Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Design of multi-phase dynamic chemical networks

Abstract

Template-directed polymerization reactions enable the accurate storage and processing of nature's biopolymer information. This mutualistic relationship of nucleic acids and proteins, a network known as life's central dogma, is now marvellously complex, and the progressive steps necessary for creating the initial sequence and chain-length-specific polymer templates are lost to time. Here we design and construct dynamic polymerization networks that exploit metastable prion cross-β phases. Mixed-phase environments have been used for constructing synthetic polymers, but these dynamic phases emerge naturally from the growing peptide oligomers and create environments suitable both to nucleate assembly and select for ordered templates. The resulting templates direct the amplification of a phase containing only chain-length-specific peptide-like oligomers. Such multi-phase biopolymer dynamics reveal pathways for the emergence, self-selection and amplification of chain-length- and possibly sequence-specific biopolymers.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Dynamic peptide network analyses.
Figure 2: NF-CHO dynamic peptide network.
Figure 3: NFF-CHO dynamic peptide network.
Figure 4: Cross-seeding the NFF-CHO network.

Similar content being viewed by others

References

  1. Rodriguez-Navarro, C., Kudlacz, K., Cizer, O. & Ruiz-Agudo, E. Formation of amorphous calcium carbonate and its transformation into mesostructured calcite. CrystEngComm 17, 58–72 (2015).

    Article  CAS  Google Scholar 

  2. Wallace, A. F. et al. Microscopic evidence for liquid-liquid separation in supersaturated CaCO3 solutions. Science 341, 885–889 (2013).

    Article  CAS  PubMed  Google Scholar 

  3. Auer, S., Ricchiuto, P. & Kashchiev, D. Two-step nucleation of amyloid fibrils: omnipresent or not? J. Mol. Biol. 422, 723–730 (2012).

    Article  CAS  PubMed  Google Scholar 

  4. Erdemir, D., Lee, A. Y. & Myerson, A. S. Nucleation of crystals from solution: classical and two-step models. Acc. Chem. Res. 42, 621–629 (2009).

    Article  CAS  PubMed  Google Scholar 

  5. Pulawski, W., Ghoshdastider, U., Andrisano, V. & Filipek, S. Ubiquitous amyloids. Appl. Biochem. Biotechnol. 166, 1626–1643 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Stephan Joseph, S. et al. The CPEB3 protein is a functional prion that interacts with the actin cytoskeleton. Cell Rep. 11, 1772–1785 (2015).

    Article  CAS  PubMed  Google Scholar 

  7. Jucker, M. & Walker, L. C. Self-propagation of pathogenic protein aggregates in neurodegenerative diseases. Nature 501, 45–51 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sanders, D. W., Kaufman, S. K., Holmes, B. B. & Diamond, M. I. Prions and protein assemblies that convey biological information in health and disease. Neuron 89, 433–448 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Tjernberg, L. O. et al. Arrest of β-amyloid fibril formation by a pentapeptide ligand. J. Biol. Chem. 271, 8545–8548 (1996).

    Article  CAS  PubMed  Google Scholar 

  10. Xue, W.-F., Homans, S. W. & Radford, S. E. Systematic analysis of nucleation-dependent polymerization reveals new insights into the mechanism of amyloid self-assembly. Proc. Natl Acad. Sci. USA 105, 8926–8931 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Smith, J. E. et al. Defining the dynamic conformational networks of cross-β peptide assembly. Isr. J. Chem. 55, 763–769 (2015).

    Article  CAS  Google Scholar 

  12. Liang, C. et al. Kinetic intermediates in amyloid assembly. J. Am. Chem. Soc. 136, 15146–15149 (2014).

    Article  CAS  PubMed  Google Scholar 

  13. Hansen, F. K. & Ugelstad, J. Particle nucleation in emulsion polymerization. I. A theory for homogeneous nucleation. J. Polym. Sci. Polym. Chem. Ed. 16, 1953–1979 (1978).

