Fast widefield scan provides tunable and uniform illumination optimizing super-resolution microscopy on large fields

Waveguide Evanescent Field Fluorescence Microscopy Images of Osteoblast Cells: The Effect of Trypsin and Image Processing Using TrackMate

Waveguide evanescent field fluorescence microscopy (WEFF) is an evanescent-based microscopy that utilizes a confined thin film of light, around 100 nm, to image the plasma membrane of cells attached to a waveguide. Low photobleaching and low background besides its high axial resolution allows time-lapse imaging to investigate changes in cell morphology in the presence or absence of chemical agents. Both large field of view (FOV) and uniform illumination are very important while imaging cell-substrate contacts with an evanescent field. In the current study, we demonstrate that the WEFF microscope is capable of large FOVs with a uniform illumination source and imaging over a very long time period with a simple and inexpensive experimental setup. The interaction of the trypsin with plasma membranes of live osteoblast cells is investigated. To analyze cell images (250 images), instead of relying on manual tracking, which is time-consuming and can introduce numerous errors, we performed image processing using TrackMate to investigate the dynamic response of cells upon exposure to trypsin. This helps to save time and increase the accuracy of the analysis. The powerful tracking and analysis capabilities of the TrackMate plugin in ImageJ are used to automatically detect the cells border and trace each cluster of cells. The reduction in cell area is accompanied by a notable increase in mean intensity, reflecting changes in the intracellular environment. However, the background did not change during the experiment, which proves that the fluorescence material remains attached to the cell membrane and does not leak into the cell medium.

Advancing Super-Resolution Microscopy: Recent Innovations in Commercial Instruments

Super-resolution microscopy techniques have accelerated scientific progress, enabling researchers to explore cellular structures and dynamics with unprecedented detail. This review highlights the most recent developments in commercially available super-resolution microscopes, focusing on the most widely used techniques: confocal laser scanning systems, structured illumination microscopy (SIM), stimulated emission depletion (STED) microscopy, and single-molecule localization microscopy (SMLM). We detail the technological advancements of Confocal.NL's GAIA, Nikon's NSPARC, CSR Biotech's MI-SIM, Zeiss's Lattice SIM 5, Leica's STELLARIS STED, and abberior's STED and MINFLUX systems, as well as Abbelight's SAFe MN360 and Bruker's Vutara VXL SMLM platforms. These advancements address the need for enhanced resolution, reduced phototoxicity, and improved imaging capabilities in a range of sample types, while also aiming to enhance user friendliness.

Enabling real-time reconstruction for large field-of-view single-molecule localization microscopy using discrete field-dependent point-spread function

Single-molecule localization microscopy (SMLM) is a powerful super-resolution imaging technique that offers resolution far beyond the optical diffraction limit. The commonly used high numerical-aperture (NA) objective lenses in SMLM can only provide a nearly ideal point-spread function (PSF) at the center of the field-of-view (FOV), whereas the off-axis PSF is often distorted due to optical aberrations. Since precision and accuracy of three-dimensional (3D) spatial localization of single molecules heavily depend on the system's PSF, the FOV of 3D SMLM is often restricted to about 50 µm × 50 µm limiting its applications in visualizing intra-/intercellular interactions and high-throughput single-molecule analysis. Here we present a systematic study to show the influence of optical aberrations on large FOV 3D SMLM using unmodified, astigmatic, and double-helix PSFs. Our results show that optical aberrations introduce significant localization errors during image reconstruction and thereby produce unreliable imaging results at the corner of the FOV. To maximize SMLM's FOV, we proposed and verified the potential of using discrete field-dependent PSFs to retain precise and accurate single-molecule localization and compare their reconstruction results using simulated resolution test patterns and biological structures. Moreover, GPU acceleration empowers a discrete PSF calibration model with high localization speed, which can provide real-time SMLM image reconstruction. We envision these results will further guide the development of strategies that can provide real-time and reliable image reconstruction in large FOV 3D SMLM.

Advances in Microsphere-Based Super-Resolution Imaging

Techniques to resolve images beyond the diffraction limit of light with a large field of view (FOV) are necessary to foster progress in various fields such as cell and molecular biology, biophysics, and nanotechnology, where nanoscale resolution is crucial for understanding the intricate details of large-scale molecular interactions. Although several means of achieving super-resolutions exist, they are often hindered by factors such as high costs, significant complexity, lengthy processing times, and the classical tradeoff between image resolution and FOV. Microsphere-based super-resolution imaging has emerged as a promising approach to address these limitations. In this review, we delve into the theoretical underpinnings of microsphere-based imaging and the associated photonic nanojet. This is followed by a comprehensive exploration of various microsphere-based imaging techniques, encompassing static imaging, mechanical scanning, optical scanning, and acoustofluidic scanning methodologies. This review concludes with a forward-looking perspective on the potential applications and future scientific directions of this innovative technology.

