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Mechanochemical self-organization determines search pattern in migratory cells

Nature Physics volume 15, pages 848–857 (2019)Cite this article

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Abstract

To reach their destination, migrating cells rely on polarized signal inputs to align the direction of their motion. However, navigational guidance cues are not always present, which establishes the need for exploratory search mechanisms in cells seeking signal inputs. Here, we investigate how non-Brownian search patterns emerge in adherent vertebrate cells. Combining experimental and theoretical analysis, we demonstrate that nanoscale plasma membrane deformations nucleate a mechanochemical feedback loop that mediates longevity of the cell’s leading edge, a necessary requirement for directed cell migration. We further observe stochastic transitions between phases of random and persistent cell motion, whereby the mechanochemical circuit augments cell persistence and search area. Collectively, these findings are consistent with a self-organizing system for a superdiffusive pattern of motion that is spontaneously employed by migratory cells in the absence of external signal inputs.

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Fig. 1: Lamellipodial and migration dynamics of NIH 3T3 cells.
Fig. 2: Curvature-dependent self-organization drives lamellipodial re-initiation at the leading edge.
Fig. 3: Theoretical model and experimental validation of self-organizing system.
Fig. 4: Artificial PM deformations trigger activation of self-organizing system.
Fig. 5: Self-organizing system determines motion persistence and search area in NIH 3T3 fibroblasts.
Fig. 6: Self-organizing system determines motion persistence and search area in neutrophil-like PLB-985 cells.

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Data availability

The data that support the findings of this study are available from the corresponding author on reasonable request. No restrictions apply.

References

  1. Bourne, H. R. & Weiner, O. A chemical compass. Nature 419, 21 (2002).

    Article  ADS  Google Scholar 

  2. 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  Google Scholar 

  3. Harris, T. H. et al. Generalized Levy walks and the role of chemokines in migration of effector CD8+ T cells. Nature 486, 545–548 (2012).

    Article  ADS  Google Scholar 

  4. Vargas, P. et al. Innate control of actin nucleation determines two distinct migration behaviours in dendritic cells. Nat. Cell Biol. 18, 43–53 (2016).

    Article  Google Scholar 

  5. Viswanathan, G. M. et al. Optimizing the success of random searches. Nature 401, 911–914 (1999).

    Article  ADS  Google Scholar 

  6. Benichou, O., Coppey, M., Moreau, M., Suet, P. H. & Voituriez, R. Optimal search strategies for hidden targets. Phys. Rev. Lett. 94, 198101 (2005).

    Article  ADS  Google Scholar 

  7. Benichou, O., Loverdo, C., Moreau, M. & Voituriez, R. Two-dimensional intermittent search processes: an alternative to Levy flight strategies. Phys. Rev. E 74, 020102 (2006).

    Article  ADS  Google Scholar 

  8. Jikeli, J. F. et al. Sperm navigation along helical paths in 3D chemoattractant landscapes. Nat. Commun. 6, 7985 (2015).

    Article  ADS  Google Scholar 

  9. Charras, G. & Paluch, E. Blebs lead the way: how to migrate without lamellipodia. Nat. Rev. Mol. Cell Biol. 9, 730–736 (2008).

    Article  Google Scholar 

  10. Small, J. V., Stradal, T., Vignal, E. & Rottner, K. The lamellipodium: where motility begins. Trends Cell Biol. 12, 112–120 (2002).

    Article  Google Scholar 

  11. Maiuri, P. et al. Actin flows mediate a universal coupling between cell speed and cell persistence. Cell 161, 374–386 (2015).

    Article  Google Scholar 

  12. Xu, J. et al. Divergent signals and cytoskeletal assemblies regulate self-organizing polarity in neutrophils. Cell 114, 201–214 (2003).

    Article  Google Scholar 

  13. Gardel, M. L. et al. Traction stress in focal adhesions correlates biphasically with actin retrograde flow speed. J. Cell Biol. 183, 999–1005 (2008).

    Article  Google Scholar 

  14. Beningo, K. A., Dembo, M., Kaverina, I., Small, J. V. & Wang, Y. L. Nascent focal adhesions are responsible for the generation of strong propulsive forces in migrating fibroblasts. J. Cell Biol. 153, 881–888 (2001).

    Article  Google Scholar 

  15. Short, B. Lamellipodial actin branches out. J. Cell Biol. 211, 6 (2015).

    Article  Google Scholar 

  16. Svitkina, T. M., Verkhovsky, A. B., McQuade, K. M. & Borisy, G. G. Analysis of the actin-myosin II system in fish epidermal keratocytes: mechanism of cell body translocation. J. Cell Biol. 139, 397–415 (1997).