    Article  CAS  Google Scholar 

  14. Nomura, M., Tobita, H. & Suzuki, K. in Polymer Particles Advances in Polymer Science (ed. Okubo, M.) 1–128 (Springer, 2005).

    Book  Google Scholar 

  15. Derkatch, I. L., Bradley, M. E., Hong, J. Y. & Liebman, S. W. Prions affect the appearance of other prions: the story of [PIN+]. Cell 106, 171–182 (2001).

    Article  CAS  PubMed  Google Scholar 

  16. Mehta, A. K. et al. Facial symmetry in protein self-assembly. J. Am. Chem. Soc. 130, 9829–9835 (2008).

    Article  CAS  PubMed  Google Scholar 

  17. Eichner, T. & Radford, S. E. A diversity of assembly mechanisms of a generic amyloid fold. Mol. Cell. 43, 8–18 (2011).

    Article  CAS  PubMed  Google Scholar 

  18. Childers, W. S., Anthony, N. R., Mehta, A. K., Berland, K. M. & Lynn, D. G. Phase networks of cross-β peptide assemblies. Langmuir 28, 6386–6395 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Rubinov, B. et al. Transient fibril structures facilitating nonenzymatic self-replication. ACS Nano 5, 7893–7901 (2012).

    Article  CAS  Google Scholar 

  20. Goodwin, J. T. & Lynn, D. G. Template-directed synthesis: use of a reversible reaction. J. Am. Chem. Soc. 114, 9197–9198 (1992).

    Article  CAS  Google Scholar 

  21. Li, X., Zhan, Z. Y., Knipe, R. & Lynn, D. G. DNA-catalyzed polymerization. J. Am. Chem. Soc. 124, 746–747 (2002).

    Article  CAS  PubMed  Google Scholar 

  22. Li, X. Y., Hernandez, A. F., Grover, M. A., Hud, N. V. & Lynn, D. G. Step-growth control in template-directed polymerization. Heterocycles 82, 1477–1488 (2011).

    CAS  Google Scholar 

  23. Green, D. G., Liu, J. & Abbass, H. Dual Phase Evolution 1st edn (Springer, 2014).

    Book  Google Scholar 

  24. Frederix, P. W. J. M., Ulijn, R. V., Hunt, N. T. & Tuttle, T. Virtual screening for dipeptide aggregation: toward predictive tools for peptide self-assembly. J. Phys. Chem. Lett. 2, 2380–2384 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Fife, T. H. & Jao, L. K. General acid catalysis of acetal hydrolysis. The hydrolysis of 2-aryloxytetrahydropyrans. J. Am. Chem. Soc. 90, 4081–4085 (1968).

    Article  CAS  Google Scholar 

  26. Giuseppone, N. & Lehn, J.-M. Protonic and temperature modulation of constituent expression by component selection in a dynamic combinatorial library of imines. Chem. Eur. J. 12, 1715–1722 (2006).

    Article  CAS  PubMed  Google Scholar 

  27. Gilbert, R. G. Emulsion Polymerization: A Mechanistic Approach (Academic, 1995).

    Google Scholar 

  28. Krebs, M. R. H., Bromley, E. H. C. & Donald, A. M. The binding of thioflavin-T to amyloid fibrils: localisation and implications. J. Struct. Biol. 149, 30–37 (2005).

    Article  CAS  PubMed  Google Scholar 

  29. Hamilton-Brown, P., Bekard, I., Ducker, W. A. & Dunstan, D. E. How does shear affect Aβ fibrillogenesis? J. Phys. Chem. B. 112, 16249–16252 (2008).

    Article  CAS  PubMed  Google Scholar 

  30. Peters, R. in Xenopus Protocols: Cell Biology and Signal Transduction (ed. Johné Liu, X.) 235–258 (Humana, 2006).

    Book  Google Scholar 

  31. Hilbich, C., Kisters-Woike, B., Reed, J., Masters, C. L. & Beyreuther, K. Substitutions of hydrophobic amino acids reduce the amyloidogenicity of Alzheimer's disease βA4 peptides. J. Mol. Biol. 228, 460–473 (1992).

