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:

An excitable signal integrator couples to an idling cytoskeletal oscillator to drive cell migration

Nature Cell Biology volume 15, pages 1307–1316 (2013)Cite this article

Subjects

Abstract

It is generally believed that cytoskeletal activities drive random cell migration, whereas signal transduction events initiated by receptors regulate the cytoskeleton to guide cells. However, we find that the cytoskeletal network, involving SCAR/WAVE, Arp 2/3 and actin-binding proteins, is capable of generating only rapid oscillations and undulations of the cell boundary. The signal transduction network, comprising multiple pathways that include Ras GTPases, PI(3)K and Rac GTPases, is required to generate the sustained protrusions of migrating cells. The signal transduction network is excitable, exhibiting wave propagation, refractoriness and maximal response to suprathreshold stimuli, even in the absence of the cytoskeleton. We suggest that cell motility results from coupling of ‘pacemaker’ signal transduction and ‘idling motor’ cytoskeletal networks, and various guidance cues that modulate the threshold for triggering signal transduction events are integrated to control the mode and direction of migration.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: Fast oscillations of the cytoskeletal activities revealed by t-stacking.
Figure 2: The slow, excitable signalling network.
Figure 3: Rac activity correlates with the dynamics of the signalling network.
Figure 4: Coupling of signal transduction and cytoskeletal networks in protrusions.
Figure 5: The STEN–CON coupling model and computer simulation.
Figure 6: Predictions of STEN–CON coupling for cell migration.

Similar content being viewed by others

References

  1. Ridley, A. J. et al. Cell migration: integrating signals from front to back. Science 302, 1704–1709 (2003).

    Article  CAS  PubMed  Google Scholar 

  2. Bosgraaf, L. & Van Haastert, P. J. The ordered extension of pseudopodia by amoeboid cells in the absence of external cues. PLoS ONE 4, e5253 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Tranquillo, R. T., Lauffenburger, D. A. & Zigmond, S. H. A stochastic model for leukocyte random motility and chemotaxis based on receptor binding fluctuations. J. Cell Biol. 106, 303–309 (1988).

    Article  CAS  PubMed  Google Scholar 

  4. Arrieumerlou, C. & Meyer, T. A local coupling model and compass parameter for eukaryotic chemotaxis. Dev. Cell 8, 215–227 (2005).

    Article  CAS  PubMed  Google Scholar 

  5. Welf, E. S. & Haugh, J. M. Signaling pathways that control cell migration: models and analysis. WIRes Syst. Biol. Med. 3, 231–240 (2011).

    Article  CAS  Google Scholar 

  6. Pollard, T. D. & Borisy, G. G. Cellular motility driven by assembly and disassembly of actin filaments. Cell 112, 453–465 (2003).

    Article  CAS  PubMed  Google Scholar 

  7. Hall, A. Rho GTPases and the control of cell behaviour. Biochem. Soc. Trans. 33, 891–895 (2005).

    Article  CAS  PubMed  Google Scholar 

  8. Ridley, A. J. Rho GTPases and actin dynamics in membrane protrusions and vesicle trafficking. Trends Cell Biol. 16, 522–529 (2006).

    Article  CAS  PubMed  Google Scholar 

  9. Machacek, M. et al. Coordination of Rho GTPase activities during cell protrusion. Nature 461, 99–103 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Welch, C. M., Elliott, H., Danuser, G. & Hahn, K. M. Imaging the coordination of multiple signalling activities in living cells. Nat. Rev. Mol. Cell Biol. 12, 749–756 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Cain, R. J. & Ridley, A. J. Phosphoinositide 3-kinases in cell migration. Biol. Cell 101, 13–29 (2009).

    Article  CAS  PubMed  Google Scholar 

  12. Sasaki, A. T. et al. G protein-independent Ras/PI3K/F-actin circuit regulates basic cell motility. J. Cell Biol. 178, 185–191 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Inoue, T. & Meyer, T. Synthetic activation of endogenous PI3K and Racidentifies an AND-gate switch for cell polarization and migration. PLoS ONE 3, e3068 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Weiner, O. D. et al. A PtdInsP(3)- and Rho GTPase-mediated positive feedback loop regulates neutrophil polarity. Nat. Cell Biol. 4, 509–513 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Asano, Y., Nagasaki, A. & Uyeda, T. Q. Correlated waves of actin filaments and PIP3 in Dictyostelium cells. Cell Motil. Cytoskeleton 65, 923–934 (2008).

