Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging

Tomáš Lukeš, Daniela Glatzová, Zuzana Kvíčalová, Florian Levet, Aleš Benda, Sebastian Letschert, Markus Sauer, Tomáš Brdička, Theo Lasser () and Marek Cebecauer ()
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Tomáš Lukeš: École Polytechnique Fédérale de Lausanne, STI-IBI
Daniela Glatzová: Czech Academy of Sciences
Zuzana Kvíčalová: Czech Academy of Sciences
Florian Levet: UMR 5297 CNRS Université de Bordeaux
Aleš Benda: Czech Academy of Sciences
Sebastian Letschert: University of Wuerzburg
Markus Sauer: University of Wuerzburg
Tomáš Brdička: Czech Academy of Sciences
Theo Lasser: École Polytechnique Fédérale de Lausanne, STI-IBI
Marek Cebecauer: Czech Academy of Sciences

Nature Communications, 2017, vol. 8, issue 1, 1-7

Abstract: Abstract Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed super-resolution imaging techniques. Current tools employ statistical algorithms to determine clusters of molecules based on single-molecule localization microscopy (SMLM) data. These approaches are limited by the ability of SMLM techniques to identify and localize molecules in densely populated areas and experimental conditions of sample preparation and image acquisition. We have developed a robust, model-free, quantitative clustering analysis to determine the distribution of membrane molecules that excels in densely labeled areas and is tolerant to various experimental conditions, i.e. multiple-blinking or high blinking rates. The method is based on a TIRF microscope followed by a super-resolution optical fluctuation imaging (SOFI) analysis. The effectiveness and robustness of the method is validated using simulated and experimental data investigating nanoscale distribution of CD4 glycoprotein mutants in the plasma membrane of T cells.

Date: 2017
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DOI: 10.1038/s41467-017-01857-x

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