Mitochondrial STED Imaging and Membrane Potential Monitoring with a Cationic Molecular Probe

Mitochondria are essential organelles that not only undergo dynamic morphological changes but also exhibit functional activities such as mitochondrial membrane potential (MMP). While super-resolution techniques such as stimulated emission depletion (STED) nanoscopy can visualize the ultrastructure of mitochondria and the MMP probe can monitor mitochondria function, few dyes meet both demands. Here, a small molecule (MitoPDI-90) based on perylene diimide with cationic groups is reported and used for mitochondrial STED imaging and MMP indication. Characterized by excellent photostability, biocompatibility, and high quantum yield, MitoPDI-90 exhibits STED imaging compatibility, facilitating visualization of mitochondrial cristae and time-lapse imaging of highly dynamic mitochondria in living cells. Besides, MitoPDI-90 targets the mitochondria through electrical potential, also enabling live-cell MMP monitoring. MitoPDI-90 allows for super-resolution visualization and time-lapse imaging of mitochondria, and more importantly, indication of changes in MMP, providing insight into the functional activity of live-cell mitochondria.

Parameter-free super-resolution structured illumination microscopy via a physics-enhanced neural network

With full-field imaging and high photon efficiency advantages, structured illumination microscopy (SIM) is one of the most potent super-resolution (SR) modalities in bioscience. Regarding SR reconstruction for SIM, spatial domain reconstruction (SDR) has been proven to be faster than traditional frequency domain reconstruction (FDR), facilitating real-time imaging of live cells. Nevertheless, SDR relies on high-precision parameter estimation for reconstruction, which tends to suffer from low signal-to-noise ratio (SNR) conditions and inevitably leads to artifacts that seriously affect the accuracy of SR reconstruction. In this Letter, a physics-enhanced neural network-based parameter-free SDR (PNNP-SDR) is proposed, which can achieve SR reconstruction directly in the spatial domain. As a result, the peak-SNR (PSNR) of PNNP-SDR is improved by about 4 dB compared to the cross-correlation (COR) SR reconstruction; meanwhile, the reconstruction speed of PNNP-SDR is even about five times faster than the fast approach based on principal component analysis (PCA). Given its capability of achieving parameter-free imaging, noise robustness, and high-fidelity and high-speed SR reconstruction over conventional SIM microscope hardware, the proposed PNNP-SDR is expected to be widely adopted in biomedical SR imaging scenarios.

Facile Conversion and Optimization of Structured Illumination Image Reconstruction Code into the GPU Environment

Superresolution, structured illumination microscopy (SIM) is an ideal modality for imaging live cells due to its relatively high speed and low photon-induced damage to the cells. The rate-limiting step in observing a superresolution image in SIM is often the reconstruction speed of the algorithm used to form a single image from as many as nine raw images. Reconstruction algorithms impose a significant computing burden due to an intricate workflow and a large number of often complex calculations to produce the final image. Further adding to the computing burden is that the code, even within the MATLAB environment, can be inefficiently written by microscopists who are noncomputer science researchers. In addition, they do not take into consideration the processing power of the graphics processing unit (GPU) of the computer. To address these issues, we present simple but efficient approaches to first revise MATLAB code, followed by conversion to GPU-optimized code. When combined with cost-effective, high-performance GPU-enabled computers, a 4- to 500-fold improvement in algorithm execution speed is observed as shown for the image denoising Hessian-SIM algorithm. Importantly, the improved algorithm produces images identical in quality to the original.