Unveiling the cell biology of hippocampal neurons with dendritic axon origin

In mammalian axon-carrying-dendrite (AcD) neurons, the axon emanates from a basal dendrite, instead of the soma, to create a privileged route for action potential generation at the axon initial segment (AIS). However, it is unclear how such unusual morphology is established and whether the structure and function of the AIS in AcD neurons are preserved. By using dissociated hippocampal cultures as a model, we show that the development of AcD morphology can occur prior to synaptogenesis and independently of the in vivo environment. A single precursor neurite first gives rise to the axon and then to the AcD. The AIS possesses a similar cytoskeletal architecture as the soma-derived AIS and similarly functions as a trafficking barrier to retain axon-specific molecular composition. However, it does not undergo homeostatic plasticity, contains lesser cisternal organelles, and receives fewer inhibitory inputs. Our findings reveal insights into AcD neuron biology and underscore AIS structural differences based on axon onset.

Calibration-free estimation of field dependent aberrations for single molecule localization microscopy across large fields of view

Image quality in single molecule localization microscopy (SMLM) depends largely on the accuracy and precision of the localizations. While under ideal imaging conditions the theoretically obtainable precision and accuracy are achieved, in practice this changes if (field dependent) aberrations are present. Currently there is no simple way to measure and incorporate these aberrations into the Point Spread Function (PSF) fitting, therefore the aberrations are often taken constant or neglected all together. Here we introduce a model-based approach to estimate the field-dependent aberration directly from single molecule data without a calibration step. This is made possible by using nodal aberration theory to incorporate the field-dependency of aberrations into our fully vectorial PSF model. This results in a limited set of aberration fit parameters that can be extracted from the raw frames without a bead calibration measurement, also in retrospect. The software implementation is computationally efficient, enabling fitting of a full 2D or 3D dataset within a few minutes. We demonstrate our method on 2D and 3D localization data of microtubuli and nuclear pore complexes over fields of view (FOV) of up to 180 μm and compare it with spline-based fitting and a deep learning based approach.

DivIVA controls the dynamics of septum splitting and cell elongation in Streptococcus pneumoniae

Bacterial shape and division rely on the dynamics of cell wall assembly, which involves regulated synthesis and cleavage of the peptidoglycan. In ovococci, these processes are coordinated within an annular mid-cell region with nanometric dimensions. More precisely, the cross-wall synthesized by the divisome is split to generate a lateral wall, whose expansion is insured by the insertion of the so-called peripheral peptidoglycan by the elongasome. Septum cleavage and peripheral peptidoglycan synthesis are, thus, crucial remodeling events for ovococcal cell division and elongation. The structural DivIVA protein has long been known as a major regulator of these processes, but its mode of action remains unknown. Here, we integrate click chemistry-based peptidoglycan labeling, direct stochastic optical reconstruction microscopy, and in silico modeling, as well as epifluorescence and stimulated emission depletion microscopy to investigate the role of DivIVA in Streptococcus pneumoniae cell morphogenesis. Our work reveals two distinct phases of peptidoglycan remodeling during the cell cycle that are differentially controlled by DivIVA. In particular, we show that DivIVA ensures homogeneous septum cleavage and peripheral peptidoglycan synthesis around the division site and their maintenance throughout the cell cycle. Our data additionally suggest that DivIVA impacts the contribution of the elongasome and class A penicillin-binding proteins to cell elongation. We also report the position of DivIVA on either side of the septum, consistent with its known affinity for negatively curved membranes. Finally, we take the opportunity provided by these new observations to propose hypotheses for the mechanism of action of this key morphogenetic protein.IMPORTANCEThis study sheds light on fundamental processes governing bacterial growth and division, using integrated click chemistry, advanced microscopy, and computational modeling approaches. It addresses cell wall synthesis mechanisms in the opportunistic human pathogen Streptococcus pneumoniae, responsible for a range of illnesses (otitis, pneumonia, meningitis, septicemia) and for one million deaths every year worldwide. This bacterium belongs to the morphological group of ovococci, which includes many streptococcal and enterococcal pathogens. In this study, we have dissected the function of DivIVA, which is a structural protein involved in cell division, morphogenesis, and chromosome partitioning in Gram-positive bacteria. This work unveils the role of DivIVA in the orchestration of cell division and elongation along the pneumococcal cell cycle. It not only enhances our understanding of how ovoid bacteria proliferate but also offers the opportunity to consider how DivIVA might serve as a scaffold and sensor for particular membrane regions, thereby participating in various cell cycle processes.

Photonic lantern TIRF microscopy for highly efficient, uniform, artifact-free imaging

We report a method for generating uniform, artifact-free total internal reflection fluorescence (TIRF) excitation via a photonic lantern. Our tapered waveguide, consisting of a multimode input and nine few-mode outputs, enables single-shot TIRF illumination from nine azimuthal directions simultaneously without the introduction of nonstationary devices. Utilizing the photonic lantern for multi-beam excitation provides a low-loss mechanism that supports a wide range of light sources, including high-coherence lasers and various wavelengths in the visible spectrum. Our excitation system also allows tuning of the TIRF penetration depth. The high-quality excitation produced by photonic lantern TIRF (PL-TIRF) enables unbiased imaging across the entire illumination field-of-view. The simplicity and robustness of our technique provides advantages over other TIRF approaches, which often have complicated setups with scanning devices or other impracticalities. In this paper we discuss the lantern design process, characterize its performance, and demonstrate flat-field super-resolution imaging and shadowless live-cell imaging using PL-TIRF.

