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Building in vitro transcriptional regulatory networks by successively integrating multiple functional circuit modules

Abstract

The regulation of cellular dynamics and responses to stimuli by genetic regulatory networks suggests how in vitro chemical reaction networks might analogously direct the dynamics of synthetic materials or chemistries. A key step in developing genetic regulatory network analogues capable of this type of sophisticated regulation is the integration of multiple coordinated functions within a single network. Here, we demonstrate how such functional integration can be achieved using in vitro transcriptional genelet circuits that emulate essential features of cellular genetic regulatory networks. By successively incorporating functional genelet modules into a bistable circuit, we construct an integrated regulatory network that dynamically changes its state in response to upstream stimuli and coordinates the timing of downstream signal expression. We use quantitative models to guide module integration and develop strategies to mitigate undesired interactions between network components that arise as the size of the network increases. This approach could enable the construction of in vitro networks capable of multifaceted chemical and material regulation.

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Fig. 1: Genelets and a switchable bistable network.
Fig. 2: Inducer RNAs switch the state of the bistable network.
Fig. 3: Upstream nodes that produce inducer RNAs switch the state of the iBN.
Fig. 4: Connecting the iBN-uA to downstream nodes enables switching between the production of different downstream RNA signals.
Fig. 5: A fan-out feed-forward architecture enables mutually exclusive downstream signal expression states.

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Data availability

The data that support the findings of this study are available from the corresponding authors on reasonable request.

Code availability

The MATLAB code that was used in the Supplementary Information to conduct the simulations presented in this study is available from the corresponding authors on reasonable request.

References

  1. Davidson, E. H. et al. A genomic regulatory network for development. Science 295, 1669–1678 (2002).

    Article  CAS  PubMed  Google Scholar 

  2. Revilla-i-Domingo, R., Oliveri, P. & Davidson, E. H. A missing link in the sea urchin embryo gene regulatory network: hesC and the double-negative specification of micromeres. Proc. Natl Acad. Sci. USA 104, 12383–12388 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Oppenheim, A. B., Kobiler, O., Stavans, J., Court, D. L. & Adhya, S. Switches in bacteriophage lambda development. Annu. Rev. Genet. 39, 409–429 (2005).

    Article  CAS  PubMed  Google Scholar 

  4. Schultz, D., Wolynes, P. G., Jacob, E. B. & Onuchic, J. N. Deciding fate in adverse times: sporulation and competence in Bacillus subtilis. Proc. Natl Acad. Sci. USA 106, 21027–21034 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Strmecki, L., Greene, D. M. & Pears, C. J. Developmental decisions in Dictyostelium discoideum. Dev. Biol. 284, 25–36 (2005).

    Article  CAS  PubMed  Google Scholar 

  6. Alon, U. Network motifs: theory and experimental approaches. Nat. Rev. Genet. 8, 450–461 (2007).

    Article  CAS  PubMed  Google Scholar 

  7. Peter, I. S. & Davidson, E. H. Assessing regulatory information in developmental gene regulatory networks. Proc. Natl Acad. Sci. USA 114, 5862 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tyson, J. J., Chen, K. C. & Novak, B. Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. Curr. Opin. Cell Biol. 15, 221–231 (2003).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  10. Ackermann, J., Wlotzka, B. & McCaskill, J. S. In vitro DNA-based predator–prey system with oscillatory kinetics. Bull. Math. Biol. 60, 329–354 (1998).

    Article  CAS  Google Scholar 

  11. Montagne, K., Plasson, R., Sakai, Y., Fujii, T. & Rondelez, Y. Programming an in vitro DNA oscillator using a molecular networking strategy. Mol. Syst. Biol. 7, 466 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Semenov, S. N. et al. Rational design of functional and tunable oscillating enzymatic networks. Nat. Chem. 7, 160–165 (2015).