    Article  CAS  PubMed  Google Scholar 

  32. Wood, S. J., Wetzel, R., Martin, J. D. & Hurle, M. R. Prolines and aamyloidogenicity in fragments of the Alzheimer's peptide b/A4. Biochemistry 34, 724–730 (1995).

    Article  CAS  PubMed  Google Scholar 

  33. Williams, A. D. et al. Mapping Aβ amyloid fibril secondary structure using scanning proline mutagenesis. J. Mol. Biol. 335, 833–842 (2004).

    Article  CAS  PubMed  Google Scholar 

  34. Childers, W. S., Mehta, A. K., Ni, R., Taylor, J. V. & Lynn, D. G. Peptides organized as bilayer membranes. Angew. Chem. Int. Ed. 49, 4104–4107 (2010).

    Article  CAS  Google Scholar 

  35. Li, S. et al. Design of asymmetric peptide bilayer membranes. J. Am. Chem. Soc. 138, 3579–3586 (2016).

    Article  CAS  PubMed  Google Scholar 

  36. Serio, T. R. et al. Nucleated conformational conversion and the replication of conformational information by a prion determinant. Science 289, 1317–1321 (2000).

    Article  CAS  PubMed  Google Scholar 

  37. Collinge, J. Prion strain mutation and selection. Science 328, 1111–1112 (2010).

    Article  CAS  PubMed  Google Scholar 

  38. Goodwin, J. T. et al. Alternative Chemistries of Life: Empirical Approaches (NASA, NSF, 2014).

    Google Scholar 

  39. Higgs, P. G. & Lehman, N. The RNA World: molecular cooperation at the origins of life. Nat. Rev. Genet. 16, 7–17 (2015).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  41. Leunissen, M. E. et al.. Ionic colloidal crystals of oppositely charged particles. Nature 437, 235–240 (2005).

    Article  CAS  PubMed  Google Scholar 

  42. Tagliazucchi, M., Weiss, E. A. & Szleifer, I. Dissipative self-assembly of particles interacting through time-oscillatory potentials. Proc. Natl Acad. Sci. USA 111, 9751–9756 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  Google Scholar 

  44. Carnall, J. M. A. et al.. Mechanosensitive self-replication driven by self-organization. Science 327, 1502–1506 (2010).

    Article  CAS  PubMed  Google Scholar 

  45. Wagner, N., Tannenbaum, E. & Ashkenasy, G. Second order catalytic quasispecies yields discontinuous mean fitness at error threshold. Phys. Rev. Lett. 104, 188101 (2010).

    Article  CAS  PubMed  Google Scholar 

  46. Rubinov, B., Wagner, N., Rapaport, H. & Ashkenasy, G. Self-replicating amphiphilic β-sheet peptides. Angew. Chem. Int. Ed. 48, 6683–6686 (2009).

    Article  CAS  Google Scholar 

  47. Cougnon, F. B. L. & Sanders, J. K. M. Evolution of dynamic combinatorial chemistry. Acc. Chem. Res. 45, 2211–2221 (2011).

    Article  CAS  PubMed  Google Scholar 

  48. Rowan, S. J., Cantrill, S. J., Cousins, G. R. L., Sanders, J. K. M. & Stoddart, J. F. Dynamic covalent chemistry. Angew. Chem. Int. Ed. 41, 898–952 (2002).

    Article  Google Scholar 

  49. Ruiz-Mirazo, K., Umerez, J. & Moreno, A. Enabling conditions for ‘open-ended evolution’. Biol. Philos. 23, 67–85 (2008).

    Article  Google Scholar 

  50. Goodman, J. Evidence for ecological learning and domain specificity in rational asset pricing and market efficiency. J. Socio. Econ. 48, 27–39 (2014).

