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Multiplexed GTPase and GEF biosensor imaging enables network connectivity analysis

Abstract

Here we generate fluorescence resonance energy transfer biosensors for guanine exchange factors (GEFs) by inserting a fluorescent protein pair in a structural ‘hinge’ common to many GEFs. Fluorescent biosensors can map the activation of signaling molecules in space and time, but it has not been possible to quantify how different activation events affect one another or contribute to a specific cell behavior. By imaging the GEF biosensors in the same cells as red-shifted biosensors of Rho GTPases, we can apply partial correlation analysis to parse out the extent to which each GEF contributes to the activation of a specific GTPase in regulating cell movement. Through analysis of spontaneous cell protrusion events, we identify when and where the GEF Asef regulates the GTPases Cdc42 and Rac1 to control cell edge dynamics. This approach exemplifies a powerful means to elucidate the real-time connectivity of signal transduction networks.

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Fig. 1: Biosensors for Asef and Vav2.
Fig. 2: Biosensors for RhoGEFs without high-resolution structures.
Fig. 3: RhoGEF and GTPase activity in living cells.
Fig. 4: Correlation of protein activities with edge motion.
Fig. 5: Multiplex imaging of two protein activities.
Fig. 6: Partial correlation analysis.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. Figures 46 have associated raw data used to produce the correlation plots.

Code availability

All code used for the data analysis was written in MATLAB 2014b. All the code can be downloaded from the Danuser Lab github: https://github.com/DanuserLab under Biosensor, Windowing-Protrusion and Time-Series-Tools repositories.

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Acknowledgements

Grant nos. R01-GM062299 (J.S.), R01 GM071868 (G.D.) and R35GM122596 (K.M.H.) supported this work. D.J.M. was supported by funding from the Leukemia and Lymphoma Society. J.H. was supported by a Human Frontiers in Sciences Program. G.G. was supported by the ‘Integrated Training in Cancer Model Systems’ Training Program, T32CA009156. We thank the Calabrese laboratory and F. Pimenta for the shRNA expression vector.

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D.J.M., J.S. and K.M.H. designed the biosensors. D.J.M. carried out all experiments, except for work by J.R. in building Tiam1, Tim, B-Pix and LARG biosensors. G.G. and M.A. contributed to initial design of Tim and LARG biosensors, respectively. M.V., J.H. and G.D. developed and carried out computational analysis. G.D., J.S. and K.M.H. provided intellectual input in all phases of the study and directed the work. The paper was written by D.J.M., M.V., G.D., J.S. and K.M.H., with input from all authors.

Corresponding authors

Correspondence to Gaudenz Danuser, John Sondek or Klaus M. Hahn.

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Supplementary Figs. 1–10.

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Supplementary Video 1

Cdc42 (left) and Rac1 (right) activation reported by biosensors in MDA-MB-231 cells undergoing random edge motion.

Supplementary Video 2

Asef (left, middle) and Vav2 (right) activation reported by biosensors in MDA-MB-231 cells undergoing random edge motion.

Supplementary Video 3

Simultaneously imaged RhoGEF and Rho GTPase biosensors in MDA-MB-231 cells undergoing constitutive edge motion.

Supplementary Video 4

Simultaneously imaged Cdc42 and Rac1 biosensors in MDA-MB-231 cells undergoing constitutive edge motion.

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Marston, D.J., Vilela, M., Huh, J. et al. Multiplexed GTPase and GEF biosensor imaging enables network connectivity analysis. Nat Chem Biol 16, 826–833 (2020). https://doi.org/10.1038/s41589-020-0542-9

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