Widely accessible method for superresolution fluorescence imaging of living systems.

Research paper by Peter P Dedecker, Gary C H GC Mo, Thomas T Dertinger, Jin J Zhang

Indexed on: 20 Jun '12Published on: 20 Jun '12Published in: PNAS


Superresolution fluorescence microscopy overcomes the diffraction resolution barrier and allows the molecular intricacies of life to be revealed with greatly enhanced detail. However, many current superresolution techniques still face limitations and their implementation is typically associated with a steep learning curve. Patterned illumination-based superresolution techniques [e.g., stimulated emission depletion (STED), reversible optically-linear fluorescence transitions (RESOLFT), and saturated structured illumination microscopy (SSIM)] require specialized equipment, whereas single-molecule-based approaches [e.g., stochastic optical reconstruction microscopy (STORM), photo-activation localization microscopy (PALM), and fluorescence-PALM (F-PALM)] involve repetitive single-molecule localization, which requires its own set of expertise and is also temporally demanding. Here we present a superresolution fluorescence imaging method, photochromic stochastic optical fluctuation imaging (pcSOFI). In this method, irradiating a reversibly photoswitching fluorescent protein at an appropriate wavelength produces robust single-molecule intensity fluctuations, from which a superresolution picture can be extracted by a statistical analysis of the fluctuations in each pixel as a function of time, as previously demonstrated in SOFI. This method, which uses off-the-shelf equipment, genetically encodable labels, and simple and rapid data acquisition, is capable of providing two- to threefold-enhanced spatial resolution, significant background rejection, markedly improved contrast, and favorable temporal resolution in living cells. Furthermore, both 3D and multicolor imaging are readily achievable. Because of its ease of use and high performance, we anticipate that pcSOFI will prove an attractive approach for superresolution imaging.