    Article  CAS  PubMed  Google Scholar 

  16. Bretschneider, T. et al. The three-dimensional dynamics of actin waves, a model of cytoskeletal self-organization. Biophys. J. 96, 2888–2900 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Case, L. B. & Waterman, C. M. Adhesive F-actin waves: a novel integrin-mediated adhesion complex coupled to ventral actin polymerization. PLoS ONE 6, e26631 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Gerisch, G. Self-organizing actin waves that simulate phagocytic cup structures. PMC Biophys. 3, 7 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Gerisch, G. et al. Self-organizing actin waves as planar phagocytic cup structures. Cell Adhes. Migr. 3, 373–382 (2009).

    Article  Google Scholar 

  20. Gerisch, G. et al. Mobile actin clusters and traveling waves in cells recovering from actin depolymerization. Biophys. J. 87, 3493–3503 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Vicker, M. G. F-actin assembly in Dictyostelium cell locomotion and shape oscillations propagates as a self-organized reaction-diffusion wave. FEBS Lett. 510, 5–9 (2002).

    Article  CAS  PubMed  Google Scholar 

  22. Vicker, M. G. Eukaryotic cell locomotion depends on the propagation of self-organized reaction-diffusion waves and oscillations of actin filament assembly. Exp. Cell Res. 275, 54–66 (2002).

    Article  CAS  PubMed  Google Scholar 

  23. Weiner, O. D., Marganski, W. A., Wu, L. F., Altschuler, S. J. & Kirschner, M. W. An actin-based wave generator organizes cell motility. PLoS Biol. 5, e221 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Xiong, Y., Huang, C. H., Iglesias, P. A. & Devreotes, P. N. Cells navigate with a local-excitation, global-inhibition-biased excitable network. Proc. Natl Acad. Sci. USA 107, 17079–17086 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Arai, Y. et al. Self-organization of the phosphatidylinositol lipids signaling system for random cell migration. Proc. Natl Acad. Sci. USA 107, 12399–12404 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Hecht, I., Kessler, D. A. & Levine, H. Transient localized patterns in noise-driven reaction-diffusion systems. Phys. Rev. Lett. 104, 158301 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Vicker, M. G. Reaction-diffusion waves of actin filament polymerization/depolymerization in Dictyostelium pseudopodium extension and cell locomotion. Biophys. Chem. 84, 87–98 (2000).

    Article  CAS  PubMed  Google Scholar 

  28. Meinhardt, H. Orientation of chemotactic cells and growth cones: models and mechanisms. J. Cell Sci. 112, 2867–2874 (1999).

    CAS  PubMed  Google Scholar 

  29. Hecht, I. et al. Activated membrane patches guide chemotactic cell motility. PLoS Comput. Biol. 7, e1002044 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Bretschneider, T. et al. Dynamic actin patterns and Arp2/3 assembly at the substrate-attached surface of motile cells. Curr. Biol. 14, 1–10 (2004).

    Article  CAS  PubMed  Google Scholar 

  31. Kae, H., Lim, C. J., Spiegelman, G. B. & Weeks, G. Chemoattractant-induced Ras activation during Dictyostelium aggregation. EMBO Rep. 5, 602–606 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Parent, C. A., Blacklock, B. J., Froehlich, W. M., Murphy, D. B. & Devreotes, P. N. G protein signaling events are activated at the leading edge of chemotactic cells. Cell 95, 81–91 (1998).

    Article  CAS  PubMed  Google Scholar 

  33. Kabacoff, C. et al. Dynacortin facilitates polarization of chemotaxing cells. BMC Biol. 5, 53 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Veltman, D. M., King, J. S., Machesky, L. M. & Insall, R. H. SCAR knockouts in Dictyostelium: WASP assumes SCAR’s position and upstream regulators in pseudopods. J. Cell Biol. 198, 501–508 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Uetrecht, A. C. & Bear, J. E. Coronins: the return of the crown. Trends Cell Biol. 16, 421–426 (2006).

    Article  CAS  PubMed  Google Scholar 

  36. Sirotkin, V., Berro, J., Macmillan, K., Zhao, L. & Pollard, T. D. Quantitative analysis of the mechanism of endocytic actin patch assembly and disassembly in fission yeast. Mol. Biol. Cell 21, 2894–2904 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Uchida, K. S. & Yumura, S. Dynamics of novel feet of Dictyostelium cells during migration. J. Cell Sci. 117, 1443–1455 (2004).