PCNA as Protein-Based Nanoruler for Sub-10 nm Fluorescence Imaging

Super-resolution microscopy has revolutionized biological imaging enabling direct insight into cellular structures and protein arrangements with so far unmatched spatial resolution. Today, refined single-molecule localization microscopy methods achieve spatial resolutions in the one-digit nanometer range. As the race for molecular resolution fluorescence imaging with visible light continues, reliable biologically compatible reference structures will become essential to validate the resolution power. Here, PicoRulers (protein-based imaging calibration optical rulers), multilabeled oligomeric proteins designed as advanced molecular nanorulers for super-resolution fluorescence imaging are introduced. Genetic code expansion (GCE) is used to site-specifically incorporate three noncanonical amino acids (ncAAs) into the homotrimeric proliferating cell nuclear antigen (PCNA) at 6 nm distances. Bioorthogonal click labeling with tetrazine-dyes and tetrazine-functionalized oligonucleotides allows efficient labeling of the PicoRuler with minimal linkage error. Time-resolved photoswitching fingerprint analysis is used to demonstrate the successful synthesis and DNA-based points accumulation for imaging in nanoscale topography (DNA-PAINT) is used to resolve 6 nm PCNA PicoRulers. Since PicoRulers maintain their structural integrity under cellular conditions they represent ideal molecular nanorulers for benchmarking the performance of super-resolution imaging techniques, particularly in complex biological environments.

Superresolution structured illumination microscopy reconstruction algorithms: a review

Structured illumination microscopy (SIM) has become the standard for next-generation wide-field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view, and long-term imaging. Over the past decade, SIM hardware and software have flourished, leading to successful applications in various biological questions. However, unlocking the full potential of SIM system hardware requires the development of advanced reconstruction algorithms. Here, we introduce the basic theory of two SIM algorithms, namely, optical sectioning SIM (OS-SIM) and superresolution SIM (SR-SIM), and summarize their implementation modalities. We then provide a brief overview of existing OS-SIM processing algorithms and review the development of SR-SIM reconstruction algorithms, focusing primarily on 2D-SIM, 3D-SIM, and blind-SIM. To showcase the state-of-the-art development of SIM systems and assist users in selecting a commercial SIM system for a specific application, we compare the features of representative off-the-shelf SIM systems. Finally, we provide perspectives on the potential future developments of SIM.

Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy

Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells. However, during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures, limits this technique from becoming a routine imaging tool for biologists. To address these issues, an accelerated, artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm (JSFR-AR-SIM) was developed by integrating a high-speed reconstruction framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact. Consequently, JSFR-AR-SIM produces high-quality, super-resolution images with minimal artifacts, and the reconstruction speed is increased. We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories.

Electron-beam patterned calibration structures for structured illumination microscopy

Super-resolution fluorescence microscopy can be achieved by image reconstruction after spatially patterned illumination or sequential photo-switching and read-out. Reconstruction algorithms and microscope performance are typically tested using simulated image data, due to a lack of strategies to pattern complex fluorescent patterns with nanoscale dimension control. Here, we report direct electron-beam patterning of fluorescence nanopatterns as calibration standards for super-resolution fluorescence. Patterned regions are identified with both electron microscopy and fluorescence labelling of choice, allowing precise correlation of predefined pattern dimensions, a posteriori obtained electron images, and reconstructed super-resolution images.

Total variation and spatial iteration-based 3D structured illumination microscopy

Three-dimensional structured illumination microscopy (3D-SIM) plays an essential role in biological volumetric imaging with the capabilities of improving lateral and axial resolution. However, the traditional linear 3D algorithm is sensitive to noise and generates artifacts, while the low temporal resolution hinders live-cell imaging. In this paper, we propose a novel 3D-SIM algorithm based on total variation (TV) and fast iterative shrinkage threshold algorithm (FISTA), termed TV-FISTA-SIM. Compared to conventional algorithms, TV-FISTA-SIM achieves higher reconstruction fidelity with the least artifacts, even when the signal-to-noise ratio (SNR) is as low as 5 dB, and a faster reconstruction rate. Through simulation, we have verified that TV-FISTA-SIM can effectively reduce the amount of required data with less deterioration. Moreover, we demonstrate TV-FISTA-SIM for high-quality multi-color 3D super-resolution imaging, which can be potentially applied to live-cell imaging applications.

Frequency-spatial domain joint optimization for improving super-resolution images of nonlinear structured illumination microscopy

Introducing nonlinear fluorophore excitation into structured illumination microscopy (SIM) can further extend its spatial resolution without theoretical limitation. However, it is a great challenge to recover the weak higher-order harmonic signal and reconstruct high-fidelity super-resolution (SR) images. Here, we proposed a joint optimization strategy in both the frequency and spatial domains to reconstruct high-quality nonlinear SIM (NL-SIM) images. We demonstrate that our method can reconstruct SR images with fewer artifacts and higher fidelity on the BioSR dataset with patterned-activation NL-SIM. This method could robustly overcome one of the long-lived obstacles on NL-SIM imaging, thereby promoting its wide application in biology.

