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Plasmonic Nanosensors Reveal a Height Dependence of MinDE Protein Oscillations on Membrane Features

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Khmelinskaia,  Alena
Schwille, Petra / Cellular and Molecular Biophysics, Max Planck Institute of Biochemistry, Max Planck Society;

Heermann,  Tamara
Schwille, Petra / Cellular and Molecular Biophysics, Max Planck Institute of Biochemistry, Max Planck Society;

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Raso,  Ana
Schwille, Petra / Cellular and Molecular Biophysics, Max Planck Institute of Biochemistry, Max Planck Society;

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Schwille,  Petra
Schwille, Petra / Cellular and Molecular Biophysics, Max Planck Institute of Biochemistry, Max Planck Society;

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Citation

Ye, W., Celiksoy, S., Jakab, A., Khmelinskaia, A., Heermann, T., Raso, A., et al. (2018). Plasmonic Nanosensors Reveal a Height Dependence of MinDE Protein Oscillations on Membrane Features. Journal of the American Chemical Society, 140(51), 17901-17906. doi:10.1021/jacs.8b07759.


Cite as: http://hdl.handle.net/21.11116/0000-0002-D39A-2
Abstract
Single-particle plasmon spectroscopy has become a standard technique to detect and quantify the presence of unlabeled macromolecules. Here, we extend this method to determine their exact distance from the plasmon sensors with sub-nanometer resolution by systematically varying the sensing range into the surrounding by adjusting the size of the plasmonic nanoparticles. We improved current single-particle plasmon spectroscopy to record continuously for hours the scattering spectra of thousands of nanoparticles of different sizes simultaneously with 1.8 s time resolution. We apply this technique to study the interaction dynamics of bacterial Min proteins with supported lipid membranes of different composition. Our experiments reveal a surprisingly flexible operating mode of the Min proteins: In the presence of cardiolipin and membrane curvature induced by nanoparticles, the protein oscillation occurs on top of a stationary MinD patch. Our results reveal the need to consider membrane composition and local curvature as important parameters to quantitatively understand the Min protein system and could be extrapolated to other macromolecular systems. Our label-free method is generally easily implementable and well suited to measure distances of interacting biological macromolecules.