    Article  Google Scholar 

  17. Svitkina, T. M. & Borisy, G. G. Arp2/3 complex and actin depolymerizing factor/cofilin in dendritic organization and treadmilling of actin filament array in lamellipodia. J. Cell Biol. 145, 1009–1026 (1999).

    Article  Google Scholar 

  18. Giannone, G. et al. Periodic lamellipodial contractions correlate with rearward actin waves. Cell 116, 431–443 (2004).

    Article  Google Scholar 

  19. Giannone, G. et al. Lamellipodial actin mechanically links myosin activity with adhesion-site formation. Cell 128, 561–575 (2007).

    Article  Google Scholar 

  20. Krause, M. & Gautreau, A. Steering cell migration: lamellipodium dynamics and the regulation of directional persistence. Nat. Rev. Mol. Cell Biol. 15, 577–590 (2014).

    Article  Google Scholar 

  21. Harms, B. D., Bassi, G. M., Horwitz, A. R. & Lauffenburger, D. A. Directional persistence of EGF-induced cell migration is associated with stabilization of lamellipodial protrusions. Biophys. J. 88, 1479–1488 (2005).

    Article  Google Scholar 

  22. Wollman, R. & Meyer, T. Coordinated oscillations in cortical actin and Ca2+ correlate with cycles of vesicle secretion. Nat. Cell Biol. 14, 1261–1269 (2012).

    Article  Google Scholar 

  23. Chen, B. C. et al. Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science 346, 1257998 (2014).

    Article  Google Scholar 

  24. Planchon, T. A. et al. Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination. Nat. Methods 8, 417–423 (2011).

    Article  Google Scholar 

  25. Gov, N. S. & Gopinathan, A. Dynamics of membranes driven by actin polymerization. Biophys. J. 90, 454–469 (2006).

    Article  ADS  Google Scholar 

  26. Ramaswamy, S., Toner, J. & Prost, J. Nonequilibrium fluctuations, traveling waves, and instabilities in active membranes. Phys. Rev. Lett. 84, 3494–3497 (2000).

    Article  ADS  Google Scholar 

  27. Shlomovitz, R. & Gov, N. S. Membrane waves driven by actin and myosin. Phys. Rev. Lett. 98, 168103 (2007).

    Article  ADS  Google Scholar 

  28. 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  ADS  Google Scholar 

  29. Miki, H., Yamaguchi, H., Suetsugu, S. & Takenawa, T. IRSp53 is an essential intermediate between Rac and WAVE in the regulation of membrane ruffling. Nature 408, 732–735 (2000).

    Article  ADS  Google Scholar 

  30. Nakagawa, H. et al. IRSp53 is colocalised with WAVE2 at the tips of protruding lamellipodia and filopodia independently of Mena. J. Cell Sci. 116, 2577–2583 (2003).

    Article  Google Scholar 

  31. Prevost, C. et al. IRSp53 senses negative membrane curvature and phase separates along membrane tubules. Nat. Commun. 6, 8529 (2015).

    Article  ADS  Google Scholar 

  32. Mattila, P. K. et al. Missing-in-metastasis and IRSp53 deform PI(4,5)P2-rich membranes by an inverse BAR domain-like mechanism. J. Cell Biol. 176, 953–964 (2007).

    Article  Google Scholar 

  33. Yamagishi, A., Masuda, M., Ohki, T., Onishi, H. & Mochizuki, N. A novel actin bundling/filopodium-forming domain conserved in insulin receptor tyrosine kinase substrate p53 and missing in metastasis protein. J. Biol. Chem. 279, 14929–14936 (2004).

    Article  Google Scholar 

  34. Millard, T. H. et al. Structural basis of filopodia formation induced by the IRSp53/MIM homology domain of human IRSp53. EMBO J. 24, 240–250 (2005).

    Article  Google Scholar 

  35. Galic, M. et al. External push and internal pull forces recruit curvature-sensing N-BAR domain proteins to the plasma membrane. Nat. Cell Biol. 14, 874–881 (2012).

    Article  Google Scholar 

  36. Galic, M. et al. Dynamic recruitment of the curvature-sensitive protein ArhGAP44 to nanoscale membrane deformations limits exploratory filopodia initiation in neurons. eLife 3, e03116 (2014).

    Article  Google Scholar 

  37. Begemann, I., Viplav, A., Rasch, C. & Galic, M. Stochastic micro-pattern for automated correlative fluorescence–scanning electron microscopy. Sci. Rep. 5, 17973 (2015).

