Nature Photonics

DNA-based technologies rely on short, transient hybridization events, but selecting sequences with desired kinetic properties remains largely empirical because hybridization kinetics are difficult to predict from sequence and slow to measure one sequence at a time. Here, we introduce SPARXS-Hyb, an implementation of SPARXS (Single-molecule Parallel Analysis for Rapid eXploration of Sequence space) for multiplexed sequence-resolved screening of DNA hybridization. Using a surface-immobilized docking-strand library and a quencher-labelled imager-strand library, we screened 128 different DNA sequences in a single kinetic measurement, exposing all sequences to identical experimental conditions. This multiplexed approach removes a major confounding factor of serial measurements, allowing sequence-dependent differences to be compared directly. The resulting dataset reveals sequence-dependent transient binding behaviours and enabled us to identify a sequence with which an order-of-magnitude higher sampling rate can be achieved in DNA-PAINT (DNA points accumulation for imaging in nanoscale topography), a super-resolution microscopy technique based on DNA hybridization. By enabling multiplexed screening across a sequence library, SPARXS-Hyb provides a route to kinetics-guided sequence selection for programmable transient interactions in DNA nanotechnology.

Quantitative fluorescence imaging techniques such as fluorescence lifetime imaging microscopy and hyperspectral imaging infer molecular contrast from photons distributed across spatial pixels and temporal or spectral channels. In the few-photon regime, however, conventional pixel-wise analysis discards the spatial relationships imposed across neighboring pixels by the microscope point-spread function (PSF). Here we show that this spatially distributed information can be recovered without prior knowledge of emitter positions, spatial support or component assignments. We introduce SPOOL (Spatially Pooled Optical Observation Likelihood), a training-free Poisson inverse framework that jointly recovers source-space amplitudes and quantitative contrast by combining the PSF with temporal-decay or spectral-response dictionaries. For an isolated source, the attainable precision gain is governed by a dimensionless optical quantity: the PSF width expressed in detector pixels. The predicted gain therefore scales with optical sampling rather than with the physical origin of the contrast. The model predicts that lifetime-precision gain scales approximately linearly with the number of pixels spanning the PSF full width at half maximum, a scaling reproduced by Monte Carlo simulations. At one detected photon per foreground pixel, the reconstruction reduces lifetime dispersion sixfold in fluorescent-bead experiments and decreases the lifetime root-mean-square error relative to a high-photon reference from 1.19 to 0.45 ns in dual-labeled cells. The same framework transfers unchanged to hyperspectral imaging, recovering spectral contrast from generic emission bands without prior fluorophore spectra.

Visual neuroscience requires precise spatiotemporal projection of optical stimulation onto the retina, especially in experimental mouse models. However, in vivo patterned stimulation in mice is profoundly hindered by the extreme optical power and severe anatomical aberrations of the eye. Consequently, visual stimulation relies mainly on unverifiable, open-loop approximations that often lack spatial precision. Here, we introduce a closed-loop, spatially modulated stimulation platform that overcomes these barriers. By integrating a digital micromirror device (DMD) with electronically tunable lenses (ETLs) and a real-time, fundus camera-guided focus optimization module, we directly verify the location of patterned stimuli on the retina while dynamically correcting for chromatic and geometric defocus. This platform delivers quantitatively verified static and dynamic patterned stimuli to the living retina with lateral resolutions as fine as 6.7 {micro}m. Guided by ray-tracing optical analysis, our work establishes a technological foundation that enables highly reproducible, cellular-scale interrogations of the visual pathway.

Spectroscopic single-molecule localization microscopy (sSMLM) enables multiplexed super-resolution imaging by simultaneously acquiring the spatial position and spectral information of individual fluorophores. Dual-wedge prism (DWP)-based implementations provide a compact, alignment-stable approach to spectral dispersion, but trade-offs between localization precision, spectral precision, and experimental complexity remain. We systematically compare five DWP-based sSMLM configurations, including two-dimensional (2D) and three-dimensional (3D) implementations using single DWP (DWP-sSMLM) and symmetrically-dispersed DWP (SDDWP-sSMLM). We evaluate lateral precision, spectral precision, and ease of use. SDDWP configurations acquire spectral images in both channels and utilize both for spatial localization, yielding the highest lateral and spectral precision. However, for applications that do not require axial information, 2D-DWP provides a simple, plug-and-play solution with robust performance. This work offers a guideline for selecting DWP configurations based on experimental needs.

