Capturing dynamic cellular processes in live cells requires fast imaging with very high resolution beyond the diffraction limit. Fluctuation-based super-resolution techniques overcome this limit by exploiting correlations in fluorescence blinking, but they typically require hundreds of frames and computationally intensive post-processing, prohibiting real-time imaging of fast cellular events. Recent deep learning approaches aim to increase temporal resolution; however, many rely on extensive pre-processing or large, complex models that increase training costs and inference latency, preventing real-time deployment. To address this, we employ a lightweight recurrent neural network model that integrates sequential low-resolution frames to extract spatio-temporally correlated signals. It significantly improves temporal resolution by reducing the required number of frames down to as few as 8 frames while doubling the spatial resolution in an inference time under 30 ms. Furthermore, gentle imaging conditions are essential for extracting reliable biologically relevant information, especially in long-term experiments. Our method is suitable for live-cell imaging under extreme signal/noise ratio conditions, allowing imaging under very low laser intensities to prevent photodamage. By combining simulation-based training with an efficient network architecture, we introduce real-time super-resolution fluctuation imaging (RESURF), a deep-learning-based real-time super-resolution fluctuation imaging framework. We demonstrate that RESURF generalizes across different biological structures and can be readily adapted to various microscope setups using a small data set for transfer learning. The accompanying data set, comprising simulations and experiments across multiple subcellular structures and labeling strategies, establishes a benchmarking platform for fluctuation-based super-resolution techniques. RESURF offers a practical, low-latency deep-learning framework for high-throughput imaging and real-time, smart live-cell super-resolution imaging.

Methyltransferase (MTase)-based DNA labeling has become a powerful strategy for genomic and epigenetic analysis because of its unique ability to recognize and functionalize DNA sequences in a site-specific manner. Expanding this toolbox is essential to fully exploit MTases as programmable molecular guides. Here, we introduce an MTase-directed proximity labeling approach that enables sequence-specific DNA modification beyond the natural catalytic transfer site: GLOW, Guided Labeling Outside the natural site With MTases. Using newly designed S-adenosyl-L-methionine (SAM) analogues, we demonstrate sequence-specific DNA labeling revealed by single-molecule fluorescence imaging and gel-based restriction enzyme assays, confirming that labeling occurs adjacent to, rather than within, the canonical recognition site. Unlike conventional MTase-mediated methods, this strategy provides enhanced ligand stability and avoids interference from endogenous DNA methylation, thereby broadening its potential to complex genomic contexts. These findings establish MTase-guided proximity labeling as a conceptually new mode of enzymatic targeting that enriches the chemical biology toolkit for sequence-specific DNA modification.

Genetically encoded fluorescent biosensors convert specific biomolecular events into optically detectable signals. However, imaging biomolecular processes often requires modifying the proteins involved, and many molecular processes are still to be imaged. Here, we present a biosensor design that uses a hitherto overlooked detection principle: directionality of optical properties of fluorescent proteins. The biosensors (termed FLIPs) offer an extremely simple design, high sensitivity, multiplexing capability, ratiometric readout, and other advantages, without requiring modifications to their targets. We demonstrate the sensor performance by real-time imaging activity of G protein-coupled receptors (GPCRs), G proteins, arrestins, and other membrane-associated proteins, as well as by identifying a previously undescribed, pronounced, endocytosis-associated conformational change in a GPCR-β-arrestin complex. In combination with an original tri-scanning linear dichroism confocal microscope, FLIPs allow unparalleled imaging of activity of nonmodified, endogenously expressed G proteins. Thus, FLIPs establish a powerful molecular platform for imaging cell signaling, allowing numerous future developments and insights.

Membrane proteins are central to cellular function and constitute the majority of drug targets, yet their structural and functional characterization at the single-molecule level requires stabilization within a native-like lipid environment. Here, we introduce a robust and tunable DNA origami nanodisc that incorporates inherently planar lipid bicelles as a promising platform for future membrane protein studies. The highly charged and bulky DNA envelope acts as a structural stabilizer, enabling efficient bicelle incorporation and stabilization. Moreover, bilayer geometry can be precisely tuned by adjusting the long-chain to short-chain lipid ratio (q-ratio), yielding diameters from ∼18 to 26 nm. As a proof of concept, we demonstrate the successful association of Fragaceatoxin C (FraC) monomers, a pore-forming membrane protein, with the DNA-stabilized bicelles. Potential applications of this versatile platform include high-throughput membrane protein analysis, hydrophobic drug delivery, and hybrid nanopore sensing.

