineering. After in vivo implementation of the refined model, expression data can be compared with the expected deviation of multiple stochastic model simulations in order to identify runtime reactions, events or other instructions that did not occur as expected in vivo via simulation breakpoints provided by the debugger. This technique increases the prediction of defects that cause unexpected behavior in synthetic organisms and allows for a much more efficient iterative process. We applied the debugging methodology to a variety of different models to test the methodology’s viability. The models ranged from classic examples of designs in synthetic biology to completely novel systems. In each case we demonstrated the effectiveness of the debugger in identifying runtime defects and demonstrate how useful the methodology can be for improving iterative design of synthetic organisms. Funding for this project provided by the National Science Council (NSC) of Taiwan (NSC 101-2319-B-010-002 and NSC101-3113-P-110-002).