Direct modulation of neural activity with high spatiotemporal precision is a cornerstone in experimental neuroscience. Here, we present a blood-mediated optoacoustic stimulation (BOAS) approach that utilizes blood as an endogenous transducer for brain stimulation. By delivering 532-nm nanosecond pulsed laser to the cortex, we demonstrate that the absorption of hemoglobin generates sufficient acoustic pressure to trigger neuronal activity. By integrating BOAS with calcium imaging in GCaMP6f-expressing mice, localized neuronal responses were observed. Quantitative analysis reveals that BOAS produces responses comparable to natural visual stimulation and is significantly more efficient than the photothermal stimulation. Furthermore, we show that the response is dose-dependent. At high energy doses, BOAS induces cortical spreading depression. Histological evaluation confirmed that the brain maintains tissue integrity even under these stimulation parameters. Together, this work establishes a versatile method for precise brain stimulation as an alternative method for stimulating neuron at cortex.

Weak, reversible interactions underpin biomolecular recognition, and single-molecule fluorescence (smF) imaging techniques can provide unprecedented insight into those biological processes. Unfortunately, such studies often require micromolar concentrations of fluorophore-labeled biomolecules, which is beyond the accessible range of conventional smF microscopies. Here, we describe a surface-functionalization method based on cloud-point polyethylene glycol (PEG) grafting that enables widefield smF microscopy measurements at micromolar concentrations without the use of nanophotonic devices. Using conventional total internal reflection fluorescence (TIRF) microscopy, we detected single-molecule fluorescence resonance energy transfer (smFRET) from surface-tethered, donor-labeled target molecules with up to 8 micromolar concentrations of freely diffusing, acceptor-labeled analyte molecules in the background--two orders of magnitude higher than typical studies in the literature. Weak, DNA-hybridization and protein-RNA binding equilibria were measured across micromolar range titrations. Together with advances in high-background data analysis, the robust method presented here enables kinetic and thermodynamic analyses of weak biomolecular interactions, especially those limited by nonspecific adsorption and high fluorescence backgrounds, using only standard smF instrumentation.

High-speed three-dimensional imaging in scattering tissues remains challenging because volumetric microscopy generally requires scanning, whereas snapshot light-field approaches divide limited detector pixels among multiple views. This constraint is particularly severe in the second near-infrared window (NIR-II), where commonly used InGaAs cameras typically have relatively small sensor formats and high detector noise. Here we introduce NIR-II squeezed light-field microscopy (NIR-II SLIM), which optically rotates and compresses multiple perspective views before detection, allowing efficient use of camera pixels while retaining complementary spatial information for three-dimensional reconstruction. NIR-II SLIM acquires volumes at up to 600 volumes s-1 with a reconstructed lateral sampling grid of 512 x 512 pixels. We use the method for label-free four-dimensional imaging of cardiac dynamics in pigmented late-larval zebrafish, resolving chamber deformation and millisecond-scale atrioventricular-valve motion, and for NIR-II fluorescence imaging of vascular and lymphatic transport in mice. NIR-II SLIM provides a detector-efficient approach for high-speed volumetric imaging of rapid biological dynamics in scattering tissues.

Mechanical amplification of minute length changes enables precise measurements across many orders of magnitude, from macroscopic metrology to optical instrumentation. Extending this principle to molecular systems could provide a route to monitoring nanoscale structural changes without relying on analyte labeling or fluorescence-based distance measurements. Here we present a DNA origami nanomechanical amplifier that converts subnanometre-scale molecular conformational changes into amplified mechanical displacements that can be tracked in real time at the single-molecule level. The platform resolves geometric changes associated with DNA hybridization, secondary-structure formation, DNA strand-exchange dynamics, and ligand-induced aptamer folding, enabling quantitative analysis of molecular kinetics and direct observation of transient intermediates and heterogeneous conformational ensembles. By translating molecular recognition events into mechanically amplified signals, our approach establishes a general framework for monitoring binding-coupled conformational dynamics and extends the scope of single-molecule measurements beyond conventional optical readouts.

