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Super-resolution microscopy wins the 2014 Nobel Prize in Chemistry

Super-resolution fluorescence microscopy is an emerging multidisciplinary field that has opened up new opportunities in studying the living cell at the nanometer scale. It overcomes the classical diffraction limit of Abbe, yielding images of biological structures that have lateral resolution down to 10 nm. One of the most promising techniques in this field is single molecule localization. It was announced Method of the Year 2008 by the Nature Methods journal [1] and was was recognized with the 2014 Nobel Prize in chemistry [2]. This technique has been gaining growing attention in microscopy, biology, and engineering conferences, among them ISBI, ever since. The method is based on exciting a spatially sparse set of fluorophores at each time instant, and on fitting the acquired images with a PSF (point spread function) model. This technique was originally proposed and introduced by three independent groups in 2006, giving rise to several acronyms: PALM (photo-activated localization microscopy by Eric Betzig et al.), STORM (stochastic optical reconstruction microscopy by Xiaowei Zhuang et al.), and F-PALM (fluorescence PALM by Samuel Hess). Unlike classical fluorescence microscopy, however, the acquired data cannot be visualized and inspected directly, and an additional processing step is required in this regard. The algorithmic aspects of the single molecule method are therefore extremely important, and this is the focus of the challenge we propose here.

Computational reconstruction by image-analysis software packages

There are currently numerous image-analysis software packages that process super resolution data. A typical data set consists of millions of excited fluorophores, distributed over thousands of images. The excited fluorophores are then detected, localized and visualized by these software tools. Automation is an indispensable aspect of the method [3] and a challenging task [4], as the data is very long image sequence.

Reference

• [1] Editorial, Method of the Year 2008, Nature Methods 6, 2009.
• [2] Eric Betzig, Stefan W. Hell and William E. Moerner, Development of super-resolved fluorescence microscopy, Nobel Prize in Chemistry 2014.
• [3] S. Manley, J. Gunzenhäuser, N. Olivier, A starter kit for point-localization super-resolution imaging, Current Opinion in Chemical Biology 15, 2011.
• [4] A.L. McEvoy, D. Greenfield, M. Bates, J. Liphardt, Single-molecule localization microscopy for biological imaging, BMC Biology, 8:106, 2010

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