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High-resolution mapping of bifurcations in nonlinear biochemical circuits

Abstract

Analog molecular circuits can exploit the nonlinear nature of biochemical reaction networks to compute low-precision outputs with fewer resources than digital circuits. This analog computation is similar to that employed by gene-regulation networks. Although digital systems have a tractable link between structure and function, the nonlinear and continuous nature of analog circuits yields an intricate functional landscape, which makes their design counter-intuitive, their characterization laborious and their analysis delicate. Here, using droplet-based microfluidics, we map with high resolution and dimensionality the bifurcation diagrams of two synthetic, out-of-equilibrium and nonlinear programs: a bistable DNA switch and a predator–prey DNA oscillator. The diagrams delineate where function is optimal, dynamics bifurcates and models fail. Inverse problem solving on these large-scale data sets indicates interference from enzymatic coupling. Additionally, data mining exposes the presence of rare, stochastically bursting oscillators near deterministic bifurcations.

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Figure 1: Workflow for mapping the bifurcation diagram of nonlinear biochemical systems.
Figure 2: Biochemical details of the nonlinear circuits.
Figure 3: Experimental bifurcations in a bistable circuit.
Figure 4: Bifurcation diagram of a synthetic molecular predator–prey oscillator.

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References

  1. Rothemund, P. W. K. Folding DNA to create nanoscale shapes and patterns. Nature 440, 297–302 (2006).

    Article  CAS  Google Scholar 

  2. Kuzyk, A. et al. DNA-based self-assembly of chiral plasmonic nanostructures with tailored optical response. Nature 483, 311–314 (2012).

    Article  CAS  Google Scholar 

  3. Zhang, D. Y., Chen, S. X. & Yin, P. Optimizing the specificity of nucleic acid hybridization. Nature Chem. 4, 208–214 (2012).

    Article  CAS  Google Scholar 

  4. Seelig, G. et al. Enzyme-free nucleic acid logic circuits. Science 314, 1585–1588 (2006).

    Article  CAS  Google Scholar 

  5. Takinoue, M. et al. Experiments and simulation models of a basic computation element of an autonomous molecular computing system. Phys. Rev. E 78, 041921 (2008).

    Article  Google Scholar 

  6. Katz, E. & Privman, V. Enzyme-based logic systems for information processing. Chem. Soc. Rev. 39, 1835–1857 (2010).

    Article  CAS  Google Scholar 

  7. Genot, A. J., Bath, J. & Turberfield, A. J. Reversible logic circuits made of DNA. J. Am. Chem. Soc. 133, 20080–20083 (2011).

    Article  CAS  Google Scholar 

  8. Qian, L. & Winfree, E. Scaling up digital circuit computation with DNA strand displacement cascades. Science 332, 1196–1201 (2011).

    Article  CAS  Google Scholar 

  9. Orbach, R. et al. Logic reversibility and thermodynamic irreversibility demonstrated by DNAzyme-based Toffoli and Fredkin logic gates. Proc. Natl Acad. Sci. USA 109, 21228–21233 (2012).

    Article  CAS  Google Scholar 

  10. Genot, A. J., Bath, J. & Turberfield, A. J. Combinatorial displacement of DNA strands: application to matrix multiplication and weighted sums. Angew. Chem. Int. Ed. 52, 1189–1192 (2013).

    Article  CAS  Google Scholar 

  11. Daniel, R. et al. Synthetic analog computation in living cells. Nature 497, 619–623 (2013).

    Article  CAS  Google Scholar 

  12. Sarpeshkar, R. Analog synthetic biology. Phil. Trans. R. Soc. A 372, 20130110 (2014).

    Article  CAS  Google Scholar 

  13. Alon, U. An Introduction to Systems Biology (Chapman and Hall, 2007).

    Google Scholar 

  14. Hatakeyama, T. S. & Kaneko, K. Generic temperature compensation of biological clocks by autonomous regulation of catalyst concentration. Proc. Natl Acad. Sci. USA 109, 8109–8114 (2012).

    Article  CAS  Google Scholar 

  15. Fujii, T. & Rondelez, Y. Predator–prey molecular ecosystems. ACS Nano 7, 27–34 (2013).

    Article  CAS  Google Scholar 

  16. Montagne, K. et al. Programming an in vitro DNA oscillator using a molecular networking strategy. Mol. Syst. Biol. 7, 466 (2011).