    Article  CAS  PubMed  Google Scholar 

  13. Niederholtmeyer, H. et al. Rapid cell-free forward engineering of novel genetic ring oscillators. eLife 4, e09771 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  15. Montagne, K., Gines, G., Fujii, T. & Rondelez, Y. Boosting functionality of synthetic DNA circuits with tailored deactivation. Nat. Commun. 7, 13474 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. 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  PubMed  PubMed Central  Google Scholar 

  17. Subsoontorn, P., Kim, J. & Winfree, E. Ensemble bayesian analysis of bistability in a synthetic transcriptional switch. ACS Synth. Biol. 1, 299–316 (2012).

    Article  CAS  PubMed  Google Scholar 

  18. Genot, A. J. et al. High-resolution mapping of bifurcations in nonlinear biochemical circuits. Nat. Chem. 8, 760–767 (2016).

    Article  Google Scholar 

  19. Postma, S. G. J., te Brinke, D., Vialshin, I. N., Wong, A. S. Y. & Huck, W. T. S. A trypsin-based bistable switch. Tetrahedron 73, 4896–4900 (2017).

    Article  CAS  Google Scholar 

  20. 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  PubMed  PubMed Central  Google Scholar 

  21. Kim, J., Khetarpal, I., Sen, S. & Murray, R. M. Synthetic circuit for exact adaptation and fold-change detection. Nucleic Acids Res. 42, 6078–6089 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Helwig, B., van Sluijs, B., Pogodaev, A. A., Postma, S. G. J. & Huck, W. T. S. Bottom-up construction of an adaptive enzymatic reaction network. Angew. Chem. Int. Ed. 57, 14065–14069 (2018).

    Article  CAS  Google Scholar 

  23. Srinivas, N., Parkin, J., Seelig, G., Winfree, E. & Soloveichik, D. Enzyme-free nucleic acid dynamical systems. Science 358, eaal2052 (2017).

    Article  PubMed  Google Scholar 

  24. Semenov, S. N. et al. Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions. Nature 537, 656–660 (2016).

    Article  CAS  PubMed  Google Scholar 

  25. Kar, S. & Ellington, A. D. In vitro transcription networks based on hairpin promoter switches. ACS Synth. Biol. 7, 1937–1945 (2018).

    Article  CAS  PubMed  Google Scholar 

  26. Kishi, J. Y., Schaus, T. E., Gopalkrishnan, N., Xuan, F. & Yin, P. Programmable autonomous synthesis of single-stranded. DNA. Nat. Chem. 10, 155–164 (2017).

    Article  PubMed  Google Scholar 

  27. Orbán, M., Kurin-Csörgei, K. & Epstein, I. R. pH-Regulated chemical oscillators. Acc. Chem. Res. 48, 593–601 (2015).

    Article  PubMed  Google Scholar 

  28. Whitesides, G. M. & Grzybowski, B. Self-assembly at all scales. Science 295, 2418–2421 (2002).

    Article  CAS  PubMed  Google Scholar 

  29. Mattia, E. & Otto, S. Supramolecular systems chemistry. Nat. Nanotechnol. 10, 111–119 (2015).

    Article  CAS  PubMed  Google Scholar 

  30. van Roekel, H. W. H. et al. Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach. Chem. Soc. Rev. 44, 7465–7483 (2015).

    Article  PubMed  Google Scholar 

  31. van Esch, J. H., Klajn, R. & Otto, S. Chemical systems out of equilibrium. Chem. Soc. Rev. 46, 5474–5475 (2017).

    Article  PubMed  Google Scholar 

  32. Whitesides, G. M. Reinventing chemistry. Angew. Chem. Int. Ed. 54, 3196–3209 (2015).

    Article  CAS  Google Scholar 

  33. Lehn, J.-M. Perspectives in chemistry—steps towards complex matter. Angew. Chem. Int. Ed. 52, 2836–2850 (2013).

    Article  CAS  Google Scholar 

  34. Garamella, J., Marshall, R., Rustad, M. & Noireaux, V. The all E. coli TX-TL toolbox 2.0: a platform for cell-free synthetic biology. ACS Synth. Biol. 5, 344–355 (2016).

    Article  CAS  PubMed  Google Scholar 

  35. Zadorin, A. S. et al. Synthesis and materialization of a reaction–diffusion French flag pattern. Nat. Chem. 9, 990–996 (2017).

