Nature Photonics

Beams of light that feature an intensity zero are essential to a variety of optical microscopy methods. Super-resolution techniques like STED and RESOLFT, together with localization strategies like MINFLUX and MINSTED, rely on accurate and fast displacements of such beams and their zeros. Extending these methods to the third dimension requires axial deflection, which, in contrast to lateral deflection, remains technologically challenging on the microsecond scale. Here, we present a fast general-purpose beam-shaping polarization interferometer that, instead of displacing the entire beam, enables such axial deflections by deforming the beam shape to deflect its zero. Based on this approach, we showcase a four-channel dual-color excitation system for three-dimensional MINFLUX imaging and tracking. We include first demonstrations of improved MINFLUX localization schemes that utilize the combination of distinct beam shapes and three-dimensional multi-emitter tracking. We believe that the presented approach will facilitate the broader adoption of three dimensional MINFLUX and provides a versatile basis for future implementations of advanced single-molecule localization methods.

Single-molecule localization microscopy (SMLM) enables nanoscale imaging but remains limited in three-dimensional (3D), high-speed, and high-density applications due to background fluorescence, photon inefficiency, and large point-spread function (PSF) footprints. Here, we present single-objective light-sheet microscopy with PSF-engineering enhanced biplane detection (SoLiD-3D), a versatile imaging platform that integrates dual-wavelength light-sheet illumination with dual-color, multi-configuration biplane imaging for parallel acquisition with PSF engineered detection for high-speed volumetric SMLM. Parallelized single-objective light-sheet excitation combined with PSF engineering overcomes key limitations of conventional wide-field and biplane approaches. Independent control of two excitation wavelengths for optical sectioning enables simultaneous dual-target imaging and single-target dual-color imaging with improved contrast and temporal resolution utilizing dynamically displaced light sheets for volumetric coverage. Using SoLiD-3D, we demonstrate high-speed single- and dual-target dual-color imaging that doubles localization density without sacrificing photon efficiency and continuous volumetric imaging via PSF-engineering enhanced biplane detection for whole-cell 3D imaging with improved axial localization performance over extended depth ranges. We further demonstrate improved speed by utilizing the Hummus PSF, a compact engineered PSF that enables high-precision 3D localization with a substantially reduced spatial footprint, for the first time for super-resolution imaging applications. Taken together, SoLiD-3D mitigates the trade-off between axial range and localization precision and offers improved speed compared to conventional 3D SMLM approaches.

Optical imaging systems are fundamentally constrained by a tradeoff between field of view (FoV) and spatial resolution. Long working-distance objectives, routinely used in biological imaging and especially in light-sheet microscopy, provide large FoV but reduced numerical aperture (NA) and magnification, broadening the point spread function (PSF) while coarsening detector sampling. As a result, even PSF-limited resolution is often undersampled. Here we demonstrate photon superlocalization as a strategy to mitigate this tradeoff. On intensified detectors, individual photons form multipixel detection clouds that can be centroided and reassigned to a finer virtual grid, thereby increasing the effective sampling frequency without optical modifications or FoV penalty. Proof-of-principle epifluorescence and light-sheet experiments show that photon superlocalization restores near-PSF-limited resolution and reveals subcellular structure otherwise obscured by undersampling. This approach provides a generalizable, photon-efficient pathway for improving spatial resolution across imaging modalities constrained by the FoV-resolution tradeoff.

Although several open-source, easy-to-assemble light-sheet microscope platforms already exist--such as mesoSPIM, OpenSPIM, and OpenSpin--they are optimized for imaging large specimens and lack the resolution required to visualize sub-cellular features, such as organelles or cytoskeletal architectures. In contrast, Latice Light-Sheet Microscopy (LLSM) achieves the resolution necessary to resolve such fine structures but, in its open-source implementation, can be alignment- and maintenance-intensive, often requiring specialist expertise. To address this gap, we developed Altair-LSFM, a high-resolution, open-source, sample-scanning light-sheet microscope specifically designed for sub-cellular imaging. By optimizing the optical pathway in silico, we created a custom baseplate that greatly simplifies alignment and assembly. The system integrates streamlined optoelectronics and optomechanics with seamless operation through our open-source software, navigate. Altair-LSFM achieves lateral and axial resolutions of approximately 235 nm and 350 nm, respectively, across a 266-micron field of view after deconvolution. We validate the systems capabilities by imaging sub-diffraction fluorescent nanospheres and visualizing fine structural details in mammalian cells, including microtubules, actin filaments, nuclei, and Golgi apparatus. We further demonstrate its live-cell imaging capabilities by visualizing microtubules and vimentin intermediate filaments in actively migrating cells.

