Humans can now construct and piece together DNA sequences in order to design new biological systems and organisms. We can do this more quickly and less expensively than ever. Applications abound for our synthetic biological constructs, from sensors of biochemical and chemical weapons, to devices that will remove environmental pollutants, to gene therapies. Synthetic biology is the discipline that focuses on the construction of these novel biological systems. It has all the characteristic features of an engineering discipline: applying technical and scientific knowledge to design and implement devices, systems, and processes that safely realize a desired objective. Mathematical modeling has always been an important component of engineering disciplines. It can play an important role in synthetic biology the same way modeling helps in aircraft or architecture design: models and computer simulations can quickly provide a clear picture of how different components influence the behavior of the whole, reaching objectives quickly. The proposed activities will result in modeling tools that will help scientists and engineers to construct complex synthetic biological systems. These tools will be standardized, so that they are applicable to any synthetic biological system. The activities will also produce novel synthetic gene regulatory networks that can find applications in pharmaceutical production and gene therapies. We will develop sophisticated mathematical models of synthetic biological systems that connect the targeted biological phenotype (what we want the synthetic biological system to do) to the DNA sequence (that we need to physically construct to realize the synthetic biological system). We will conduct simulations of many alternate designs to decide on the optimum set of molecular components, before we go into the wet laboratory. We will then construct these designs in E. coli and optimize them for performance. We propose to work with synthetic tetracycline inducible networks because they have significant biomedical applications, mainly as gene therapy expression vectors. Tetracycline is a small antibiotic molecule that can safely turn on the production of any protein, when this protein is expressed under the control of a tetracycline-responsive DNA promoter. We will model, design, build and test these promoters to determine how to best control protein expression with tetracycline induction.
Imagine trying to engineer a biological sensor that senses a small drug molecule and responds by turning on the expression of a therapeutic protein, say insulin. Now imagine having a software tool that can assist in engineering the sensor quickly. The proposed activities will result in modeling tools for computer-aided construction of complex synthetic biological systems. The activities will also produce novel synthetic gene regulatory networks with applications in pharmaceutical production and gene therapies. 25-word Summary/Public Health Relevance Statement The proposed activities will result in publicly available mathematical tools, useful in computeraided construction of synthetic biological systems, which find applications in gene therapies
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| Borrero, Juan; Chen, Yuqing; Dunny, Gary M et al. (2015) Modified lactic acid bacteria detect and inhibit multiresistant enterococci. ACS Synth Biol 4:299-306 |
| Afroz, Taliman; Biliouris, Konstantinos; Boykin, Kelsey E et al. (2015) Trade-offs in engineering sugar utilization pathways for titratable control. ACS Synth Biol 4:141-9 |
| Kaznessis, Yiannis N (2014) Multiscale Models of Antibiotic Probiotics. Curr Opin Chem Eng 6:18-24 |
| Smadbeck, Patrick; Kaznessis, Yiannis N (2014) Solution of Chemical Master Equations for Nonlinear Stochastic Reaction Networks. Curr Opin Chem Eng 5:90-95 |
| Afroz, Taliman; Biliouris, Konstantinos; Kaznessis, Yiannis et al. (2014) Bacterial sugar utilization gives rise to distinct single-cell behaviours. Mol Microbiol 93:1093-1103 |
| Volzing, Katherine; Borrero, Juan; Sadowsky, Michael J et al. (2013) Antimicrobial peptides targeting Gram-negative pathogens, produced and delivered by lactic acid bacteria. ACS Synth Biol 2:643-50 |
| Smadbeck, Patrick; Kaznessis, Yiannis N (2013) A closure scheme for chemical master equations. Proc Natl Acad Sci U S A 110:14261-5 |
| Smadbeck, Patrick; Kaznessis, Yiannis (2012) Stochastic model reduction using a modified Hill-type kinetic rate law. J Chem Phys 137:234109 |
| Smadbeck, P; Kaznessis, Y N (2012) Efficient Moment Matrix Generation for Arbitrary Chemical Networks. Chem Eng Sci 84:612-618 |
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