    Article  PubMed  Google Scholar 

  36. Green, L. N. et al. Autonomous dynamic control of DNA nanostructure self-assembly. Nat. Chem. 11, 510–520 (2019).

    Article  CAS  PubMed  Google Scholar 

  37. Postma, S. G. J., Vialshin, I. N., Gerritsen, C. Y., Bao, M. & Huck, W. T. S. Preprogramming complex hydrogel responses using enzymatic reaction networks. Angew. Chem. Int. Ed. 56, 1794–1798 (2017).

    Article  CAS  Google Scholar 

  38. Meijer, L. H. H. et al. Hierarchical control of enzymatic actuators using DNA-based switchable memories. Nat. Commun. 8, 1117 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  39. 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  PubMed  PubMed Central  Google Scholar 

  40. Gines, G. et al. Microscopic agents programmed by DNA circuits. Nat. Nanotechnol. 12, 351–359 (2017).

    Article  PubMed  Google Scholar 

  41. Karzbrun, E., Tayar, A. M., Noireaux, V. & Bar-Ziv, R. H. Programmable on-chip DNA compartments as artificial cells. Science 345, 829–832 (2014).

    Article  Google Scholar 

  42. Dupin, A. & Simmel, F. C. Signalling and differentiation in emulsion-based multi-compartmentalized in vitro gene circuits. Nat. Chem. 11, 32–39 (2019).

    Article  CAS  PubMed  Google Scholar 

  43. Franco, E., Giordano, G., Forsberg, P.-O. & Murray, R. M. Negative autoregulation matches production and demand in synthetic transcriptional networks. ACS Synth. Biol. 3, 589–599 (2014).

    Article  CAS  PubMed  Google Scholar 

  44. Kim, J., Hopfield, J. & Winfree, E. in Advances in Neural Information Processing Systems (eds Saul, L. K. et al.) 681–688 (MIT Press, 2005).

  45. McAllister, W. T. in Mechanisms of Transcription Vol. 11 (eds Eckstein, F. & Lilley, D. M. J.) 15–25 (Springer Berlin, 1997).

  46. Maslak, M. & Martin, C. T. Kinetic analysis of T7 RNA polymerase transcription initiation from promoters containing single-stranded regions. Biochemistry 32, 4281–4285 (1993).

    Article  CAS  PubMed  Google Scholar 

  47. Osumi-Davis, P. A. et al. Bacteriophage T7 RNA polymerase and its active-site mutants: kinetic, spectroscopic and calorimetric characterization. J. Mol. Biol. 237, 5–19 (1994).

    Article  CAS  PubMed  Google Scholar 

  48. Takinoue, M., Kiga, D., Shohda, K. & Suyama, A. Experiments and simulation models of a basic computation element of an autonomous molecular computing system. Phys. Rev. E 78, 041921 (2008).

    Article  Google Scholar 

  49. Jasinski, D., Haque, F., Binzel, D. W. & Guo, P. Advancement of the emerging field of RNA nanotechnology. ACS Nano 11, 1142–1164 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Famulok, M., Hartig, J. S. & Mayer, G. Functional aptamers and aptazymes in biotechnology, diagnostics, and therapy. Chem. Rev. 107, 3715–3743 (2007).

    Article  CAS  PubMed  Google Scholar 

  51. Milligan, J. F., Groebe, D. R., Witherell, G. W. & Uhlenbeck, O. C. Oligoribonucleotide synthesis using T7 RNA polymerase and synthetic DNA templates. Nucleic Acids Res. 15, 8783–8798 (1987).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Arnold, S. et al. Kinetic modeling and simulation of in vitro transcription by phage T7 RNA polymerase. Biotechnol. Bioeng. 72, 548–561 (2001).

    Article  CAS  PubMed  Google Scholar 

  53. Kern, J. A. & Davis, R. H. Application of solution equilibrium analysis to in vitro RNA transcription. Biotechnol. Prog. 13, 747–756 (1997).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Zadeh, J. N. et al. NUPACK: analysis and design of nucleic acid systems. J. Comput. Chem. 32, 170–173 (2011).