The volumetric architecture of organelles and molecules inside cells can only be investigated with microscopes featuring sufficiently high resolving power in all three spatial dimensions. Current methods suffer from severe limitations when applied to live cell imaging such as long recording times and/or photobleaching. By introducing a novel optical scheme to switch reversibly switchable fluorescent molecules, we demonstrate volumetric nanoscopy of living cells with resolution below 100 nm in 3D, large field of view and minimal illumination intensities (W-kW/cm2).

Ultra-high resolution 3D single-molecule localization microscopy (SMLM) traditionally requires complex dual-objective lenses (4Pi) configurations to enhance axial (z) precision through interferometry. Here we present a streamlined chip-based alternative, Silicon-assisted interferometric Localization Microscopy (SiLM), which achieves comparable performance using a single-objective lens design. By combining tunable axial structured illumination field, arising from surface-generated excitation interference, with asynchronous interferometry, SiLM enhances axial localization precision to approximately twice that of the lateral (xy), comparable to 4Pi-based methods. Additionally, SiLM provides intrinsic axial self-referencing, offering dramatically improved robustness against mechanical drift. Our method is readily implementable on standard SMLM-capable microscopes and supports a broad range of applications including dual-color imaging, extended-depth imaging, and live-cell 3D single-molecule tracking. Using SiLM, we demonstrate accurate mapping of the stratified nanoscale architecture of integrin-based focal adhesions, establishing it as a powerful and accessible method for high-precision 3D structural cell biology.

Although three-dimensional (3D) fluorescence microscopy is an essential tool for life science research, the fundamentally-limited optical throughput, as reflected in the compromise between speed and resolution, so far prevents further movement towards faster, clearer, and higher-throughput applications. We herein report a dual-stage mutual-feedback deep-learning approach that allows gradual reversion of microscopy degradation from high-resolution targets to low-resolution images. Using a single blurred-and-pixelated 3D image as input, our trained network infers a 3D output with notably higher resolution and improved contrast. The performance is better than conventional 1-stage network approaches. It pushes the throughput limit of current 3D fluorescence microscopy in three ways: notably reducing the acquisition time for accurate mapping of large organs, breaking the diffraction limit for imaging subcellular events with faster lower-toxicity measurement, and improving temporal resolution for capturing instantaneous biological processes. Combining our network approach with light-sheet fluorescence microscopy, we demonstrate the imaging of vessels and neurons in the mouse brain at single-cell resolution and with a throughput of 6 minutes for a whole brain. We also image cell organelles beyond the diffraction limit at a 2-Hz volume rate, and map neuronal activities of freely-moving C. elegans at single-cell resolution and 30-Hz volume rate.

Light sheet fluorescence microscopy (LSFM) has become a leading standard in high-resolution imaging of living samples in 2- and 3-dimensions. Biological samples are however not restricted to a single observation plane and several molecular processes evolve rapidly in 3D. The conventional mechanical scanning required in LSFM limits the range of observable dynamics and are usually restricted in resolution. Here we introduce a new strategy for instantaneous volumetric excitation and volumetric imaging of single-molecules in cell aggregates. The technique combines, for the first time, the use of light sheet microscopy and multifocus microscopy (MFM) and enables a volumetric 4D imaging of biological samples with single-molecule resolution. We engineered the excitation beam to yield a modular and uniform excitation matching the observable detection range of MFM. The strength of the method is highlighted with examples of single-molecule 3D tracking and 3D super-resolution imaging in multicellular samples.

