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Dynamic kinesin-1 clustering on microtubules due to mutually attractive interactions

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Roos,  Wouter
Cellular Biophysics, Max Planck Institute for Medical Research, Max Planck Society;

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Spatz,  Joachim P.
Cellular Biophysics, Max Planck Institute for Medical Research, Max Planck Society;
Biophysical Chemistry, Institute of Physical Chemistry, University of Heidelberg, 69120 Heidelberg, Germany;

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Citation

Roos, W., Campàs, O., Montel, F., Woehlke, G., Spatz, J. P., Bassereau, P., et al. (2008). Dynamic kinesin-1 clustering on microtubules due to mutually attractive interactions. Physical Biology, 5(4): 046004, pp. 1-10. doi:10.1088/1478-3975/5/4/046004.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-4182-A
Abstract
Molecular motors often work collectively inside the cell. While the properties of individual motors have been extensively studied over the last decade, much less is known on how motors coordinate their action when working in ensembles. The motor collective behaviour in conditions where they contact each other, as in intracellular transport, may strongly depend on their mutual interactions. In particular, mutual interactions may result in motor clustering without the need of additional proteins. Here we study the interactions between kinesin-1 molecules by analysing their attachment/detachment kinetics on microtubules in the absence of motor motion. Our in vitro experiments show that kinesins-1 remain longer attached to the microtubule in the presence of neighbouring motors, resulting in the formation of motor clusters. Numerical simulations of the motor attachment/detachment dynamics show that the presence of attractive interactions between motors quantitatively accounts for the experimental observations. From the comparison of the numerical results and the experimental data we estimate the interaction energy between kinesin-1 molecules to be 1.6 +/- 0.5K(B)T. The existence of attractive interactions between kinesins-1 provides a new insight into the coordination mechanism between motor proteins and may be crucial to understand the large scale traffic in cells.