Frontiers in artificial intelligence-directed light-sheet microscopy for uncovering biological phenomena and multi-organ imaging

Light-sheet fluorescence microscopy (LSFM) introduces fast scanning of biological phenomena with deep photon penetration and minimal phototoxicity. This advancement represents a significant shift in 3-D imaging of large-scale biological tissues and 4-D (space + time) imaging of small live animals. The large data associated with LSFM requires efficient imaging acquisition and analysis with the use of artificial intelligence (AI)/machine learning (ML) algorithms. To this end, AI/ML-directed LSFM is an emerging area for multi-organ imaging and tumor diagnostics. This review will present the development of LSFM and highlight various LSFM configurations and designs for multi-scale imaging. Optical clearance techniques will be compared for effective reduction in light scattering and optimal deep-tissue imaging. This review will further depict a diverse range of research and translational applications, from small live organisms to multi-organ imaging to tumor diagnosis. In addition, this review will address AI/ML-directed imaging reconstruction, including the application of convolutional neural networks (CNNs) and generative adversarial networks (GANs). In summary, the advancements of LSFM have enabled effective and efficient post-imaging reconstruction and data analyses, underscoring LSFM's contribution to advancing fundamental and translational research.

Observing multi-frequency structured illumination patterns based on an evanescent field in a millimeter-scale polymer slide

Millimeter-scale slide optical waveguides (OWGs) show the potential to break the barrier of easy-to-use and versatility for total internal reflection (TIR) fluorescence technology. In this paper, multi-frequency structured illumination (SI) patterns resulting from the evanescent field (EF) on the surface of a millimeter-scale polymer slide OWG are observed by measuring the fluorescence intensity distribution of fluorescent dyes deposited on the top of the OWG. The frequency, intensity, and stability of the SI patterns show a strong dependence on the coupling angle of the incident light (changing with the incident position). The distribution of multi-frequency SI patterns in the frequency space is demonstrated for different numerical aperture (NA) imaging systems (NA = 0.3, 0.6, and 0.8), indicating the potential for enhanced resolution for low NA systems with a simple and cheap polymer slide.

Build and operation of a custom 3D, multicolor, single-molecule localization microscope

Single-molecule localization microscopy (SMLM) enables imaging scientists to visualize biological structures with unprecedented resolution. Particularly powerful implementations of SMLM are capable of three-dimensional, multicolor and high-throughput imaging and can yield key biological insights. However, widespread access to these technologies is limited, primarily by the cost of commercial options and complexity of de novo development of custom systems. Here we provide a comprehensive guide for interested researchers who wish to establish a high-end, custom-built SMLM setup in their laboratories. We detail the initial configuration and subsequent assembly of the SMLM, including the instructions for the alignment of all the optical pathways, the software and hardware integration, and the operation of the instrument. We describe the validation steps, including the preparation and imaging of test and biological samples with structures of well-defined geometries, and assist the user in troubleshooting and benchmarking the system's performance. Additionally, we provide a walkthrough of the reconstruction of a super-resolved dataset from acquired raw images using the Super-resolution Microscopy Analysis Platform. Depending on the instrument configuration, the cost of the components is in the range US$95,000-180,000, similar to other open-source advanced SMLMs, and substantially lower than the cost of a commercial instrument. A builder with some experience of optical systems is expected to require 4-8 months from the start of the system construction to attain high-quality three-dimensional and multicolor biological images.

Organelle Proximity Analysis for Enhanced Quantification of Mitochondria-Endoplasmic Reticulum Interactions in Single Cells via Super-Resolution Microscopy

Mitochondria (MT) and the endoplasmic reticulum (ER) maintain lipid and calcium homeostasis through membrane contacts, particularly MT-ER contacts (MERCs), spanning distances from 10 to 50 nm. However, the variation of different distance ranges and the metabolic factors influencing this variation remain poorly understood. This study employed microfluidic chip-based super-resolution microscopy in conjunction with a Moore-Neighbor tracing-incorporated organelle proximity analysis algorithm. This approach enabled precise three-dimensional localization of single-fluorescence protein molecules within narrow and irregular membrane proximities. It achieved lateral localization precision of less than 20 nm, resulting in a minimum MERC distance of approximately 8 nm in spatial and mean distances across multiple threshold ranges. Additionally, we demonstrated that the MERC distance variation was correlated with MT size rather than ER width. The proportion of each distance range varied significantly after the stimuli. Free cholesterol showed a negative correlation with various distances, while distances of 10-30 nm were associated with glucose, glutamine, and pyruvic acid. Furthermore, the 30-40 nm range was influenced by citric acid. These results underscore the role of advanced subcellular organelle analysis in elucidating the single-molecule behavior and organelle morphology in single-cell studies.

Correlative single-molecule and structured illumination microscopy of fast dynamics at the plasma membrane

Total internal reflection fluorescence (TIRF) microscopy offers powerful means to uncover the functional organization of proteins in the plasma membrane with very high spatial and temporal resolution. Traditional TIRF illumination, however, shows a Gaussian intensity profile, which is typically deteriorated by overlaying interference fringes hampering precise quantification of intensities-an important requisite for quantitative analyses in single-molecule localization microscopy (SMLM). Here, we combine flat-field illumination by using a standard πShaper with multi-angular TIR illumination by incorporating a spatial light modulator compatible with fast super-resolution structured illumination microscopy (SIM). This distinct combination enables quantitative multi-color SMLM with a highly homogenous illumination. By using a dual camera setup with optimized image splitting optics, we achieve a versatile combination of SMLM and SIM with up to three channels. We deploy this setup for establishing robust detection of receptor stoichiometries based on single-molecule intensity analysis and single-molecule Förster resonance energy transfer (smFRET). Homogeneous illumination furthermore enables long-term tracking and localization microscopy (TALM) of cell surface receptors identifying spatial heterogeneity of mobility and accessibility in the plasma membrane. By combination of TALM and SIM, spatially and molecularly heterogenous diffusion properties can be correlated with nanoscale cytoskeletal organization and dynamics.

