Abstract
Synthetic biology has impressively progressed during the last decades making it possible to rationally design and implement genetic networks with new functionalities in living microorganisms. With these new technologies the expression of genes can be observed using fluorescent markers and influenced using light flashes and photo-active expression inducers. In this contribution, we suggest the implementation of external feedback control for dynamic trajectory tracking of a synthetic genetic network. The feedback control can be implemented in living microorganisms using fluorescent markers for system readout and photo-active gene expression inducers for external control signals. In particular we show that hierarchical or sequential design for synthetic gene networks makes controlled trajectory tracking possible using the readout and control actions on few instead of all genes. Optimised trajectory tracking opens the possibility to interact and influence genetic networks in a very precise manner in terms of time and location with minimal cell burden.
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References
Csete, M.E., Doyle, J.C.: Reverse engineering of biological complexity. Science 295, 1664–1669 (2002)
Lin, F., Muthuraman, K., Lawley, M.: An optimal control theory approach to non-pharmaceutical interventions. BMC Infectious Diseases 10, 32 (2010)
Stan, G.B., Belmudes, F., Fonteneau, R., Zeggwagh, F., Lefebvre, M.A., et al.: Modelling the influence of activation-induced apoptosis of cd4[sup + ] and cd8[sup + ] t-cells on the immune system response of a hiv-infected patient. IET Systems Biology 2, 94–102 (2008)
Schiff, S.J., Sauer, T.: Kalman filter control of a model of spatiotemporal cortical dynamics. J. Neural Eng. 5, 1–8 (2008)
Khalil, A.S., Collins, J.J.: Synthetic biology: applications come of age. Nat. Rev. Genet. 11, 367–379 (2010)
Cameron, D.E., Bashor, C.J., Collins, J.J.: A brief history of synthetic biology. Nat. Rev. Micro. 12, 381–390 (2014)
Cai, L., Friedman, N., Xie, X.S.: Stochastic protein expression in individual cells at the single molecule level. Nature 440, 358–362 (2006)
Bennett, M.R., Hasty, J.: Microfluidic devices for measuring gene network dynamics in single cells. Nat. Rev. Genet. 10, 628–638 (2009)
Shimizu-Sato, S., Huq, E., Tepperman, J.M., Quail, P.H.: A light-switchable gene promoter system. Nat. Biotech. 20, 1041–1044 (2002)
Levskaya, A., Weiner, O.D., Lim, W.A., Voigt, C.A.: Spatiotemporal control of cell signalling using a light-switchable protein interaction. Nature 461, 997–1001 (2009)
Slotine, J.J.E., Li, W.: Applied nonlinear control. Prentice-Hall, New Jersey (1991)
Ernst, D., Geurts, P., Wehenkel, L.: Tree-based batch mode reinforcement learning. Journal of Machine Learning Research 6, 503–556 (2005)
Strelkowa, N.: Inference of Optimized Control Strategies for Genetic Networks. In: ISCS 2013: Interdisciplinary Symposium on Complex Systems. Emergence, Complexity and Computation, vol. 8, pp. 265–270. Springer, Heidelberg (2014)
Bertsekas, D.: Dynamic Programming and Optimal Control, 2nd edn., vol. I. Athena Scientific, Belmont (2000)
van Kampen, N.G.: Stochastic Processes in Physics and Chemistry, 3rd edn. Elsevier, Amsterdam (2007)
Strelkowa, N., Barahona, M.: Switchable genetic oscillator operating in quasi-stable mode. Journal of the Royal Society Interface (2010)
Strelkowa, N., Barahona, M.: Transient dynamics around unstable periodic orbits in the generalized repressilator model. Chaos: An Interdisciplinary Journal of Nonlinear Science 21, 023104 (2011)
El-Samad, H., Khammash, M.: Modelling and analysis of gene regulatory networks using feedback control theory. International Journal of Systems Science 41, 17–33 (2010)
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Strelkowa, N. (2015). Trajectory Tracking for Genetic Networks Using Control Theory. In: Sanayei, A., E. Rössler, O., Zelinka, I. (eds) ISCS 2014: Interdisciplinary Symposium on Complex Systems. Emergence, Complexity and Computation, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-319-10759-2_28
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DOI: https://doi.org/10.1007/978-3-319-10759-2_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10758-5
Online ISBN: 978-3-319-10759-2
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