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.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
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
Davidson, E. H. et al. A genomic regulatory network for development. Science 295, 1669–1678 (2002).
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).
Oppenheim, A. B., Kobiler, O., Stavans, J., Court, D. L. & Adhya, S. Switches in bacteriophage lambda development. Annu. Rev. Genet. 39, 409–429 (2005).
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).
Strmecki, L., Greene, D. M. & Pears, C. J. Developmental decisions in Dictyostelium discoideum. Dev. Biol. 284, 25–36 (2005).
Alon, U. Network motifs: theory and experimental approaches. Nat. Rev. Genet. 8, 450–461 (2007).
Peter, I. S. & Davidson, E. H. Assessing regulatory information in developmental gene regulatory networks. Proc. Natl Acad. Sci. USA 114, 5862 (2017).
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).
Weitz, M. et al. Diversity in the dynamical behaviour of a compartmentalized programmable biochemical oscillator. Nat. Chem. 6, 295–302 (2014).
Ackermann, J., Wlotzka, B. & McCaskill, J. S. In vitro DNA-based predator–prey system with oscillatory kinetics. Bull. Math. Biol. 60, 329–354 (1998).
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).
Semenov, S. N. et al. Rational design of functional and tunable oscillating enzymatic networks. Nat. Chem. 7, 160–165 (2015).
Niederholtmeyer, H. et al. Rapid cell-free forward engineering of novel genetic ring oscillators. eLife 4, e09771 (2015).
Kim, J. & Winfree, E. Synthetic in vitro transcriptional oscillators. Mol. Syst. Biol. 7, 465 (2011).
Montagne, K., Gines, G., Fujii, T. & Rondelez, Y. Boosting functionality of synthetic DNA circuits with tailored deactivation. Nat. Commun. 7, 13474 (2016).
Padirac, A., Fujii, T. & Rondelez, Y. Bottom-up construction of in vitro switchable memories. Proc. Natl Acad. Sci. USA 109, E3212–E3220 (2012).
Subsoontorn, P., Kim, J. & Winfree, E. Ensemble bayesian analysis of bistability in a synthetic transcriptional switch. ACS Synth. Biol. 1, 299–316 (2012).
Genot, A. J. et al. High-resolution mapping of bifurcations in nonlinear biochemical circuits. Nat. Chem. 8, 760–767 (2016).
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).
Kim, J., White, K. S. & Winfree, E. Construction of an in vitro bistable circuit from synthetic transcriptional switches. Mol. Syst. Biol. 2, 68 (2006).
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).
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).
Srinivas, N., Parkin, J., Seelig, G., Winfree, E. & Soloveichik, D. Enzyme-free nucleic acid dynamical systems. Science 358, eaal2052 (2017).
Semenov, S. N. et al. Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions. Nature 537, 656–660 (2016).
Kar, S. & Ellington, A. D. In vitro transcription networks based on hairpin promoter switches. ACS Synth. Biol. 7, 1937–1945 (2018).
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).
Orbán, M., Kurin-Csörgei, K. & Epstein, I. R. pH-Regulated chemical oscillators. Acc. Chem. Res. 48, 593–601 (2015).
Whitesides, G. M. & Grzybowski, B. Self-assembly at all scales. Science 295, 2418–2421 (2002).
Mattia, E. & Otto, S. Supramolecular systems chemistry. Nat. Nanotechnol. 10, 111–119 (2015).
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).
van Esch, J. H., Klajn, R. & Otto, S. Chemical systems out of equilibrium. Chem. Soc. Rev. 46, 5474–5475 (2017).
Whitesides, G. M. Reinventing chemistry. Angew. Chem. Int. Ed. 54, 3196–3209 (2015).
Lehn, J.-M. Perspectives in chemistry—steps towards complex matter. Angew. Chem. Int. Ed. 52, 2836–2850 (2013).
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).
Zadorin, A. S. et al. Synthesis and materialization of a reaction–diffusion French flag pattern. Nat. Chem. 9, 990–996 (2017).
Green, L. N. et al. Autonomous dynamic control of DNA nanostructure self-assembly. Nat. Chem. 11, 510–520 (2019).
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).
Meijer, L. H. H. et al. Hierarchical control of enzymatic actuators using DNA-based switchable memories. Nat. Commun. 8, 1117 (2017).
Franco, E. et al. Timing molecular motion and production with a synthetic transcriptional clock. Proc. Natl Acad. Sci. USA 108, E784–E793 (2011).