    Article  CAS  PubMed  Google Scholar 

  38. Chen, L. et al. Two phases of actin polymerization display different dependencies on PI(3,4,5)P3 accumulation and have unique roles during chemotaxis. Mol. Biol. Cell 14, 5028–5037 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Postma, M. et al. Uniform cAMP stimulation of Dictyostelium cells induces localized patches of signal transduction and pseudopodia. Mol. Biol. Cell 14, 5019–5027 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ridley, A. J., Paterson, H. F., Johnston, C. L., Diekmann, D. & Hall, A. The small GTP-binding protein rac regulates growth factor-induced membrane ruffling. Cell 70, 401–410 (1992).

    Article  CAS  PubMed  Google Scholar 

  41. Jaffe, A. B. & Hall, A. Rho GTPases: biochemistry and biology. Annu. Rev. Cell Dev. Biol. 21, 247–269 (2005).

    Article  CAS  PubMed  Google Scholar 

  42. Filic, V., Marinovic, M., Faix, J. & Weber, I. A dual role for Rac1 GTPases in the regulation of cell motility. J. Cell Sci. 125, 387–398 (2012).

    Article  CAS  PubMed  Google Scholar 

  43. Dumontier, M., Hocht, P., Mintert, U. & Faix, J. Rac1 GTPases control filopodia formation, cell motility, endocytosis, cytokinesis and development in Dictyostelium. J. Cell Sci. 113, 2253–2265 (2000).

    CAS  PubMed  Google Scholar 

  44. Eden, S., Rohatgi, R., Podtelejnikov, A. V., Mann, M. & Kirschner, M. W. Mechanism of regulation of WAVE1-induced actin nucleation by Rac1 and Nck. Nature 418, 790–793 (2002).

    Article  CAS  PubMed  Google Scholar 

  45. Kitamura, Y. et al. Interaction of Nck-associated protein 1 with activated GTP-binding protein Rac. Biochem. J. 322, 873–878 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Taniguchi, D. et al. Phase geometries of two-dimensional excitable waves govern self-organized morphodynamics of amoeboid cells. Proc. Natl Acad. Sci. USA 110, 5016–5021 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Iglesias, P. A. & Devreotes, P. N. Biased excitable networks: how cells direct motion in response to gradients. Curr. Opin. Cell Biol. 24, 245–253 (2012).

    Article  CAS  PubMed  Google Scholar 

  48. Hoeller, O. & Kay, R. R. Chemotaxis in the absence of PIP3 gradients. Curr. Biol. 17, 813–817 (2007).

    Article  CAS  PubMed  Google Scholar 

  49. Cai, H. et al. Ras-mediated activation of the TORC2-PKB pathway is critical for chemotaxis. J. Cell Biol. 190, 233–245 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhang, S., Charest, P. G. & Firtel, R. A. Spatiotemporal regulation of Ras activity provides directional sensing. Curr. Biol. 18, 1587–1593 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Srinivasan, S. et al. Rac and Cdc42 play distinct roles in regulating PI(3,4,5)P3 and polarity during neutrophil chemotaxis. J. Cell Biol. 160, 375–385 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Yoo, S. K. et al. Differential regulation of protrusion and polarity by PI3K during neutrophil motility in live zebrafish. Dev. Cell 18, 226–236 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Decave, E. et al. Shear flow-induced motility of Dictyostelium discoideum cells on solid substrate. J. Cell Sci. 116, 4331–4343 (2003).

    Article  CAS  PubMed  Google Scholar 

  54. Zhao, M. et al. Electrical signals control wound healing through phosphatidylinositol-3-OH kinase-gamma and PTEN. Nature 442, 457–460 (2006).

