Sam Duwé

Localizer: fast, accurate, open-source, and modular software package for superresolution microscopy

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.

RefSOFI for Mapping Nanoscale Organization of Protein-Protein Interactions in Living Cells

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 (ER) Ca(2+) sensor STIM1 and the pore-forming channel subunit ORAI1, a crucial process in store-operated Ca(2+) 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.

Model-free uncertainty estimation in stochastical optical fluctuation imaging (SOFI) leads to a doubled temporal resolution.

Stochastic optical fluctuation imaging (SOFI) is a super-resolution fluorescence imaging technique that makes use of stochastic fluctuations in the emission of the fluorophores. During a SOFI measurement multiple fluorescence images are acquired from the sample, followed by the calculation of the spatiotemporal cumulants of the intensities observed at each position. Compared to other techniques, SOFI works well under conditions of low signal-to-noise, high background, or high emitter densities. However, it can be difficult to unambiguously determine the reliability of images produced by any superresolution imaging technique. In this work we present a strategy that enables the estimation of the variance or uncertainty associated with each pixel in the SOFI image. In addition to estimating the image quality or reliability, we show that this can be used to optimize the signal-to-noise ratio (SNR) of SOFI images by including multiple pixel combinations in the cumulant calculation. We present an algorithm to perform this optimization, which automatically takes all relevant instrumental, sample, and probe parameters into account. Depending on the optical magnification of the system, this strategy can be used to improve the SNR of a SOFI image by 40% to 90%. This gain in information is entirely free, in the sense that it does not require additional efforts or complications. Alternatively our approach can be applied to reduce the number of fluorescence images to meet a particular quality level by about 30% to 50%, strongly improving the temporal resolution of SOFI imaging.

Sparse deconvolution of high-density super-resolution images

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.

Diffraction‐Unlimited Fluorescence Microscopy of Living Biological Samples Using pcSOFI

The complex microscopic nature of many live biological processes is often obscured by the diffraction limit of light, requiring diffraction‐unlimited fluorescence microscopy to resolve them. Because of the vast range of different processes that can be studied, sub‐diffraction imaging should work efficiently under many different conditions. Photochromic stochastic optical fluctuation imaging (pcSOFI) is a recent addition to the field of diffraction‐unlimited fluorescence microscopy. This robust and versatile method employs a statistical analysis of random fluctuations in the emission of single labels, in this case reversibly switchable fluorescent proteins (RSFPs), to retrieve super‐resolution information. Added to the resolution enhancement, pcSOFI also offers contrast enhancement and background reduction in a practical and convenient way. Here, we describe the necessary steps to obtain diffraction‐unlimited images, including multicolor and three‐dimensional imaging, and highlight the advantages of pcSOFI together with the circumstances under which pcSOFI can be favorably applied.

Super-resolution imaging goes fast and deep

Advances in image scanning microscopy move super-resolution imaging deeper into tissues with faster visualization and finer details.

A cost-effective approach to Super-resolution Optical Fluctuation (SOFI) microscopy using an industry-grade CMOS camera

Abstract Super-Resolution (SR) fluorescence microscopy is typically carried out on high-end research microscopes. Super-resolution Optical Fluctuation Imaging (SOFI) is a fast SR technique capable of live-cell imaging, that is compatible with many wide-field microscope systems. However, especially when employing fluorescent proteins, a key part of the imaging system is a very sensitive and well calibrated camera sensor. The substantial costs of such systems preclude many research groups from employing super-resolution imaging techniques. Here, we examine to what extent SOFI can be performed using a range of imaging hardware comprising different technologies and costs. In particular, we quantitatively compare the performance of an industry-grade CMOS camera to both state-of-the-art emCCD and sCMOS detectors, with SOFI-specific metrics. We show that SOFI data can be obtained using a cost-efficient industry-grade sensor, both on commercial and home-built microscope systems, though our analysis also readily exposes the merits of the per-pixel corrections performed in scientific cameras.Super-resolution (SR) fluorescence microscopy, especially at high speeds, is typically carried out on high-performance research microscopes. The substantial cost of such equipment, combined with the limited distribution of such instruments in imaging facilities, have complicated access to super-resolution imaging for research groups in the biosciences. In this work we promote the accessibility of Super-resolution Optical Fluctuation Imaging (SOFI) to the scientific community by demonstrating its flexibility in terms of the minimal required performance of the imaging system. We show that SOFI data can be acquired using a very cost-efficient industrial-grade detector on both a standard research microscope and an entirely home-built wide-field system. This enables more scientists to enter the field of live-cell super-resolution imaging, as it provides access to a robust and fast SR imaging modality at comparatively modest cost.

Reduced Fluorescent Protein Switching Fatigue by Binding-Induced Emissive State Stabilization

Reversibly switchable fluorescent proteins (RSFPs) enable advanced fluorescence imaging, though the performance of this imaging crucially depends on the properties of the labels. We report on the use of an existing small binding peptide, named Enhancer, to modulate the spectroscopic properties of the recently developed rsGreen series of RSFPs. Fusion constructs of Enhancer with rsGreen1 and rsGreenF revealed an increased molecular brightness and pH stability, although expression in living E. coli or HeLa cells resulted in a decrease of the overall emission. Surprisingly, Enhancer binding also increased off-switching speed and resistance to switching fatigue. Further investigation suggested that the RSFPs can interconvert between fast- and slow-switching emissive states, with the overall protein population gradually converting to the slow-switching state through irradiation. The Enhancer modulates the spectroscopic properties of both states, but also preferentially stabilizes the fast-switching state, supporting the increased fatigue resistance. This work demonstrates how the photo-physical properties of RSFPs can be influenced by their binding to other small proteins, which opens up new horizons for applications that may require such modulation. Furthermore, we provide new insights into the photoswitching kinetics that should be of general consideration when developing new RSFPs with improved or different photochromic properties.