Abstract Reversibly photoswitchable fluorophores have enabled a broad range of applications in advanced fluorescence bioimaging. Here, we introduce RSpFAST, a new class of reversibly photoswitchable fluorescent labels that combine a biomolecular host (pFAST protein tag) with a reversibly photoisomerizable guest (fluorogen), allowing fluorescence brightness to be modulated through illumination and molecular complexation. We combine thermokinetic, photochemical, and structural investigations to obtain a comprehensive mechanistic and kinetic understanding of RSpFAST. Building on this theoretical framework, we demonstrate in both live and fixed cells that RSpFAST exhibits an unprecedented dual behavior: a stable and wash-free fluorescent labeling tag turns into a negative reversible photoswitcher by decreasing the fluorogen concentration and increasing light intensity. In this photoejection-driven kinetic regime, RSpFAST is shown to be an efficient marker for dynamic contrast and super-resolution microscopy.

Reliable detection of micro- and nanoplastics (MNPs) in human tissues remains analytically challenging due to complex biological matrices, contamination risks, and limited sensitivity of existing spectroscopic and mass-based techniques toward submicrometer particles. Here, we present a histology-compatible analytical approach that enables in situ, volumetric detection and quantification of MNPs in biological tissues with submicrometer sensitivity. The method combines hydrogel-based tissue transformation and optical clearing with fluorescence staining and three-dimensional optical imaging, preserving the spatial architecture of the tissue while removing interfering biological components. This approach effectively minimizes external contamination and enables Nile Red-based identification of MNPs embedded within intact tissue volumes. Analytical performance was validated using spiked biological models and reference polymers, demonstrating reliable retention, detection, and classification of MNPs down to a conservatively defined limit of approximately 0.4 μm. False positives from endogenous hydrophobic structures are suppressed by enzymatic delipidation and are benchmarked using orthogonal fluorescence lifetime signatures against lipid artifacts and plastic reference materials. Applied to human placental tissue, the workflow resolves a particle population dominated by submicrometer MNPs (73% below 1 μm). This size fraction is systematically excluded by filtration-based workflows and, because its cumulative mass is negligible, falls below the detection limits of bulk pyrolysis-based methods. Consequently, the number-dominant MNP fraction in human tissue has remained largely inaccessible to existing analytical approaches. By enabling sensitive, structurally (rather than procedurally) contamination-resistant, and spatially resolved detection of MNPs directly within intact tissues, this approach bridges a critical gap between nanomaterials characterization and exposure biology. It provides a broadly applicable platform for future biomonitoring, exposure assessment, and hypothesis-driven studies on the biological fate of MNPs.

Ratiometric analysis of two or more fluorescence signals is a staple of quantitative imaging. However, this analysis becomes complicated at (near-) diffraction limited resolutions due to differences in how the emission colors are imaged by the microscope optics. We investigate this and find that point-spread function (PSF) mismatch between different emission wavelengths readily introduces spurious structuring in ratiometric images. We develop a postprocessing strategy that can correct for this effect by matching the respective PSFs, thus eliminating this deviation. To demonstrate this approach in live cells, we develop a highly photostable FRET biosensor against protein kinase A (PKA) activity and apply it to diffraction-limited biosensing, demonstrating that the spurious structuring can indeed be removed from the analyzed images. Our work further supports the feasibility of high-resolution ratiometric imaging using stable molecular probes and suitable correction strategies.

