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DNA-based communication in populations of synthetic protocells


Developing molecular communication platforms based on orthogonal communication channels is a crucial step towards engineering artificial multicellular systems. Here, we present a general and scalable platform entitled ‘biomolecular implementation of protocellular communication’ (BIO-PC) to engineer distributed multichannel molecular communication between populations of non-lipid semipermeable microcapsules. Our method leverages the modularity and scalability of enzyme-free DNA strand-displacement circuits to develop protocellular consortia that can sense, process and respond to DNA-based messages. We engineer a rich variety of biochemical communication devices capable of cascaded amplification, bidirectional communication and distributed computational operations. Encapsulating DNA strand-displacement circuits further allows their use in concentrated serum where non-compartmentalized DNA circuits cannot operate. BIO-PC enables reliable execution of distributed DNA-based molecular programs in biologically relevant environments and opens new directions in DNA computing and minimal cell technology.

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Fig. 1: Design elements for BIO-PC.
Fig. 2: Signalling cascade between protocell populations using non-enzymatic DNA signal amplification.
Fig. 3: Three-layer amplified signalling cascade.
Fig. 4: Protocellular negative feedback loop.
Fig. 5: Compartmentalized DNA-based Boolean logic circuits.
Fig. 6: Compartmentalized DNA reaction networks in 50% FBS.

Data availability

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


  1. 1.

    Waters, C. M. & Bassler, B. L. Quorum sensing: cell-to-cell communication in bacteria. Annu. Rev. Cell Dev. Biol. 21, 319–346 (2005).

    CAS  Article  Google Scholar 

  2. 2.

    Doganer, B. A., Yan, L. K. & Youk, H. Autocrine signaling and quorum sensing: extreme ends of a common spectrum. Trends Cell Biol. 26, 262–271 (2016).

    Article  Google Scholar 

  3. 3.

    Barcena Menendez, D., Senthivel, V. R. & Isalan, M. Sender–receiver systems and applying information theory for quantitative synthetic biology. Curr. Opin. Biotechnol. 31, 101–107 (2015).

    CAS  Article  Google Scholar 

  4. 4.

    Hart, Y., Antebi, Y. E., Mayo, A. E., Friedman, N. & Alon, U. Design principles of cell circuits with paradoxical components. Proc. Natl Acad. Sci. USA 109, 8346–8351 (2012).

    CAS  Article  Google Scholar 

  5. 5.

    You, L., Cox, R. S. III, Weiss, R. & Arnold, F. H. Programmed population control by cell–cell communication and regulated killing. Nature 428, 868–871 (2004).

  6. 6.

    Basu, S., Gerchman, Y., Collins, C. H., Arnold, F. H. & Weiss, R. A synthetic multicellular system for programmed pattern formation. Nature 434, 1130–1134 (2005).

    CAS  Article  Google Scholar 

  7. 7.

    Tabor, J. J. et al. A synthetic genetic edge detection program. Cell 137, 1272–1281 (2009).

    Article  Google Scholar 

  8. 8.

    Ortiz, M. E. & Endy, D. Engineered cell–cell communication via DNA messaging. J. Biol. Eng. 6, 16 (2012).

    CAS  Article  Google Scholar 

  9. 9.

    Youk, H. & Lim, W. Secreting and sensing the same molecule allows cells to achieve versatile social behaviors. Science 343, 1242782 (2014).

    Article  Google Scholar 

  10. 10.

    Balagaddé et al. A synthetic Escherichia coli predator–prey ecosystem. Mol. Syst. Biol. 4, 187 (2008).

    Article  Google Scholar 

  11. 11.

    Bacchus, W. et al. Synthetic two-way communication between mammalian cells. Nat. Biotechnol. 30, 991–996 (2012).

    CAS  Article  Google Scholar 

  12. 12.

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

    CAS  Google Scholar 

  13. 13.

    Tamsir, A., Tabor, J. J. & Voigt, C. A. Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’. Nature 469, 212–215 (2011).

    CAS  Article  Google Scholar 

  14. 14.

    Regot et al. Distributed biological computation with multicellular engineered networks. Nature 469, 207–211 (2011).

    CAS  Article  Google Scholar 

  15. 15.

    Huang, S. et al. Coupling spatial segregation with synthetic circuits to control bacterial survival. Mol. Syst. Biol. 12, 859 (2016).

    Article  Google Scholar 

  16. 16.

    Cardinale, S. & Arkin, A. P. Contextualizing context for synthetic biology—identifying causes of failure of synthetic biological systems. Biotechnol. J. 7, 856–866 (2012).

    CAS  Article  Google Scholar 

  17. 17.

    Lentini, R., Yeh Martín, N. & Mansy, S. S. Communicating artificial cells. Curr. Opin. Chem. Biol. 34, 53–61 (2016).

    CAS  Article  Google Scholar 

  18. 18.