Structured illumination microscopy with noise-controlled image reconstructions

Super-resolution structured illumination microscopy (SIM) has become a widely used method for biological imaging. Standard reconstruction algorithms, however, are prone to generate noise-specific artifacts that limit their applicability for lower signal-to-noise data. Here we present a physically realistic noise model that explains the structured noise artifact, which we then use to motivate new complementary reconstruction approaches. True-Wiener-filtered SIM optimizes contrast given the available signal-to-noise ratio, and flat-noise SIM fully overcomes the structured noise artifact while maintaining resolving power. Both methods eliminate ad hoc user-adjustable reconstruction parameters in favor of physical parameters, enhancing objectivity. The new reconstructions point to a trade-off between contrast and a natural noise appearance. This trade-off can be partly overcome by further notch filtering but at the expense of a decrease in signal-to-noise ratio. The benefits of the proposed approaches are demonstrated on focal adhesion and tubulin samples in two and three dimensions, and on nanofabricated fluorescent test patterns.

Structured illumination microscopy artefacts caused by illumination scattering

Despite its wide application in live-cell super-resolution (SR) imaging, structured illumination microscopy (SIM) suffers from aberrations caused by various sources. Although artefacts generated from inaccurate reconstruction parameter estimation and noise amplification can be minimized, aberrations due to the scattering of excitation light on samples have rarely been investigated. In this paper, by simulating multiple subcellular structure with the distinct refractive index from water, we study how different thicknesses of this subcellular structure scatter incident light on its optical path of SIM excitation. Because aberrant interference light aggravates with the increase in sample thickness, the reconstruction of the 2D-SIM SR image degraded with the change of focus along the axial axis. Therefore, this work may guide the future development of algorithms to suppress SIM artefacts caused by scattering in thick samples. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Super-resolution STED microscopy in live brain tissue

STED microscopy is one of several fluorescence microscopy techniques that permit imaging at higher spatial resolution than what the diffraction-limit of light dictates. STED imaging is unique among these super-resolution modalities in being a beam-scanning microscopy technique based on confocal or 2-photon imaging, which provides the advantage of superior optical sectioning in thick samples. Compared to the other super-resolution techniques that are based on widefield microscopy, this makes STED particularly suited for imaging inside live brain tissue, such as in slices or in vivo. Notably, the 50 nm resolution provided by STED microscopy enables analysis of neural morphologies that conventional confocal and 2-photon microscopy approaches cannot resolve, including all-important synaptic structures. Over the course of the last 20 years, STED microscopy has undergone extensive developments towards ever more versatile use, and has facilitated remarkable neurophysiological discoveries. The technique is still not widely adopted for live tissue imaging, even though one of its particular strengths is exactly in resolving the nanoscale dynamics of synaptic structures in brain tissue, as well as in addressing the complex morphologies of glial cells, and revealing the intricate structure of the brain extracellular space. Not least, live tissue STED microscopy has so far hardly been applied in settings of pathophysiology, though also here it shows great promise for providing new insights. This review outlines the technical advantages of STED microscopy for imaging in live brain tissue, and highlights key neurobiological findings brought about by the technique.

High-fidelity structured illumination microscopy by point-spread-function engineering

Structured illumination microscopy (SIM) has become a widely used tool for insight into biomedical challenges due to its rapid, long-term, and super-resolution (SR) imaging. However, artifacts that often appear in SIM images have long brought into question its fidelity, and might cause misinterpretation of biological structures. We present HiFi-SIM, a high-fidelity SIM reconstruction algorithm, by engineering the effective point spread function (PSF) into an ideal form. HiFi-SIM can effectively reduce commonly seen artifacts without loss of fine structures and improve the axial sectioning for samples with strong background. In particular, HiFi-SIM is not sensitive to the commonly used PSF and reconstruction parameters; hence, it lowers the requirements for dedicated PSF calibration and complicated parameter adjustment, thus promoting SIM as a daily imaging tool.

Method for assessing the spatiotemporal resolution of structured illumination microscopy (SIM)

A method is proposed for assessing the temporal resolution of structured illumination microscopy (SIM), by tracking the amplitude of different spatial frequency components over time, and comparing them to a temporally-oscillating ground-truth. This method is used to gain insight into the performance limits of SIM, along with alternative reconstruction techniques (termed 'rolling SIM') that claim to improve temporal resolution. Results show that the temporal resolution of SIM varies considerably between low and high spatial frequencies, and that, despite being used in several high profile papers and commercial microscope software, rolling SIM provides no increase in temporal resolution over conventional SIM.

Rapid Image Reconstruction of Structured Illumination Microscopy Directly in the Spatial Domain

Super-resolution structured illumination microscopy (SIM) routinely performs image reconstruction in the frequency domain using an approach termed frequency-domain reconstruction (FDR). Due to multiple Fourier transforms between the spatial and frequency domains, SIM suffers from low reconstruction speed, constraining its applications in real-time, dynamic imaging. To overcome this limitation, we developed a new method for SIM image reconstruction, termed spatial domain reconstruction (SDR). SDR is intrinsically simpler than FDR, does not require Fourier transforms and the theory predicts it to be a rapid image reconstruction method. Results show that SDR reconstructs a super-resolution image 7-fold faster than FDR, producing images that are equal to either FDR or the widely-used FairSIM. We provide a proof-of-principle using mobile fluorescent beads to demonstrate the utility of SDR in imaging moving objects. Consequently, replacement of the FDR approach with SDR significantly enhances SIM as the desired method for live-cell, instant super-resolution imaging. This means that SDR-SIM is a "What You See Is What You Get" approach to super-resolution imaging.

Live-cell RESOLFT nanoscopy of transgenic Arabidopsis thaliana

Subdiffraction super-resolution fluorescence microscopy, or nanoscopy, has seen remarkable developments in the last two decades. Yet, for the visualization of plant cells, nanoscopy is still rarely used. In this study, we established RESOLFT nanoscopy on living green plant tissue. Live-cell RESOLFT nanoscopy requires and utilizes comparatively low light doses and intensities to overcome the diffraction barrier. We generated a transgenic Arabidopsis thaliana plant line expressing the reversibly switchable fluorescent protein rsEGFP2 fused to the mammalian microtubule-associated protein 4 (MAP4) in order to ubiquitously label the microtubule cytoskeleton. We demonstrate the use of RESOLFT nanoscopy for extended time-lapse imaging of cortical microtubules in Arabidopsis leaf discs. By combining our approach with fluorescence lifetime gating, we were able to acquire live-cell RESOLFT images even close to chloroplasts, which exhibit very strong autofluorescence. The data demonstrate the feasibility of subdiffraction resolution imaging in transgenic plant material with minimal requirements for sample preparation.

Super-resolution imaging and quantification of megakaryocytes and platelets

Recent advances in super-resolution (sub-diffraction limited) microscopy have yielded remarkable insights into the nanoscale architecture and behavior of cells. In addition to the capacity to provide sub 100 nm resolution, these technologies offer unique quantitative opportunities with particular relevance to platelet and megakaryocyte biology. In this review, we provide a short introduction to modern super-resolution microscopy, its applications in the field of platelet and megakaryocyte biology, and emerging quantitative approaches which will allow for unprecedented insights into the biology of these unique cell types.

Fast TIRF-SIM imaging of dynamic, low-fluorescent biological samples

Fluorescence microscopy is the standard imaging technique to investigate the structures and dynamics of living cells. However, increasing the spatial resolution comes at the cost of temporal resolution and vice versa. In addition, the number of images that can be taken in sufficiently high quality is limited by fluorescence bleaching. Hence, super-resolved imaging at several Hertz of low fluorescent biological samples is still a big challenge and, especially in structured illumination microscopy (SIM), is often visible as imaging artifacts. In this paper, we present a TIRF-SIM system based on scan-mirrors and a Michelson interferometer, which generates images at 110 nm spatial resolution and up to 8 Hz temporal resolution. High resolution becomes possible by optimizing the illumination interference contrast, even for low fluorescent, moving samples. We provide a framework and guidelines on how the modulation contrast, which depends on laser coherence, polarization, beam displacement or sample movements, can be mapped over the entire field of view. In addition, we characterize the influence of the signal-to-noise ratio and the Wiener filtering on the quality of reconstructed SIM images, both in real and frequency space. Our results are supported by theoretical descriptions containing the parameters leading to image artifacts. This study aims to help microscopists to better understand and adjust optical parameters for structured illumination, thereby leading to more trustworthy measurements and analyses of biological dynamics.

Super-resolution nanoscopy by coherent control on nanoparticle emission

Super-resolution nanoscopy based on wide-field microscopic imaging provided high efficiency but limited resolution. Here, we demonstrate a general strategy to push its resolution down to ~50 nm, which is close to the range of single molecular localization microscopy, without sacrificing the wide-field imaging advantage. It is done by actively and simultaneously modulating the characteristic emission of each individual emitter at high density. This method is based on the principle of excited state coherent control on single-particle two-photon fluorescence. In addition, the modulation efficiently suppresses the noise for imaging. The capability of the method is verified both in simulation and in experiments on ZnCdS quantum dot-labeled films and COS7 cells. The principle of coherent control is generally applicable to single-multiphoton imaging and various probes.

High spatiotemporal resolution and low photo-toxicity fluorescence imaging in live cells and in vivo

Taking advantage of high contrast and molecular specificity, fluorescence microscopy has played a critical role in the visualization of subcellular structures and function, enabling unprecedented exploration from cell biology to neuroscience in living animals. To record and quantitatively analyse complex and dynamic biological processes in real time, fluorescence microscopes must be capable of rapid, targeted access deep within samples at high spatial resolutions, using techniques including super-resolution fluorescence microscopy, light sheet fluorescence microscopy, and multiple photon microscopy. In recent years, tremendous breakthroughs have improved the performance of these fluorescence microscopies in spatial resolution, imaging speed, and penetration. Here, we will review recent advancements of these microscopies in terms of the trade-off among spatial resolution, sampling speed and penetration depth and provide a view of their possible applications.

Fourier ring correlation simplifies image restoration in fluorescence microscopy

Fourier ring correlation (FRC) has recently gained popularity among fluorescence microscopists as a straightforward and objective method to measure the effective image resolution. While the knowledge of the numeric resolution value is helpful in e.g., interpreting imaging results, much more practical use can be made of FRC analysis—in this article we propose blind image restoration methods enabled by it. We apply FRC to perform image de-noising by frequency domain filtering. We propose novel blind linear and non-linear image deconvolution methods that use FRC to estimate the effective point-spread-function, directly from the images. We show how FRC can be used as a powerful metric to observe the progress of iterative deconvolution. We also address two important limitations in FRC that may be of more general interest: how to make FRC work with single images (within certain practical limits) and with three-dimensional images with highly anisotropic resolution.

Fourier ring correlation (FRC) analysis is commonly used in fluorescence microscopy to measure effective image resolution. Here, the authors demonstrate that FRC can also be leveraged in blind image restoration methods, such as image deconvolution.

Faster, sharper, and deeper: structured illumination microscopy for biological imaging

Structured illumination microscopy (SIM) allows rapid, super-resolution (SR) imaging in live specimens. We review recent technical advances in SR-SIM, with emphasis on imaging speed, resolution, and depth. Since its introduction decades ago, the technique has grown to offer myriad implementations, each with its own strengths and weaknesses. We discuss these, aiming to provide a practical guide for biologists and to highlight which approach is best suited to a given application.

Enhanced photon collection enables four dimensional fluorescence nanoscopy of living systems

The theoretically unlimited spatial resolution of fluorescence nanoscopy often comes at the expense of time, contrast and increased dose of energy for recording. Here, we developed MoNaLISA, for Molecular Nanoscale Live Imaging with Sectioning Ability, a nanoscope capable of imaging structures at a scale of 45–65 nm within the entire cell volume at low light intensities (W-kW cm⁻²). Our approach, based on reversibly switchable fluorescent proteins, features three distinctly modulated illumination patterns crafted and combined to gain fluorescence ON–OFF switching cycles and image contrast. By maximizing the detected photon flux, MoNaLISA enables prolonged (40–50 frames) and large (50 × 50 µm²) recordings at 0.3–1.3 Hz with enhanced optical sectioning ability. We demonstrate the general use of our approach by 4D imaging of organelles and fine structures in epithelial human cells, colonies of mouse embryonic stem cells, brain cells, and organotypic tissues.

Super-resolution microscopy often suffers from low contrast and slow recording times. Here the authors present an optical implementation which makes the fluorescent proteins’ ON–OFF switching cycles more efficient, enhancing contrast and spatio-temporal resolution in 3D cell and tissue imaging.

Automated distinction of shearing and distortion artefacts in structured illumination microscopy

Any motion during an image acquisition leads to an artefact in the final image. Structured illumination microscopy (SIM) combines several raw images into one high-resolution image and is thus particularly prone to these motion artefacts. Their unpredictable shape cannot easily be distinguished from real high-resolution content. We previously implemented a motion detection specifically for SIM, which had two shortcomings which are solved here. First, the brightness dependency of the motion signal is removed. Second, the empirical threshold of the calculated motion signal was not a threshold at a maximum allowed artefact. Here we investigate which artefacts are still acceptable and which linear movement creates them. Thus, the motion signal is linked with the maximal strength of the expected artefact. A signal-to-noise analysis including classification successfully distinguishes between artefact-free imaging, shearing and distortion artefacts in biological specimens. A shearing, as in wide-field microscopy, is the dominant reconstruction artefact, while distortions arise not until surprisingly fast movements.

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.

Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy

To increase the temporal resolution and maximal imaging time of super-resolution (SR) microscopy, we have developed a deconvolution algorithm for structured illumination microscopy based on Hessian matrixes (Hessian-SIM). It uses the continuity of biological structures in multiple dimensions as a priori knowledge to guide image reconstruction and attains artifact-minimized SR images with less than 10% of the photon dose used by conventional SIM while substantially outperforming current algorithms at low signal intensities. Hessian-SIM enables rapid imaging of moving vesicles or loops in the endoplasmic reticulum without motion artifacts and with a spatiotemporal resolution of 88 nm and 188 Hz. Its high sensitivity allows the use of sub-millisecond excitation pulses followed by dark recovery times to reduce photobleaching of fluorescent proteins, enabling hour-long time-lapse SR imaging of actin filaments in live cells. Finally, we observed the structural dynamics of mitochondrial cristae and structures that, to our knowledge, have not been observed previously, such as enlarged fusion pores during vesicle exocytosis.

Three-dimensional live multi-label light-sheet imaging with synchronous excitation-multiplexed structured illumination

Multiplexed imaging is a powerful tool for studying complex interactions inside biological systems. Spectral imaging methods that capture multiple fluorescent markers synchronously without sacrificing the imaging speed or resolution are most suitable for live imaging. We describe spectral-encoded structured illumination (spectral-SIM) light-sheet microscopy, which enables parallel multi-excitation-channel imaging in 3D. Spectral-SIM encodes the excitation wavelength as the phase of the illumination pattern, and allows synchronous image capture over multiple excitation channels at the same speed and spatial resolution as mono-channel structured light-sheet imaging. The technique retains structured light-sheet microscopy's ability in removing out-of-focus and scattered emission background, and generates clear 3D multiplexed images in thick tissue. The capability of this technique was demonstrated by the imaging of live triple-labeled transgenic zebrafish to over 300 μm deep with 0.5μm-by-2μm (lateral-by-axial) resolution.

Fluorescence nanoscopy in cell biology

Fluorescence nanoscopy uniquely combines minimally invasive optical access to the internal nanoscale structure and dynamics of cells and tissues with molecular detection specificity. While the basic physical principles of 'super-resolution' imaging were discovered in the 1990s, with initial experimental demonstrations following in 2000, the broad application of super-resolution imaging to address cell-biological questions has only more recently emerged. Nanoscopy approaches have begun to facilitate discoveries in cell biology and to add new knowledge. One current direction for method improvement is the ambition to quantitatively account for each molecule under investigation and assess true molecular colocalization patterns via multi-colour analyses. In pursuing this goal, the labelling of individual molecules to enable their visualization has emerged as a central challenge. Extending nanoscale imaging into (sliced) tissue and whole-animal contexts is a further goal. In this Review we describe the successes to date and discuss current obstacles and possibilities for further development.

Strategic and practical guidelines for successful structured illumination microscopy

Linear 2D- or 3D-structured illumination microscopy (SIM or3D-SIM, respectively) enables multicolor volumetric imaging of fixed and live specimens with subdiffraction resolution in all spatial dimensions. However, the reliance of SIM on algorithmic post-processing renders it particularly sensitive to artifacts that may reduce resolution, compromise data and its interpretations, and drain resources in terms of money and time spent. Here we present a protocol that allows users to generate high-quality SIM data while accounting and correcting for common artifacts. The protocol details preparation of calibration bead slides designed for SIM-based experiments, the acquisition of calibration data, the documentation of typically encountered SIM artifacts and corrective measures that should be taken to reduce them. It also includes a conceptual overview and checklist for experimental design and calibration decisions, and is applicable to any commercially available or custom platform. This protocol, plus accompanying guidelines, allows researchers from students to imaging professionals to create an optimal SIM imaging environment regardless of specimen type or structure of interest. The calibration sample preparation and system calibration protocol can be executed within 1-2 d.

Navigating challenges in the application of superresolution microscopy

In 2014, the Nobel Prize in Chemistry was awarded to three scientists who have made groundbreaking contributions to the field of superresolution (SR) microscopy (SRM). The first commercial SR microscope came to market a decade earlier, and many other commercial options have followed. As commercialization has lowered the barrier to using SRM and the awarding of the Nobel Prize has drawn attention to these methods, biologists have begun adopting SRM to address a wide range of questions in many types of specimens. There is no shortage of reviews on the fundamental principles of SRM and the remarkable achievements made with these methods. We approach SRM from another direction: we focus on the current practical limitations and compromises that must be made when designing an SRM experiment. We provide information and resources to help biologists navigate through common pitfalls in SRM specimen preparation and optimization of image acquisition as well as errors and artifacts that may compromise the reproducibility of SRM data.

Clearer view for TIRF and oblique illumination microscopy

In Total Internal Reflection Fluorescence (TIRF) microscopy, the sample is illuminated with an evanescent field that yields a thin optical section. However, its widefield detection has no rejection mechanism against out-of-focus blur from scattered light that can compromise TIRF images. Here I demonstrate that via structured illumination, out-of-focus blur can be effectively suppressed in TIRF microscopy, yielding strikingly clearer images. The same mechanism can also be applied to oblique illumination schemes that extend the reach of TIRF microscopy beyond the basal surface of the cell. The two imaging modes are used to image a biosensor, clathrin coated vesicles and the actin cytoskeleton in different cell types with improved contrast.

Optimal 2D-SIM reconstruction by two filtering steps with Richardson-Lucy deconvolution

Structured illumination microscopy relies on reconstruction algorithms to yield super-resolution images. Artifacts can arise in the reconstruction and affect the image quality. Current reconstruction methods involve a parametrized apodization function and a Wiener filter. Empirically tuning the parameters in these functions can minimize artifacts, but such an approach is subjective and produces volatile results. We present a robust and objective method that yields optimal results by two straightforward filtering steps with Richardson-Lucy-based deconvolutions. We provide a resource to identify artifacts in 2D-SIM images by analyzing two main reasons for artifacts, out-of-focus background and a fluctuating reconstruction spectrum. We show how the filtering steps improve images of test specimens, microtubules, yeast and mammalian cells.

Response to Comment on "Extended-resolution structured illumination imaging of endocytic and cytoskeletal dynamics"

Sahl et al in their Comment raise criticisms of our work that fall into three classes: image artifacts, resolution criteria, and comparative performance on live cells. We explore each of these in turn.