Gines, G. et al. Microscopic agents programmed by DNA circuits. Nat. Nanotechnol. 12, 351–359 (2017).
Karzbrun, E., Tayar, A. M., Noireaux, V. & Bar-Ziv, R. H. Programmable on-chip DNA compartments as artificial cells. Science 345, 829–832 (2014).
Dupin, A. & Simmel, F. C. Signalling and differentiation in emulsion-based multi-compartmentalized in vitro gene circuits. Nat. Chem. 11, 32–39 (2019).
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).
Kim, J., Hopfield, J. & Winfree, E. in Advances in Neural Information Processing Systems (eds Saul, L. K. et al.) 681–688 (MIT Press, 2005).
McAllister, W. T. in Mechanisms of Transcription Vol. 11 (eds Eckstein, F. & Lilley, D. M. J.) 15–25 (Springer Berlin, 1997).
Maslak, M. & Martin, C. T. Kinetic analysis of T7 RNA polymerase transcription initiation from promoters containing single-stranded regions. Biochemistry 32, 4281–4285 (1993).
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).
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).
Jasinski, D., Haque, F., Binzel, D. W. & Guo, P. Advancement of the emerging field of RNA nanotechnology. ACS Nano 11, 1142–1164 (2017).
Famulok, M., Hartig, J. S. & Mayer, G. Functional aptamers and aptazymes in biotechnology, diagnostics, and therapy. Chem. Rev. 107, 3715–3743 (2007).
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).
Arnold, S. et al. Kinetic modeling and simulation of in vitro transcription by phage T7 RNA polymerase. Biotechnol. Bioeng. 72, 548–561 (2001).
Kern, J. A. & Davis, R. H. Application of solution equilibrium analysis to in vitro RNA transcription. Biotechnol. Prog. 13, 747–756 (1997).
Niederholtmeyer, H., Stepanova, V. & Maerkl, S. J. Implementation of cell-free biological networks at steady state. Proc. Natl Acad. Sci. USA 110, 15985 (2013).
Zadeh, J. N. et al. NUPACK: analysis and design of nucleic acid systems. J. Comput. Chem. 32, 170–173 (2011).
Cherry, K. M. & Qian, L. Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks. Nature 559, 370–376 (2018).
Kotani, S. & Hughes, W. L. Multi-arm junctions for dynamic DNA nanotechnology. J. Am. Chem. Soc. 139, 6363–6368 (2017).
Groves, B. et al. Computing in mammalian cells with nucleic acid strand exchange. Nat. Nanotechnol. 11, 287–294 (2016).
Del Vecchio, D., Ninfa, A. J. & Sontag, E. D. Modular cell biology: retroactivity and insulation. Mol. Syst. Biol. 4, 161 (2008).
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).
Pelechano, V. & Steinmetz, L. M. Gene regulation by antisense transcription. Nat. Rev. Genet. 14, 880–893 (2013).
Mangan, S. & Alon, U. Structure and function of the feed-forward loop network motif. Proc. Natl Acad. Sci. USA 100, 11980–11985 (2003).
Lin, D. C., Yurke, B. & Langrana, N. A. Inducing reversible stiffness changes in DNA-crosslinked gels. J. Mater. Res. 20, 1456–1464 (2005).
Fern, J. & Schulman, R. Modular DNA strand-displacement controllers for directing material expansion. Nat. Commun. 9, 3766 (2018).
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).
Pfeiffer, F. & Mayer, G. Selection and biosensor application of aptamers for small molecules. Front. Chem. 4, 25 (2016).
Zhang, D. Y. & Seelig, G. Dynamic DNA nanotechnology using strand-displacement reactions. Nat. Chem. 3, 103–113 (2011).
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).
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).
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).
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).
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.
Author information
Authors and Affiliations
Contributions
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.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
About this article
Cite this article
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
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41557-019-0292-z
This article is cited by
-
Synthetic molecular switches driven by DNA-modifying enzymes
Nature Communications (2024)
-
Circular single-stranded DNA as a programmable vector for gene regulation in cell-free protein expression systems
Nature Communications (2024)
-
DNA-empowered synthetic cells as minimalistic life forms
Nature Reviews Chemistry (2024)
-
DNA as a universal chemical substrate for computing and data storage
Nature Reviews Chemistry (2024)
-
Distinguishing genelet circuit input pulses via a pulse detector
Natural Computing (2024)