Multimodal illumination platform for 3D single-molecule super-resolution imaging throughout mammalian cells

Single-molecule super-resolution imaging is instrumental in investigating cellular architecture and organization at the nanoscale. Achieving precise 3D nanometric localization when imaging structures throughout mammalian cells, which can be multiple microns thick, requires careful selection of the illumination scheme in order to optimize the fluorescence signal to background ratio (SBR). Thus, an optical platform that combines different wide-field illumination schemes for target-specific SBR optimization would facilitate more precise 3D nanoscale studies of a wide range of cellular structures. Here, we demonstrate a versatile multimodal illumination platform that integrates the sectioning and background reduction capabilities of light sheet illumination with homogeneous, flat-field epi- and TIRF illumination. Using primarily commercially available parts, we combine the fast and convenient switching between illumination modalities with point spread function engineering to enable 3D single-molecule super-resolution imaging throughout mammalian cells. For targets directly at the coverslip, the homogenous intensity profile and excellent sectioning of our flat-field TIRF illumination scheme improves single-molecule data quality by providing low fluorescence background and uniform fluorophore blinking kinetics, fluorescence signal, and localization precision across the entire field of view. The increased contrast achieved with LS illumination, when compared with epi-illumination, makes this illumination modality an excellent alternative when imaging targets that extend throughout the cell. We validate our microscopy platform for improved 3D super-resolution imaging by two-color imaging of paxillin - a protein located in the focal adhesion complex - and actin in human osteosarcoma cells.

Multimodal illumination platform for 3D single-molecule super-resolution imaging throughout mammalian cells

Single-molecule super-resolution imaging is instrumental for investigating cellular architecture and organization at the nanoscale. Achieving precise 3D nanometric localization when imaging structures throughout mammalian cells, which can be multiple microns thick, requires careful selection of the illumination scheme in order to optimize the fluorescence signal to background ratio (SBR). Thus, an optical platform that combines different wide-field illumination schemes for target-specific SBR optimization would facilitate more precise, 3D nanoscale studies of a wide range of cellular structures. Here we demonstrate a versatile multimodal illumination platform that integrates the sectioning and background reduction capabilities of light sheet illumination with homogeneous, flat-field epi-and TIRF illumination. Using primarily commercially available parts, we combine the fast and convenient switching between illumination modalities with point spread function engineering to enable 3D single-molecule super-resolution imaging throughout mammalian cells. For targets directly at the coverslip, the homogenous intensity profile and excellent sectioning of our flat-field TIRF illumination scheme improves single-molecule data quality by providing low fluorescence background and uniform fluorophore blinking kinetics, fluorescence signal, and localization precision across the entire field of view. The increased contrast achieved with LS illumination, when compared with epi-illumination, makes this illumination modality an excellent alternative when imaging targets that extend throughout the cell. We validate our microscopy platform for improved 3D super-resolution imaging by two-color imaging of paxillin - a protein located in the focal adhesion complex - and actin in human osteosarcoma cells.

Multidimensional Widefield Infrared-Encoded Spontaneous Emission Microscopy: Distinguishing Chromophores by Ultrashort Infrared Pulses

Photoluminescence (PL) imaging has broad applications in visualizing biological activities, detecting chemical species, and characterizing materials. However, the chemical information encoded in the PL images is often limited by the overlapping emission spectra of chromophores. Here, we report a PL microscopy based on the nonlinear interactions between mid-infrared and visible excitations on matters, which we termed MultiDimensional Widefield Infrared-encoded Spontaneous Emission (MD-WISE) microscopy. MD-WISE microscopy can distinguish chromophores that possess nearly identical emission spectra via conditions in a multidimensional space formed by three independent variables: the temporal delay between the infrared and the visible pulses (t), the wavelength of visible pulses (λvis), and the frequencies of the infrared pulses (ωIR). This method is enabled by two mechanisms: (1) modulating the optical absorption cross sections of molecular dyes by exciting specific vibrational functional groups and (2) reducing the PL quantum yield of semiconductor nanocrystals, which was achieved through strong field ionization of excitons. Importantly, MD-WISE microscopy operates under widefield imaging conditions with a field of view of tens of microns, other than the confocal configuration adopted by most nonlinear optical microscopies, which require focusing the optical beams tightly. By demonstrating the capacity of registering multidimensional information into PL images, MD-WISE microscopy has the potential of expanding the number of species and processes that can be simultaneously tracked in high-speed widefield imaging applications.