    Article  CAS  PubMed  Google Scholar 

  55. Welf, E. S., Ahmed, S., Johnson, H. E., Melvin, A. T. & Haugh, J. M. Migrating fibroblasts reorient directionality by a metastable, PI3K-dependent mechanism. J. Cell Biol. 197, 105–114 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Westendorf, C. et al. Actin cytoskeleton of chemotactic amoebae operates close to the onset of oscillations. Proc. Natl Acad. Sci. USA 110, 3853–3858 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Lee, S., Shen, Z., Robinson, D. N., Briggs, S. & Firtel, R. A. Involvement of the cytoskeleton in controlling leading-edge function during chemotaxis. Mol. Biol. Cell 21, 1810–1824 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Charest, P. G. et al. A Ras signaling complex controls the RasC-TORC2 pathway and directed cell migration. Dev. Cell 18, 737–749 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Wu, L., Valkema, R., Van Haastert, P.J. & Devreotes, P. N. The G protein beta subunit is essential for multiple responses to chemoattractants in Dictyostelium. J. Cell Biol. 129, 1667–1675 (1995).

    Article  CAS  PubMed  Google Scholar 

  60. Iijima, M. & Devreotes, P. Tumor suppressor PTEN mediates sensing of chemoattractant gradients. Cell 109, 599–610 (2002).

    Article  CAS  PubMed  Google Scholar 

  61. Chen, L. et al. PLA2 and PI3K/PTEN pathways act in parallel to mediate chemotaxis. Dev. Cell 12, 603–614 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Fitzhugh, R. Impulses and physiological states in theoretical models of nerve membrane. Biophys. J. 1, 445–466 (1961).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Kim, J., Heslop-Harrison, P., Postlethwaite, I. & Bates, D. G. Stochastic noise and synchronisation during Dictyostelium aggregation make cAMP oscillations robust. PLoS Comput. Biol. 3, e218 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Vilar, J. M., Sole, R. V. & Rubi, J. M. Noise and periodic modulations in neural excitable media. Phys. Rev. E 59, 5920–5927 (1999).

    Article  CAS  Google Scholar 

  65. Weinberger, L. S., Burnett, J. C., Toettcher, J. E., Arkin, A. P. & Schaffer, D. V. Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity. Cell 122, 169–182 (2005).

    Article  CAS  PubMed  Google Scholar 

  66. Yang, L. et al. Modeling cellular deformations using the level set formalism. BMC Syst. Biol. 2, 68 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Poirier, C. C., Ng, W. P., Robinson, D. N. & Iglesias, P. A. Deconvolution of the cellular force-generating subsystems that govern cytokinesis furrow ingression. PLoS Comput. Biol. 8, e1002467 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Mitchell, I. M. The flexible, extensible and efficient toolbox of level set methods. J. Sci. Comput. 35, 300–329 (2008).

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank M. Amzel, D. Montell, M. Iijima, T. Inoue and members of the Devreotes and Iglesias laboratories for helpful suggestions, B. Diplas for generating cell centroid tracks, P. Van Haastert for the RBD–GFP construct, R. Insall (The Beatson Institute, UK) for the HSPC300–GFP construct, G. Gerisch (Max Planck Institute for Biochemistry, Germany) for the LimE–RFP construct, and D. Robinson (Johns Hopkins University, USA) for coronin–GFP and the original video of dynacortin-expressing cells. We are grateful to V. Filic and I. Weber (Ruder Boskovic Institute, Croatia) for sharing the PAK(GBD)–YFP biosensor for Rac activity. This work was supported in part by grants from the National Institutes of Health, GM28007 (to P.N.D.), GM34933 (to P.N.D.) and GM71920 (to P.A.I.), and a H. L. Plotnick Fellowship from the Damon Runyon Cancer Research Foundation, DRG2019-09 (to C.H.H.).

Author information

Author notes

  1. Chuan-Hsiang Huang and Ming Tang: These authors contributed equally to this work

Authors and Affiliations

  1. Department of Cell Biology, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA

    Chuan-Hsiang Huang, Ming Tang & Peter N. Devreotes

  2. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA

    Changji Shi & Pablo A. Iglesias

Authors
  1. Chuan-Hsiang Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ming Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Changji Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pablo A. Iglesias
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Peter N. Devreotes
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

C-H.H. and M.T. performed the experiments. C.S. and P.A.I. carried out computer simulations. All authors analysed the data and wrote the manuscript. P.N.D. supervised the study.

Corresponding author

Correspondence to Peter N. Devreotes.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Cytoskeletal network.

