Fast live-cell conventional fluorophore nanoscopy with ImageJ through super-resolution radial fluctuations

Abstract

Despite significant progress, high-speed live-cell super-resolution studies remain limited to specialized optical setups, generally requiring intense phototoxic illumination. Here, we describe a new analytical approach, super-resolution radial fluctuations (SRRF), provided as a fast graphics processing unit-enabled ImageJ plugin. In the most challenging data sets for super-resolution, such as those obtained in low-illumination live-cell imaging with GFP, we show that SRRF is generally capable of achieving resolutions better than 150 nm. Meanwhile, for data sets similar to those obtained in PALM or STORM imaging, SRRF achieves resolutions approaching those of standard single-molecule localization analysis. The broad applicability of SRRF and its performance at low signal-to-noise ratios allows super-resolution using modern widefield, confocal or TIRF microscopes with illumination orders of magnitude lower than methods such as PALM, STORM or STED. We demonstrate this by super-resolution live-cell imaging over timescales ranging from minutes to hours.

Introduction

Camera based super-resolution approaches such as photoactivated localization microscopy (PALM)1 and Stochastic Optical Reconstruction Microscopy (STORM)2 have become well-established methods for structural cell biology studies, achieving lateral resolutions under 30 nm. Comparably, structured illumination microscopy (SIM)3, is an attractive alternative approach for live-cell super-resolution due to the reduced illumination requirements, fast acquisition rates and compatibility with conventional fluorophores such as greenfluorescent protein (GFP). SIM, however, requires expensive additional optical components to achieve resolutions on the order of B150 nm. As a consequence, recent years have seen considerable focus put on adapting PALM- and STORM-like approaches to allow live-cell nanoscopy. These single-molecule localization microscopy (SMLM) approaches circumvent Abbe’s diffraction limit through the acquisition of a large sequence of frames (typically thousands), each containing a small population of transiently emitting non-overlapping fluorophores. The analytical detection and localization of these individually resolvable fluorophores populates a highly accurate map of fluorophore positions1,2.

Live-cell SMLM depends on the capacity to detect enough fluorophores to super-resolve structures, in a time small enough to minimize motion-blur artefacts4–6. A recent analysis of 430 software packages designed for processing SMLM data7 shows that these algorithms are capable of approaching the Crame´r–Rao theoretical precision limit8 when the distance between emitting fluorophores is 4B1.5 mm. Some specialized ‘high-density’ algorithms are capable of localizing fluorophores separated by distances in the range of 1.5 mm down to 0.15 mm at the cost of poorer precision7,9. Nonetheless, at smaller separations (or equivalently, higher densities), even these algorithms suffer from substantial imprecision, poor recall and artefacts7. As a consequence, it becomes critical to maintain the density of fluorophores actively emitting in each acquired frame within the boundaries of the analytical approach used. This task is difficult or impossible when dealing with dynamic processes in cells that frequently present a large heterogeneity in fluorophore densities. Three algorithms in particular have overcome this maximum density limit by circumventing the requirement for individual fluorophore localizations. These are deconSTORM10, which reconstructs super-resolution images by averaging extensively deconvolved images of sub-populations of fluorophores; 3B (ref. 11), which uses Bayesian analysis; and super-resolution optical fluctuation imaging (SOFI)12, which uses higher-order statistical analysis of temporal fluorophore intensity fluctuations.

Here, we present a novel analytical approach, super-resolution radial fluctuations (SRRF), which follows similar principles to deconSTORM, 3B and SOFI, where analysis of a sequence of images acquired in a standard widefield or total internal reflection fluorescence (TIRF) microscope directly generates a superresolution reconstruction without fluorophore detection and localization. However, contrary to other approaches, SRRF provides a single analytical framework that enables high-fidelity reconstructions for a wide variety of data sets, with the final resolution of the SRRF image dictated by the properties of the data set analysed. For example, super-resolution reconstructions at a resolution of at least 50 nm, comparable to current benchmark localization algorithms, are obtained for SMLM data. High-resolution reconstructions are also obtained for confocal microscopy data (80–98 nm) and widefield LED-illuminated data (103–106 nm). Moreover, super-resolution information at a temporal resolution of 1 s and a spatial resolution down to 60 nm can be extracted from live samples using conventional fluorophores, low-intensity illumination and as few as 100 raw frames.

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