Background Micro- and nanoplastics (MNPs) contamination may pose a significant risk to human health. However, their true impact remains underexplored due to substantial limitations of current analytical methods. Traditional techniques like Raman and FTIR microscopy, coupled with filtration, fail to detect smaller MNPs and are prone to external contamination. Likewise, pyrolysis-GC/MS lacks the ability to pinpoint MNP size or location. Methods This study presents a universal approach for MNPs detection in tissues, validated to mitigate external contamination risks and enable the identification of significantly smaller MNPs. The method preserves histological information, allowing for comprehensive spatial analysis, including assesment of local DNA damage using the y-H2AX histone. Findings Applying this method to human placenta samples revealed orders of magnitude higher MNP loads than previously reported, with quantities ranging from thousands to millions per cm3, far exceeding current reports of fewer than 1 MNP per gram or cm3 of tissue. Importantly, within the observed concentration range, we found a positive association between MNP load and placental DNA damage. Interpretation Our findings show that that the prevalence of MNPs in biological tissues has been substantially underestimated, as the smallest and potentially most harmful MNPs go undetected with traditional methods. Furthermore, we found that the concentations were linked with genotoxic effects in the placenta. This novel analytical workflow represents a significant advancement in MNPs research and provides crucial insights into their impact on human health. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by research Foundation Flanders - FWO ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of University Hospitals Leuven gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Reversibly photoswitchable fluorophores have enabled a broad range of applications in advanced fluorescence bioimaging. Here, we provide an entirely new class of representatives based on a pair: a biomolecular host and a dark photoisomerizable guest, which becomes bright upon complexation. Hence, we introduce RSpFAST , which delivers the first non-covalent chemogenetic reversibly photoswitchable fluorescent proteins from combining photoisomerizable fluorogens with the FAST protein tag. Our experimental strategy involving thermokinetic, photochemical, and structural investigations provides a comprehensive mechanistic and kinetic understanding of RSpFAST . Building on this theoretical framework, we demonstrate in both live and fixed cells that RSpFAST exhibits an unprecedented dual behavior: a stable and wash-free fluorescent labeling tag turns into a negative reversible photoswitcher by simply lowering the fluorogen concentration and increasing light intensity. In this photoejection-driven kinetic regime, RSpFAST is shown to be an efficient marker for dynamic contrast and super-resolution microscopy.

Super-resolution fluorescence microscopy is a powerful method to image molecular processes that occur beyond the diffraction limit of light. Förster resonance energy transfer (FRET) is widely used to probe molecular interactions, though its combination with super-resolution imaging has remained challenging. Here, we demonstrate that super-resolution optical fluctuation imaging (SOFI) can be used to measure FRET by combining a blinking donor with a nonblinking acceptor. We develop a theoretical model that reveals that FRET-SOFI has a reduced sensitivity to distortions such as donor leakage and direct acceptor excitation, unlike conventional imaging, though at the cost of a more complex relationship between the FRET efficiency and the observed signal. We demonstrate this by imaging the intermolecular association of a FRET pair consisting of a fluorescent protein and a synthetic dye with a subdiffraction resolution in live cells. By requiring only a sensitive wide-field microscope, FRET-SOFI expands the possibilities to image molecular interactions at the nanoscale.

DNA optical mapping is a powerful technique commonly used for structural variant calling and genome assembly verification. Despite being inherently high-throughput, the method has not yet been applied to highly complex settings such as species identification in microbiome analysis due to the lack of alignment algorithms that can both assign large numbers of reads in minutes and handle large database size. In this work, we present a novel genomic classification pipeline based on deep convolutional neural networks for optical mapping data (DeepMAP), which can perform fast and accurate assignment of individual optical maps to their respective genomes. We furthermore achieve a superior performance of DeepMAP in the presence of evolutionary divergent sequences, making it robust to the presence of unknown strains within metagenomic samples. We evaluate DeepMAP on genomic DNA extracted from bacterial mixtures, reaching species-level resolution with true positive rates of around 75% and a false positive rate of less than 1%, with measured classification speeds significantly outpacing those of previously developed approaches for high-density optical mapping data alignment.

