Coordination of Rho GTPase activities during cell protrusion (original) (raw)

Nature volume 461, pages 99–103 (2009)Cite this article

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Abstract

The GTPases Rac1, RhoA and Cdc42 act together to control cytoskeleton dynamics1,2,3. Recent biosensor studies have shown that all three GTPases are activated at the front of migrating cells4,5,6,7, and biochemical evidence suggests that they may regulate one another: Cdc42 can activate Rac1 (ref. 8), and Rac1 and RhoA are mutually inhibitory9,10,11,12. However, their spatiotemporal coordination, at the seconds and single-micrometre dimensions typical of individual protrusion events, remains unknown. Here we examine GTPase coordination in mouse embryonic fibroblasts both through simultaneous visualization of two GTPase biosensors and using a ‘computational multiplexing’ approach capable of defining the relationships between multiple protein activities visualized in separate experiments. We found that RhoA is activated at the cell edge synchronous with edge advancement, whereas Cdc42 and Rac1 are activated 2 μm behind the edge with a delay of 40 s. This indicates that Rac1 and RhoA operate antagonistically through spatial separation and precise timing, and that RhoA has a role in the initial events of protrusion, whereas Rac1 and Cdc42 activate pathways implicated in reinforcement and stabilization of newly expanded protrusions.

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Change history

Author affiliations for P.N. were changed on 3 September 2009.

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Acknowledgements

We acknowledge funding from the Swiss National Science Foundation and the Novartis Foundation, formerly the Ciba-Geigy Jubilee Foundation (M.M.), NIH T32 GM008719 and NIH F30 HL094020 (C.W.), NIH R01 GM57464 (K.M.H.), NIH R01 GM71868 (G.D.), and the Cell Migration Consortium, grant U54 GM064346 from NIGMS (G.D. and K.M.H.).

Author Contributions M.M. initiated the project, conceptualized the idea of computational multiplexing, wrote all image analysis software pertinent to multiplexing, and contributed to the writing of the manuscript; L.H. developed simultaneous imaging of RhoA and Cdc42, including the modification and validation of the meroCBD probe, developed the intermolecular RhoA sensor, including controls and validation, studying the effects of biosensor stoichiometry and expression level, developed the new version of the Rac biosensor, and contributed to writing of the manuscript; C.W. produced stable cell lines of the intermolecular RhoA biosensor and conducted imaging experiments for the comparison of intra- and intermolecular biosensor designs; H.E. contributed simulations for validation of the correlation analysis and assisted with image processing; O.P. and P.N. contributed image data of RhoA and Cdc42 activity, respectively; A.A. and G.L.J. contributed valuable advice and unpublished reagents; K.M.H. and G.D. coordinated the study and wrote the final version of the manuscript and supplement.

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Author notes

  1. Matthias Machacek, Louis Hodgson & Olivier Pertz
    Present address: Present addresses: Novartis Pharma AG, Lichtstrasse 35, CH-4056 Basel, Switzerland (M.M.); Department of Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Ave, Bronx, New York 10461, USA (L.H.); Department of Biomedicine, University of Basel, Mattenstrasse 28, CH-4058 Basel, Switzerland (O.P.).,
  2. Matthias Machacek, Louis Hodgson and Christopher Welch: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Cell Biology, The Scripps Research Institute, 10550 N. Torrey Pines Road, La Jolla, California 92037, USA,
    Matthias Machacek, Hunter Elliott, Olivier Pertz & Gaudenz Danuser
  2. Departments of Pharmacology, Medicinal Chemistry and Lineberger Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA,
    Louis Hodgson, Christopher Welch, Amy Abell, Gary L. Johnson & Klaus M. Hahn
  3. Department of Molecular Cell Biology, Center for Medical Biotechnology, University of Duisburg-Essen, 45117 Essen, Germany
    Perihan Nalbant

Authors

  1. Matthias Machacek
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  2. Louis Hodgson
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  3. Christopher Welch
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  4. Hunter Elliott
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  5. Olivier Pertz
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  6. Perihan Nalbant
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  7. Amy Abell
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  8. Gary L. Johnson
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  9. Klaus M. Hahn
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  10. Gaudenz Danuser
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Corresponding authors

Correspondence toKlaus M. Hahn or Gaudenz Danuser.