The ultrastructure of endothelial cells (ECs) "in situ" is of great interest due to their involvement in many physiological processes. In some organs, these cells form transcellular pores or fenestrae, allowing for the rapid exchange of molecules between blood and interstitium. Despite their importance, no optical images of these dynamic morphological structures have yet been acquired in situ. Major obstacles to their in-situ imaging are the lack of specifical labels for fenestrae and their size well below the optical diffraction limit. Here, we report how we have overcome these challenges and managed to visualize the EC ultrastructure in situ in 25 {micro}m thick liver sections. To enable this, a lipophilic, fluorescent membrane dye was infused into the portal vein of murine livers to stain the sinusoidal ECs before the organ was harvested. Tissue sections were subsequently imaged using a novel, super-resolution optical-sectioning structured illumination microscope (OS-SIM), providing approx. 170 nm spatial resolution with significantly faster image acquisition compared to confocal microscopy.

A comprehensive understanding of the mechanisms underlying biological systems requires correlative analysis of multiple complementary molecular properties through multidimensional measurements. High-speed atomic force microscopy (HS-AFM) is a powerful tool for elucidating biomolecular structural dynamics at the single-molecule level with high spatiotemporal resolution. However, structural information alone is often insufficient for fully understanding the biological function mechanisms. Here, we report high-speed atomic force-Raman microscopy (HS-AFRM), which enables multimodal measurements combining video-rate structural imaging with chemical-bond analysis. Raman spectroscopy is a powerful, non-invasive technique that probes molecular vibrations to provide chemical information. We achieved several key technical developments that facilitated the seamless integration of HS-AFM and micro-Raman spectroscopy, allowing reliable correlative measurements of structural and chemical information. We validated the versatility of the developed system using representative samples, including two-dimensional materials and a protein. Furthermore, we demonstrate probing of changes in the surrounding environment, which are inaccessible by HS-AFM alone. Multimodal measurements incorporating fluorescence spectroscopy were also demonstrated as an additional practical extension. This multimodal approach substantially enhances the analytical capability of HS-AFM, providing a powerful platform for revealing correlated structural and chemical properties across diverse research fields.

Viral diagnostics during early phases of infection are often limited by target scarcity and the deployment tempo. We significantly advance both quantitative accuracy and diagnostic throughput of viral agglutination assays with Immuno-Janus Particle (IJP) aggregation behavior that "flicker" stochastically with size-dependent statistics. By scrutinizing microscale blinking patterns of time series fluorescent videos, we decipher Brownian dynamics of individual IJP-Virus conjugates and IJP aggregates via windowed Ito stochastic analysis (termed the Culsans method). High-frequency rotational fluctuation is deconvolved from corrupting drifts caused by gravitational sedimentation and Brownian translational motion. This methodology enables a non-linear mapping of angular positions of detected IJPs and IJP aggregates to extract rotational diffusivity (Dr) (and subsequently overall construct size) with superior linearity (R2[≥]0.85). The aggregation behavior exhibits a maximum when the IJP and viral particle concentrations are equal. The virion-bridged IJP-IJP conjugates significantly shift the detectable hydrodynamic diameter in the Poisson limit of reduced virus concentration with respect to IJPs, pushing the limit of detection (LOD) to 103 - 104 virions per mL in untreated human plasma. This tunable platform offers a rapid, low-volume, and scalable alternative to lab-based RT-PCR, bridging the gap between virion sensitivity and field-readiness.

Structural characterization of macromolecular assemblies within intact cells remains one of the central challenges in cell biology. While cryo-electron tomography provides unparalleled structural information, its applicability is limited by sample thickness, imaging throughput, and accessibility. Fluorescence microscopy offers molecular specificity and compatibility with intact biological specimens but has so far lacked the spatial resolution required to visualize cellular ultrastructure. Here we introduce Mega-expansion microscopy (Mega-ExM), a fluorescence imaging approach that enables structural visualization of whole cells using conventional confocal microscopes. Mega-ExM combines iterative hydrogel expansion with whole-proteome NHS-dye labeling and post-expansion immunostaining to achieve tunable expansion factors of up to [~]1,500-fold while preserving ultrastructure. At expansion factors of 40-260x, Mega-ExM resolves centrioles, mitochondrial cristae, protein-dense domains within mitochondrial cristae consistent with respiratory-chain supercomplexes, the synaptonemal complex, and nuclear pore complexes (NPCs) with high fidelity. Particle averaging of [~]200x expanded NPCs yields reconstructions with a structural resolution of [~]35 [A], approaching what cryo-electron tomography has achieved for selected protein assemblies. By combining molecular specificity, large imaging volumes, and nanoscale structural resolution on conventional fluorescence microscopes, Mega-ExM establishes a broadly accessible platform for in situ structural biology.