Genetically-encoded fluorescent biosensors have revolutionized our understanding of complex systems by permitting the in situ observation of chemical activities. However, only a comparatively small set of chemical activities can be monitored, largely due to the need to identify protein domains that undergo conformational and/or association changes in response to a stimulus. Here, we present a strategy that can convert ‘simple’ affinity binders such as nanobodies into biosensors for their innate targets by introducing a peptide sequence that competes for the binding site. We demonstrate proof-of-concept implementations of this ‘NanoBlock’ design, developing sensors based on the ALFA nanobody and on the PDZ domain of Erbin. We show that these sensors can reliably detect their targets in vitro , in mammalian cells, and as part of fluorescence-activated cell sorting (FACS) experiments. In doing so, our strategy offers a way to strongly expand the range of cellular processes that can be probed using fluorescent biosensors. ### Competing Interest Statement The authors have declared no competing interest.

Multicolor fluorescence microscopy is an essential tool to visualize structures and dynamics in the life and materials sciences. However, the near-simultaneous acquisition of labels differing in excitation spectrum is difficult and renders such measurements prone to artifacts. We present a simple strategy to provide quasi-simultaneous fluorescence imaging with multiple excitation wavelengths by using an optical element to displace the sample image on the sensor at a rate that is much faster than the image acquisition rate and synchronizing this with the illumination. The emission elicited by the different wavelengths can then be encoded into the point-spread function of the imaging or visualized as multiple distinct images. In doing so, our approach can eliminate or mitigate artifacts caused by temporal aliasing in conventional sequential imaging. We demonstrate the use of our system to uncover hidden emissive states in single quantum dots and for the imaging of Ca2+ signaling in neurons.

We present a way to encode more information in fluorescence imaging by splitting the original point spread function (PSF), which offers broadband operation and compatibility with other PSF engineering modalities and existing analysis tools. We demonstrate the approach using the ‘Circulator’, an add-on that encodes the fluorophore emission band into the PSF, enabling simultaneous multicolor super-resolution and single-molecule microscopy using essentially the full field of view. Point spread function (PSF) splitting with the ‘Circulator’, which encodes the fluorophore emission band into the PSF, improves the information content of fluorescence microscopy and enables improved super-resolution imaging and single-particle tracking.

AbstractWe present a way to encode more information in fluorescence imaging by splitting the emission into copies of the original point-spread function (PSF), which offers broadband operation and compatibility with other PSF engineering modalities and existing analysis tools. We demonstrate the approach using the ‘Circulator’, an add-on that encodes the fluorophore emission band into the PSF, enabling simultaneous multicolor super-resolution and single-molecule microscopy using essentially the full field of view.

Microbial abundance profiling is rapidly becoming an essential method in biomedical research, though it is often costly and time intensive. We present DynaMAP, a rapid approach for microbiome profiling that uses single-molecule imaging to develop an optical map of metagenomic DNA. DynaMAP achieves strain-level taxonomic profiling without requiring base-by-base sequencing and with a one-day turnaround time. In doing so, it delivers microbiome profiling that is comparable to shotgun sequencing but operates more efficiently, strongly expanding the possibility for microbiome analysis. ### Competing Interest Statement The authors have declared no competing interest.

The most common methods for multiplexed immunohistochemistry rely on cyclic procedures, whereby cells or tissues are repeatedly stained, imaged, and regenerated. Here, we present a simple and inexpensive approach for amine-targeted labeling of antibodies using a linker that can be easily cleaved by a mild reducing agent. This method requires only inexpensive and readily-available reagents, and can be carried out without synthetic experience in a simple one-pot reaction. We demonstrate the applicability of this approach by performing repeated staining-imaging-removal cycles on isolated cells and tissue sections, finding that over 94% of the labels can be removed within 30 minutes using only the gentle application of reducing agent, increasing up to 99% by extending the incubation duration to 1 hour. By providing a convenient way to introduce cleavable linkers, our method simplifies methodologies such as high-content imaging or multiplexed immunohistochemistry.

Multilabel fluorescence imaging is essential for the visualization of complex systems, though a major challenge is the limited width of the useable spectral window. Here, we present a new method, exNEEMO, that enables per-pixel quantification of spectrally-overlapping fluorophores based on their light-induced dynamics, in a way that is compatible with a very broad range of timescales over which these dynamics may occur. Our approach makes use of intra-exposure modulation of the excitation light to distinguish the different emitters given their reference responses to this modulation. We use the approach to simultaneously image four green photochromic fluorescent proteins at the full spatial resolution of the imaging.