Multiplexed and Millimeter-Scale Fluorescence Nanoscopy of Cells and Tissue Sections via Prism-Illumination and Microfluidics-Enhanced DNA-PAINT

Fluorescence nanoscopy has become increasingly powerful for biomedical research, but it has historically afforded a small field-of-view (FOV) of around 50 μm × 50 μm at once and more recently up to ∼200 μm × 200 μm. Efforts to further increase the FOV in fluorescence nanoscopy have thus far relied on the use of fabricated waveguide substrates, adding cost and sample constraints to the applications. Here we report PRism-Illumination and Microfluidics-Enhanced DNA-PAINT (PRIME-PAINT) for multiplexed fluorescence nanoscopy across millimeter-scale FOVs. Built upon the well-established prism-type total internal reflection microscopy, PRIME-PAINT achieves robust single-molecule localization with up to ∼520 μm × 520 μm single FOVs and 25-40 nm lateral resolutions. Through stitching, nanoscopic imaging over mm2 sample areas can be completed in as little as 40 min per target. An on-stage microfluidics chamber facilitates probe exchange for multiplexing and enhances image quality, particularly for formalin-fixed paraffin-embedded (FFPE) tissue sections. We demonstrate the utility of PRIME-PAINT by analyzing ∼106 caveolae structures in ∼1,000 cells and imaging entire pancreatic cancer lesions from patient tissue biopsies. By imaging from nanometers to millimeters with multiplexity and broad sample compatibility, PRIME-PAINT will be useful for building multiscale, Google-Earth-like views of biological systems.

Assessing crosstalk in simultaneous multicolor single-molecule localization microscopy

Single-molecule localization microscopy (SMLM) can reach sub-50 nm resolution using techniques such as stochastic optical reconstruction microscopy (STORM) or DNA-point accumulation for imaging in nanoscale topography (PAINT). Here we implement two approaches for faster multicolor SMLM by splitting the emitted fluorescence toward two cameras: simultaneous two-color DNA-PAINT (S2C-DNA-PAINT) that images spectrally separated red and far-red imager strands on each camera, and spectral demixing dSTORM (SD-dSTORM) where spectrally close far-red fluorophores appear on both cameras before being identified by demixing. Using S2C-DNA-PAINT as a reference for low crosstalk, we evaluate SD-dSTORM crosstalk using three types of samples: DNA origami nanorulers of different sizes, single-target labeled cells, or cells labeled for multiple targets. We then assess if crosstalk can affect the detection of biologically relevant subdiffraction patterns. Extending these approaches to three-dimensional acquisition and SD-dSTORM to three-color imaging, we show that spectral demixing is an attractive option for robust and versatile multicolor SMLM investigations.

Fibroblasts generate topographical cues that steer cancer cell migration

Fibroblasts play a fundamental role in tumor development. Among other functions, they regulate cancer cells' migration through rearranging the extracellular matrix, secreting soluble factors, and establishing direct physical contacts with cancer cells. Here, we report that migrating fibroblasts deposit on the substrate a network of tubular structures that serves as a guidance cue for cancer cell migration. Such membranous tubular network, hereafter called tracks, is stably anchored to the substrate in a β5-integrin-dependent manner. We found that cancer cells specifically adhere to tracks by using clathrin-coated structures that pinch and engulf tracks. Tracks thus represent a spatial memory of fibroblast migration paths that is read and erased by cancer cells directionally migrating along them. We propose that fibroblast tracks represent a topography-based intercellular communication system capable of steering cancer cell migration.

Deep learning-enhanced fluorescence microscopy via confocal physical imaging model

Confocal microscopy is one of the most widely used tools for high-resolution cellular, tissue imaging and industrial inspection. Micrograph reconstruction based on deep learning has become an effective tool for modern microscopy imaging techniques. While most deep learning methods neglect the imaging process mechanism, which requires a lot of work to solve the multi-scale image pairs aliasing problem. We show that these limitations can be mitigated via an image degradation model based on Richards-Wolf vectorial diffraction integral and confocal imaging theory. The low-resolution images required for network training are generated by model degradation from their high-resolution counterparts, thereby eliminating the need for accurate image alignment. The image degradation model ensures the generalization and fidelity of the confocal images. By combining the residual neural network with a lightweight feature attention module with degradation model of confocal microscopy ensures high fidelity and generalization. Experiments on different measured data report that compared with the two deconvolution algorithms, non-negative least squares algorithm and Richardson-Lucy algorithm, the structural similarity index between the network output image and the real image reaches a high level above 0.82, and the peak signal-to-noise ratio can be improved by more than 0.6 dB. It also shows good applicability in different deep learning networks.

Flattened Gaussian focal spot with uniform phase produced by photon sieve

The equivalent pupil and the point spread function constitute the Fourier-Bessel transform relation. Based on this, we established the equivalent pupil function theory of rotating symmetric photon sieve and derived the Fourier transform of the flattened Gaussian function. The focal spot produced by this type of photon sieve exhibits a uniform intensity and phase distribution. According to the numerical results, the flattened Gaussian field distribution is consistent with the designed function. In addition, the nonuniformity in intensity and phase is approximately 1% and less than 1/170 wavelength, respectively.