Stimulated emission depletion (STED) fluorescence nanoscopy allows the three-dimensional (3D) visualization of nanoscale subcellular structures, providing unique insights into their spatial organization. However, 3D-STED imaging and quantification of dense features are obstructed by the low signal-to-background ratio (SBR), resulting from optical aberrations and out-of-focus background. Here, combining with adaptive optics, we present an easy-to-implement and flexible method to improve SBR by dynamic phase switching. By switching to a counterclockwise vortex phase mask and a top-hat one with an incorrect inner radius, the depletion pattern features a nonzero-intensity center, enabling accurate background recordings. When the recorded background is subtracted from the aberration-corrected 3D-STED image, the SBR in dense sample areas can be improved by a factor of 3-6 times. We demonstrate our method on various dense subcellular structures, showing more advantages than the software-based background subtraction algorithms. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/497623v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@7aacd6org.highwire.dtl.DTLVardef@1e91f14org.highwire.dtl.DTLVardef@1f774acorg.highwire.dtl.DTLVardef@10ccf5d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Hyperspectral imaging is highly sought after in many fields including mineralogy and geology, environment and agriculture, astronomy and, importantly, biomedical imaging and biological fluorescence. We developed ultrafast phasor-based hyperspectral snapshot microscopy based on sine/cosine interference filters for biomedical imaging not feasible with conventional hyperspectral detection methods. Current approaches rely on slow spatial or spectral scanning limiting their application in living biological tissues, while faster snapshot methods such as image mapping spectrometry and multispectral interferometry are limited in spatial and/or spectral resolution, are computationally demanding, and imaging devices are very expensive to manufacture. Leveraging light sheet microscopy, phasor-based hyperspectral snapshot microscopy improved imaging speed 10-100 fold which, combined with minimal light exposure and high detection efficiency, enabled hyperspectral metabolic imaging of live, three-dimensional mouse tissues not feasible with other methods. As a fit-free method that does not require any a priori information often unavailable in complex and evolving biological systems, the rule of linear combinations of the phasor could spectrally resolve subtle differences between cell types in the developing zebrafish retina and spectrally separate and track multiple organelles in 3D cultured cells over time. The sine/cosine snapshot method is adaptable to any microscope or imaging device thus making hyperspectral imaging and fit-free analysis based on linear combinations broadly available to researchers and the public.

Electron microscopy (EM) and fluorescence imaging are indispensable techniques that provide complementary information on cellular organization. Combining these two modalities is a long-standing challenge in bioimaging. In principle, it should be possible to use the electron beam both for ultrastructural imaging and for molecular localization. The latter could be accomplished by directly exciting suitable biomolecular labels and detecting their luminescence - a process termed cathodoluminescence (CL). Here, we achieve multicolor, single-particle CL imaging of sub-20-nm lanthanide nanocrystals (cathodophores) in the same field of view on the surface of a mammalian cell while simultaneously imaging cellular ultrastructure. In pursuit of this goal, we have developed a comprehensive framework for single-particle CL imaging of lanthanide nanocrystals. By mitigating nonlocal excitation due to secondary electrons, we achieved single-particle detection of multiple spectrally distinct types of sub-20-nm cathodophores. The smallest detectable cathodophores were sub-12 nm in diameter. We found that the CL emission rate scaled linearly with nanocrystal diameter. Furthermore, even in the absence of inert shells, cathodophores were not quenched in the context of mammalian cells processed for EM imaging using heavy-metal staining and sputter-coating. These findings establish cathodophores as promising biomolecular tags for multicolor EM. Moreover, our results inform general design rules for precise control and rational engineering of future generations of single-particle cathodoluminescent nanoprobes.

High-quality cellular imaging, especially in live cells, remains constrained by the trade-off among signal-to-noise ratio, phototoxicity, and instrumentation complexity. Here, we report a scalable plasmonic metasurface that generates a spatially ordered array of fluorescence-enhancing near-field hotspots and enables self-supervised denoised, cellular imaging with improved feature readability on a conventional wide-field microscope. The registered hotspot lattice serves as a physics-derived functional prior that identifies where fluorescence amplification is physically grounded and steers neural-network training accordingly, reducing reliance on paired ground truth, large external pretrained models, or extensive supervised datasets. We demonstrate two labeling-density-dependent operating regimes: dense labeling for cytoskeleton structural imaging and sparse labeling for multiplexed sensing of plasma-membrane-associated dynamics across the hotspot array. Our work unites scalable nanophotonic hardware and self-supervised computational imaging into a practical platform for structural bioimaging and on-chip live-cell biosensing under simple wide-field imaging conditions.

