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.

A hydrodynamic instability drives protein droplet formation on microtubules to nucleate branches

Abstract

Liquid–liquid phase separation1,2 occurs not only in bulk liquid, but also on surfaces. In physiology, the nature and function of condensates on cellular structures remain unexplored. Here we study how the condensed protein TPX2 behaves on microtubules to initiate branching microtubule nucleation3,4,5, which is critical for spindle assembly in eukaryotic cells6,7,8,9,10. Using fluorescence, electron and atomic force microscopies and hydrodynamic theory, we show that TPX2 on a microtubule reorganizes according to the Rayleigh–Plateau instability, like dew droplets patterning a spider web11,12. After uniformly coating microtubules, TPX2 forms regularly spaced droplets, from which branches nucleate. Droplet spacing increases with greater TPX2 concentration. A stochastic model shows that droplets make branching nucleation more efficient by confining the space along the microtubule where multiple necessary factors colocalize to nucleate a branch.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: TPX2 uniformly coats microtubules and then forms periodically spaced droplets that can nucleate branches.
Fig. 2: AFM measurements reveal condensed TPX2 dynamics on microtubules.
Fig. 3: Hydrodynamic theory predicts TPX2 droplet formation on a microtubule surface.
Fig. 4: A stochastic model predicts that TPX2 droplets enhance the efficiency of branching microtubule nucleation.

Data availability

Source data are provided with this paper. All other data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request.

Code availability

Algorithms and simulation codes are described in Methods and Supplementary Information.

References

  1. 1.

    Shin, Y. & Brangwynne, C. P. Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 (2017).

  2. 2.

    Alberti, S., Gladfelter, A. & Mittag, T. Considerations and challenges in studying liquid–liquid phase separation and biomolecular condensates. Cell 176, 419–434 (2019).

    Article  Google Scholar 

  3. 3.

    Petry, S., Groen, A., Ishihara, K., Mitchison, T. & Vale, R. Branching microtubule nucleation in Xenopus egg extracts mediated by augmin and TPX2. Cell 152, 768–777 (2013).

    Article  Google Scholar 

  4. 4.

    Thawani, A., Stone, H. A., Shaevitz, J. W. & Petry, S. Spatiotemporal organization of branched microtubule networks. eLife 8, e43890 (2019).

    Article  Google Scholar 

  5. 5.

    King, M. R. & Petry, S. Phase separation of TPX2 enhances and spatially coordinates microtubule nucleation. Nat. Commun. 11, 270 (2020).

    ADS  Article  Google Scholar 

  6. 6.

    Uehara, R. & Goshima, G. Functional central spindle assembly requires de novo microtubule generation in the interchromosomal region during anaphase. J. Cell Biol. 191, 259–267 (2010).

    Article  Google Scholar 

  7. 7.

    Uehara, R. et al. The augmin complex plays a critical role in spindle microtubule generation for mitotic progression and cytokinesis in human cells. Proc. Natl Acad. Sci. USA 106, 6998–7003 (2009).

    ADS  Article  Google Scholar 

  8. 8.

    Petry, S., Pugieux, C., Nédélec, F. J. & Vale, R. D. Augmin promotes meiotic spindle formation and bipolarity in Xenopus egg extracts. Proc. Natl Acad. Sci. USA 108, 14473–14478 (2011).

    ADS  Article  Google Scholar 

  9. 9.

    Lawo, S. et al. HAUS, the 8-subunit human augmin complex, regulates centrosome and spindle integrity. Curr. Biol. 19, 816–826 (2009).

    Article  Google Scholar 

  10. 10.

    Hotta, T. et al. Characterization of the Arabidopsis augmin complex uncovers its critical function in the assembly of the acentrosomal spindle and phragmoplast microtubule arrays. Plant Cell 24, 1494–1509 (2012).

    Article  Google Scholar 

  11. 11.

    Rayleigh, L. On the instability of jets. Proc. Lond. Math. Soc. 1, 4–13 (1878).

    MathSciNet  Article  Google Scholar 

  12. 12.

    Quéré, D. Fluid coating on a fiber. Annu. Rev. Fluid Mech. 31, 347–384 (1999).

    ADS  Article  Google Scholar 

  13. 13.

    Pérez de Castro, I. & Malumbres, M. Mitotic stress and chromosomal instability in cancer: the case for TPX2. Genes Cancer 3, 721–730 (2012).

