Abstract. We present Localizer, a freely available and open source software package that implements the computational data processing inherent to several types of superresolution fluorescence imaging, such as localization (PALM/STORM/GSDIM) and fluctuation imaging (SOFI/pcSOFI). Localizer delivers high accuracy and performance and comes with a fully featured and easy-to-use graphical user interface but is also designed to be integrated in higher-level analysis environments. Due to its modular design, Localizer can be readily extended with new algorithms as they become available, while maintaining the same interface and performance. We provide front-ends for running Localizer from Igor Pro, Matlab, or as a stand-alone program. We show that Localizer performs favorably when compared with two existing superresolution packages, and to our knowledge is the only freely available implementation of SOFI/pcSOFI microscopy. By dramatically improving the analysis performance and ensuring the easy addition of current and future enhancements, Localizer strongly improves the usability of superresolution imaging in a variety of biomedical studies.

Smart fluorophores", such as reversibly switchable fluorescent proteins (RSFPs), are crucial for advanced fluorescence imaging. However, only a limited number of such labels is available and many display reduced biological performance compared to more classical variants.We present the development of robustly photoswitchable variants of EGFP, named rsGreens, that display up to 30-fold higher fluorescence in E. coli colonies grown at 37°C and more than 4-fold higher fluorescence when expressed in HEK293T cells compared to their ancestor protein rsEGFP. This enhancement is not due to an intrinsic increase in the fluorescence brightness of the probes, but rather due to enhanced expression levels that allow many more probe molecules to be functional at any given time. We developed rsGreens displaying a range of photoswitching kinetics and show how these can be used for multi-modal diffraction-unlimited fluorescence imaging such as pcSOFI and RESOLFT, achieving a spatial resolution of ~70 nm. By determining the first ever crystal structures of a negative reversibly switchable FP derived from Aequorea victoria in both the "on"-and "off"-conformation we were able to confirm the presence of a cis-trans isomerization and provide further insights into the mechanisms underlying the photochromism. Our work demonstrates that genetically encoded "smart fluorophores" can be readily optimized for biological performance, and provides a practical strategy for developing maturation-and stability-enhanced photochromic fluorescent proteins.KEYWORDS: fluorescent proteins, reversible photoswitching, super-resolution fluorescence microscopy, SOFI, RESOLFT, crystal structure determination, rsEGFP, superfolder Fluorescent proteins (FPs) enable the minimally-invasive labeling of intracellular structures in live systems. 1 The discovery and development of "smart photoactive FPs", 2,3 with features such as irreversible photoactivation and photoconversion, or reversible photoswitching, allowed the development of diffraction-unlimited imaging techniques such as (f)PALM 4,5 ((fluorescence) photoactivated localization microscopy), RESOLFT 6 (reversible saturable optical fluorescence transitions) and (pc)SOFI 7,8 ((photochromic) stochastic optical fluctuation imaging). These techniques strongly rely on the performance of the fluorophores and considerable efforts have therefore been dedicated to create optimized "smart labels". 9 This is exemplified by the continuous optimization and diversification of the EosFP family, 10-15 or the development of Dronpa 16 mutants with different or added photophysical properties. [17][18][19][20][21][22] Probes that combine multiple "smart" behaviors have also been engineered. [23][24][25] On the whole, however, the general acceptance of the FP-based "smart labels" has not quite risen up to the high expectations set by the many applications they enable. In some cases this is due to concerns surrounding the biological compatibility of the labels, meaning that the label may interfere with the functioning of the syst...

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Summary It has become increasingly clear that protein-protein interactions (PPIs) are compartmentalized in nanoscale domains that define the biochemical architecture of the cell. Despite tremendous advances in super-resolution imaging, strategies to observe PPIs at sufficient resolution to discern their organization are just emerging. Here we describe a strategy in which PPIs induce reconstitution of fluorescent proteins (FPs) that are capable of exhibiting single-molecule fluctuations suitable for Stochastic Optical Fluctuation Imaging (SOFI). Subsequently, spatial maps of these interactions can be resolved in super-resolution in living cells. Using this strategy, termed reconstituted fluorescence-based SOFI (refSOFI), we investigated the interaction between the endoplasmic reticulum Ca2+ sensor STIM1 and the pore-forming channel subunit ORAI1, a crucial process in store-operated Ca2+ entry (SOCE). Stimulating SOCE does not appear to change the size of existing STIM1/ORAI1 interaction puncta at the ER-plasma membrane junctions, but results in an apparent increase in the number of interaction puncta.

In wide-field super-resolution microscopy, investigating the nanoscale structure of cellular processes, and resolving fast dynamics and morphological changes in cells requires algorithms capable of working with a high-density of emissive fluorophores. Current deconvolution algorithms estimate fluorophore density by using representations of the signal that promote sparsity of the super-resolution images via an L1-norm penalty. This penalty imposes a restriction on the sum of absolute values of the estimates of emitter brightness. By implementing an L0-norm penalty – on the number of fluorophores rather than on their overall brightness – we present a penalized regression approach that can work at high-density and allows fast super-resolution imaging. We validated our approach on simulated images with densities up to 15 emitters per μm-2 and investigated total internal reflection fluorescence (TIRF) data of mitochondria in a HEK293-T cell labeled with DAKAP-Dronpa. We demonstrated super-resolution imaging of the dynamics with a resolution down to 55 nm and a 0.5 s time sampling.