Epi oblique illumination selective plane microscopy (EOPM) facilitates open-top, straightforward sample mounting, enabling high-resolution and high-speed imaging without perturbing biological specimens. However, current EOPM systems typically require three separate microscopes equipped with specialized objectives. This configuration leads to complex and costly setups, significant long-term drift during imaging, reduced numerical aperture, and limited flexibility in adjusting the illumination tilt angle. We introduce Reflected Inline Detection in Epi-Oblique Plane Microscopy (RIDE-OPM), a novel, simplified, and cost-effective design that removes the necessity for a separate inline tertiary microscope and specialized objectives. Our tilt-angle-independent approach leverages the maximum NA of standard objectives, ensuring optimal illumination across the entire field of view without compromising imaging speed or quality, while significantly reducing long-term system drift. The compact and stable RIDE-OPM platform demonstrates robust, unsupervised long-term imaging capabilities. We validated this performance by successfully imaging various biological specimens, including C. elegans, Drosophila fly brain, human and mouse epithelial cells, and live E. coli, underscoring its suitability for advanced long-term biological imaging applications.

High-order multiplexing in single-molecule localisation microscopy (SMLM) is limited by trade-offs between spectral discrimination, imaging speed, and experimental complexity. Here, we show that RGB cameras provide a simple and scalable solution for multi-colour SMLM by exploiting their intrinsic spectral sensitivity for statistical fluorophore discrimination. Using a realistic simulation framework incorporating experimentally derived photon budgets, optical response functions, and camera noise, we achieve simultaneous classification of up to six fluorophores with a mean precision of [~]98%, including perfect discrimination of spectrally overlapping dye pairs, while maintaining an average localisation precision of [~]3.2 nm. Performance remains robust to variations in classification thresholds but degrades with increasing fluorophore number and reduced photon budgets due to spectral overlap and photon noise. These results establish RGB detection as a cost-effective and experimentally straightforward alternative to conventional spectral imaging approaches, enabling accessible, high-throughput multiplexed super-resolution imaging.

Light-sheet microscopy (LSM) has revolutionized bioimaging by delivering high-contrast volumetric resolution with minimal photodamage. Spatial wavefront shaping, used to gen{-}erate lattice and Airy light-sheets, has been particularly effective in advancing LSM be{-}yond the Rayleigh limit. Despite its broad adoption, most LSM implementations rely on rigid dual-objective geometries that complicate sample handling and impose a trade-off between imaging field of view (FoV) and axial resolution. Here, we introduce space-time light-sheet microscopy (ST-LSM), a single-objective strategy that exploits space-time (ST) correlations for the first time. ST-LSM goes beyond separate spatial or temporal modulation to jointly modulate the spatiotemporal spectral structure of a pulse. This uniquely enabled light-sheets with wavelength-scale thickness over millimeter-scale dis{-}tances. When compared to state-of-the-art approaches, ST-LSM eliminates the dual-objective constraint, expands the sample-accessible volume by 25x, and increases the FoV by 10x without sacrificing sectioning resolution. We demonstrate the versatility of ST-LSM by using a single setup to image specimens across four orders of magnitude in size, from whole roots and developing embryos, down to mammalian cells with sub-cellular axial resolution. These results position ST-LSM as an accessible and high-performance optical microscopy platform at a variety of biological scales, by translating space-time wave-packet physics into a practical imaging modality.

Refined single-molecule localization microscopy methods demonstrated superior localization precisions on isolated sample but remain limited by labeling density and imaging speed in cells. Here we combine expansion microscopy (ExM) with two-dye-imager (TDI)-DNA-PAINT to resolve fine molecular details of protein assemblies in [~]8-fold expanded cells with nanometer resolution. Using lattice light-sheet (LLS) microscopy, Ex-TDI-DNA-PAINT provides a robust platform for three-dimensional (3D) volumetric nanoscopy of the molecular organization of cells.