    Article  Google Scholar 

  14. 14.

    Uhlen, M. et al. A pathology atlas of the human cancer transcriptome. Science 357, eaan2507 (2017).

  15. 15.

    Hernández-Vega, A. et al. Local nucleation of microtubule bundles through tubulin concentration into a condensed tau phase. Cell Rep. 20, 2304–2312 (2017).

    Article  Google Scholar 

  16. 16.

    Siahaan, V. et al. Kinetically distinct phases of tau on microtubules regulate kinesin motors and severing enzymes. Nat. Cell Biol. 21, 1086–1092 (2019).

    Article  Google Scholar 

  17. 17.

    Jiang, H. et al. Phase transition of spindle-associated protein regulate spindle apparatus assembly. Cell 163, 108–122 (2015).

    Article  Google Scholar 

  18. 18.

    von Appen, A. et al. LEM2 phase separation promotes ESCRT-mediated nuclear envelope reformation. Nature 582, 115–118 (2020).

  19. 19.

    Wühr, M. et al. Deep proteomics of the Xenopus laevis egg using an mRNA-derived reference database. Curr. Biol. 24, 1467–1475 (2014).

    Article  Google Scholar 

  20. 20.

    Alfaro-Aco, R., Thawani, A. & Petry, S. Biochemical reconstitution of branching microtubule nucleation. eLife 9, e49797 (2020).

    Article  Google Scholar 

  21. 21.

    Desai, A. & Mitchison, T. J. Microtubule polymerization dynamics. Annu. Rev. Cell Dev. Biol. 13, 83–117 (1997).

    Article  Google Scholar 

  22. 22.

    Goren, S. L. The instability of an annular thread of fluid. J. Fluid Mech. 12, 309–319 (1962).

    ADS  MathSciNet  Article  Google Scholar 

  23. 23.

    Boulogne, F., Pauchard, L. & Giorgiutti-Dauphiné, F. Instability and morphology of polymer solutions coating a fibre. J. Fluid Mech. 704, 232–250 (2012).

    ADS  Article  Google Scholar 

  24. 24.

    Haefner, S. et al. Influence of slip on the Plateau–Rayleigh instability on a fibre. Nat. Commun. 6, 4–9 (2015).

    Article  Google Scholar 

  25. 25.

    Tonon, G. et al. High-resolution genomic profiles of human lung cancer. Proc. Natl Acad. Sci. USA 102, 9625–9630 (2005).

    ADS  Article  Google Scholar 

  26. 26.

    Neumayer, G., Belzil, C., Gruss, O. J. & Nguyen, M. D. TPX2: of spindle assembly, DNA damage response, and cancer. Cell. Mol. Life Sci. 71, 3027–3047 (2014).

    Article  Google Scholar 

  27. 27.

    Cao, L. et al. The structure of apo-kinesin bound to tubulin links the nucleotide cycle to movement. Nat. Commun. 5, 5364 (2014).

    ADS  Article  Google Scholar 

  28. 28.

    Shang, Z. et al. High-resolution structures of kinesin on microtubules provide a basis for nucleotide-gated force-generation. eLife 3, e04686 (2014).

    Article  Google Scholar 

  29. 29.

    Gillespie, D. T. Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81, 2340–2361 (1977).

    Article  Google Scholar 

  30. 30.

    Caudron, M., Bunt, G., Bastiaens, P. & Karsenti, E. Spatial coordination of spindle assembly by chromosome-mediated signaling gradients. Science 309, 1373–1376 (2005).

    ADS  Article  Google Scholar 

  31. 31.

    Brugués, J., Nuzzo, V., Mazur, E. & Needleman, D. J. Nucleation and transport organize microtubules in metaphase spindles. Cell 149, 554–564 (2012).

    Article  Google Scholar 

  32. 32.

    Decker, F., Oriola, D., Dalton, B. & Brugués, J. Autocatalytic microtubule nucleation determines the size and mass of Xenopus laevis egg extract spindles. eLife 7, e31149 (2018).

    Article  Google Scholar 

  33. 33.

    Feric, M. et al. Coexisting liquid phases underlie nucleolar subcompartments. Cell 165, 1686–1697 (2016).

    Article  Google Scholar 

  34. 34.

    Duprat, C., Protiere, S., Beebe, A. & Stone, H. A. Wetting of flexible fibre arrays. Nature 482, 510–513 (2012).