Error-Correction Method for High-Throughput Sizing of Nanoscale Vesicles with Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) allows super-resolution imaging, mapping, counting, and sizing of biological nanostructures such as cell organelles and extracellular vesicles (EVs), but sizing structures smaller than ∼100 nm can be inaccurate due to single-molecule localization error caused by distortion of the point spread function and limited photon number. Here we demonstrate a method to correct localization error when sizing vesicles and other spherical nanoparticles with SMLM and compare sizing results using two vesicle labeling schemes. We use mean approximation theory to derive a simple equation using full width at half-maximum (FWHM) for correcting particle sizes measured by two-dimensional SMLM, validate the method by sizing streptavidin-coated polystyrene nanobeads with the SMLM technique dSTORM with and without error correction, using transmission electron microscopy (TEM) for comparison, and then apply the method to sizing small seminal EVs. Nanobead sizes measured by dSTORM became increasingly less accurate (larger than TEM values) for beads smaller than 50 nm. The error-correction method reduced the size difference versus TEM from 15% without error correction to 7% with error correction for 40 nm beads, from 44% to 9% for 30 nm beads, and from 66% to 15% for 20 nm beads. Seminal EVs were labeled with a lipophilic membrane dye (MemBright 700) and with an Alexa Fluor 488-anti-CD63 antibody conjugate, and were sized separately using both dyes by dSTORM. Error-corrected exosome diameters were smaller than uncorrected values: 72 nm vs 79 nm mean diameter with membrane dyes; 84 nm vs 97 nm with the antibody-conjugated dyes. The mean error-corrected diameter was 12 nm smaller when using the membrane dye than when using the antibody-conjugated dye likely due to the large size of the antibody. Thus, both the error-correction method and the compact membrane labeling scheme reduce overestimation of vesicle size by SMLM. This error-correction method has a low computational cost as it does not require correction of individual blinking events, and it is compatible with all SMLM techniques (e.g., PALM, STORM, and DNA-PAINT).

An open-source microscopy framework for simultaneous control of image acquisition, reconstruction, and analysis

We present a computational framework to simultaneously perform image acquisition, reconstruction, and analysis in the context of open-source microscopy automation. The setup features multiple computer units intersecting software with hardware devices and achieves automation using python scripts. In practice, script files are executed in the acquisition computer and can perform any experiment by modifying the state of the hardware devices and accessing experimental data. The presented framework achieves concurrency by using multiple instances of ImSwitch and napari working simultaneously. ImSwitch is a flexible and modular open-source software package for microscope control, and napari is a multidimensional image viewer for scientific image analysis. The presented framework implements a system based on file watching, where multiple units monitor a filesystem that acts as the synchronization primitive. The proposed solution is valid for any microscope setup, supporting various biological applications. The only necessary element is a shared filesystem, common in any standard laboratory, even in resource-constrained settings. The file watcher functionality in Python can be easily integrated into other python-based software. We demonstrate the proposed solution by performing tiling experiments using the molecular nanoscale live imaging with sectioning ability (MoNaLISA) microscope, a high-throughput super-resolution microscope based on reversible saturable optical fluorescence transitions (RESOLFT).

Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging

Single-molecule localization microscopy in a typical wide-field setup has been widely used for investigating subcellular structures with super resolution; however, field-dependent aberrations restrict the field of view (FOV) to only tens of micrometers. Here, we present a deep-learning method for precise localization of spatially variant point emitters (FD-DeepLoc) over a large FOV covering the full chip of a modern sCMOS camera. Using a graphic processing unit-based vectorial point spread function (PSF) fitter, we can fast and accurately model the spatially variant PSF of a high numerical aperture objective in the entire FOV. Combined with deformable mirror-based optimal PSF engineering, we demonstrate high-accuracy three-dimensional single-molecule localization microscopy over a volume of ~180 × 180 × 5 μm³, allowing us to image mitochondria and nuclear pore complexes in entire cells in a single imaging cycle without hardware scanning; a 100-fold increase in throughput compared to the state of the art.

Adaptive Design of Fluorescence Imaging Systems for Custom Resolution, Fields of View, and Geometries

Objective and Impact Statement: We developed a generalized computational approach to design uniform, high-intensity excitation light for low-cost, quantitative fluorescence imaging of in vitro, ex vivo, and in vivo samples with a single device. Introduction: Fluorescence imaging is a ubiquitous tool for biomedical applications. Researchers extensively modify existing systems for tissue imaging, increasing the time and effort needed for translational research and thick tissue imaging. These modifications are application-specific, requiring new designs to scale across sample types. Methods: We implemented a computational model to simulate light propagation from multiple sources. Using a global optimization algorithm and a custom cost function, we determined the spatial positioning of optical fibers to generate 2 illumination profiles. These results were implemented to image core needle biopsies, preclinical mammary tumors, or tumor-derived organoids. Samples were stained with molecular probes and imaged with uniform and nonuniform illumination. Results: Simulation results were faithfully translated to benchtop systems. We demonstrated that uniform illumination increased the reliability of intraimage analysis compared to nonuniform illumination and was concordant with traditional histological findings. The computational approach was used to optimize the illumination geometry for the purposes of imaging 3 different fluorophores through a mammary window chamber model. Illumination specifically designed for intravital tumor imaging generated higher image contrast compared to the case in which illumination originally optimized for biopsy images was used. Conclusion: We demonstrate the significance of using a computationally designed illumination for in vitro, ex vivo, and in vivo fluorescence imaging. Application-specific illumination increased the reliability of intraimage analysis and enhanced the local contrast of biological features. This approach is generalizable across light sources, biological applications, and detectors.

