Super-resolution optical fluctuation imaging (SOFI) provides an elegant way of overcoming the diffraction limit in all three spatial dimensions by computing higher-order cumulants of image sequences of blinking fluorophores acquired with a classical widefield microscope. Previously, three-dimensional (3D) SOFI has been demonstrated by sequential imaging of multiple depth positions. Here we introduce a multiplexed imaging scheme for the simultaneous acquisition of multiple focal planes. Using 3D cross-cumulants, we show that the depth sampling can be increased. The simultaneous acquisition of multiple focal planes significantly reduces the acquisition time and thus the photobleaching. We demonstrate multiplane 3D SOFI by imaging fluorescently labelled cells over an imaged volume of up to 65 × 65 × 3.5 μm3 without depth scanning. In particular, we image the 3D network of mitochondria in fixed C2C12 cells immunostained with Alexa 647 fluorophores and the 3D vimentin structure in living Hela cells expressing the fluorescent protein Dreiklang.

Success in super-resolution imaging relies on a proper choice of fluorescent probes. Here, we suggest novel easily produced and biocompatible nanoparticles-carbon nanodots-for super-resolution optical fluctuation bioimaging (SOFI). The particles revealed an intrinsic dual-color fluorescence, which corresponds to two subpopulations of particles of different electric charges. The neutral nanoparticles localize to cellular nuclei suggesting their potential use as an inexpensive, easily produced nucleus-specific label. The single particle study revealed that the carbon nanodots possess a unique hybrid combination of fluorescence properties exhibiting characteristics of both dye molecules and semiconductor nanocrystals. The results suggest that charge trapping and redistribution on the surface of the particles triggers their transitions between emissive and dark states. These findings open up new possibilities for the utilization of carbon nanodots in the various super-resolution microscopy methods based on stochastic optical switching.

Stochastic Optical Fluctuation Imaging (SOFI) is a super-resolution fluorescence microscopy technique which allows to enhance the spatial resolution of an image by evaluating the temporal fluctuations of blinking fluorescent emitters. SOFI is not based on the identification and localization of single molecules such as in the widely used Photoactivation Localization Microsopy (PALM) or Stochastic Optical Reconstruction Microscopy (STORM), but computes a superresolved image via temporal cumulants from a recorded movie. A technical challenge hereby is that, when directly applying the SOFI algorithm to a movie of raw images, the pixel size of the final SOFI image is the same as that of the original images, which becomes problematic when the final SOFI resolution is much smaller than this value. In the past, sophisticated cross-correlation schemes have been used for tackling this problem. Here, we present an alternative, exact, straightforward, and simple solution using an interpolation scheme based on Fourier transforms. We exemplify the method on simulated and experimental data.

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