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Nature-Methods, September 2015 - SR-Tesseler

SR-Tesseler: a method to segment and quantify localization-based super-resolution microscopy data

Due to the diffraction of light, the resolution of conventional light microscopy is limited as stated by Ernst Abbe in 1873. Localization-based super-resolution techniques are part of the techniques developed to break this diffraction limit and capture images at a higher resolution. They revolutionized the quantification of molecular organization by making it possible to monitor fluorescent probes in living cells close to molecular spatial resolution (a few nanometers). Despite its youth, this breakthrough was awarded with the Nobel Prize in Chemistry 2014. However, the analysis of the data acquired with these techniques often involves complex image processing adapted to the specific topology and quality of the image to be analyzed.

In a paper entitled “SR-Tesseler: a method to segment and quantify localization-based super-resolution microscopy data” published Monday 7 of September in Nature Methods, researchers from the IINS in Bordeaux developed a new method packaged as an open-source segmentation software. It allows precise, robust and automatic quantification of protein organization at different scales, from the cellular level down to clusters of a few fluorescent markers. SR-Tesseler is insensitive to cell shape, molecular organization, background and noise, allowing comparing efficiently different biological conditions in a non-biased manner, and perform quantifications on various proteins and cell types. SR-Tesseler software comes with a very simple and intuitive graphical user interface, providing direct visual feedback of the results and is freely available under GPLv3 license.

Florian Levet, Eric Hosy, Adel Kechkar, Corey Butler, Anne Beghin, Daniel Choquet & Jean-Baptiste Sibarita

Florian Levet and Jean-Baptiste Sibarita

- More informations can be found here:
- Published online: 7 September 2015