Benchmarking Thiolate-Driven Photoswitching of Cyanine Dyes

Carbocyanines are among the best performing dyes in single-molecule localization microscopy (SMLM), but their performance critically relies on optimized photoswitching buffers. Here, we study the versatile role of thiols in cyanine photoswitching at varying intensities generated in a single acquisition by a microelectromechanical systems (MEMS) mirror placed in the excitation path. The key metrics we have analyzed as a function of the thiolate concentration are photon budget, on-state and off-state lifetimes and the corresponding impact on image resolution. We show that thiolate acts as a concentration bandpass filter for the maximum achievable resolution and determine a minimum of ∼1 mM is necessary to facilitate SMLM measurements. We also identify a concentration bandwidth of 1-16 mM in which the photoswitching performance can be balanced between high molecular brightness and high off-time to on-time ratios. Furthermore, we monitor the performance of the popular oxygen scavenger system based on glucose and glucose oxidase over time and show simple measures to avoid acidification during prolonged measurements. Finally, the impact of buffer settings is quantitatively tested on the distribution of the glucose transporter protein 4 within the plasma membrane of adipocytes. Our work provides a general strategy for achieving optimal resolution in SMLM with relevance for the development of novel buffers and dyes.

Microtubules self-repair in living cells

Microtubule self-repair has been studied both in vitro and in vivo as an underlying mechanism of microtubule stability. The turnover of tubulin dimers along the microtubule has challenged the pre-existing dogma that only growing ends are dynamic. However, although there is clear evidence of tubulin incorporation into the shaft of polymerized microtubules in vitro, the possibility of such events occurring in living cells remains uncertain. In this study, we investigated this possibility by microinjecting purified tubulin dimers labeled with a red fluorophore into the cytoplasm of cells expressing GFP-tubulin. We observed the appearance of red dots along the pre-existing green microtubule within minutes. We found that the fluorescence intensities of these red dots were inversely correlated with the green signal, suggesting that the red dimers were incorporated into the microtubules and replaced the pre-existing green dimers. Lateral distance from the microtubule center was similar to that in incorporation sites and in growing ends. The saturation of the size and spatial frequency of incorporations as a function of injected tubulin concentration and post-injection delay suggested that the injected dimers incorporated into a finite number of damaged sites. By our low estimate, within a few minutes of the injections, free dimers incorporated into major repair sites every 70 μm of microtubules. Finally, we mapped the location of these sites in micropatterned cells and found that they were more concentrated in regions where the actin filament network was less dense and where microtubules exhibited greater lateral fluctuations.

Single-molecule counting applied to the study of GPCR oligomerization

Single-molecule counting techniques enable a precise determination of the intracellular abundance and stoichiometry of proteins and macromolecular complexes. These details are often challenging to quantitatively assess yet are essential for our understanding of cellular function. Consider G-protein-coupled receptors-an expansive class of transmembrane signaling proteins that participate in many vital physiological functions making them a popular target for drug development. While early evidence for the role of oligomerization in receptor signaling came from ensemble biochemical and biophysical assays, innovations in single-molecule measurements are now driving a paradigm shift in our understanding of its relevance. Here, we review recent developments in single-molecule counting with a focus on photobleaching step counting and the emerging technique of quantitative single-molecule localization microscopy-with a particular emphasis on the potential for these techniques to advance our understanding of the role of oligomerization in G-protein-coupled receptor signaling.

A new mechanism of fibronectin fibril assembly revealed by live imaging and super-resolution microscopy

Fibronectin (Fn1) fibrils have long been viewed as continuous fibers composed of extended, periodically aligned Fn1 molecules. However, our live-imaging and single-molecule localization microscopy data are inconsistent with this traditional view and show that Fn1 fibrils are composed of roughly spherical nanodomains containing six to eleven Fn1 dimers. As they move toward the cell center, Fn1 nanodomains become organized into linear arrays, in which nanodomains are spaced with an average periodicity of 105±17 nm. Periodical Fn1 nanodomain arrays can be visualized between cells in culture and within tissues; they are resistant to deoxycholate treatment and retain nanodomain periodicity in the absence of cells. The nanodomain periodicity in fibrils remained constant when probed with antibodies recognizing distinct Fn1 epitopes or combinations of antibodies recognizing epitopes spanning the length of Fn1. Treatment with FUD, a peptide that binds the Fn1 N-terminus and disrupts Fn1 fibrillogenesis, blocked the organization of Fn1 nanodomains into periodical arrays. These studies establish a new paradigm of Fn1 fibrillogenesis. This article has an associated First Person interview with the first author of the paper.

Spatio-Temporal Properties of Amused, Embarrassed, and Pained Smiles

Smiles are universal but nuanced facial expressions that are most frequently used in face-to-face communications, typically indicating amusement but sometimes conveying negative emotions such as embarrassment and pain. Although previous studies have suggested that spatial and temporal properties could differ among these various types of smiles, no study has thoroughly analyzed these properties. This study aimed to clarify the spatiotemporal properties of smiles conveying amusement, embarrassment, and pain using a spontaneous facial behavior database. The results regarding spatial patterns revealed that pained smiles showed less eye constriction and more overall facial tension than amused smiles; no spatial differences were identified between embarrassed and amused smiles. Regarding temporal properties, embarrassed and pained smiles remained in a state of higher facial tension than amused smiles. Moreover, embarrassed smiles showed a more gradual change from tension states to the smile state than amused smiles, and pained smiles had lower probabilities of staying in or transitioning to the smile state compared to amused smiles. By comparing the spatiotemporal properties of these three smile types, this study revealed that the probability of transitioning between discrete states could help distinguish amused, embarrassed, and pained smiles.