    Article  Google Scholar 

  17. Kim, J. & Winfree, E. Synthetic in vitro transcriptional oscillators. Mol. Syst. Biol. 7, 465 (2011).

    Article  Google Scholar 

  18. Padirac, A., Fujii, T. & Rondelez, Y. Bottom-up construction of in vitro switchable memories. Proc. Natl Acad. Sci. USA 109, E3212–E3220 (2012).

    Article  CAS  Google Scholar 

  19. Kim, J., White, K. S. & Winfree, E. Construction of an in vitro bistable circuit from synthetic transcriptional switches. Mol. Syst. Biol. 2, 68 (2006).

    Article  Google Scholar 

  20. Qian, L., Winfree, E. & Bruck, J. Neural network computation with DNA strand displacement cascades. Nature 475, 368–372 (2011).

    Article  CAS  Google Scholar 

  21. Chen, Y.-J. et al. Programmable chemical controllers made from DNA. Nature Nanotech. 8, 755–762 (2013).

    Article  CAS  Google Scholar 

  22. Franco, E. et al. Timing molecular motion and production with a synthetic transcriptional clock. Proc. Natl Acad. Sci. USA 108, E784–E793 (2011).

    Article  CAS  Google Scholar 

  23. Karzbrun, E. et al. Programmable on-chip DNA compartments as artificial cells. Science 345, 829–832 (2014).

    Article  CAS  Google Scholar 

  24. Niederholtmeyer, H. et al. Rapid cell-free forward engineering of novel genetic ring oscillators. eLife e09771 (2015).

  25. Epstein, I. R. & Pojman, J. A. An Introduction to Nonlinear Chemical Dynamics (Oxford Univ. Press, 1998).

    Google Scholar 

  26. Wei, B., Dai, M. & Yin, P. Complex shapes self-assembled from single-stranded DNA tiles. Nature 485, 623–626 (2012).

    Article  CAS  Google Scholar 

  27. Niederholtmeyer, H., Stepanova, V. & Maerkl, S. J. Implementation of cell-free biological networks at steady state. Proc. Natl Acad. Sci. USA 110, 15985–15990 (2013).

    Article  CAS  Google Scholar 

  28. Galas, J.-C., Haghiri-Gosnet, A.-M. & Estevez-Torres, A. A nanoliter-scale open chemical reactor. Lab Chip 13, 415–423 (2013).

    Article  CAS  Google Scholar 

  29. Sugiura, H. et al. Pulse-density modulation control of chemical oscillation far from equilibrium in a droplet open-reactor system. Nature Commun. 7, 10212 (2016).

    Article  CAS  Google Scholar 

  30. Hasatani, K. et al. High-throughput and long-term observation of compartmentalized biochemical oscillators. Chem. Commun. 49, 8090–8092 (2013).

    Article  CAS  Google Scholar 

  31. Weitz, M. et al. Diversity in the dynamical behaviour of a compartmentalized programmable biochemical oscillator. Nature Chem. 6, 295–302 (2014).

    Article  CAS  Google Scholar 

  32. Song, H., Chen, D. L. & Ismagilov, R. F. Reactions in droplets in microfluidic channels. Angew. Chem. Int. Ed. 45, 7336–7356 (2006).

    Article  CAS  Google Scholar 

  33. Agresti, J. J. et al. Ultrahigh-throughput screening in drop-based microfluidics for directed evolution. Proc. Natl Acad. Sci. USA 107, 4004–4009 (2010).

    Article  CAS  Google Scholar 

  34. Gardner, T. S., Cantor, C. R. & Collins, J. J. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339–342 (2000).

    Article  CAS  Google Scholar 

  35. Baccouche, A. et al. Dynamic DNA-toolbox reaction circuits: a walkthrough. Methods 67, 234–249 (2014).

    Article  CAS  Google Scholar 

  36. Crawford, J. D. Introduction to bifurcation theory. Rev. Mod. Phys. 63, 991–1037 (1991).

    Article  Google Scholar 

  37. Dai, L. et al. Generic indicators for loss of resilience before a tipping point leading to population collapse. Science 336, 1175–1177 (2012).

