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Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging
T. Lukeš, D. Glatzová, Z. Kvíčalová, F. Levet, A. Benda, S. Letschert, M. Sauer, T. Brdička, T. Lasser, M. Cebecauer,
Language English Country England, Great Britain
Document type Journal Article, Research Support, Non-U.S. Gov't, Validation Study
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- MeSH
- Algorithms MeSH
- CD4 Antigens genetics metabolism MeSH
- Cell Membrane metabolism MeSH
- Fluorescent Dyes MeSH
- Microscopy, Fluorescence methods statistics & numerical data MeSH
- Jurkat Cells MeSH
- Humans MeSH
- Membrane Proteins genetics metabolism MeSH
- Mutant Proteins genetics metabolism MeSH
- Optical Imaging methods statistics & numerical data MeSH
- Cluster Analysis MeSH
- T-Lymphocytes immunology metabolism MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Validation Study MeSH
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.
References provided by Crossref.org
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- $a Lukeš, Tomáš $u Laboratoire d'Optique Biomédicale, École Polytechnique Fédérale de Lausanne, STI-IBI, CH-1015, Lausanne, Switzerland. Department of Radioelectronics, FEE, Czech Technical University in Prague, 166 27, Prague, Czech Republic.
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- $a 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.
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- $a Glatzová, Daniela $u Department of Biophysical Chemistry, J. Heyrovsky Institute of Physical Chemistry, Czech Academy of Sciences, 182 23, Prague, Czech Republic. Laboratory of Leukocyte Signalling, Institute of Molecular Genetics, Czech Academy of Sciences, 142 20, Prague, Czech Republic.
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- $a Kvíčalová, Zuzana $u Department of Biophysical Chemistry, J. Heyrovsky Institute of Physical Chemistry, Czech Academy of Sciences, 182 23, Prague, Czech Republic.
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- $a Levet, Florian $u Interdisciplinary Institute for Neuroscience, UMR 5297 CNRS Université de Bordeaux, 33077, Bordeaux, France. Bordeaux Imaging Center, UMS 3420 CNRS Université de Bordeaux US4 INSERM, 33077, Bordeaux, France.
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- $a Benda, Aleš $u Department of Biophysical Chemistry, J. Heyrovsky Institute of Physical Chemistry, Czech Academy of Sciences, 182 23, Prague, Czech Republic. Imaging Methods Core Facility, BIOCEV, 252 50, Vestec u Prahy, Czech Republic.
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- $a Letschert, Sebastian $u Department of Biotechnology and Biophysics, Biocenter, University of Wuerzburg, D-97074, Wuerzburg, Germany.
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- $a Cebecauer, Marek $u Department of Biophysical Chemistry, J. Heyrovsky Institute of Physical Chemistry, Czech Academy of Sciences, 182 23, Prague, Czech Republic. marek.cebecauer@jh-inst.cas.cz.
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