    ADS  Article  Google Scholar 

  35. 35.

    Li, Q. et al. LLPSDB: a database of proteins undergoing liquid–liquid phase separation in vitro. Nucleic Acids Res. 48, D320–D327 (2020).

  36. 36.

    Alfaro-Aco, R., Thawani, A. & Petry, S. Structural analysis of the role of TPX2 in branching microtubule nucleation. J. Cell Biol. 216, 983–997 (2017).

    Article  Google Scholar 

  37. 37.

    Song, J. et al. Mechanism of how augmin directly targets the γ-tubulin ring complex to microtubules. J. Cell Biol. 217, 2417–2428 (2018).

    Article  Google Scholar 

  38. 38.

    Murray, A. W. & Kirschner, M. W. Cyclin synthesis drives the early embryonic cell cycle. Nature 339, 275–280 (1989).

    ADS  Article  Google Scholar 

  39. 39.

    Hannak, E. & Heald, R. Investigating mitotic spindle assembly and function in vitro using Xenopus laevis egg extracts. Nat. Protoc. 1, 2305–2314 (2006).

    Article  Google Scholar 

  40. 40.

    Case, R. B., Pierce, D. W., Hom-Booher, N., Hart, C. L. & Vale, R. D. The directional preference of kinesin motors is specified by an element outside of the motor catalytic domain. Cell 90, 959–966 (1997).

    Article  Google Scholar 

  41. 41.

    Gell, C. et al. in Methods in Cell Biology Vol. 95 (eds Wilson, L. & Correia, J. J.) 221–245 (Elsevier, 2010).

  42. 42.

    Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  Google Scholar 

  43. 43.

    Hamon, L., Curmi, P. A. & Pastré, D. in Methods in Cell Biology Vol. 95 (eds Wilson, L. & Correia, J. J.) 157–174 (Elsevier, 2010).

  44. 44.

    Nečas, D. & Klapetek, P. Gwyddion: an open-source software for SPM data analysis. Open Phys. 10, 181–188 (2012).

    ADS  Article  Google Scholar 

  45. 45.

    Thevenaz, P., Ruttimann, U. E. & Unser, M. A pyramid approach to subpixel registration based on intensity. IEEE Trans. Image Process. 7, 27–41 (1998).

    ADS  Article  Google Scholar 

Download references

Acknowledgements

We thank S. Lee, T.-M. Chou and M. Libera at Stevens Institute of Technology for access to their atomic force microscope; I. Armstrong and S. Dutta at Bruker for access to and support for their atomic force microscope; M. King, B. Bratton, M. Safari, M. Koch, P. Ronceray and N. Wingreen for discussions; A. Thawani for purification of TPX2; H. Ando, C. Holmes, physiology students V. Baena, D. Laundon and L. Ma, and the Physiology Course at the Marine Biological Lab for assisting with the first AFM trials; and Princeton’s Imaging and Analysis Center, which is partially supported by the Princeton Center for Complex Materials, an NSF-MRSEC programme (DMR-1420541). B.G. was supported by PD Soros and NSF GRFP. S.U.S. was supported by NIH NCI NRSA 1F31CA236160 and NHGRI training grant 5T32HG003284. This work was funded by NIH NIA 1DP2GM123493, Pew Scholars Program 00027340, Packard Foundation 2014-40376 and CPBF NSF PHY-1734030.

Author information

Affiliations

Authors

Contributions

S.U.S., B.G., J.W.S., H.A.S. and S.P. conceptualized the project. B.G. and S.U.S. performed fluorescence microscopy, and B.G. performed analysis of fluorescence microscopy data. B.G. performed TPX2-only electron microscopy with assistance from R.A.-A. and S.U.S., theory and simulations. S.U.S. and B.G. performed AFM, and S.U.S. performed analysis of AFM data. S.U.S. performed meiotic cytosol experiments. R.A.-A. performed branching reconstitution and multiple-protein electron microscopy, and S.U.S. performed analysis of branching reconstitution data. S.U.S. and B.G. wrote the paper with assistance from J.W.S., H.A.S. and S.P. J.W.S., H.A.S. and S.P. supervised the research. All authors discussed and interpreted results and revised the paper.

