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A variety of modern super-resolution microscopy methods provide researchers with previously inconceivable biological sample imaging opportunities at a molecular resolution. All of these techniques excel at imaging samples that are close to the coverslip, however imaging at large depths remains a challenge due to aberrations caused by the sample, diminishing the resolution of the microscope. Originating in astro-imaging, the adaptive optics (AO) approach for wavefront shaping using a deformable mirror is gaining momentum in modern microscopy as a convenient approach for wavefront control. AO has the ability not only to correct aberrations but also enables engineering of the PSF shape, allowing localization of the emitter axial position over several microns. In this study, we demonstrate remote focusing as another AO benefit for super-resolution microscopy. We show the ability to record volumetric data (45 × 45 × 10 µm), while keeping the sample axially stabilized using a standard widefield setup with an adaptive optics addon. We processed the data with single-molecule localization routines and/or computed spatiotemporal correlations, demonstrating subdiffraction resolution.

Abnormal aggregation of TAR DNA‐binding protein 43 (TDP‐43) is a pathological hallmark of motor neuron disease (MND), yet current methods for quantifying these aggregates in biological samples remain limited in sensitivity and resolution. Here, single‐molecule fluorescence microscopy is applied to post‐mortem brain extracts to quantitatively characterize aggregates containing TDP‐43 at the individual particle level. The resulting aggregate fingerprints, consisting of morphological and compositional profiles, are sufficient to distinguish MND donors from neurologically normal controls and further discriminate between clinically distinct MND subgroups. Comparative proteomic analysis confirms and extends these findings, revealing convergent and complementary molecular signatures. These results demonstrate, for the first time, that single‐molecule aggregate profiling can stratify MND cases using patient‐derived tissues, paving the way for the development of sensitive minimally invasive diagnostics and mechanistically informed disease monitoring tools. Single‐molecule fluorescence microscopy is combined with proteomic profiling to fingerprint the morphology and composition of TDP‐43 protein aggregates found in post‐mortem motor neuron disease brain tissues. Aggregate fingerprints can distinguish disease from control donors and detect unexpected TDP‐43 pathology in SOD1‐MND. These findings challenge existing models and offer a new route toward sensitive diagnostics and patient stratification tools.

Precise quantitative information about the molecular architecture of synapses is essential to understanding the functional specificity and downstream signaling processes at specific populations of synapses. Glycine receptors (GlyRs) are the primary fast inhibitory neurotransmitter receptors in the spinal cord and brainstem. These inhibitory glycinergic networks crucially regulate motor and sensory processes. Thus far, the nanoscale organization of GlyRs underlying the different network specificities has not been defined. Here, we have quantitatively characterized the molecular arrangement and ultra-structure of glycinergic synapses in spinal cord tissue using quantitative super-resolution correlative light and electron microscopy. We show that endogenous GlyRs exhibit equal receptor-scaffold occupancy and constant packing densities of about 2000 GlyRs µm -2 at synapses across the spinal cord and throughout adulthood, even though ventral horn synapses have twice the total copy numbers, larger postsynaptic domains, and more convoluted morphologies than dorsal horn synapses. We demonstrate that this stereotypic molecular arrangement is maintained at glycinergic synapses in the oscillator mouse model of the neuromotor disease hyperekplexia despite a decrease in synapse size, indicating that the molecular organization of GlyRs is preserved in this hypomorph. We thus conclude that the morphology and size of inhibitory postsynaptic specializations rather than differences in GlyR packing determine the postsynaptic strength of glycinergic neurotransmission in motor and sensory spinal cord networks.