Ultra-thin, transparent films are being used as protective layers on semiconductors, solar cells, as well as for nano-composite materials and optical coatings. Nano-sensors, photonic devices and calibration tools for axial super-resolution microscopies, all rely on the controlled fabrication and analysis of ultra-thin layers. Here, we describe a simple, non-invasive, optical technique for simultaneously characterizing the refractive index, thickness, and homogeneity of nanometric transparent films. In our case, these layers are made of the biomimetic polymer, My-133-MC, having a refractive index of 1.33, so as to approach the cytosol for biological applications. Our technique is based on the detection in the far field and the analysis of supercritical angle fluorescence (SAF), i.e., near-field emission from molecular dipoles located very close to the dielectric interface. SAF emanates from a 5-nm J-aggregate emitter layer deposited on and in contact with the inspected polymer film. Our results compare favorably to that obtained through a combination of atomic force and electron microscopy, surface-plasmon resonance spectroscopy and ellipsometry. We illustrate the value of the approach in two applications, (i), the measurement of axial fluorophore distance in a total internal reflection fluorescence geometry; and, (ii), axial super-resolution imaging of organelle dynamics in a living biological sample, cortical astrocytes, an important type of brain cell. In the later case, our approach removes uncertainties in the interpretation of the nanometric axial dynamics of fluorescently labeled vesicles. Our technique is cheap, versatile and it has obvious applications in microscopies, profilometry and optical nano-metrology.

Discerning two or more identical and constantly scattering point sources using freely propagating waves is thought to be limited by diffraction. Here we show both theoretically and experimentally that by employing a diffraction minimum rather than a maximum for resolution, a given number of point scatterers can be discerned at tiny fractions of the employed wavelength. Specifically, we identify an 8 nm distance between two constantly emitting (non-blinking, non-switchable) fluorescent molecules, corresponding to 1/80 of the wavelength. Moreover, we show that contrary to naive expectations, the measurement precision improves with decreasing distance between the scatterers and with increased scatterer density, thus opening up the prospect of resolving clusters of (optical) point scatterers at tiny fractions of the wavelength.

Widefield fluorescence microscopy is widely used for imaging at subcellular resolution, but its performance in complex samples is degraded by optical aberrations. Because aberrations can vary spatially across the field of view (FOV), accurate aberration measurement and correction at multiple FOV locations are essential for achieving high-quality imaging over large areas. Here, we introduce parallel frequency-multiplexed aberration measurement (PFAM) to perform massively parallel aberration measurements across an extended FOV. We validated PFAM using fluorescent beads and demonstrated simultaneous measurement and effective correction of spatially varying aberrations at 125 FOV locations. To address the challenges of wavefront sensing in complex samples, we further developed PFAM-SIFT by integrating structured illumination, thereby achieving robust aberration measurement in both brain slices and the mouse brain in vivo. Together, PFAM and PFAM-SIFT provide accurate and scalable wavefront sensing solutions for widefield imaging, enabling simultaneous aberration measurement of spatially varying aberrations in complex biological samples.

Event-based sensors (EBS), or neuromorphic vision sensors, offer a novel approach to imaging by recording light intensity changes asynchronously, unlike conventional cameras that capture light over fixed exposure times. This capability results in high temporal resolution, reduced data redundancy, and a wide dynamic range. This makes EBS ideal for Single-Molecule Localization Microscopy (SMLM) as SMLM relies on the sequential imaging of sparse, blinking fluorescent emitters to achieve super-resolution. Recent studies have shown that EBS can effectively capture these emitters, achieving spatial resolution comparable to traditional cameras. However, existing analyses of event-based SMLM (eveSMLM) data have relied on converting event lists into image frames for conventional analysis, limiting the full potential of the technology. To overcome this limitation, we developed EVE, a specialized software for analyzing eveSMLM data. EVE offers an integrated platform for detection, localization, and post-processing, with various algorithmic options tailored for the unique structure of eveSMLM data. EVE is user-friendly and features an open, modular infrastructure that supports ongoing development and optimization. EVE is the first dedicated tool for event-based SMLM, transforming the analysis process to fully utilize the spatiotemporal data generated by EBS. This allows researchers to explore the full potential of eveSMLM and encourages the development of new analytical methods and experimental improvements.