    Article  ADS  Google Scholar 

  38. Brock, A. et al. Geometric determinants of directional cell motility revealed using microcontact printing. Langmuir 19, 1611–1617 (2003).

    Article  Google Scholar 

  39. Suetsugu, S. et al. Optimization of WAVE2 complex-induced actin polymerization by membrane-bound IRSp53, PIP(3), and Rac. J. Cell Biol. 173, 571–585 (2006).

    Article  Google Scholar 

  40. Shutova, M., Yang, C., Vasiliev, J. M. & Svitkina, T. Functions of nonmuscle myosin II in assembly of the cellular contractile system. PloS ONE 7, e40814 (2012).

    Article  ADS  Google Scholar 

  41. Roux, A. et al. Membrane curvature controls dynamin polymerization. Proc. Natl Acad. Sci. USA 107, 4141–4146 (2010).

    Article  ADS  Google Scholar 

  42. Berg, H. C. & Brown, D. A. Chemotaxis in Escherichia coli analyzed by three-dimensional tracking. Antibiot. Chemother. 19, 55–78 (1974).

    Article  Google Scholar 

  43. Berg, H. C. & Brown, D. A. Chemotaxis in Escherichia coli analysed by three-dimensional tracking. Nature 239, 500–504 (1972).

    Article  ADS  Google Scholar 

  44. Huber, A. R., Kunkel, S. L., Todd, R. F. III & Weiss, S. J. Regulation of transendothelial neutrophil migration by endogenous interleukin-8. Science 254, 99–102 (1991).

    Article  ADS  Google Scholar 

  45. Kreisel, D. et al. In vivo two-photon imaging reveals monocyte-dependent neutrophil extravasation during pulmonary inflammation. Proc. Natl Acad. Sci. USA 107, 18073–18078 (2010).

    Article  ADS  Google Scholar 

  46. Zheng, D. et al. Abba promotes PDGF-mediated membrane ruffling through activation of the small GTPase Rac1. Biochem. Biophys. Res. Commun. 401, 527–532 (2010).

    Article  Google Scholar 

  47. Weiner, O. D. et al. Spatial control of actin polymerization during neutrophil chemotaxis. Nat. Cell Biol. 1, 75–81 (1999).

    Article  Google Scholar 

  48. Zheng, X. et al. Non-Gaussian statistics for the motion of self-propelled Janus particles, experiment versus theory. Phys Rev E 88, 032304 (2013).

    Article  ADS  Google Scholar 

  49. Yamada, D., Hondou, T. & Sano, M. Coherent dynamics of an asymmetric particle in a vertically vibrating bed. Phys Rev E 67, 040301 (2003).

    Article  ADS  Google Scholar 

  50. Wu, C. et al. BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. Genome Biol. 10, R130 (2009).

    Article  Google Scholar 

  51. Houk, A. R. et al. Membrane tension maintains cell polarity by confining signals to the leading edge during neutrophil migration. Cell 148, 175–188 (2012).

    Article  Google Scholar 

  52. Meinhardt, H. & Gierer, A. Applications of a theory of biological pattern formation based on lateral inhibition. J. Cell Sci. 15, 321–346 (1974).

    MATH  Google Scholar 

  53. Jilkine, A. & Edelstein-Keshet, L. A comparison of mathematical models for polarization of single eukaryotic cells in response to guided cues. PLoS Comput. Biol. 7, e1001121 (2011).

    Article  ADS  MathSciNet  Google Scholar 

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Acknowledgements

We would like to thank A. Ricker, K. Tkotz, J. Lehrich, A. Bodzeta, H. Nüsse and S. Kohaus for excellent technical assistance and N. Gov for insightful discussions on the force model. Special thanks go to R. Kurre from the integrated Bioimaging Facility Osnabrueck (iBIOs, University of Osnabrück) for help with LLM. This work was supported by funds from the DFG to M.G. (EXC-1003; GA 2268/2-1, CRC1348/A06, CRC944/P22), M.M. (EXC-1003/FF-2015-07), J.K. (CRC1348/A02, CRC944/P5) and V.G. (CRC1348/A04, CRC1009/A06) and the Medical Faculty of the University of Münster to M.G. (IMF IGA-121610) and M.M. (IZKF Mat2/019/16).

