Effect of probe diffusion on the SOFI imaging accuracy

Cross-correlation increases sampling in diffusion-based super-resolution optical fluctuation imaging

Correlation signal processing of optical three-dimensional (x, y, t) data can produce super-resolution images. The second order cross-correlation function XC 2 has been documented to produce super-resolution imaging with static and blinking emitters but not for diffusing emitters. Here, we both analytically and numerically demonstrate cross-correlation analysis for diffusing particles. We then expand our fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) analysis to use cross-correlation as a post-processing computational technique to extract both dynamic and structural information of particle diffusion in nanoscale structures simultaneously. We further show how this method increases sampling rates and reduces aliasing for spatial information in both simulated and experimental data. Our work demonstrates how fcsSOFI with cross-correlation can be a powerful signal-processing tool to resolve the nanoscale dynamics and structure in samples relevant to biological and soft materials.

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Nanoparticles for super-resolution microscopy: intracellular delivery and molecular targeting

Following an overview of the approaches and techniques used to acheive super-resolution microscopy, this review presents the advantages supplied by nanoparticle based probes for these applications. The various clases of nanoparticles that have been developed toward these goals are then critically described and these discussions are illustrated with a variety of examples from the recent literature.

Design of experiments for the optimization of SOFI super-resolution microscopy imaging

Super-resolution optical fluctuation imaging (SOFI) is a well-known super-resolution technique appreciated for its versatility and broad applicability. However, even though an extended theoretical description is available, it is still not fully understood how the interplay between different experimental parameters influences the quality of a SOFI image. We investigated the relationship between five experimental parameters (measurement time, on-time t _on, off-time t _off, probe brightness, and out of focus background) and the quality of the super-resolved images they yielded, expressed as Signal to Noise Ratio (SNR). Empirical relationships were modeled for second- and third-order SOFI using data simulated according to a D-Optimal design of experiments, which is an ad-hoc design built to reduce the experimental load when the total number of trials to be conducted becomes too high for practical applications. This approach proves to be more reliable and efficient for parameter optimization compared to the more classical parameter by parameter approach. Our results indicate that the best image quality is achieved for the fastest emitter blinking (lowest t _on and t _off), lowest background level, and the highest measurement duration, while the brightness variation does not affect the quality in a statistically significant way within the investigated range. However, when the ranges spanned by the parameters are constrained, a different set of optimal conditions may arise. For example, for second-order SOFI, we identified situations in which the increase of t _off can be beneficial to SNR, such as when the measurement duration is long enough. In general, optimal values of t _on and t _off have been found to be highly dependent from each other and from the measurement duration.

Smoothness correction for better SOFI imaging

Sub-diffraction or super-resolution fluorescence imaging allows the visualization of the cellular morphology and interactions at the nanoscale. Statistical analysis methods such as super-resolution optical fluctuation imaging (SOFI) obtain an improved spatial resolution by analyzing fluorophore blinking but can be perturbed by the presence of non-stationary processes such as photodestruction or fluctuations in the illumination. In this work, we propose to use Whittaker smoothing to remove these smooth signal trends and retain only the information associated to independent blinking of the emitters, thus enhancing the SOFI signals. We find that our method works well to correct photodestruction, especially when it occurs quickly. The resulting images show a much higher contrast, strongly suppressed background and a more detailed visualization of cellular structures. Our method is parameter-free and computationally efficient, and can be readily applied on both two-dimensional and three-dimensional data.

Spectral cross-cumulants for multicolor super-resolved SOFI imaging

Super-resolution optical fluctuation imaging provides a resolution beyond the diffraction limit by analysing stochastic fluorescence fluctuations with higher-order statistics. Using nth order spatio-temporal cross-cumulants the spatial resolution and the sampling can be increased up to n-fold in all spatial dimensions. In this study, we extend the cumulant analysis into the spectral domain and propose a multicolor super-resolution scheme. The simultaneous acquisition of two spectral channels followed by spectral cross-cumulant analysis and unmixing increases the spectral sampling. The number of discriminable fluorophore species is thus not limited to the number of physical detection channels. Using two color channels, we demonstrate spectral unmixing of three fluorophore species in simulations and experiments in fixed and live cells. Based on an eigenvalue/vector analysis, we propose a scheme for an optimized spectral filter choice. Overall, our methodology provides a route for easy-to-implement multicolor sub-diffraction imaging using standard microscopes while conserving the spatial super-resolution property.

An extended quantitative model for super-resolution optical fluctuation imaging (SOFI)

Super-resolution optical fluctuation imaging (SOFI) provides super-resolution (SR) fluorescence imaging by analyzing fluctuations in the fluorophore emission. The technique has been used both to acquire quantitative SR images and to provide SR biosensing by monitoring changes in fluorophore blinking dynamics. Proper analysis of such data relies on a fully quantitative model of the imaging. However, previous SOFI imaging models made several assumptions that can not be realized in practice. In this work we address these limitations by developing and verifying a fully quantitative model that better approximates real-world imaging conditions. Our model shows that (i) SOFI images are free of bias, or can be made so, if the signal is stationary and fluorophores blink independently, (ii) allows a fully quantitative description of the link between SOFI imaging and probe dynamics, and (iii) paves the way for more advanced SOFI image reconstruction by offering a computationally fast way to calculate SOFI images for arbitrary probe, sample and instrumental properties.