Single‐molecule localization microscopy (SMLM) data can reveal differences in protein organization between different disease types or samples. Classification of samples is an important task that allows for automated recognition and grouping of data by sample type for downstream analysis. However, methods for classifying structures larger than single clusters of localizations in SMLM point‐cloud datasets are not well developed. A graph‐based deep learning pipeline is presented for classification of SMLM point‐cloud data over a field of view of any size. The pipeline combines features of individual clusters (calculated from their constituent localizations) with the structure formed by the positions of multiple clusters (supracluster structure). This method outperforms previous classification results on a model open‐source DNA‐PAINT dataset, with 99% accuracy. It is also applied to a challenging new SMLM dataset from colorectal cancer tissue. Explainability tools Uniform Manifold Approximation and Projection and SubgraphX allow exploration of the influence of spatial features and structures on classification results, and demonstrate the importance of supracluster structure in classification. ClusterNet is a graph‐based deep learning pipeline for classifying single‐molecule localization microscopy (SMLM) data. It acts directly on point‐cloud localization data from a field of view of any size, using features of individual clusters of localizations together with their spatial arrangement. It is successfully tested on a model SMLM dataset and on data acquired from biological samples.

To advance the development of novel and efficient electrochemical systems, it is crucial to dynamically image electrochemical reaction processes in real‐time at the single‐particle or single‐molecule level. Single‐molecule fluorescence microscopy has emerged as a powerful tool for in situ imaging of dynamic reaction processes, which is extensively utilized in the field of electrochemical reactions. In this perspective, we provide a concise summary of the recent applications of single‐molecule fluorescence microscopy and super‐resolution fluorescence microscopy within energy electrochemistry. This paper offers insights and evidence regarding electron transfer, surface adsorption, and desorption of reactants, as well as the kinetic processes and mechanisms involved in energy‐related electrochemical reactions. Finally, several remaining challenges are outlined based on the vision for the expanded application of single‐molecule fluorescence microscopy across a broader spectrum of energy‐related fields, including carbon dioxide reduction, methanol electrooxidation, nitric acid electroreduction, furfural electrooxidation reaction, etc. Single‐molecule fluorescence microscopy, characterized by its high spatial and temporal resolution, has been extensively employed to investigate the kinetics of electrochemical reaction processes as well as the distribution of active sites in electrocatalysts. Gaining a profound understanding of the mechanisms underlying electrochemical reactions can provide valuable inspiration for the rational design of high‐performance electrocatalysts in energy‐related fields.

Probing light–matter interaction at the nanometer scale is one of the most fascinating topics of modern optics. Its importance is underlined by the large span of fields in which such accurate knowledge of light–matter interaction is needed, namely nanophotonics, quantum electrodynamics, atomic physics, biosensing, quantum computing and many more. Increasing innovations in the field of microscopy in the last decade have pushed the ability of observing such phenomena across multiple length scales, from micrometers to nanometers. In bioimaging, the advent of super-resolution single-molecule localization microscopy (SMLM) has opened a completely new perspective for the study and understanding of molecular mechanisms, with unprecedented resolution, which take place inside the cell. Since then, the field of SMLM has been continuously improving, shifting from an initial drive for pushing technological limitations to the acquisition of new knowledge. Interestingly, such developments have become also of great interest for the study of light–matter interaction in nanostructured materials, either dielectric, metallic, or hybrid metallic-dielectric. The purpose of this review is to summarize the recent advances in the field of nanophotonics that have leveraged SMLM, and conversely to show how some concepts commonly used in nanophotonics can benefit the development of new microscopy techniques for biophysics. To this aim, we will first introduce the basic concepts of SMLM and the observables that can be measured. Then, we will link them with their corresponding physical quantities of interest in biophysics and nanophotonics and we will describe state-of-the-art experiments that apply SMLM to nanophotonics. The problem of localization artifacts due to the interaction of the fluorescent emitter with a resonant medium and possible solutions will be also discussed. Then, we will show how the interaction of fluorescent emitters with plasmonic structures can be successfully employed in biology for cell profiling and membrane organization studies. We present an outlook on emerging research directions enabled by the synergy of localization microscopy and nanophotonics.

