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Computational Synthetic Biology, 2015

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In this theme, students will learn how to use computational modeling tools for design and evaluation of synthetic gene networks. We will review basic modeling approaches including Boolean networks, mass action kinetics, stochastic simulation algorithms and provide hands-on training sessions on using corresponding software tools. Then we will apply these tools to the design and analysis of basic elements of synthetic circuits such as positive and feedback loops, oscillators, toggle switches, logical gates, quorum-sensing circuits, enzymatic machinery. Issues of stochasticity, cell-to-cell variability, robustness and parameter sensitivity will be addressed in depth in regards to evaluation of synthetic circuit performance. The morning lectures will be shared with the Experimental Synthetic Biology track, while the afternoon hands-on tutorials and group project work will be track-specific.


Project Mentors

  • Philip Bittihn
  • Bart Borek
  • Rob Cooper
  • Andriy Didovyk
  • Meng Jin
  • PJ Steiner
  • Krzysztof Wabnik


  • Fundamentals of Biochemical Reaction Kinetics: Elementary Reactions, Law of Mass Action, Chemical Equilibrium, Enzyme Kinetics, Stochastic Reaction Kinetics
  • Basic modeling approaches: Deterministic ODE models, Bifurcation analysis, Stochastic Simulation Algorithm and its modifications, Multiscale modeling, Parameter fitting, Sensitivity analysis
  • Transcriptional regulation: Repressor-Operator Binding, Cooperative Transcription Factor Binding, DNA looping, Feedback
  • Post-transcriptional regulation: Splicing, Zero-order ultrasensitivity, Queueing
  • Signaling cascades NFkB pathway, Erk pathway, Information transmission,
  • Positive and Negative Feedback
  • Bistable Switches: Lambda and the Engineered Toggle Switch
  • Logic gates and pulse generators
  • Genetic Oscillators: positive-negative feedback, time-delayed negative feedback, coupled oscillators, synchronization
  • Gene expression noise: translational bursting, transcriptional bursting, transcription factor fluctuations, feedback circuits for effective noise control
  • Noise-induced transitions and bistability


Suggested Reading

[1] Gardner, T. S., Cantor, C. R. & Collins, J. J. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339–42 (2000).

[2] Elowitz, M. B. & Leibler, S. A synthetic oscillatory network of transcriptional regulators. Nature 403, 335–8 (2000).

[3] Daunert, S. et al. Genetically engineered whole-cell sensing systems: coupling biological recognition with reporter genes. Chemical Reviews 100, 2705–2738 (2000).

[4] Hasty, J., McMillen, D. & Collins, J. J. Engineered gene circuits. Nature 420, 224–30 (2002).

[5] Sprinzak, D. & Elowitz, M. B. Reconstruction of genetic circuits. Nature 438, 443–8 (2005).

[6] Kobayashi, H. et al. Programmable cells: interfacing natural and engineered gene networks. Proc. Natl. Acad. Sci. U. S. A. 101, 8414–9 (2004).

[7] You, L., Cox, I., R. S.,Weiss, R. & Arnold, F. H. Programmed population control by cell-cell communication and regulated killing. Nature 428, 868–71 (2004).

[8] Basu, S., Gerchman, Y., Collins, C. H., Arnold, F. H. & Weiss, R. A synthetic multicellular system for programmed pattern formation. Nature 434, 1130–4 (2005).

[9] Stricker, J. et al. A fast, robust and tunable synthetic gene oscillator. Nature 456, 516–9 (2008).

[10] Raj, A. & van Oudenaarden, A. Nature, nurture, or chance: stochastic gene expression and its consequences. Cell 135, 216–226 (2008).

[11] Mukherji, S.&Van Oudenaarden, A. Synthetic biology: understanding biological design from synthetic circuits. Nature Reviews Genetics 10, 859–871 (2009).

[12] P. E. M. Purnick & R. Weiss The second wave of synthetic biology: from modules to systems. Nature Reviews Molecular Cell Biology 10, 410-422 (2009)

[13] Mather, W., Bennett, M., Hasty, J. & Tsimring, L. Delay-Induced Degrade-and-Fire Oscillations in Small Genetic Circuits. Biophys. J Phys Rev Lett 102, 068105 (2009).

[14] Ellis, T., Wang, X. & Collins, J. Diversity-based, model-guided construction of synthetic gene networks with predicted functions. Nature biotechnology 27, 465 (2009).

[15] Friedland, A. et al. Synthetic gene networks that count. Science 324, 1199 (2009).

[16] Cagatay, T., Turcotte, M., Elowitz, M., Garcia-Ojalvo, J. & Suel, G. M. Architecture-dependent noise discriminates functionally analogous differentiation circuits. Cell 139, 512–522 (2009).

[17] Danino, T., Mondragon-Palomino, O., Tsimring, L. & Hasty, J. A synchronized quorum of genetic clocks. Nature 463, 326–330 (2010).

[18] Tamsir, A., Tabor, J. & Voigt, C. Robust multicellular computing using genetically encoded nor gates and chemical/wires/’. Nature 469, 212–215 (2010).

[19] van der Meer, J. & Belkin, S. Where microbiology meets microengineering: design and applications of reporter bacteria. Nature Reviews Microbiology 8, 511–522 (2010).

[20] Mondragon-Palomino, O., Danino, T., Selimkhanov, J., Tsimring, L. & Hasty, J. Entrainment of a population of synthetic genetic oscillators. Science 333 (2011).

[21] S. Payne and L. You. Engineered Cell-Cell Communication and its applications. Adv. Biochem. Eng. Biotechnol. (2013).