Live-Cell Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (nanoscopy) enables imaging with a spatial resolution much higher than the diffraction limit of optical microscopy. However, the methods of fluorescence nanoscopy are still poorly suitable for studying living cells. In this review, we describe some of methods for nanoscopy and specific fluorescent labeling aimed to decrease the damaging effects of light illumination on live samples.

GMars-T Enabling Multimodal Subdiffraction Structural and Functional Fluorescence Imaging in Live Cells

Fluorescent probes with multimodal and multilevel imaging capabilities are highly valuable as imaging with such probes not only can obtain new layers of information but also enable cross-validation of results under different experimental conditions. In recent years, the development of genetically encoded reversibly photoswitchable fluorescent proteins (RSFPs) has greatly promoted the application of various kinds of live-cell nanoscopy approaches, including reversible saturable optical fluorescence transitions (RESOLFT) and stochastic optical fluctuation imaging (SOFI). However, these two classes of live-cell nanoscopy approaches require different optical characteristics of specific RSFPs. In this work, we developed GMars-T, a monomeric bright green RSFP which can satisfy both RESOLFT and photochromic SOFI (pcSOFI) imaging in live cells. We further generated biosensor based on bimolecular fluorescence complementation (BiFC) of GMars-T which offers high specificity and sensitivity in detecting and visualizing various protein-protein interactions (PPIs) in different subcellular compartments under physiological conditions (e.g., 37 °C) in live mammalian cells. Thus, the newly developed GMars-T can serve as both structural imaging probe with multimodal super-resolution imaging capability and functional imaging probe for reporting PPIs with high specificity and sensitivity based on its derived biosensor.

Directed Evolution to Engineer Monobody for FRET Biosensor Assembly and Imaging at Live-Cell Surface

Monitoring enzymatic activities at the cell surface is challenging due to the poor efficiency of transport and membrane integration of fluorescence resonance energy transfer (FRET)-based biosensors. Therefore, we developed a hybrid biosensor with separate donor and acceptor that assemble in situ. The directed evolution and sequence-function analysis technologies were integrated to engineer a monobody variant (PEbody) that binds to R-phycoerythrin (R-PE) dye. PEbody was used for visualizing the dynamic formation/separation of intercellular junctions. We further fused PEbody with the enhanced CFP and an enzyme-specific peptide at the extracellular surface to create a hybrid FRET biosensor upon R-PE capture for monitoring membrane-type-1 matrix metalloproteinase (MT1-MMP) activities. This biosensor revealed asymmetric distribution of MT1-MMP activities, which were high and low at loose and stable cell-cell contacts, respectively. Therefore, directed evolution and rational design are promising tools to engineer molecular binders and hybrid FRET biosensors for monitoring molecular regulations at the surface of living cells.

Observing the Assembly of Protein Complexes in Living Eukaryotic Cells in Super-Resolution Using refSOFI

Few approaches are currently available that allow the detection of protein-protein interactions (PPIs) in super-resolution, and the observation of the assembly of protein complexes in living cells has been particularly challenging. We developed reconstituted fluorescence-based stochastic optical fluctuation imaging (refSOFI), which is based on bimolecular fluorescence complementation (BiFC) and SOFI, allowing us to detect protein complex assembly 30 min after the induction of complex formation. Here we describe how to use refSOFI to map the assembly of two proteins of interest into a complex within living cells at super-resolution.

Correcting for photodestruction in super-resolution optical fluctuation imaging

Super-resolution optical fluctuation imaging overcomes the diffraction limit by analyzing fluctuations in the fluorophore emission. A key assumption of the imaging is that the fluorophores are independent, though this is invalidated in the presence of photodestruction. In this work, we evaluate the effect of photodestruction on SOFI imaging using theoretical considerations and computer simulations. We find that photodestruction gives rise to an additional signal that does not present an easily interpretable view of the sample structure. This additional signal is strong and the resulting images typically exhibit less noise. Accordingly, these images may be mis-interpreted as being more visually pleasing or more informative. To address this uncertainty, we develop a procedure that can robustly estimate to what extent any particular experiment is affected by photodestruction. We also develop a detailed assessment methodology and use it to evaluate the performance of several correction algorithms. We identify two approaches that can correct for the presence of even strong photodestruction, one of which can be implemented directly in the SOFI calculation software.

Live-cell monochromatic dual-label sub-diffraction microscopy by mt-pcSOFI

We present mt-pcSOFI, live-cell monochromatic sub-diffraction imaging and illustrate the method with existing RSFPs and the newly developed ffDronpa-F.