We present localization with stimulated emission depletion (LocSTED) microscopy, a combination of STED and single-molecule localization microscopy (SMLM). We use the simplest form of a STED microscope that is cost effective and synchronization free, comprising continuous wave (CW) lasers for both excitation and depletion. By utilizing the reversible blinking of fluorophores, single molecules of Alexa 555 are localized down to ~5 nm. Imaging fluorescently labeled proteins attached to nanoanchors structured by STED lithography shows that LocSTED microscopy can resolve molecules with a resolution of at least 15 nm, substantially improving the classical resolution of a CW STED microscope of about 60 nm. LocSTED microscopy also allows estimating the total number of proteins attached on a single nanoanchor.

Specific macromolecules are rapidly transported across the nuclear envelope via the nuclear pore complex (NPC). The selective transport process is facilitated when nuclear transport receptors (NTRs) weakly and transiently bind to intrinsically disordered constituents of the NPC, FG Nups. These two types of proteins help maintain the selective NPC barrier. To interrogate their binding interactions in vitro, we deployed an NPC barrier mimic. We created the stationary phase by covalently attaching fragments of a yeast FG Nup called Nsp1 to glass coverslips. We used a tunable mobile phase containing NTR, nuclear transport factor 2 (NTF2). In the stationary phase, three main factors affected binding: the number of FG repeats, the charge of fragments, and the fragment density. We also identified three main factors affecting binding in the mobile phase: the avidity of the NTF2 variant for Nsp1, the presence of nonspecific proteins, and the presence of additional NTRs. We used both experimentally determined binding parameters and molecular dynamics simulations of Nsp1FG fragments to create an agent-based model. The results suggest that NTF2 binding is negatively cooperative and dependent on the density of Nsp1FG molecules. Our results demonstrate the strengths of combining experimental and physical modeling approaches to study NPC-mediated transport.

Single-molecule localization microscopy (SMLM) plays an irreplaceable role in biological studies, in which nanometer-sized biomolecules are hardly to be resolved due to diffraction limit unless being stochastically activated and accurately located by SMLM. For biological samples preimmobilized for SMLM, most biomolecules are cross-linked and constrained at their immobilizing sites but still expected to undergo confined stochastic motion in regard to their nanometer sizes. However, few lines of direct evidence have been reported about the detectability and influence of confined biomolecule stochastic motion on localization precision in SMLM. Here, we access the potential stochastic motion for each immobilized single biomolecule by calculating the displacements between any two of its localizations at different frames during sequential imaging of Alexa Fluor-647-conjugated oligonucleotides. For most molecules, localization displacements are remarkably larger at random frame intervals than at shortest intervals even after sample drift correction, increase with interval times and then saturate, showing that biomolecule stochastic motion is detected and confined around the immobilizing sizes in SMLM. Moreover, localization precision is inversely proportional to confined biomolecule stochastic motion, whereas it can be deteriorated or improved by enlarging the biomolecules or adding a post-crosslinking step, respectively. Consistently, post-crosslinking of cell samples sparsely stained for tubulin proteins results in a better localization precision. Overall, this study reveals that confined stochastic motion of immobilized biomolecules worsens localization precision in SMLM, and improved localization precision can be achieved via restricting such a motion.

The exposed active sites of semiconductor catalysts are essential to the photocatalytic energy conversion efficiency. However, it is difficult to directly observe such active sites and understand the photogenerated electron/hole pairs’ dynamics on a single catalyst particle. Here, we applied a quasi-total internal reflection fluorescence microscopy and laser-scanning confocal microscopy to identify the photocatalytic active sites at a single-molecule level and visualized the photogenerated hole–electron pair dynamics on a single TiO₂ particle, the most widely used photocatalyst. The experimental results and density functional theory calculations reveal that holes and electrons tend to reach and react at the same surface sites, i.e., crystal edge/corner, within a single anatase TiO₂ particle owing to the highly exposed (001) and (101) facets. The observation provides solid proof for the existence of the surface junction “edge or corner” on single TiO₂ particles. These findings also offer insights into the nature of the photocatalytic active sites and imply an activity-based strategy for rationally engineering catalysts for improved photocatalysis, which can be also applied for other catalytic materials.