    Buddingh, B. & van Hest, J. C. M. Artificial cells: synthetic compartments with life-like functionality and adaptivity. Acc. Chem. Res. 50, 769–777 (2017).

    CAS  Article  Google Scholar 

  19. 19.

    Salehi-Reyhani, A., Ces, O. & Elani, Y. Artificial cell mimics as simplified models for the study of cell biology. Exp. Biol. Med. 242, 1309–1317 (2017).

    CAS  Article  Google Scholar 

  20. 20.

    Lim, W. A., Lee, C. M. & Tang, C. Design principles of regulatory networks: searching for the molecular algorithms of the cell. Mol. Cell 49, 202–212 (2013).

    CAS  Article  Google Scholar 

  21. 21.

    Points, L. J., Taylor, J. W., Grizou, J., Donkers, K. & Cronin, L. Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior. Proc. Natl Acad. Sci. USA 115, 885–890 (2018).

    CAS  Article  Google Scholar 

  22. 22.

    Adamala, K. P., Martin-Alarcon, D. A., Guthrie-Honea, K. R. & Boyden, E. S. Engineering genetic circuit interactions within and between synthetic minimal cells. Nat. Chem. 9, 431–439 (2017).

    CAS  Article  Google Scholar 

  23. 23.

    Qiao, Y., Li, M., Booth, R. & Mann, S. Predatory behaviour in synthetic protocell communities. Nat. Chem. 9, 110–119 (2016).

    Article  Google Scholar 

  24. 24.

    Tang, T.-Y. D. et al. Gene-mediated chemical communication in synthetic protocell communities. ACS Synth. Biol. 7, 339–346 (2018).

    CAS  Article  Google Scholar 

  25. 25.

    Sun, S. et al. Chemical signaling and functional activation in colloidosome-based protocells. Small 12, 1920–1927 (2016).

    CAS  Article  Google Scholar 

  26. 26.

    Huang, X. et al. Interfacial assembly of protein–polymer nano-conjugates into stimulus-responsive biomimetic protocells. Nat. Commun. 4, 2239 (2013).

    Article  Google Scholar 

  27. 27.

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

    CAS  Article  Google Scholar 

  28. 28.

    Yurke, B. et al. A DNA-fuelled molecular machine made of DNA. Nature 406, 605–608 (2000).

    CAS  Article  Google Scholar 

  29. 29.

    Seelig, G., Soloveichik, D., Zhang, D. Y. & Winfree, E. Enzyme-free nucleic acid logic circuits. Science 314, 1585–1588 (2006).

    CAS  Article  Google Scholar 

  30. 30.

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

    CAS  Article  Google Scholar 

  31. 31.

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

    CAS  Article  Google Scholar 

  32. 32.

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

    CAS  Article  Google Scholar 

  33. 33.

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

    Article  Google Scholar 

  34. 34.

    Frezza, B. M., Cockroft, S. L. & Ghadiri, M. R. Modular multi-level circuits from immobilized DNA-based logic gates. J. Am. Chem. Soc. 129, 14875–14879 (2007).

    CAS  Article  Google Scholar 

  35. 35.

    Yashin, R., Rudchenko, S. & Stojanovic, M. N. Networking particles over distance using oligonucleotide-based devices. J. Am. Chem. Soc. 129, 15581–15584 (2007).

    CAS  Article  Google Scholar 

  36. 36.

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

    CAS  Article  Google Scholar 

  37. 37.

    Zhang, D. Y. & Winfree, E. Control of DNA strand displacement kinetics using toehold exchange. J. Am. Chem. Soc. 131, 17303–17314 (2009).

    CAS  Article  Google Scholar 

  38. 38.

    Dunn, K. E., Trefzer, M. A., Johnson, S. & Tyrrell, A. M. Investigating the dynamics of surface-immobilized DNA nanomachines. Sci. Rep. 6, 29581 (2016).

    CAS  Article  Google Scholar 

  39. 39.

    Teichmann, M., Kopperger, E. & Simmel, F. C. Robustness of localized DNA strand displacement cascades. ACS Nano 8, 8487–8496 (2014).

    CAS  Article  Google Scholar 

  40. 40.

    Chatterjee, G., Dalchau, N., Muscat, R. A., Phillips, A. & Seelig, G. A spatially localized architecture for fast and modular DNA computing. Nat. Nanotechnol. 12, 920–927 (2017).

    CAS  Article  Google Scholar 

  41. 41.

    Zhang, D. Y., Turberfield, A. J., Yurke, B. & Winfree, E. Engineering entropy-driven reactions and networks catalyzed by DNA. Science 318, 1121–1125 (2007).

    CAS  Article  Google Scholar 

  42. 42.

    Lakin, M. R., Youssef, S., Polo, F., Emmott, S. & Phillips, A. Visual DSD: a design and analysis tool for DNA strand displacement systems. Bioinformatics 27, 3211–3213 (2011).