Corresponding authors

Correspondence to Joshua W. Shaevitz, Howard A. Stone or Sabine Petry.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review informationNature Physics thanks Amy Gladfelter and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Statistics of droplet patterned microtubules imaged with TIRF microscopy.

a, Histogram of droplet sizes and spacings for TIRF experiments at 1 μM GFP–TPX2. N = 35 microtubules were analyzed with a mean size of 0.5 ± 0.1μm and spacing 0.6 ± 0.2μm (mean ± standard deviation). b, Average power spectrum of GFP–TPX2 fluorescence intensities of droplet patterns for TIRF experiments at 1 μM GFP–TPX2 (N = 35 microtubules). The peak indicates the emergence of a periodic pattern with wavelength \({\lambda }_{\max }=0.6\pm 0.1\,\mu {\rm{m}}\) (mean ± standard deviation), in agreement with the histogram analysis. Shaded regions are 95% bootstrap confidence intervals. For calculation details, see Methods.

Source data

Extended Data Fig. 2 TPX2 on the microtubule can appear uniform when imaged via optical microscopy.

a, TIRF microscopy time lapses showing that a 0.1 μM TPX2 coating does not break up into visible droplets like the 1 μM TPX2 coating does. b, Branching microtuble nucleation visualized by TIRF microscopy in X. laevis meiotic cytosol at 0.1 μM TPX2, indicating that branching can occur from diffraction limited droplets.

Extended Data Fig. 3 Raw and smoothed AFM height profiles, and power spectra of raw height profiles.

a, Raw height profiles of the topographies in Fig. 2a. The smoothed profile from Fig. 2b is shown again for reference. b, Power spectra of the raw height profiles in (a). The red curve shows the mean ± standard error of the mean over nine topographies of the microtubule after the droplet pattern had formed. The frequency f at which the peak in the red curve occurs gives the droplet spacing measured for this microtubule, according to λ = 1/f.

Source data

Extended Data Fig. 4 Schematic of the Rayleigh-Plateau instability.

The viscosity of the condensed film is μ, γ is the surface tension of the interface, and p is the far field pressure provided by the solvent. The microtubule has radius ri. Initially, the interface is flat at \(\xi \left(z,t=0\right)={r}_{{\rm{o}}}\), but this scenario is unstable against the capillary pressure γ/ro, so \(\xi \left(z,t\right)\) will evolve to a lower energy state. The unit normal n and unit tangent t track the geometry of the interface during its evolution.

Extended Data Fig. 5 AFM height profiles and power spectra at additional TPX2 concentrations.

For 0.1 μM, the power spectrum is averaged over N = 5 topographies after the droplet pattern had formed. For 0.6 μM, N = 3. For 0.8 μM, N = 4; the uncoated height profile for this specific microtubule is unavailable because the sample moved after TPX2 addition. Height profiles were smoothed using a moving-average window of 40nm. All power spectra after droplet formation show mean ± standard error of the mean.

Source data

Extended Data Fig. 6 Growth of the condensed film.

a, Schematic of the model for growth of the condensed protein film. Microtubules of radius ri are spaced periodically by a distance \(2\bar{R}\), where \(\bar{R}=1/\sqrt{\pi nl}\) where l is the typical microtubule length and n is the number density of microtubules. Soluble protein phase separates from solution and nucleates a spatially uniform condensed film on the microtubule surface, whose interfacial position we denote by \(r=\xi \left(t\right)\). b, Final film thickness h versus initial concentration c0 as measured by atomic force microscopy (blue) and as predicted by equation (19) (black) and using \(1/{c}_{{\rm{R}}}\left({\bar{R}}^{2}/{r}_{{\rm{i}}}^{2}-1\right)\) as a least-squares fit parameter. c, Evolution of the interfacial position of the film ξ/ri over time T for \(S={r}_{{\rm{i}}}/{r}_{{\rm{o}}}\in \left[0.5,0.7\right]\), which is our experimentally observed range of S. Solid lines are the exact solution and dashed lines are the asymptotic formula (34b).

Source data

Extended Data Fig. 7 Average power spectra from AFM data for all concentrations of TPX2 and for uncoated, initially TPX2-coated, C-terminal-TPX2-bound, and kinesin-1-bound microtubules.