    Article  CAS  PubMed  Google Scholar 

  56. Cherry, K. M. & Qian, L. Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks. Nature 559, 370–376 (2018).

    Article  CAS  PubMed  Google Scholar 

  57. Kotani, S. & Hughes, W. L. Multi-arm junctions for dynamic DNA nanotechnology. J. Am. Chem. Soc. 139, 6363–6368 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Groves, B. et al. Computing in mammalian cells with nucleic acid strand exchange. Nat. Nanotechnol. 11, 287–294 (2016).

    Article  CAS  PubMed  Google Scholar 

  59. Del Vecchio, D., Ninfa, A. J. & Sontag, E. D. Modular cell biology: retroactivity and insulation. Mol. Syst. Biol. 4, 161 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Franco, E., Del Vecchio, D. & Murray, R. M. Design of insulating devices for in vitro synthetic circuits. In Proc. 48th IEEE Conference on Decision and Control (CDC) Held Jointly with 2009 28th Chinese Control Conference 4584–4589 (IEEE, 2009).

  61. Pelechano, V. & Steinmetz, L. M. Gene regulation by antisense transcription. Nat. Rev. Genet. 14, 880–893 (2013).

    Article  Google Scholar 

  62. Mangan, S. & Alon, U. Structure and function of the feed-forward loop network motif. Proc. Natl Acad. Sci. USA 100, 11980–11985 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Lin, D. C., Yurke, B. & Langrana, N. A. Inducing reversible stiffness changes in DNA-crosslinked gels. J. Mater. Res. 20, 1456–1464 (2005).

    Article  CAS  Google Scholar 

  64. Fern, J. & Schulman, R. Modular DNA strand-displacement controllers for directing material expansion. Nat. Commun. 9, 3766 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Rogers, W. B., Shih, W. M. & Manoharan, V. N. Using DNA to program the self-assembly of colloidal nanoparticles and microparticles. Nat. Rev. Mater. 1, 16008 (2016).

    Article  CAS  Google Scholar 

  66. Pfeiffer, F. & Mayer, G. Selection and biosensor application of aptamers for small molecules. Front. Chem. 4, 25 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Zhang, D. Y. & Seelig, G. Dynamic DNA nanotechnology using strand-displacement reactions. Nat. Chem. 3, 103–113 (2011).

    Article  CAS  PubMed  Google Scholar 

  68. O’Reilly, R. K., Turberfield, A. J. & Wilks, T. R. The evolution of DNA-templated synthesis as a tool for materials discovery. Acc. Chem. Res. 50, 2496–2509 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Cunningham, P. & Ofengand, J. Use of inorganic pyrophosphatase to improve the yield of in vitro transcription reactions catalyzed by T7 RNA polymerase. BioTechniques 9, 713–714 (1990).

    CAS  PubMed  Google Scholar 

  70. Schwarz-Schilling, M. et al. in Cell Cycle Oscillators: Methods and Protocols Vol. 1342 (eds. Coutts, A. S. & Weston, L.) 185–199 (Springer New York, 2016).

  71. Filonov, G. S., Moon, J. D., Svensen, N. & Jaffrey, S. R. Broccoli: rapid selection of an RNA mimic of green fluorescent protein by fluorescence-based selection and directed evolution. J. Am. Chem. Soc. 136, 16299–16308 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors would like to thank E. Franco, L. Green, H. Subramanian and C. C. Samaniego for their help with the initial genelet experiments, and J. Fern for insightful conversations. S.S. was supported by National Science Foundation Graduate Research Fellowship DGE-1746891. Materials, supplies and R.S. were supported by the Department of Energy BES DE-SC001 0426.

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S.W.S. conceived and designed the study, designed and performed the experiments, analysed and interpreted the data, and wrote the manuscript. R.S. conceived and supervised the study, interpreted the data and wrote the manuscript.

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Correspondence to Samuel W. Schaffter or Rebecca Schulman.

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Schaffter, S.W., Schulman, R. Building in vitro transcriptional regulatory networks by successively integrating multiple functional circuit modules. Nat. Chem. 11, 829–838 (2019). https://doi.org/10.1038/s41557-019-0292-z

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