The inherent opacity of most mammalian tissues limits deep-tissue optical imaging and light delivery. In contrast, the natural transparency of certain species and ocular tissues has been hypothesized to involve proteins with unusually high refractive indices. Here, we systematically analyze the ultraviolet absorption and visible-range refractive index modulation of canonical amino acids to identify key contributors to high-refractive index proteins. We identify arginine as a leading candidate, combining strong ultraviolet absorption, efficient refractive index modulation, physiological pH, and biocompatibility. These properties are validated through successful achievement of optical transparency in both ex vivo and in vivo tissues. Our findings establish a foundation for using abundant endogenous biomolecules to achieve in vivo tissue transparency and suggest a strategy for engineering proteins enriched in high-performing amino acids to enable efficient, biocompatible tissue clearing.

Single-molecule techniques can resolve biological reactions at unmatched detail, but their low throughput and single-modality readouts have kept them out of data-intensive pipelines such as omics and drug discovery, and beyond reach of low-yield biological systems. Here we introduce a multimodal platform integrating high-throughput magnetic tweezers with ultra-wide-and flat-field objective-based total internal reflection fluorescence, enabling simultaneous force, torque, multicolor fluorescence, and temperature-dependent measurements on up to thousands of individual molecules in parallel and in real time. We demonstrate accurate single-molecule Forster resonance energy transfer (smFRET) for prism-based spectral imaging, capture temperature-dependent hairpin folding dynamics at high temporal resolution with smFRET and use correlative torque-fluorescence measurements to unravel the open-complex formation dynamics during bacterial transcription initiation. By unifying high resolution, throughput, and multimodal readout, this platform enables multidimensional dissection of complex biomolecular reactions with high statistical confidence, unlocking single-molecule biophysics for integration with drug discovery, omics, and cryo-EM workflows.

Epithelial tissues continuously remodel their curvature during morphogenesis, homeostasis, regeneration, and disease, yet experimental access to time-varying curvature remains limited. Here, we introduce CurvoChip, a pneumatically actuated microsystem that reversibly deforms confluent epithelial monolayers cultured on a 20-m elastic membrane into concave or convex geometries. The device operates either in a standard incubator or on a microscope stage and provides programmable control over pressure amplitude, direction, and cycling. Analytical scaling, finite-element simulations, and confocal profilometry establish predictable membrane deformation across the operating range, whereas cycling between -400 and +400 mbar for 120 cycles produces stable deflection without detectable drift or residual deformation. We further implement a three-dimensional surface-reconstruction and segmentation workflow to quantify cell and nuclear morphology on curved monolayers. Acute curvature induction produces a marked polarity-dependent response: convex deformation causes greater cell spreading and epithelial thinning than concave deformation, while nuclear projected area, thickness, and volume change in a direction- and position-dependent manner. These results show that epithelial architecture is sensitive not only to curvature magnitude but also to its orientation relative to the apico-basal axis. CurvoChip therefore provides an accessible platform for dissecting how epithelial tissues integrate dynamic geometric cues.

Biomarker analysis requires detecting analyte classes that span nucleic acids, proteins, small molecules, and metabolites, yet testing remains fragmented across target-specific assays and instruments. Here we report a molecular information-transduction strategy that converts target recognition across molecular classes into a common, error-tolerant DNA code readable by nanopore sequencing. Target recognition triggers a hybridization chain reaction that generates concatemers containing periodically repeated 10-nucleotide target-specific barcodes. A matched-filter decoder exploits this periodicity and the linear scaling of read length with match count to reject spurious matches by two to three orders of magnitude. Multi-class detection is demonstrated for a small molecule (ATP), two cardiovascular-associated microRNAs and thrombin in singleplex and multiplexed assays. By separating molecular recognition from sequence readout, this architecture provides a modular framework for converting heterogeneous analytes into a shared, redundancy-encoded signal for high-fidelity molecular sensing.