Peaks indicate characteristic wavelengths that correspond to a typical droplet spacing (Supplementary Table 3) (N = 25, 17, 23, and 21 microtubules, respectively, for increasing TPX2 concentration). Also included are average power spectra for uncoated microtubules (N = 29 microtubules), microtubules initially coated uniformly with TPX2 (N = 25 microtubules), kinesin-bound microtubules (N = 19 microtubules), and C-terminal-TPX2-bound microtubules (N = 4 microtubules)—none of which show any characteristic spatial features. For kinesin-bound microtubules, h = 2.9 ± 2.0nm, consistent with what one would expect for the kinesin construct used27,28. For C-terminal-TPX2-bound microtubules, h = 3.7 ± 1.8nm. Heights are mean ± standard deviation. Shaded regions represents 95% bootstrap confidence intervals.

Source data

Extended Data Fig. 8 The growth of the instability for early times is exponential.

The average spectral amplitude at the most unstable frequency grows exponentially for early times (black line, N = 21 microtubules). Spectral amplitude = \(\sqrt{{\rm{spectral}}\ {\rm{power}}}\). Individual measurements are black dots. Shaded region represents 95% bootstrap confidence intervals. At later times, the spectral amplitude levels off due to nonlinear forces as the pattern sets in. For the exponential fit (red), \({\sigma }_{\max }=0.03\,{\min }^{-1}\), with R2 = 0.95.

Source data

Extended Data Fig. 9 γ-TuRC localization on bare microtubules.

Typical electron microscopy experiment with just γ-TuRC and microtubules. Clearly, the localization of γ-TuRC to the microtubule without TPX2 and augmin is negligible (Supplementary Table 4). Scale bar is 100 nm.

Extended Data Fig. 10 Parametric study of Monte Carlo simulations.

a, Time τ to colocalize two distinct factors, and hence form a branch, as a function of N and s for a uniform and periodic protein coating. For a given s, the periodic coating is uniformly more efficient at colocalizing well-mixed factors. Each data point is the average of 107 independent simulations. b, Typical histogram of 107 independent simulations for F = 2, N = 50, and s = 10.

Supplementary information

Supplementary Information

Theoretical derivations, experimental materials and methods, Supplementary Tables 1–5 and references.

Reporting Summary

Supplementary Video 1

Rayleigh–Plateau instability of TPX2 on microtubules visualized using TIRF microscopy. GFP–TPX2 at 1 μM was spiked onto a passivated glass surface covered with Alexa568-labelled microtubules at t = 0 s. TPX2 coats the microtubules and then proceeds to break up into droplets. Scale bar, 1 μm.

Supplementary Video 2

Microtubule branches nucleating from TPX2 droplets on a preexisting microtubule. During acquisition, only the soluble tubulin channel was imaged to enable capturing nucleation and polymerization of branched microtubules at high temporal resolution. Scale bar, 5 μm.

Supplementary Video 3

Branching microtubule nucleation visualized using TIRF microscopy. TPX2 at 0.1 μM is added to X. laevis meiotic cytosol purified from eggs. TPX2 coats the mother microtubule, from which daughter microtubules then nucleate, leading to an autocatalytic branched network. The frame dimensions are 16 μm × 22 μm.

Supplementary Video 4

Rayleigh–Plateau instability of TPX2 on microtubules probed using AFM. GFP–TPX2 at 0.2 ± 0.1 μM was spiked onto a mica surface covered with microtubules during acquisition. The uniform film of TPX2 is established at t = 0 s, after which the film breaks up into droplets. The frame dimensions are 2 μm × 2 μm.

Source data

Source Data Fig. 2

AFM line scans and average power spectra.

Source Data Fig. 3

AFM wavelength versus film thickness data points and theory curve.

Source Data Fig. 4

Monte Carlo colocalization time data.

Source Data Extended Data Fig. 1

TIRF histogram data and average power spectrum.

Source Data Extended Data Fig. 3

Raw and smoothed AFM line scans; individual power spectra.

Source Data Extended Data Fig. 5

AFM line scans and power spectra.

Source Data Extended Data Fig. 6

Film thickness versus concentration data and fit curve.

Source Data Extended Data Fig. 7

All averaged AFM power spectra.

Source Data Extended Data Fig. 8

All averaged spectral amplitude versus time plots.

Source Data Extended Data Fig. 10

Monte Carlo colocalization time and histogram data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Setru, S.U., Gouveia, B., Alfaro-Aco, R. et al. A hydrodynamic instability drives protein droplet formation on microtubules to nucleate branches. Nat. Phys. 17, 493–498 (2021). https://doi.org/10.1038/s41567-020-01141-8

Download citation

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