    Article  Google Scholar 

  51. Cavaliere, M., Sedwards, S., Tarnita, C. E., Nowak, M. A. & Csikász-Nagy, A. Prosperity is associated with instability in dynamical networks. J. Theor. Biol. 299, 126–138 (2012).

    Article  PubMed  Google Scholar 

  52. Goodwin, J. T., Mehta, A. K. & Lynn, D. G. Digital and analog chemical evolution. Acc. Chem. Res. 45, 2189–2199 (2012).

    Article  CAS  PubMed  Google Scholar 

  53. Kapil, N., Singh, A. & Das, D. Cross-β amyloid nanohybrids loaded with cytochrome C exhibit superactivity in organic solvents. Angew. Chem. Int. Ed. 54, 6492–6495 (2015).

    Article  CAS  Google Scholar 

  54. Ivnitski, D. D. et al. Introducing charge transfer functionality into prebiotically relevant β-sheet peptide fibrils. Chem. Commun. 50, 6733–6736 (2014).

    Article  CAS  Google Scholar 

  55. Debnath, S., Roy, S. & Ulijn, R. V. Peptide nanofibers with dynamic instability through nonequilibrium biocatalytic assembly. J. Am. Chem. Soc. 135, 16789–16792 (2013).

    Article  CAS  PubMed  Google Scholar 

  56. Omosun, T. O. et al. Catalytic diversity in self-propagating peptide assemblies. Nat. Chem. http://dx.doi.org/10.1038/nchem.2738 (2017).

  57. Rodriguez-Navarro, A. B. XRD2DScan: new software for polycrystalline materials characterization using two-dimensional X-ray diffraction. J. Appl. Crystallogr. 39, 905–909 (2006).

    Article  CAS  Google Scholar 

  58. Mohamadi, F. et al.. Macromodel — an integrated software system for modeling organic and bioorganic molecules using molecular mechanics. J. Comput. Chem. 11, 440–467 (1990).

    Article  CAS  Google Scholar 

  59. Kaminski, G. A., Friesner, R. A., Tirado-Rives, J. & Jorgensen, W. L. Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J. Phys. Chem. B 105, 6474–6487 (2001).

    Article  CAS  Google Scholar 

  60. Polak, E. & Ribiere, G. PR conjugate gradient (PRCG) — best general method. Rev. Fr. Inform. Rech. O. 16, 35–43 (1969).

    Google Scholar 

  61. Bowers, K. J. et al. Scalable algorithms for molecular dynamics simulations on commodity clusters. In Proc. ACM/IEEE Conf. on Supercomputing (SC06) (2006).

    Google Scholar 

Download references

Acknowledgements

We are grateful to H. Yi and J. Taylor in the Emory Robert P. Apkarian Microscopy Core for TEM, the Emory Microscopy Core for fluorescence imaging, J. Bacsa in the Emory X-ray Crystallography Center for X-ray diffraction, F. Strobel in the Emory Mass Spectrometry Center for LC-MS, M. Zhou and F. Fernandez in the School of Chemistry and Biochemistry, Georgia Institute of Technology for IMS-MS, the NASA Astrobiology Program, under the NSF CCI, CHE-1004570 (CC, PT, MCH), the James S. McDonnell Foundation (J.T., M.C.H.), Emory University for supplies and personnel support, the US Department of Energy, Office of Science, Office of Basic Energy Sciences DE-FG02-02ER15377 for personnel support (C.C.) and equipment, and NSF CHE-1507932 for supplies, equipment, and structural characterization support.

Author information

Authors and Affiliations

Authors

Contributions

C.C., J.T., M.C.H, T.P, A.K.M., J.T.G, M.A.G and D.G.L. designed experiments, analysed data and wrote the paper.

Corresponding author

Correspondence to David G. Lynn.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary information

Supplementary information (PDF 2487 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, C., Tan, J., Hsieh, MC. et al. Design of multi-phase dynamic chemical networks. Nature Chem 9, 799–804 (2017). https://doi.org/10.1038/nchem.2737

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nchem.2737

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing