Artifact-free high-density localization microscopy analysis

High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation

Live-cell super-resolution microscopy enables the imaging of biological structure dynamics below the diffraction limit. Here we present enhanced super-resolution radial fluctuations (eSRRF), substantially improving image fidelity and resolution compared to the original SRRF method. eSRRF incorporates automated parameter optimization based on the data itself, giving insight into the trade-off between resolution and fidelity. We demonstrate eSRRF across a range of imaging modalities and biological systems. Notably, we extend eSRRF to three dimensions by combining it with multifocus microscopy. This realizes live-cell volumetric super-resolution imaging with an acquisition speed of ~1 volume per second. eSRRF provides an accessible super-resolution approach, maximizing information extraction across varied experimental conditions while minimizing artifacts. Its optimal parameter prediction strategy is generalizable, moving toward unbiased and optimized analyses in super-resolution microscopy.

LocNet: deep learning-based localization on a rotating point spread function with applications to telescope imaging

Three-dimensional (3D) point source recovery from two-dimensional (2D) data is a challenging problem with wide-ranging applications in single-molecule localization microscopy and space-debris localization telescops. Point spread function (PSF) engineering is a promising technique to solve this 3D localization problem. Specifically, we consider the problem of 3D localization of space debris from a 2D image using a rotating PSF where the depth information is encoded in the angle of rotation of a single-lobe PSF for each point source. Instead of applying a model-based optimization, we introduce a convolution neural network (CNN)-based approach to localize space debris in full 3D space automatically. A hard sample training strategy is proposed to improve the performance of CNN further. Contrary to the traditional model-based methods, our technique is efficient and outperforms the current state-of-the-art method by more than 11% in the precision rate with a comparable improvement in the recall rate.

Super-resolution microscopy and studies of peroxisomes

Fluorescence microscopy is an important tool for studying cellular structures such as organelles. Unfortunately, many details in the corresponding images are hidden due to the resolution limit of conventional lens-based far-field microscopy. An example is the study of peroxisomes, where important processes such as molecular organization during protein important can simply not be studied with conventional far-field microscopy methods. A remedy is super-resolution fluorescence microscopy, which is nowadays a well-established technique for the investigation of inner-cellular structures but has so far to a lesser extent been applied to the study of peroxisomes. To help advancing the latter, we here give an overview over the different super-resolution microscopy approaches and their potentials and challenges in cell-biological research, including labelling issues and a focus on studies on peroxisomes. Here, we also highlight experiments beyond simple imaging such as observations of diffusion dynamics of peroxisomal proteins.

Small-molecule fluorogenic probes for mitochondrial nanoscale imaging

Mitochondria are inextricably linked to the development of diseases and cell metabolism disorders. Super-resolution imaging (SRI) is crucial in enhancing our understanding of mitochondrial ultrafine structures and functions. In addition to high-precision instruments, super-resolution microscopy relies heavily on fluorescent materials with unique photophysical properties. Small-molecule fluorogenic probes (SMFPs) have excellent properties that make them ideal for mitochondrial SRI. This paper summarizes recent advances in the field of SMFPs, with a focus on the chemical and spectroscopic properties required for mitochondrial SRI. Finally, we discuss future challenges in this field, including the design principles of SMFPs and nanoscopic techniques.

Extending resolution within a single imaging frame

The resolution of fluorescence microscopy images is limited by the physical properties of light. In the last decade, numerous super-resolution microscopy (SRM) approaches have been proposed to deal with such hindrance. Here we present Mean-Shift Super Resolution (MSSR), a new SRM algorithm based on the Mean Shift theory, which extends spatial resolution of single fluorescence images beyond the diffraction limit of light. MSSR works on low and high fluorophore densities, is not limited by the architecture of the optical setup and is applicable to single images as well as temporal series. The theoretical limit of spatial resolution, based on optimized real-world imaging conditions and analysis of temporal image stacks, has been measured to be 40 nm. Furthermore, MSSR has denoising capabilities that outperform other SRM approaches. Along with its wide accessibility, MSSR is a powerful, flexible, and generic tool for multidimensional and live cell imaging applications.

Nanoscale organization of the pre-synapse: Tracking the neurotransmitter release machinery

Chemical communication is underpinned by the fusion of neurotransmitter-containing synaptic vesicles with the plasma membrane at active zones. With the advent of super-resolution microscopy, the door is now opened to unravel the dynamic remodeling of synapses underpinning learning and memory. Imaging proteins with conventional light microscopy cannot provide submicron information vital to determining the nanoscale organization of the synapse. We will first review the current super-resolution microscopy techniques available to investigate the localization and movement of synaptic proteins and how they have been applied to visualize the synapse. We discuss the new techniques and analytical approaches have provided comprehensive insights into synaptic organization in various model systems. Finally, this review provides a brief update on how these super-resolution techniques and analyses have opened the way to a much greater understanding of the synapse, the fusion and compensatory endocytosis machinery.

Simple methods for quantifying super-resolved cortical actin

Cortical actin plays a key role in cell movement and division, but has also been implicated in the organisation of cell surface receptors such as G protein-coupled receptors. The actin mesh proximal to the inner membrane forms small fenced regions, or 'corrals', in which receptors can be constrained. Quantification of the actin mesh at the nanoscale has largely been attempted in single molecule datasets and electron micrographs. This work describes the development and validation of workflows for analysis of super resolved fixed cortical actin images obtained by Super Resolved Radial Fluctuations (SRRF), Structured Illumination Microscopy (3D-SIM) and Expansion Microscopy (ExM). SRRF analysis was used to show a significant increase in corral area when treating cells with the actin disrupting agent cytochalasin D (increase of 0.31 µm² ± 0.04 SEM), and ExM analysis allowed for the quantitation of actin filament densities. Thus, this work allows complex actin networks to be quantified from super-resolved images and is amenable to both fixed and live cell imaging.

Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

Technological advances in super-resolution microscopy to study cellular processes

Since its initial demonstration in 2000, far-field super-resolution light microscopy has undergone tremendous technological developments. In parallel, these developments have opened a new window into visualizing the inner life of cells at unprecedented levels of detail. Here, we review the technical details behind the most common implementations of super-resolution microscopy and highlight some of the recent, promising advances in this field.

Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science

We have developed “Microscope-Cockpit” (Cockpit), a highly adaptable open source user-friendly Python-based Graphical User Interface (GUI) environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses “Python-Microscope” (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.

Studying the Dynamics of Chromatin-Binding Proteins in Mammalian Cells Using Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) allows the super-resolved imaging of proteins within mammalian nuclei at spatial resolutions comparable to that of a nucleosome itself (~20 nm). The technique is therefore well suited to the study of chromatin structure. Fixed-cell SMLM has already allowed temporal "snapshots" of how proteins are arranged on chromatin within mammalian nuclei. In this chapter, we focus on how recent developments, for example in selective plane illumination, 3D SMLM, and protein labeling, have led to a range of live-cell SMLM studies. We describe how to carry out single-particle tracking (SPT) of single proteins and, by analyzing their diffusion parameters, how to determine whether proteins interact with chromatin, diffuse freely, or do both. We can study the numbers of proteins that interact with chromatin and also determine their residence time on chromatin. We can determine whether these proteins form functional clusters within the nucleus as well as whether they form specific nuclear structures.

Blinking Acoustic Nanodroplets Enable Fast Super-resolution Ultrasound Imaging

The advent of localization-based super-resolution ultrasound (SRUS) imaging creates a vista for precision vasculature and hemodynamic measurements in brain science, cardiovascular diseases, and cancer. As blinking fluorophores are crucial to super-resolution optical imaging, blinking acoustic contrast agents enabling ultrasound localization microscopy have been highly sought, but only with limited success. Here we report on the discovery and characterization of a type of blinking acoustic nanodroplets (BANDs) ideal for SRUS. BANDs of 200-500 nm diameters comprise a perfluorocarbon-filled core and a shell of DSPC, Pluronic F68, and DSPE-PEG2000. When driven by clinically safe acoustic pulses (MI < 1.9) provided by a diagnostic ultrasound transducer, BANDs underwent reversible vaporization and reliquefaction, manifesting as "blinks", at rates of up to 5 kHz. By sparse activation of perfluorohexane-filled BANDs-C₆ at high concentrations, only 100 frames of ultrasound imaging were sufficient to reconstruct super-resolution images of a no-flow tube through either cumulative localization or temporal radiality autocorrelation. Furthermore, the use of high-density BANDs-C_6-4 (1 × 10⁸/mL) with a 1:9 admixture of perfluorohexane and perfluorobutane supported the fast SRUS imaging of muscle vasculature in live animals, at 64 μm resolution requiring only 100 frames per layer. We anticipate that the BANDs developed here will greatly boost the application of SRUS in both basic science and clinical settings.

Sub-diffraction error mapping for localisation microscopy images

Assessing the quality of localisation microscopy images is highly challenging due to the difficulty in reliably detecting errors in experimental data. The most common failure modes are the biases and errors produced by the localisation algorithm when there is emitter overlap. Also known as the high density or crowded field condition, significant emitter overlap is normally unavoidable in live cell imaging. Here we use Haar wavelet kernel analysis (HAWK), a localisation microscopy data analysis method which is known to produce results without bias, to generate a reference image. This enables mapping and quantification of reconstruction bias and artefacts common in all but low emitter density data. By avoiding comparisons involving intensity information, we can map structural artefacts in a way that is not adversely influenced by nonlinearity in the localisation algorithm. The HAWK Method for the Assessment of Nanoscopy (HAWKMAN) is a general approach which allows for the reliability of localisation information to be assessed.

Determining the quality of localisation microscopy images is currently challenging. Here the authors report use of the Haar wavelet kernel analysis (HAWK) Method for the Assessment of Nanoscopy, termed HAWKMAN, to assess the reliability of localisation information.

DETECTOR: structural information guided artifact detection for super-resolution fluorescence microscopy image

Super-resolution fluorescence microscopy, with a spatial resolution beyond the diffraction limit of light, has become an indispensable tool to observe subcellular structures at a nanoscale level. To verify that the super-resolution images reflect the underlying structures of samples, the development of robust and reliable artifact detection methods has received widespread attention. However, the existing artifact detection methods are prone to report false alert artifacts because it relies on absolute intensity mismatch between the wide-field image and resolution rescaled super-resolution image. To solve this problem, we proposed DETECTOR, a structural information-guided artifact detection method for super-resolution images. It detects artifacts by computing the structural dissimilarity between the wide-field image and the resolution rescaled super-resolution image. To focus on structural similarity, we introduce a weight mask to weaken the influence of strong autofluorescence background and proposed a structural similarity index for super-resolution images, named MASK-SSIM. Simulations and experimental results demonstrated that compared with the state-of-the-art methods, DETECTOR has advantages in detecting structural artifacts in super-resolution images. It is especially suitable for wide-field images with strong autofluorescence background and super-resolution images of single molecule localization microscopy (SMLM). DETECTOR has extreme sensitivity to the weak signal region. Moreover, DETECTOR can guide data collection and parameter tuning during image reconstruction.

Silinanyl Rhodamines and Silinanyl Fluoresceins for Super-Resolution Microscopy

Single-molecule localization microscopy (SMLM) enables the visualization of biomolecules at unprecedented resolution and requires control of the fluorescent blinking (ON/OFF) states of fluorophores to detect single-molecule fluorescence without overlapping of the signals. Although SMLM probes based on the intramolecular spirocyclization of Si-xanthene fluorophores have been developed, fluorophores with lower ON/OFF ratios are required for SMLM visualization of high-density structures. Here, we describe a silinane structure that lowers the ON/OFF ratio of Si-xanthene fluorophores. On the basis of Mulliken population analysis, we replaced the dimethylsilane moiety in Si-rhodamine with a silinane moiety to increase the partial charge at the 9-position of the carbon atom in the Si-xanthene ring and to promote the ring-closure reaction. Evaluation of fluorescence properties in a solution and in single-molecule imaging indicated that introducing the silinane sufficiently stabilized the nonfluorescent spirocyclic forms, thus decreasing the fluorescence ON/OFF ratio. This novel substitution was applied to Si-rhodamines with various amine structures and to an Si-fluorescein to expand the color palette. We demonstrated SMLM observation of microtubules in fixed HeLa cells using the developed fluorophores in two color channels. The results demonstrated the feasibility of extending the design strategies of SMLM probes based on Si-xanthenes through modification of the substituents on the Si atom.

Super-resolved live-cell imaging using random illumination microscopy

Current super-resolution microscopy (SRM) methods suffer from an intrinsic complexity that might curtail their routine use in cell biology. We describe here random illumination microscopy (RIM) for live-cell imaging at super-resolutions matching that of 3D structured illumination microscopy, in a robust fashion. Based on speckled illumination and statistical image reconstruction, easy to implement and user-friendly, RIM is unaffected by optical aberrations on the excitation side, linear to brightness, and compatible with multicolor live-cell imaging over extended periods of time. We illustrate the potential of RIM on diverse biological applications, from the mobility of proliferating cell nuclear antigen (PCNA) in U2OS cells and kinetochore dynamics in mitotic S. pombe cells to the 3D motion of myosin minifilaments deep inside Drosophila tissues. RIM's inherent simplicity and extended biological applicability, particularly for imaging at increased depths, could help make SRM accessible to biology laboratories.

Enhanced UnaG With Minimal Labeling Artifact for Single-Molecule Localization Microscopy

We introduced enhanced UnaG (eUnaG), a ligand-activatable fluorescent protein, for conventional and super-resolution imaging of subcellular structures in the mammalian cells. eUnaG is a V2L mutant of UnaG with twice brighter bulk fluorescence. We previously discovered the reversible fluorescence switching behavior of UnaG and demonstrated the high photon outputs and high localization numbers in single-molecule localization microscopy (SMLM). In this study, we showed that the fluorescence of eUnaG can be switched off under blue-light illumination, while a high concentration of fluorogenic ligands in the buffer can efficiently restore the fluorescence, as in UnaG. We demonstrated the capacity of eUnaG as an efficient protein label in mammalian cells, as well as for SMLM by utilizing its photoswitchable nature. While cytosolic UnaG proteins showed aggregated patches and fluorescence reduction at high expression levels, eUnaG-labeled protein targets successfully formed their proper structures in mammalian cells without notable distortion from the endogenous structure in the majority of transiently expressing cells. In particular, eUnaG preserved the vimentin filament structures much better than the UnaG. eUnaG provided similarly high single-molecule photon count distribution to UnaG, thus also similarly high resolution in the super-resolution images of various subcellular structures. The sampling coverage analysis of vimentin filaments in SMLM images showed the improvement of labeling efficiency of eUnaG. eUnaG is a high-performance fluorescent protein for fluorescence and single-molecule localization imaging in green emission with minimal labeling artifact.

Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science

We have developed “Microscope-Cockpit” (Cockpit), a highly adaptable open source user-friendly Python-based Graphical User Interface (GUI) environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses “Python-Microscope” (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.

Evidence that GPVI is Expressed as a Mixture of Monomers and Dimers, and that the D2 Domain is not Essential for GPVI Activation

Collagen has been proposed to bind to a unique epitope in dimeric glycoprotein VI (GPVI) and the number of GPVI dimers has been reported to increase upon platelet activation. However, in contrast, the crystal structure of GPVI in complex with collagen-related peptide (CRP) showed binding distinct from the site of dimerization. Further fibrinogen has been reported to bind to monomeric but not dimeric GPVI. In the present study, we have used the advanced fluorescence microscopy techniques of single-molecule microscopy, fluorescence correlation spectroscopy (FCS) and bioluminescence resonance energy transfer (BRET), and mutagenesis studies in a transfected cell line model to show that GPVI is expressed as a mixture of monomers and dimers and that dimerization through the D2 domain is not critical for activation. As many of these techniques cannot be applied to platelets to resolve this issue, due to the high density of GPVI and its anucleate nature, we used Förster resonance energy transfer (FRET) to show that endogenous GPVI is at least partially expressed as a dimer on resting and activated platelet membranes. We propose that GPVI may be expressed as a monomer on the cell surface and it forms dimers in the membrane through diffusion, giving rise to a mixture of monomers and dimers. We speculate that the formation of dimers facilitates ligand binding through avidity.

Analysing errors in single-molecule localisation microscopy

In single molecule localisation microscopy (SMLM) a super-resolution image of the distribution of fluorophores in the sample is built up from the localised positions of many individual molecules. It has become widely used due to its experimental simplicity and the high resolution that can be achieved. However, the factors which limit resolution in a reconstructed image, and the artefacts which can be present, are completely different to those present in standard fluorescent microscopy techniques. Artefacts may be difficult for users to identify, particularly as they can cause images to appear falsely sharp, an effect called artificial sharpening. Here we discuss the different sources of error and bias in SMLM, and the methods available for avoiding or detecting them.

Single-molecule localization microscopy

Single-molecule localization microscopy (SMLM) describes a family of powerful imaging techniques that dramatically improve spatial resolution over standard, diffraction-limited microscopy techniques and can image biological structures at the molecular scale. In SMLM, individual fluorescent molecules are computationally localized from diffraction-limited image sequences and the localizations are used to generate a super-resolution image or a time course of super-resolution images, or to define molecular trajectories. In this Primer, we introduce the basic principles of SMLM techniques before describing the main experimental considerations when performing SMLM, including fluorescent labelling, sample preparation, hardware requirements and image acquisition in fixed and live cells. We then explain how low-resolution image sequences are computationally processed to reconstruct super-resolution images and/or extract quantitative information, and highlight a selection of biological discoveries enabled by SMLM and closely related methods. We discuss some of the main limitations and potential artefacts of SMLM, as well as ways to alleviate them. Finally, we present an outlook on advanced techniques and promising new developments in the fast-evolving field of SMLM. We hope that this Primer will be a useful reference for both newcomers and practitioners of SMLM.

On-chip TIRF nanoscopy by applying Haar wavelet kernel analysis on intensity fluctuations induced by chip illumination

Photonic-chip based TIRF illumination has been used to demonstrate several on-chip optical nanoscopy methods. The sample is illuminated by the evanescent field generated by the electromagnetic wave modes guided inside the optical waveguide. In addition to the photokinetics of the fluorophores, the waveguide modes can be further exploited for introducing controlled intensity fluctuations for exploitation by techniques such as super-resolution optical fluctuation imaging (SOFI). However, the problem of non-uniform illumination pattern generated by the modes contribute to artifacts in the reconstructed image. To alleviate this problem, we propose to perform Haar wavelet kernel (HAWK) analysis on the original image stack prior to the application of (SOFI). HAWK produces a computational image stack with higher spatio-temporal sparsity than the original stack. In the case of multimoded non-uniform illumination patterns, HAWK processing breaks the mode pattern while introducing spatio-temporal sparsity, thereby differentially affecting the non-uniformity of the illumination. Consequently, this assists nanoscopy methods such as SOFI to better support super-resolution, which is otherwise compromised due to spatial correlation of the mode patterns in the raw image. Furthermore, applying HAWK prior to SOFI alleviates the problem of artifacts due to non-uniform illumination without degrading temporal resolution. Our experimental results demonstrate resolution enhancement as well as reduction in artifacts through the combination of HAWK and SOFI.

Corrected Super-Resolution Microscopy Enables Nanoscale Imaging of Autofluorescent Lung Macrophages

Observing the cell surface and underlying cytoskeleton at nanoscale resolution using super-resolution microscopy has enabled many insights into cell signaling and function. However, the nanoscale dynamics of tissue-specific immune cells have been relatively little studied. Tissue macrophages, for example, are highly autofluorescent, severely limiting the utility of light microscopy. Here, we report a correction technique to remove autofluorescent noise from stochastic optical reconstruction microscopy (STORM) data sets. Simulations and analysis of experimental data identified a moving median filter as an accurate and robust correction technique, which is widely applicable across challenging biological samples. Here, we used this method to visualize lung macrophages activated through Fc receptors by antibody-coated glass slides. Accurate, nanoscale quantification of macrophage morphology revealed that activation induced the formation of cellular protrusions tipped with MHC class I protein. These data are consistent with a role for lung macrophage protrusions in antigen presentation. Moreover, the tetraspanin protein CD81, known to mark extracellular vesicles, appeared in ring-shaped structures (mean diameter 93 ± 50 nm) at the surface of activated lung macrophages. Thus, a moving median filter correction technique allowed us to quantitatively analyze extracellular secretions and membrane structure in tissue-derived immune cells.

Highly photostable fluorescent labeling of proteins in live cells using exchangeable coiled coils heterodimerization

Fluorescent proteins are commonly used to label target proteins in live cells. However, the conventional approach based on covalent fusion of targeted proteins with fluorescent protein probes is limited by the slow rate of fluorophore maturation and irretrievable loss of fluorescence due to photobleaching. Here, we report a genetically encoded protein labeling system utilizing transient interactions of small, 21-28 residues-long helical protein tags (K/E coils, KEC). In this system, a protein of interest, covalently tagged with a single coil, is visualized through binding to a cytoplasmic fluorescent protein carrying a complementary coil. The reversible heterodimerization of KECs, whose affinity can be tuned in a broad concentration range from nanomolar to micromolar, allows continuous exchange and replenishment of the tag bound to a targeted protein with the entire cytosolic pool of soluble fluorescent coils. We found that, under conditions of partial illumination of living cells, the photostability of labeling with KECs exceeds that of covalently fused fluorescent probes by approximately one order of magnitude. Similarly, single-molecule localization microscopy with KECs provided higher labeling density and allowed a much longer duration of imaging than with conventional fusion to fluorescent proteins. We also demonstrated that this method is well suited for imaging newly synthesized proteins, because the labeling efficiency by KECs is not dependent on the rate of fluorescent protein maturation. In conclusion, KECs can be used to visualize various target proteins which are directly exposed to the cytosol, thereby enabling their advanced characterization in time and space.

Time-correlated single molecule localization microscopy enhances resolution and fidelity

Single-molecule-localization-microscopy (SMLM) enables superresolution imaging of biological samples down to ~ 10–20 nm and in single molecule detail. However, common SMLM reconstruction largely disregards information embedded in the entire intensity trajectories of individual emitters. Here, we develop and demonstrate an approach, termed time-correlated-SMLM (tcSMLM), that uses such information for enhancing SMLM reconstruction. Specifically, tcSMLM is shown to increase the spatial resolution and fidelity of SMLM reconstruction of both simulated and experimental data; esp. upon acquisition under stringent conditions of low SNR, high acquisition rate and high density of emitters. We further provide detailed guidelines and optimization procedures for effectively applying tcSMLM to data of choice. Importantly, our approach can be readily added in tandem to multiple SMLM and related superresolution reconstruction algorithms. Thus, we expect that our approach will become an effective and readily accessible tool for enhancing SMLM and superresolution imaging.

The Decade of Super-Resolution Microscopy of the Presynapse

The presynaptic compartment of the chemical synapse is a small, yet extremely complex structure. Considering its size, most methods of optical microscopy are not able to resolve its nanoarchitecture and dynamics. Thus, its ultrastructure could only be studied by electron microscopy. In the last decade, new methods of optical superresolution microscopy have emerged allowing the study of cellular structures and processes at the nanometer scale. While this is a welcome addition to the experimental arsenal, it has necessitated careful analysis and interpretation to ensure the data obtained remains artifact-free. In this article we review the application of nanoscopic techniques to the study of the synapse and the progress made over the last decade with a particular focus on the presynapse. We find to our surprise that progress has been limited, calling for imaging techniques and probes that allow dense labeling, multiplexing, longer imaging times, higher temporal resolution, while at least maintaining the spatial resolution achieved thus far.

The Axial Alignment of Titin on the Muscle Thick Filament Supports Its Role as a Molecular Ruler

The giant protein titin is expressed in vertebrate striated muscle where it spans half a sarcomere from the Z-disc to the M-band and is essential for muscle organisation, activity and health. The C-terminal portion of titin is closely associated with the thick, myosin-containing filament and exhibits a complex pattern of immunoglobulin and fibronectin domains. This pattern reflects features of the filament organisation suggesting that it acts as a molecular ruler and template, but the exact axial disposition of the molecule has not been determined. Here, we present data that allow us to precisely locate titin domains axially along the thick filament from its tip to the edge of the bare zone. We find that the domains are regularly distributed along the filament at 4-nm intervals and we can determine the domains that associate with features of the filament, such as the 11 stripes of accessory proteins. We confirm that the nine stripes ascribed to myosin binding protein-C are not related to the titin sequence previously assumed; rather, they relate to positions approximately 18 domains further towards the C terminus along titin. This disposition also allows a subgroup of titin domains comprising two or three fibronectin domains to associate with each of the 49 levels of myosin heads in each half filament. The results strongly support the role of titin as a blueprint for the thick filament and the arrangement of the myosin motor domains.

Efficient super-resolution volumetric imaging by radial fluctuation Bayesian analysis light-sheet microscopy

Various computational super-resolution methods are available based on the analysis of fluorescence fluctuation behind acquired frames. However, dilemmas often exist in the balance of fluorophore characteristics, computation cost, and achievable resolution. Here we present an approach that uses a super-resolution radial fluctuations (SRRF) image to guide the Bayesian analysis of fluorophore blinking and bleaching (3B) events, allowing greatly accelerated localization of overlapping fluorophores with high accuracy. This radial fluctuation Bayesian analysis (RFBA) approach is also extended to three dimensions for the first time and combined with light-sheet fluorescence microscopy, to achieve super-resolution volumetric imaging of thick samples densely labeled with common fluorophores. For example, a 700-nm thin Bessel plane illumination is developed to optically section the Drosophila brain, providing a high-contrast 3D image of rhythmic neurons. RFBA analyzes 30 serial volumes to reconstruct a super-resolved 3D image at 4-times higher resolutions (~70 and 170 nm), and precisely resolve the axon terminals. The computation is over 2-orders faster than conventional 3B analysis microscopy. The capability of RFBA is also verified through dual-color imaging of cell nucleus in live Drosophila brain. The spatial co-localization patterns of the nuclear envelope and DNA in a neuron deep inside the brain can be precisely extracted by our approach.

Self-Blinking Dyes Unlock High-Order and Multiplane Super-Resolution Optical Fluctuation Imaging

Most diffraction-unlimited super-resolution imaging critically depends on the switching of fluorophores between at least two states, often induced using intense laser light and specialized buffers or UV radiation. Recently, so-called self-blinking dyes that switch spontaneously between an open, fluorescent "on" state and a closed, colorless "off" state were introduced. Here, we exploit the synergy between super-resolution optical fluctuation imaging (SOFI) and spontaneously switching fluorophores for 2D and 3D imaging. SOFI analyzes higher order statistics of fluctuations in the fluorophore emission instead of localizing individual molecules. It thereby tolerates a broad range of labeling densities, switching behavior, and probe brightness. Thus, even dyes that exhibit spontaneous blinking characteristics that are not suitable or suboptimal for single molecule localization microscopy can be used successfully for SOFI-based super-resolution imaging. We demonstrate 2D imaging of fixed cells with almost uniform resolution up to 50-60 nm in 6th order SOFI and characterize changing experimental conditions. Next, we investigate volumetric imaging using biplane and eight-plane data acquisition. We extend 3D cross-cumulant analysis to 4th order, achieving super-resolution in 3D with up to 29 depth planes. Finally, the low laser excitation intensities needed for single and biplane self-blinking SOFI are well suited for live-cell imaging. We show the perspective for time-resolved imaging by observing slow membrane movements in cells. Self-blinking SOFI thus provides a more robust alternative route for easy-to-use 2D and 3D high-resolution imaging.

Combined AFM and super-resolution localisation microscopy: Investigating the structure and dynamics of podosomes

Podosomes are mechanosensitive attachment/invasion structures that form on the matrix-adhesion interface of cells and protrude into the extracellular matrix to probe and remodel. Despite their central role in many cellular processes, their exact molecular structure and function remain only partially understood. We review recent progress in molecular scale imaging of podosome architecture, including our newly developed localisation microscopy technique termed HAWK which enables artefact-free live-cell super-resolution microscopy of podosome ring proteins, and report new results on combining fluorescence localisation microscopy (STORM/PALM) and atomic force microscopy (AFM) on one setup, where localisation microscopy provides the location and dynamics of fluorescently labelled podosome components, while the spatial variation of stiffness is mapped with AFM. For two-colour localisation microscopy we combine iFluor-647, which has previously been shown to eliminate the need to change buffer between imaging modes, with the photoswitchable protein mEOS3.2, which also enables live cell imaging.

Coupling chromatin structure and dynamics by live super-resolution imaging

Chromatin conformation regulates gene expression and thus, constant remodeling of chromatin structure is essential to guarantee proper cell function. To gain insight into the spatiotemporal organization of the genome, we use high-density photoactivated localization microscopy and deep learning to obtain temporally resolved super-resolution images of chromatin in living cells. In combination with high-resolution dense motion reconstruction, we find elongated ~45- to 90-nm-wide chromatin "blobs." A computational chromatin model suggests that these blobs are dynamically associating chromatin fragments in close physical and genomic proximity and adopt topologically associated domain-like interactions in the time-average limit. Experimentally, we found that chromatin exhibits a spatiotemporal correlation over ~4 μm in space and tens of seconds in time, while chromatin dynamics are correlated over ~6 μm and last 40 s. Notably, chromatin structure and dynamics are closely related, which may constitute a mechanism to grant access to regions with high local chromatin concentration.

A Review of Super-Resolution Single-Molecule Localization Microscopy Cluster Analysis and Quantification Methods

Single-molecule localization microscopy (SMLM) is a relatively new imaging modality, winning the 2014 Nobel Prize in Chemistry, and considered as one of the key super-resolution techniques. SMLM resolution goes beyond the diffraction limit of light microscopy and achieves resolution on the order of 10-20 nm. SMLM thus enables imaging single molecules and study of the low-level molecular interactions at the subcellular level. In contrast to standard microscopy imaging that produces 2D pixel or 3D voxel grid data, SMLM generates big data of 2D or 3D point clouds with millions of localizations and associated uncertainties. This unprecedented breakthrough in imaging helps researchers employ SMLM in many fields within biology and medicine, such as studying cancerous cells and cell-mediated immunity and accelerating drug discovery. However, SMLM data quantification and interpretation methods have yet to keep pace with the rapid advancement of SMLM imaging. Researchers have been actively exploring new computational methods for SMLM data analysis to extract biosignatures of various biological structures and functions. In this survey, we describe the state-of-the-art clustering methods adopted to analyze and quantify SMLM data and examine the capabilities and shortcomings of the surveyed methods. We classify the methods according to (1) the biological application (i.e., the imaged molecules/structures), (2) the data acquisition (such as imaging modality, dimension, resolution, and number of localizations), and (3) the analysis details (2D versus 3D, field of view versus region of interest, use of machine-learning and multi-scale analysis, biosignature extraction, etc.). We observe that the majority of methods that are based on second-order statistics are sensitive to noise and imaging artifacts, have not been applied to 3D data, do not leverage machine-learning formulations, and are not scalable for big-data analysis. Finally, we summarize state-of-the-art methodology, discuss some key open challenges, and identify future opportunities for better modeling and design of an integrated computational pipeline to address the key challenges.

ERGO: Efficient Recurrent Graph Optimized Emitter Density Estimation in Single Molecule Localization Microscopy

Single molecule localization microscopy (SMLM) allows unprecedented insight into the three-dimensional organization of proteins at the nanometer scale. The combination of minimal invasive cell imaging with high resolution positions SMLM at the forefront of scientific discovery in cancer, infectious, and degenerative diseases. By stochastic temporal and spatial separation of light emissions from fluorescent labelled proteins, SMLM is capable of nanometer scale reconstruction of cellular structures. Precise localization of proteins in 3D astigmatic SMLM is dependent on parameter sensitive preprocessing steps to select regions of interest. With SMLM acquisition highly variable over time, it is non-trivial to find an optimal static parameter configuration. The high emitter density required for reconstruction of complex protein structures can compromise accuracy and introduce artifacts. To address these problems, we introduce two modular auto-tuning pre-processing methods: adaptive signal detection and learned recurrent signal density estimation that can leverage the information stored in the sequence of frames that compose the SMLM acquisition process. We show empirically that our contributions improve accuracy, precision and recall with respect to the state of the art. Both modules auto-tune their hyper-parameters to reduce the parameter space for practitioners, improve robustness and reproducibility, and are validated on a reference in silico dataset. Adaptive signal detection and density prediction can offer a practitioner, in addition to informed localization, a tool to tune acquisition parameters ensuring improved reconstruction of the underlying protein complex. We illustrate the challenges faced by practitioners in applying SMLM algorithms on real world data markedly different from the data used in development and show how ERGO can be run on new datasets without retraining while motivating the need for robust transfer learning in SMLM.

Enhanced 4Pi single-molecule localization microscopy with coherent pupil based localization

Over the last decades, super-resolution techniques have revolutionized the field of fluorescence microscopy. Among them, interferometric or 4Pi microscopy methods exhibit supreme resolving power in the axial dimension. Combined with single-molecule detection/localization and adaptive optics, current 4Pi microscopy methods enabled 10–15 nm isotropic 3D resolution throughout whole cells. However, further improving the achieved 3D resolution poses challenges arising from the complexity of single-molecule emission patterns generated by these coherent single-molecule imaging systems. These complex emission patterns render a large portion of information carrying photons unusable. Here, we introduce a localization algorithm that achieves the theoretical precision limit for a 4Pi based single-molecule switching nanoscopy (4Pi-SMSN) system, and demonstrate improvements in localization precision, accuracy as well as stability comparing with state-of-the-art 4Pi-SMSN methods.

To further improve localisation precision and biases in all the three dimensions of 4Pi single molecule localisation microscopy, Huang and Liu develop a method based on coherent pupil functions and an algorithm to extract the position information content at the theoretical information limit while dynamically compensating the temperature-induced cavity drift.

FMNL2 regulates dynamics of fascin in filopodia

Filopodia are peripheral F-actin-rich structures that enable cell sensing of the microenvironment. Fascin is an F-actin-bundling protein that plays a key role in stabilizing filopodia to support efficient adhesion and migration. Fascin is also highly up-regulated in human cancers, where it increases invasive cell behavior and correlates with poor patient prognosis. Previous studies have shown that fascin phosphorylation can regulate F-actin bundling, and that this modification can contribute to subcellular fascin localization and function. However, the factors that regulate fascin dynamics within filopodia remain poorly understood. In the current study, we used advanced live-cell imaging techniques and a fascin biosensor to demonstrate that fascin phosphorylation, localization, and binding to F-actin are highly dynamic and dependent on local cytoskeletal architecture in cells in both 2D and 3D environments. Fascin dynamics within filopodia are under the control of formins, and in particular FMNL2, that binds directly to dephosphorylated fascin. Our data provide new insight into control of fascin dynamics at the nanoscale and into the mechanisms governing rapid cytoskeletal adaptation to environmental changes. This filopodia-driven exploration stage may represent an essential regulatory step in the transition from static to migrating cancer cells.

Analysis methods for interrogating spatial organisation of single molecule localisation microscopy data

Single-molecule localisation microscopy (SMLM) gives access to biological information below the diffraction limit, allowing nanoscale cellular structures to be probed. The data output is unlike that of conventional microscopy images, instead consisting of an array of molecular coordinates. These represent a spatial point pattern that attempts to approximate, as closely as possible, the underlying positions of the molecules of interest. Here, we review the analysis methods that can be used to extract biological insight from SMLM data, in particular for the application of quantifying nanoscale molecular clustering. We review how some of the common artefacts inherent in SMLM can corrupt the acquired data, and therefore, how the output of SMLM cluster analysis should be interpreted.

Between life and death: strategies to reduce phototoxicity in super-resolution microscopy

Super-resolution microscopy (SRM) enables non-invasive, molecule-specific imaging of the internal structure and dynamics of cells with sub-diffraction limit spatial resolution. One of its major limitations is the requirement for high-intensity illumination, generating considerable cellular phototoxicity. This factor considerably limits the capacity for live-cell observations, particularly for extended periods of time. Here, we give an overview of new developments in hardware, software and probe chemistry aiming to reduce phototoxicity. Additionally, we discuss how the choice of biological model and sample environment impacts the capacity for live-cell observations.

