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, Marek Cebecauer
Nat Commun. 2017-11-23; 8(1):
DOI: 10.1038/s41467-017-01857-x

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1. Nat Commun. 2017 Nov 23;8(1):1731. doi: 10.1038/s41467-017-01857-x.

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

Lukeš T(1)(2), Glatzová D(3)(4), Kvíčalová Z(3), Levet F(5)(6), Benda A(3)(7),
Letschert S(8), Sauer M(8), Brdička T(4), Lasser T(9), Cebecauer M(10).

Author information:
(1)Laboratoire d’Optique Biomédicale, École Polytechnique Fédérale de Lausanne,
STI-IBI, CH-1015, Lausanne, Switzerland.
(2)Department of Radioelectronics, FEE, Czech Technical University in Prague, 166
27, Prague, Czech Republic.
(3)Department of Biophysical Chemistry, J. Heyrovsky Institute of Physical
Chemistry, Czech Academy of Sciences, 182 23, Prague, Czech Republic.
(4)Laboratory of Leukocyte Signalling, Institute of Molecular Genetics, Czech
Academy of Sciences, 142 20, Prague, Czech Republic.
(5)Interdisciplinary Institute for Neuroscience, UMR 5297 CNRS Université de
Bordeaux, 33077, Bordeaux, France.
(6)Bordeaux Imaging Center, UMS 3420 CNRS Université de Bordeaux US4 INSERM,
33077, Bordeaux, France.
(7)Imaging Methods Core Facility, BIOCEV, 252 50, Vestec u Prahy, Czech Republic.
(8)Department of Biotechnology and Biophysics, Biocenter, University of
Wuerzburg, D-97074, Wuerzburg, Germany.
(9)Laboratoire d’Optique Biomédicale, École Polytechnique Fédérale de Lausanne,
STI-IBI, CH-1015, Lausanne, Switzerland. .
(10)Department of Biophysical Chemistry, J. Heyrovsky Institute of Physical
Chemistry, Czech Academy of Sciences, 182 23, Prague, Czech Republic.
.

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.

DOI: 10.1038/s41467-017-01857-x
PMCID: PMC5700985
PMID: 29170394

Auteurs Bordeaux Neurocampus