(a) Illustration of the t-stack technique. The frames of a TIRF video (left) are stacked to produce the t-stack (right). The position and orientation of frames t1, t2, and t3 in the t-stack is shown (middle). The immobile red oval generates the red cylinder in the t-stack, while the expansion of the green region over time creates the oblique cone-like appendage. (b-d) T-stacks derived from published TIRF time-lapse videos of a wild-type cell expressing GFP-dynacortin (b) 1, a wild-type cell expressing GFP-Arp3 (c) 2, and a SCAR- cell expressing GFP-WASP (d) 3 showing fast oscillations of cytoskeletal proteins. The red arrowhead indicates a pseudopodium preceding oscillations of dynacortin (green arrowheads). (e) T-stacks from a cell co-expressing HSPC300-GFP and cAR1-RFP. (f-h) T-stacks of LimE expressed in gβ- cells (f), pten- cells (g), and LY294002-treated wild-type cells (h). (i) Cytoskeletal oscillations in cells expressing constitutively active Ras. LimE-RFP in rasC- cells expressing Flag-RasC (left) or Flag-RasCQ62L (right). The videos used for these t-stacks were published earlier4. (j) TIRF image(top) and t-stack (bottom) of a latrunculin-treated cell expressing HSPC300-GFP, showing foci of fluorescence that did not oscillate.

Supplementary Figure 2 Signal transduction network.

(a) TIRF images of a cell co-expressing RBD-GFP and PH-RFP showing coordinated propagation of RBD and PH waves. Video rate was 3 spf (Supplementary Video S3). (b) The temporal profiles of RBD intensity at three spots marked 1, 2, 3 in (a). (c) The progression of contour lines for gray values 10, 20 and 30 along the yellow line in (a) was used to calculate the speed of the wave propagation. In the example, the speed of the wave between 15 sec and 48 sec was 12.8 μm/min by fitting the gray value 20 contour with a least square line. (d-h) Snapshots from TIRF videos of PH-GFP in cells treated with 4 μM latrunculin A (top, Supplementary Movies S4–S8) and the corresponding t-stacks (bottom). Panels (e) and (f) are the same cells at different times, (h) is the same cell as the left cell in (d), and (g) is a different cell. To visualize interior activities, a basal level of cellular fluorescence was subtracted from each video before the t-stacks were generated.

Supplementary Figure 3 Signaling and cytoskeletal activities on protrusions.

(a) T-stacks of two cells co-expressing RBD-GFP and LimE-RFP as well as the merged t-stack. The brackets in the cell on the left point to protrusions with high RBD and LimE. The cell on the right has very low level of RBD-GFP expression, but fast LimE oscillations are visible. Note that weak oscillations in the RBD t-stack (left cell) reflect changes in the boundary which delineates cytosolic RBD rather than RBD intensity on the cortex. Video rate was 2 spf. (b) Frames from a TIRF video of cells co-expressing RBD-GFP and LimE-RFP showing the distributions of RBD and LimE in protrusions. (c) Close-up views of a protrusion (yellow boxes in (a)) showing a smoother change of RBD intensity compared with that of LimE. (d) Frames from the TIRF video of a single large protrusion of a cell expressing HSPC300-GFP (Supplementary Movie S10). (e) t-stack of the video in (d). (f) Kymograph across the dashed line in (d). Arrowheads point to pauses in HSPC300 recruitment where cell boundary expansion stalled.

Supplementary Figure 4 Simulation of coupled systems.

(a) The slow excitable system is implemented as an activator (Xs)-inhibitor (Ys) system. (b) Phase plane plot of the slow excitable system. Red and green lines are nullclines for the activator and inhibitor components, respectively. The solid black circle represents the unique, stable equilibrium, found at the intersection of the two nullclines. The blue arrows represent the system evolution at different points in the phase plane. Two different trajectories are denoted by the black lines. The dotted black line represents a sub-threshold perturbation from which the system returns quickly to the equilibrium. The solid black line illustrates a super-threshold perturbation that causes the system to undergo a large excursion before returning to the equilibrium. (c) The Fast oscillatory system is also implemented using an activator (Xf)-inhibitor (Y f) system and also incorporates the influence of stochastic perturbations. (d) Phase plane plot of the fast oscillatory system. Red and green lines are nullclines for the activator and inhibitor components, respectively. In this case the system has three equilibria, at the points where the nullclines intersect. The solid black circles denote two stable equilibria, the open black circle the unique, unstable equilibrium. The blue arrows represent the evolution at different points in the phase plane. Trajectories are denoted by the black lines.