Single-molecule protein sequencing promises to democratize clinical proteomics, but platforms retrofitting static DNA-sequencing nanopores face a fundamental biophysical bottleneck: they only measure one-dimensional excluded volume. Consequently, these static calipers struggle to resolve isobaric residues, requiring complex DNA-handle chemistries and target concentrations that exceed clinically relevant abundance ranges. Here, we introduce a dynamical, target-docking translocase engine--the anthrax toxin protective antigen (PA)--as a label-free single-molecule peptide sensor. By extracting the multi-state thermodynamic friction generated as the pore's active site dynamically "breathes" around translocating analytes, we trained a physics-informed machine learning (PIML) architecture to classify a 20-member guest-host peptide library panel representing all 20 canonical amino acids at the single-event level. Operating at low nanomolar concentrations under a 35-millisecond thermodynamic read constraint, the translocase resolved isobaric variants (leucine and isoleucine). Furthermore, we achieved 98.02 (+/-0.05)% classification accuracy on a panel of five un-tagged, native clinical biomarkers (e.g., KRAS G12D, angiotensin, bradykinin). Transitioning from static volumetric measurement to time-domain thermodynamic fingerprinting establishes the requisite protein nanopore hardware for de novo proteomics.

Direct visualisation of drug-target engagement within living cells remains a major challenge. Here we develop a cell-permeable fluorogenic analogue of the phosphodiesterase 4 (PDE4) inhibitor rolipram (MAN193), generated by conjugation to fluorescein diacetate. Following intracellular activation, the probe functions as a near-neutral PDE4 antagonist and enables direct visualisation of endogenous PDE4 populations. Using advanced fluorescence spectroscopy imaging approaches, including molecular brightness analysis and fluorescence anisotropy imaging, we demonstrate rolipram-displaceable binding of the analogue to cytosolic PDE4 and resolve thesubcellular distribution of binding sites. We further show that the probe enables visualisation of untagged PDE4 at focal adhesion complexes in cardiomyocyte-like cells. Together these findings establish fluorogenic drug conjugation combined with quantitative spectroscopy imaging as a generalisable strategy to map intracellular drug-target engagement with subcellular resolution, providing an effective framework for interrogating the spatial pharmacology of small molecules in living systems.

The lifetime of fluorescent molecules provides an orthogonal readout to fluorescence intensity, opening experimental possibilities of measuring changes in local molecular environments, mechanical tension, and metabolism, among other factors. These changes are best studied live and in vivo; however, limitations of slow imaging speeds, high phototoxicity, and increased data size and complexity have significantly impeded progress on this front. Here, we present a complete and transferable pipeline consisting of a light sheet FLIM microscope and an accompanying machine learning model for data processing that renders long-term and/or high-speed volumetric FLIM (vFLIM) tractable in living systems. We benchmark this pipeline across several biological use cases, model systems, lifetime ranges, and spatiotemporal scales, showcasing a suite of possibilities that our workflow enables. This comprehensive pipeline from imaging to analysis is a crucial step forward towards disseminating the power of live vFLIM to the broader bioimaging community.

Accurate determination of kinase inhibitor binding modes could provide essential information for understanding resistance mechanisms and accelerating drug discovery. While conventional structural methods such as X-ray crystallography, cryo-EM and NMR provide high-resolution information but are low-throughput and capture largely static snapshots of dynamic protein-ligand interactions Here, we introduce a single-molecule nanopore tweezer platform that functionally subtypes ATP-competitive Abl kinase inhibitors by resolving distinct ionic current signatures of Abl-inhibitor complexes. This approach distinguishes Type I, Type IIA, and Type IIB inhibitors without structural determination. We further show how clinically relevant Abl variants (T315I and E255V) reshape inhibitor engagement and binding modes. By combining baseline probability features with wavelet-based time-frequency descriptors, ensemble machine-learning models achieved 97.5% classification accuracy across seven kinase inhibitor binding modes at sub-angstrom resolution and enabled deconvolution of mixed-inhibitor samples at nanomolar concentrations. These results establish nanopore tweezers as a label-free, super-resolution platform for profiling kinase conformational states and inhibitor binding modes, complementing structural approaches and supporting precision oncology.