    CAS  Article  Google Scholar 

  43. 43.

    Chen, X., Briggs, N., McLain, J. R. & Ellington, A. D. Stacking nonenzymatic circuits for high signal gain. Proc. Natl Acad. Sci. USA 110, 5386–5391 (2013).

    CAS  Article  Google Scholar 

  44. 44.

    Freeman, M. Feedback control of intercellular signalling in development. Nature 408, 313–319 (2000).

    CAS  Article  Google Scholar 

  45. 45.

    Vertosick, F. T. & Kelly, R. H. Immune network theory: a role for parallel distributed processing? Immunology 66, 1–7 (1989).

    CAS  Google Scholar 

  46. 46.

    Chen, Y.-J., Groves, B., Muscat, R. A. & Seelig, G. DNA nanotechnology from the test tube to the cell. Nat. Nanotechnol. 10, 748–760 (2015).

    CAS  Article  Google Scholar 

  47. 47.

    Fern, J. & Schulman, R. Design and characterization of DNA strand-displacement circuits in serum-supplemented cell medium. ACS Synth. Biol. 6, 1774–1783 (2017).

    CAS  Article  Google Scholar 

  48. 48.

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

    CAS  Article  Google Scholar 

  49. 49.

    Lopez, R., Wang, R. & Seelig, G. A molecular multi-gene classifier for disease diagnostics. Nat. Chem. 10, 746–754 (2018).

    CAS  Article  Google Scholar 

  50. 50.

    Ugrinic, M. et al. Microfluidic formation of proteinosomes. Chem. Commun. 54, 287–290 (2018).

    CAS  Article  Google Scholar 

  51. 51.

    Liu, L. et al. Construction of biological hybrid microcapsules with defined permeability towards programmed release of biomacromolecules. Chem. Commun. 53, 11678–11681 (2017).

    CAS  Article  Google Scholar 

  52. 52.

    Fern, J. et al. DNA strand-displacement timer circuits. ACS Synth. Biol. 6, 190–193 (2017).

    CAS  Article  Google Scholar 

  53. 53.

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

    CAS  Article  Google Scholar 

  54. 54.

    Unger, M. A., Chou, H.-P., Thorsen, T., Scherer, A. & Quake, S. R. Monolithic microfabricated valves and pumps by multilayer soft lithography. Science 288, 113–116 (2000).

    CAS  Article  Google Scholar 

  55. 55.

    Padirac, A., Fujii, T. & Rondelez, Y. Quencher-free multiplexed monitoring of DNA reaction circuits. Nucleic Acids Res. 40, e118 (2012).

    CAS  Article  Google Scholar 

  56. 56.

    Dalchau, N., Seelig, G. & Phillips, A. Computational Design of Reaction–Diffusion Patterns Using DNA-Based Chemical Reaction Networks, Vol. 8727, 84–99 (Lecture Notes in Computer Science Series, Springer, 2014).

  57. 57.

    Lukacs, G. L. et al. Size-dependent DNA mobility in cytoplasm and nucleus. J. Biol. Chem. 275, 1625–1629 (2000).

    CAS  Article  Google Scholar 

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The authors thank G. Seelig, W. Mulder and L. Cronin for helpful discussions. This work was supported by the European Research Council (ERC project no. 677313 BioCircuit), the ERC Advanced Grant Scheme (EC-2016-ADG 740235) and a Marie Curie Individual Fellowship, an NWO-VIDI grant from the Netherlands Organisation for Scientific Research (NWO, 723.016.003), funding from the Ministry of Education, Culture and Science (Gravity programmes 024.001.035 and 024.003.013) and BrisSynBio (BB/L01386X/1).

Author information




A.J. designed the study, performed experiments, analysed the data and wrote the manuscript. S.Y., B.B. and P.P. performed experiments and analysed the data. A.v.d.L. and A.J. designed and fabricated the microfluidic chip. N.D. and A.P. performed computational experiments. B.V.V.S.P.K. and S.M. provided key reagents and provided critical input for the initial experiments. T.F.A.d.G. conceived, designed and supervised the study, analysed the data and wrote the manuscript. S.M. revised the manuscript. All authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Tom F. A. de Greef.

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The authors declare no competing interests.

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Journal peer review information Nature Nanotechnology thanks Friedrich Simmel and other anonymous reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary information

Supplementary Methods, Figures 1–14, Notes, Tables 1–6 and References.

Supplementary Video 1

Diffusion of a fluorescently labelled input DNA strand into protocells and activation of a fluorescent DNA gate complex.

Supplementary Video 2

Activation of the two-layer signalling cascade.

Supplementary Video 3

Negative feedback loop in two populations.

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Joesaar, A., Yang, S., Bögels, B. et al. DNA-based communication in populations of synthetic protocells. Nat. Nanotechnol. 14, 369–378 (2019).

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