    Article  CAS  Google Scholar 

  38. Ma, R. et al. Small-number effects: a third stable state in a genetic bistable toggle switch. Phys. Rev. Lett. 109, 248107 (2012).

    Article  Google Scholar 

  39. Huang, S. Reprogramming cell fates: reconciling rarity with robustness. Bioessays 31, 546–560 (2009).

    Article  CAS  Google Scholar 

  40. Genot, A. J., Fujii, T. & Rondelez, Y. Computing with competition in biochemical networks. Phys. Rev. Lett. 109, 208102 (2012).

    Article  Google Scholar 

  41. Hansen, N. & Ostermeier, A. Completely derandomized self-adaptation in evolution strategies. Evol. Comput. 9, 159–195 (2001).

    Article  CAS  Google Scholar 

  42. Prindle, A. et al. Rapid and tunable post-translational coupling of genetic circuits. Nature 508, 387–391 (2014).

    Article  CAS  Google Scholar 

  43. Van Roekel, H. W. H. et al. Automated design of programmable enzyme-driven DNA circuits. ACS Synth. Biol. 4, 735–745 (2015).

    Article  CAS  Google Scholar 

  44. Decroly, O. & Goldbeter, A. Birhythmicity, chaos, and other patterns of temporal self-organization in a multiply regulated biochemical system. Proc. Natl Acad. Sci. USA 79, 6917–6921 (1982).

    Article  CAS  Google Scholar 

  45. Tan, E. et al. Specific versus nonspecific isothermal DNA amplification through thermophilic polymerase and nicking enzyme activities. Biochemistry 47, 9987–9999 (2008).

    Article  CAS  Google Scholar 

  46. Urabe, H. et al. Compartmentalization in a water-in-oil emulsion repressed the spontaneous amplification of RNA by Qβ replicase. Biochemistry 49, 1809–1813 (2010).

    Article  CAS  Google Scholar 

  47. Tsimring, L. S. Noise in biology. Rep. Prog. Phys. 77, 026601 (2014).

    Article  Google Scholar 

  48. Yamagata, A. et al. Overexpression, purification and characterization of RecJ protein from Thermus thermophilus HB8 and its core domain. Nucleic Acids Res. 29, 4617–4624 (2001).

    Article  CAS  Google Scholar 

  49. Holtze, C. et al. Biocompatible surfactants for water-in-fluorocarbon emulsions. Lab Chip 8, 1632–1639 (2008).

    Article  CAS  Google Scholar 

  50. Edelstein, A. D. et al. Advanced methods of microscope control using μManager software. J. Biol. Methods 1, e11 (2014).

    Article  Google Scholar 

Download references

Acknowledgements

This work was financially supported by the PHC Sakura program (project number 34171WG), implemented by the French Ministry of Foreign Affairs, the French Ministry Of Higher Education and Research and Japan Society for the Promotion of Science (JSPS), a Grant-in-Aid to Y.R. from the JSPS for Scientific Research on Innovative Areas ‘Synthetic Biology for Comprehension of Biomolecular Networks’ (project number 23119001), a l'Agence Nationale de la Recherche (ANR) Retour Postdoc grant (ANR-13-PDOC-0001) and a JSPS postdoctoral fellowship to A.J.G., and a PhD fellowship from Region Alsace to J.F.B. We thank H. Fujita and M. C. Tarhan for the loan of a microfluidic pump, A. Zadorin for discussions about the theory of bifurcations, K. Hasatani for preliminary work, E. Winfree for detailed comments on the manuscript and A. Estevez-Torres and Y. Tauran for expressing and purifying the exonuclease.

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Contributions

A.J.G. designed the study, performed experiments, analysed the data and wrote the manuscript. A.B. performed experiments, improved the droplet chambers and contributed to experimental design and writing of the manuscript. R.S. developed the microfluidic platform. N.A.K. and N.B. designed, performed and analysed the fitting process. J.F.B. and V.T. synthesized the surfactant. V.T. and T.F. provided support with the droplet-based microfluidic platform. Y.R. conceived, designed and supervised the study, analysed data and wrote the manuscript. All the authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Y. Rondelez.

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Genot, A., Baccouche, A., Sieskind, R. et al. High-resolution mapping of bifurcations in nonlinear biochemical circuits. Nature Chem 8, 760–767 (2016). https://doi.org/10.1038/nchem.2544

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