Supplementary Figure 5 Washout of LY294002 reversed the motility to plaA-/piaA- cells.

(a) Trajectories of cell migration. Random migration of cells were recorded and quantified as in Figure 6. For the LY washout experiment, cells were changed to buffer without LY294002, and allowed to settle for 40 min before recording was started. Duration of tracks is 60 min. (b) Quantification of net speed, motility speed, and persistence (mean ± s.d. from n = 4, 3, 3 experiments for plaA-/piaA- with DMSO, plaA-/piaA- with LY294002, and wash off, respectively. The source data is provided in Supplementary Table 3.)

Supplementary Table 1 Parameter values for simulations.
Full size table
Supplementary Table 2 Statistics source data.
Full size table

Supplementary information

Supplementary Information

Supplementary Information (PDF 732 kb)

HSPC300-GFP.

Time-lapse TIRF video of a Dictyostelium cell expressing HSPC300-GFP with a rate of 1 spf. The video is shown at 15 frames/s and corresponds to Fig. 1a,b (MOV 1052 kb)

T-stack of HSPC300-GFP.

Rotation of the t-stack along its t(time)-axis. The speed of the rotation is shown at 40 degrees/s. The t-stack was generated from Movie S1and corresponds to Fig. 1b. (MOV 477 kb)

RBD-GFP and PH-RFP.

Time-lapse TIRF video of a Dictyostelium cell expressing RBD-GFP and PH-RFP with a rate of 3 spf. The video is shown at 15 frames/s and corresponds to Supplementary Fig. 2a. (MOV 90 kb)

PH-GFP in latrunculin-treated cell.

Time-lapse TIRF video of latrunculin-treated Dictyostelium cells expressing PH-GFP with a rate of 5 spf. The video is shown at 15 frames/s and corresponds to Supplementary Fig. 2d. (MOV 135 kb)

PH-GFP in latrunculin-treated cell.

Time-lapse TIRF video of latrunculin-treated Dictyostelium cells expressing PH-GFP with a rate of 5 spf. The video is shown at 15 frames/s and corresponds to Supplementary Fig. 2e. (MOV 87 kb)

PH-GFP in latrunculin-treated cell.

Time-lapse TIRF video of latrunculin-treated Dictyostelium cells expressing PH-GFP with a rate of 10 spf. The video is shown at 15 frames/s and corresponds to Supplementary Fig. 2f. (MOV 73 kb)

PH-GFP in latrunculin-treated cell.

Time-lapse TIRF video of a latrunculin-treated Dictyostelium cell expressing PH-GFP with a rate of 10 spf. The video is shown at 15 frames/s and corresponds to Supplementary Fig. 2g. (MOV 69 kb)

PH-GFP in latrunculin-treated cell.

Time-lapse TIRF video of latrunculin-treated Dictyostelium cells expressing PH-GFP with a rate of 10 spf. The video is shown at 15 frames/s and corresponds to Supplementary Fig. 2h. (MOV 56 kb)

RBD-GFP and LimE-RFP in undulations and protrusions.

Time-lapse TIRF video of a Dictyostelium cell co-expressing RBD-GFP and LimE-RFP with a rate of 2 spf. Cytoplasmic fluorescence of RBD-GFP and LimE-RFP was subtracted to highlight areas of increased intensity. Cell boundary (in gray) was derived from the cytoplasmic fluorescence of RBD-GFP. The video is shown at 7 frames/s and corresponds to Fig. 4b. (MOV 259 kb)

HSPC300-GFP in protrusion.

Time-lapse TIRF video of a Dictyostelium cell expressing HSPC300-GFP with a rate of 1 spf. The video is shown at 15 frames/s and corresponds to Supplementary Fig. 4d–f. (MOV 368 kb)

Computer simulation of the STEN-CON coupling model.

Level set simulation of cell movement along with the activities of the slow (Ys, in green) and fast (Yf, in red) systems as well as the merged activities. Cell membrane is driven by the signal of Yf (see Extended Experimental Procedures for simulation details). The video is shown at 20 frames/s. (MOV 1891 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Huang, CH., Tang, M., Shi, C. et al. An excitable signal integrator couples to an idling cytoskeletal oscillator to drive cell migration. Nat Cell Biol 15, 1307–1316 (2013). https://doi.org/10.1038/ncb2859

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ncb2859

This article is cited by

Search

Advanced 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