Supplementary information

Supplementary Information

This file contains Supplementary Methods, Supplementary Data, Supplementary Figures S1-S10 with Legends and Supplementary References. Please note that the Movies appeared online in the wrong order and were corrected on 16th April 2010. (PDF 939 kb)

Supplementary Movie 1

This Movie shows the Rac1 activation measured using the FRET/CyPet ratio to monitor interaction between Rac1 and the p21-binding domain from PAK1 (see Figs. 1a, S1a). Left panel: corresponding time points imaged by DIC. Frame interval: 10 s. Replay: 10 frames/s. Duration of original sequence: 20 min. Magnification 40x, 2x2 binning. Scale bar: 20 µm. Colour-bar defines the dynamic range of the corrected FRET/CyPet ratio. (MOV 8200 kb)

Supplementary Movie 2

This Movie shows the zoom of the protrusive region of Movie 1. This sector of the cell edge is analyzed in Fig. 2. (MOV 4531 kb)

Supplementary Movie 3

This Movie shows the Cdc42 activation measured using the meroCBD biosensor (see Figs. 1b, S1b). Left panel: corresponding time points imaged by DIC. Frame interval: 10 s. Duration of original sequence: 13 min. Replay: 10 frames/s. Magnification 40x, 2x2 binning. Scale bar: 20 µm. Colour-bar defines the dynamic range of the merocyanine dye/EGFP ratio. (MOV 4778 kb)

Supplementary Movie 4

This Movie shows the zoom of the protrusive region of Movie 3. This sector of the cell edge is analyzed in Fig. 2. (MOV 4656 kb)

Supplementary Movie 5

This Movie shows the RhoA activation measured using the single chain, intramolecular FRET biosensor (see Figs. 1c, S1c). Left panel: corresponding time points imaged by DIC. Frame interval: 10 s. Replay: 10 frames/s. Duration of original sequence: 10 min. Magnification 40x, 2x2 binning. Scale bar: 20 µm. Colour-bar defines the dynamic range of the FRET/CFP ratio. (MOV 4506 kb)

Supplementary Movie 6

This Movie shows the zoom of the protrusive region of Movie 5. This sector of the cell edge is analyzed in Fig. 2. (MOV 5456 kb)

Supplementary Movie 7

This Movie shows sampling windows of 1.8 µm width and 0.9 µm depth placed at 0 µm and 2.5 µm from the edge follow the cell morphology. Windows are overlaid on the time lapse sequence shown in Movie 4. Frame interval: 10s. Replay: 10 frames/s. (MOV 3343 kb)

Supplementary Movie 8

This Movie shows the RhoA activation measured using the intermolecular dual chain FRET biosensor (see Figs. S1d, S10). Frame interval: 10 s. Replay: 10 frames/s. Magnification 40x, 2x2 binning. Scale bar: 20 µm. Colour-bar defines the dynamic range of the corrected FRET/CyPet ratio. (MOV 2775 kb)

Supplementary Movie 9

This Movie shows the zoomed view of protrusion and retraction activity of a randomly migrating MEF imaged simultaneously using Cdc42 and RhoA biosensors (see Fig. S7 for snapshots of the full view time sequence). Frame interval: 10s. Replay: 10 frames/s. Magnification 40x, 2x2 binning. Scale-bar: 15 μm. Colour-bar defines the dynamic range of the Cdc42 and RhoA signals. (MOV 7432 kb)

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Machacek, M., Hodgson, L., Welch, C. et al. Coordination of Rho GTPase activities during cell protrusion.Nature 461, 99–103 (2009). https://doi.org/10.1038/nature08242

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Editorial Summary

Rho GTPases during cell protrusion

The Rho GTPase family acts in concert to regulate cyoskeletal dynamics during processes such as cell motility. In this study, Danuser and colleagues study the coordination of RhoA, Rac1 and Cdc42 during cell migration by simultaneously visualizing two molecules using complementary biosensor designs, and by computationally defining the relationships between individual molecules visualized in separate cells. The latter approach demonstrates that different biosensors, imaged separately, can be freely combined to produce maps of relative signalling activities with seconds and single-micron resolution. These technologies pave the way to defining the dynamics of many proteins in large signal transduction networks.