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Authors and Affiliations

  1. DFG Cluster of Excellence ‘Cells in Motion’, University of Münster, Muenster, Germany

    I. Begemann, T. Saha, L. Lamparter, I. Rathmann, D. Grill, L. Golbach, B. Trappmann, M. Matis, V. Gerke, J. Klingauf & M. Galic

  2. Institute of Medical Physics and Biophysics, University of Münster, Muenster, Germany

    I. Begemann, T. Saha, L. Lamparter, I. Rathmann, L. Golbach, C. Rasch, U. Keller, J. Klingauf & M. Galic

  3. Institute of Medical Biochemistry, ZMBE, University of Münster, Muenster, Germany

    D. Grill & V. Gerke

  4. Institute of Cell Biology, ZMBE, University of Münster, Muenster, Germany

    L. Golbach & M. Matis

  5. Max Planck Institute for Molecular Biomedicine, Muenster, Germany

    B. Trappmann

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  1. I. Begemann
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Contributions

I.B. performed all experimental work, except experiments with HUVEC cells and polyacrylamide gels. T.S. and I.B. developed image analysis software with input from M.M. and M.G. T.S. and I.B. performed optical tweezer experiments. T.S., L.L. and I.R. prepared mathematical models with input from I.B. and M.G. I.R. and B.T. performed polyacrylamide gel experiments. D.G., L.G., M.M. and V.G. performed HUVEC experiments. L.G. and M.M. performed quantitative PCR experiments. C.R., U.K. and J.K. prepared SEM images. I.B. and M.G. designed experiments, discussed results and wrote the manuscript with input from all authors.

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Correspondence to M. Galic.

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Supplementary Information

Supplementary Information

Supplementary Information, Supplementary Figures 1–6 and Supplementary References 1–84.

Reporting Summary

Supplementary Video 1

Single-cell trace depicting two-mode migration. NIH 3T3 cell was transfected with a cytosolic reference. Centre of mass is used to determine cell trace. Scale bar is 20 µm.

Supplementary Video 2

Lattice lightsheet of NIH 3T3 fibroblast. NIH 3T3 cell was transfected with f-tractin and imaged using LLM. Note extension–retraction cycles at the leading edge. Scale bar is 10 µm.

Supplementary Video 3

Lattice lightsheet of seed-like structure at retracting lamellipodium. NIH 3T3 cell transfected with f-tractin and imaged using LLM. Nascent lamellipodium appears at the base of retracting lamellipodium. Scale bar is 5 µm.

Supplementary Video 4

Lattice lightsheet of biosensor versus actin at leading edge. NIH 3T3 cell transfected with f-tractin (green) and biosensor (magenta), imaged using LLM. Videos depict 3D reconstruction (left), x/z re-slice (middle) and x/y re-slice (right). Scale bar (left, right) 5 µm, (middle) 2 µm.

Supplementary Video 5

Lattice lightsheet of biosensor versus paxillin at leading edge. NIH 3T3 fibroblast transfected with the FA marker paxillin (green) and the curvature-sensitive biosensor (magenta). Videos depict 3D reconstruction (left), x/z re-slice (middle) and x/y re-slice (right). Scale bar (left) 5 µm, (middle, right) 2 µm.

Supplementary Video 6

Minimal model of LE re-initiation. From left to right, simulation with default settings, in the absence of myosin-dependent pulling forces, in the absence of positive feedback loop and in the absence of adhesion.

Supplementary Video 7

Addition of ML-7 aborts lamellipodial re-initiation. Cell was transfected with a marker for filamentous actin (f-tractin). Note the loss of lamellipodial extension–retraction cycles, but not of stress fibres, on addition of ML-7. Scale bar is 20 µm.

Supplementary Video 8

Cell plated on Y-shaped micropattern shows continuous lamellipodium surrounding the whole cell. Cell plated on fibronectin-coated Y-shaped micropattern and transfected with f-tractin (red) and a cytosolic reference (green). Note lamellipodium enclosing the whole cell circumference. Scale bar is 10 µm.

Supplementary Video 9

Massive overexpression of I-BAR domain alters migration pattern. NIH 3T3 cells were transfected with a cytosolic marker (left) or the I-BAR domain (right) and imaged 20 h post-transfection. Scale bar is 20 µm.

Supplementary Video 10

Transition of migration pattern with increase of I-BAR levels. Starting 5 h post-transfection, images of NIH 3T3 cell transfected with I-BAR domain were taken for 15 h. Note loss of motion persistence as I-BAR levels increase with time. Scale bar is 20 µm.

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Begemann, I., Saha, T., Lamparter, L. et al. Mechanochemical self-organization determines search pattern in migratory cells. Nat. Phys. 15, 848–857 (2019). https://doi.org/10.1038/s41567-019-0505-9

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