Author
Listed:
- Tomáš Lukeš
(École Polytechnique Fédérale de Lausanne, STI-IBI
Czech Technical University in Prague)
- Daniela Glatzová
(Czech Academy of Sciences
Czech Academy of Sciences)
- Zuzana Kvíčalová
(Czech Academy of Sciences)
- Florian Levet
(UMR 5297 CNRS Université de Bordeaux
UMS 3420 CNRS Université de Bordeaux US4 INSERM)
- Aleš Benda
(Czech Academy of Sciences
BIOCEV)
- 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)
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.
Suggested Citation
Tomáš Lukeš & Daniela Glatzová & Zuzana Kvíčalová & Florian Levet & Aleš Benda & Sebastian Letschert & Markus Sauer & Tomáš Brdička & Theo Lasser & Marek Cebecauer, 2017.
"Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging,"
Nature Communications, Nature, vol. 8(1), pages 1-7, December.
Handle:
RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-01857-x
DOI: 10.1038/s41467-017-01857-x
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-01857-x. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.