Deep learning in single-molecule microscopy: fundamentals, caveats, and recent developments [Invited]

Deep learning-based data analysis methods have gained considerable attention in all fields of science over the last decade. In recent years, this trend has reached the single-molecule community. In this review, we will survey significant contributions of the application of deep learning in single-molecule imaging experiments. Additionally, we will describe the historical events that led to the development of modern deep learning methods, summarize the fundamental concepts of deep learning, and highlight the importance of proper data composition for accurate, unbiased results.

Bright ligand-activatable fluorescent protein for high-quality multicolor live-cell super-resolution microscopy

We introduce UnaG as a green-to-dark photoswitching fluorescent protein capable of high-quality super-resolution imaging with photon numbers equivalent to the brightest photoswitchable red protein. UnaG only fluoresces upon binding of a fluorogenic metabolite, bilirubin, enabling UV-free reversible photoswitching with easily controllable kinetics and low background under Epi illumination. The on- and off-switching rates are controlled by the concentration of the ligand and the excitation light intensity, respectively, where the dissolved oxygen also promotes the off-switching. The photo-oxidation reaction mechanism of bilirubin in UnaG suggests that the lack of ligand-protein covalent bond allows the oxidized ligand to detach from the protein, emptying the binding cavity for rebinding to a fresh ligand molecule. We demonstrate super-resolution single-molecule localization imaging of various subcellular structures genetically encoded with UnaG, which enables facile labeling and simultaneous multicolor imaging of live cells. UnaG has the promise of becoming a default protein for high-performance super-resolution imaging.

Photoconvertible proteins occupy two color channels thereby limiting multicolour localisation microscopy applications. Here the authors present UnaG, a new green-to-dark photoswitching fluorescent protein for super-resolution imaging, whose activation is based on a noncovalent binding with bilirubin.

Photoactivation of silicon rhodamines via a light-induced protonation

Photoactivatable fluorophores are important for single-particle tracking and super-resolution microscopy. Here we present a photoactivatable fluorophore that forms a bright silicon rhodamine derivative through a light-dependent protonation. In contrast to other photoactivatable fluorophores, no caging groups are required, nor are there any undesired side-products released. Using this photoactivatable fluorophore, we create probes for HaloTag and actin for live-cell single-molecule localization microscopy and single-particle tracking experiments. The unusual mechanism of photoactivation and the fluorophore's outstanding spectroscopic properties make it a powerful tool for live-cell super-resolution microscopy.

Parameter-free image resolution estimation based on decorrelation analysis

Super-resolution microscopy opened diverse new avenues of research by overcoming the resolution limit imposed by diffraction. Exploitation of the fluorescent emission of individual fluorophores made it possible to reveal structures beyond the diffraction limit. To accurately determine the resolution achieved during imaging is challenging with existing metrics. Here, we propose a method for assessing the resolution of individual super-resolved images based on image partial phase autocorrelation. The algorithm is model-free and does not require any user-defined parameters. We demonstrate its performance on a wide variety of imaging modalities, including diffraction-limited techniques. Finally, we show how our method can be used to optimize image acquisition and post-processing in super-resolution microscopy.

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.

Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software

With the widespread uptake of 2D and 3D single molecule localization microscopy, a large set of different data analysis packages have been developed to generate super-resolution images. In a large community effort we designed a competition to extensively characterise and rank the performance of 2D and 3D single molecule localization microscopy software packages. We generated realistic simulated datasets for popular imaging modalities - 2D, astigmatic 3D, biplane 3D, and double helix 3D - and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D single molecule localization microscopy software and provides a holistic view of how the latest 2D and 3D single molecule localization software perform in realistic conditions. This resource allows researchers to identify optimal analytical software for their experiments, allows 3D SMLM software developers to benchmark new software against current state of the art, and provides insight into the current limits of the field.

This study reports results from the second community-wide single molecule localization microscopy software challenge, which tested over thirty software packages on realistic simulated data for multiple popular 3D image acquisition modes as well as 2D localization microscopy.

Flat-top TIRF illumination boosts DNA-PAINT imaging and quantification

Super-resolution (SR) techniques have extended the optical resolution down to a few nanometers. However, quantitative treatment of SR data remains challenging due to its complex dependence on a manifold of experimental parameters. Among the different SR variants, DNA-PAINT is relatively straightforward to implement, since it achieves the necessary ‘blinking’ without the use of rather complex optical or chemical activation schemes. However, it still suffers from image and quantification artifacts caused by inhomogeneous optical excitation. Here we demonstrate that several experimental challenges can be alleviated by introducing a segment-wise analysis approach and ultimately overcome by implementing a flat-top illumination profile for TIRF microscopy using a commercially-available beam-shaping device. The improvements with regards to homogeneous spatial resolution and precise kinetic information over the whole field-of-view were quantitatively assayed using DNA origami and cell samples. Our findings open the door to high-throughput DNA-PAINT studies with thus far unprecedented accuracy for quantitative data interpretation.

The use of TIRF microscopy for DNA-PAINT experiments is limited by inhomogeneous illumination. Here the authors show that quantitative analysis of single-molecule TIRF experiments can be improved by using a segment-wise analysis approach and overcome by using a beam-shaping device to give a flat-top illumination profile.