PCIe-based FPGA-GPU heterogeneous computation for real-time multi-emitter fitting in super-resolution localization microscopy

Real-time multi-emitter fitting is a key technology for advancing super-resolution localization microscopy (SRLM), especially when it is necessary to achieve dynamic imaging quality control and/or optimization of experimental conditions. However, with the increase of activation densities, the requirements in the computing resources would increase rapidly due to the complexity of the fitting algorithms, making it difficult to realize real-time multi-emitter fitting for emitter density more than 0.6 mol/µm² in large field of view (FOV), even after acceleration with the popular Graphics Processing Unit (GPU) computation. Here we adopt the task parallelism strategy in computer science to construct a Peripheral Component Interconnect Express (PCIe) based all-in-one heterogeneous computing platform (AIO-HCP), where the data between two major parallel computing hardware, Field Programmable Gate Array (FPGA) and GPU, are interacted directly and executed simultaneously. Using simulated and experimental data, we verify that AIO-HCP could achieve a data throughput of up to ∼ 1.561 GB/s between FPGA and GPU. With this new platform, we develop a multi-emitter fitting method, called AIO-STORM, under big data stream parallel scheduling. We show that AIO-STORM is capable of providing real-time image processing on raw images with 100 µm × 100 µm FOV, 10 ms exposure time and 5.5 mol/µm² structure density, without scarifying image quality. This study overcomes the data throughput limitation of heterogeneous devices, demonstrates the power of the PCIe-based heterogeneous computation platform, and offers opportunities for multi-scale stitching of super-resolution images.

Simulation-driven learning: a deep learning approach for image scanning microscopy via physical imaging models

Image reconstruction based on deep learning has become an effective tool in fluorescence microscopy. Most deep learning reconstruction methods ignore the mechanism of the imaging process where a large number of datasets are required. In addition, a lot of time is spent solving the aliasing problem from multi-scaled image pairs for data pre-processing. Here we demonstrate an improved generative adversarial network for image scanning microscopy (ISM) that can be trained by simulation data and has good generalization. Based on physical imaging models, this method can generate matching image pairs from simulation images and uses them as datasets for network training, without capturing a large number of real ISM images and avoiding image alignment preprocessing. Simulation and experimental results show that this simulation data-driven method improves the imaging quality of conventional microscopic images and reduces the cost of experiments. This method provides inspiration for optimizing network generalizability of the deep learning network.

Imaging the endocannabinoid signaling system

The endocannabinoid (eCB) system is one of the most widespread neuromodulatory systems in the mammalian brain, with a multifaceted role in functions ranging from development to synaptic plasticity. Endocannabinoids are synthesized on demand from membrane lipid precursors, and act primarily on a single G-protein coupled receptor type, CB1, to carry out diverse functions. Despite the importance of the eCB system both in healthy brain function and in disease, critically important details of eCB signaling remained unknown. How eCBs are released from the membrane, how these lipid molecules are transported between cells, and how the distribution of their receptors is controlled, remained elusive. Recent advances in optical microscopy methods and biosensor engineering may open up new avenues for studying eCB signaling. We summarize applications of superresolution microscopy using single molecule localization to reveal distinct patterns of nanoscale CB1 distribution in neuronal axons and axon terminals. We review single particle tracking studies using quantum dots that allowed visualizing CB1 trajectories. We highlight the recent development of fluorescent eCB biosensors, that revealed spatiotemporally specific eCB release in live cells and live animals. Finally, we discuss future directions where method development may help to advance a precise understanding of eCB signaling.

Fluorescence nanoscopy at the sub-10 nm scale

Fluorescence nanoscopy represented a breakthrough for the life sciences as it delivers 20-30 nm resolution using far-field fluorescence microscopes. This resolution limit is not fundamental but imposed by the limited photostability of fluorophores under ambient conditions. This has motivated the development of a second generation of fluorescence nanoscopy methods that aim to deliver sub-10 nm resolution, reaching the typical size of structural proteins and thus providing true molecular resolution. In this review, we present common fundamental aspects of these nanoscopies, discuss the key experimental factors that are necessary to fully exploit their capabilities, and discuss their current and future challenges.

Tunable Wide-Field Illumination and Single-Molecule Photoswitching with a Single MEMS Mirror

Homogeneous illumination in single-molecule localization microscopy (SMLM) is key for the quantitative analysis of super-resolution images. Therefore, different approaches for flat-field illumination have been introduced as alternative to the conventional Gaussian illumination. Here, we introduce a single microelectromechanical systems (MEMS) mirror as a tunable and cost-effective device for adapting wide-field illumination in SMLM. In flat-field mode the MEMS allowed for consistent SMLM metrics across the entire field of view. Employing single-molecule photoswitching, we developed a simple yet powerful routine to benchmark different illumination schemes on the basis of local emitter brightness and ON-state lifetime. Moreover, we propose that tuning the MEMS beyond optimal flat-field conditions enables to study the kinetics of photoswitchable fluorophores within a single acquisition.