Nanoscale Resolution Research Articles

The Synergy between Topography and Lipid Domains in the Plasma Membrane of Mast Cells Controls the Localization of Signaling Proteins and Facilitates their Coordinated Activation.

Similar to T cells and B cells, mast cell surfaces are dominated by microvilli, and like these other immune cells we showed with microvillar cartography (MC) that key signaling proteins for RBL mast cells localize to these topographical features. Although stabilization of ordered lipid nanodomains around antigen-crosslinked IgE-FcεRI is known to facilitate necessary coupling with Lyn tyrosine kinase to initiate transmembrane signaling in these mast cells, the relationship of ordered-lipid nanodomains to membrane topography had not been determined. With nanoscale resolution provided by MC, SEM and co-localization probability (CP) analysis, we found that FcεRI and Lyn kinase are positioned exclusively on the microvilli of resting mast cells in separate nano-assemblies, and upon antigen-activation they merge into overlapping populations together with the LAT scaffold protein, accompanied by elongation and merger of microvilli into ridge-like ruffles. With selective lipid probes, we further found that ordered-lipid nanodomains preferentially occupy microvillar membranes, contrasting with localization of disordered lipids to flatter regions. With this proximity of signaling proteins and ordered lipid nanodomains in microvilli, the mast cells are poised to respond sensitively and efficiently to antigen but only in the presence of this stimulus. Use of a short chain ceramide to disrupt ordered-lipid regions of the plasma membrane and evaluation with MC, CP, and flow cytometry provided strong evidence that the microvillar selective localization of signaling proteins and lipid environments is facilitated by the interplay between ordered-lipid nanodomains and actin attachment proteins, ERM (ezrin, radixin, moesin) and cofilin.

Accelerated protein retention expansion microscopy using microwave radiation.

Protein retention expansion microscopy (ExM) retains fluorescent signals in fixed tissue and isotropically expands the tissue to allow nanoscale (<70nm) resolution on diffraction-limited confocal microscopes. Despite the numerous advantages of ExM, the protocol is time-consuming. Here, we adapted an ExM protocol to vibratome-sectioned brain tissue of Xenopus laevis tadpoles and implemented a microwave (M/W)-assisted protocol (M/WExM) to reduce the workflow from days to hours. Our M/WExM protocol maintains the superior resolution of the original ExM protocol and yields a higher magnitude of expansion, suggesting that M/W radiation may also facilitate the expansion process. We then adapted the M/W protocol to the whole-mount brain of Drosophila melanogaster fruit flies, and successfully reduced the processing time of a widely used Drosophila IHC-ExM protocol from 6 to 2days. This demonstrates that with appropriate adjustment of M/W parameters, this protocol can be readily adapted to different organisms and tissue types to greatly increase the efficiency of ExM experiments.

Illumination diversity in multiwavelength extreme ultraviolet ptychography

With the development of high harmonic generation (HHG), lensless extreme-ultraviolet (XUV) imaging at nanoscale resolution has become possible with table-top systems. Specifically, ptychographic phase retrieval using monochromatic XUV illumination exhibits extraordinary robustness and accuracy to computationally reconstruct the object and the illumination beam profile. In ptychography, using structured illumination has been shown to improve reconstruction robustness and image resolution by enhancing high spatial-frequency diffraction. However, broadband imaging has remained challenging, as the required multiwavelength algorithms become increasingly demanding. One major aspect is the ability to separate the available information into different physically meaningful states, such as different spectral components. Here, we show that introducing spatial diversity between spectral components of an HHG beam can significantly improve the reconstruction quality in multiwavelength XUV ptychography. We quantify the diversity in the polychromatic illumination by analyzing the diffraction patterns using established geometry- and information-theory-based dissimilarity metrics. We experimentally verify the major influence of diversity by comparing ptychography measurements using HHG beams with Gaussian and binary structured profiles as well as with beams carrying wavelength-dependent orbital angular momentum. Our results demonstrate how structured illumination acts in twofold by separating the spectral information in a single diffraction pattern while providing maximized added information with every new scan position. We anticipate our work to be a starting point for high-fidelity polychromatic imaging of next-generation nanostructured devices at XUV and soft-X-ray wavelengths.

Simulation Study of High-Precision Characterization of MeV Electron Interactions for Advanced Nano-Imaging of Thick Biological Samples and Microchips.

The resolution of a mega-electron-volt scanning transmission electron microscope (MeV-STEM) is primarily governed by the properties of the incident electron beam and angular broadening effects that occur within thick biological samples and microchips. A precise understanding and mitigation of these constraints require detailed knowledge of beam emittance, aberrations in the STEM column optics, and energy-dependent elastic and inelastic critical angles of the materials being examined. This simulation study proposes a standardized experimental framework for comprehensively assessing beam intensity, divergence, and size at the sample exit. This framework aims to characterize electron-sample interactions, reconcile discrepancies among analytical models, and validate Monte Carlo (MC) simulations for enhanced predictive accuracy. Our numerical findings demonstrate that precise measurements of these parameters, especially angular broadening, are not only feasible but also essential for optimizing imaging resolution in thick biological samples and microchips. By utilizing an electron source with minimal emittance and tailored beam characteristics, along with amorphous ice and silicon samples as biological proxies and microchip materials, this research seeks to optimize electron beam energy by focusing on parameters to improve the resolution in MeV-STEM/TEM. This optimization is particularly crucial for in situ imaging of thick biological samples and for examining microchip defects with nanometer resolutions. Our ultimate goal is to develop a comprehensive mapping of the minimum electron energy required to achieve a nanoscale resolution, taking into account variations in sample thickness, composition, and imaging mode.

Impact of Paraben on Uterine Collagen: An Integrated and Targeted Correlative Approach Using Second Harmonic Generation Microscopy, Nanoindentation, and Atomic Force Microscopy.

This study investigates the structural and mechanical changes in uterine collagen following exposure to propylparaben (PP), using a combined methodology of Second Harmonic Generation (SHG) microscopy, Nanoindentation (NI), and Atomic Force Microscopy (AFM). SHG analysis identified significant disorganization in collagen fibril orientation in the circumferential layer and heterogeneous distribution of regions with elevated forward to backward ratios (F/B) across all uterine layers due to PP exposure. High F/B can indicate multiple potential fibril-level changes like thickened fibrils, higher crosslinking, fibril disorganization - changes not fully decipherable by SHG alone. Recognizing this limitation, the study employs NI and AFM to provide complementary mechanical and nanoscale insights. NI revealed increased indentation modulus in the exposed uteri, suggesting increased stiffness. Co-registration of the indentation response with SHG parameters uncovered that elevated F/B regions show enhanced mechanical stiffness, suggesting a fibrotic transformation following PP exposure. AFM was specifically performed on regions identified by SHG as having low or high F/B, providing the necessary nanoscale resolution to elucidate the structural changes in fibrils that are likely responsible for the observed alterations. This approach confirmed the presence of disordered and entangled collagen fibrils in the circumferential layer in all regions and an increase in fibril diameter in the high F/B regions in the exposed uteri. Together, these findings demonstrate significant alterations in collagen architecture due to PP exposure, revealing disruptions at both the fiber and fibril levels and highlighting the potential for broader applications of the multi-scale, multi-modal approach in collagenous tissue studies.

Anomalous Nernst Effect-Based Near-Field Imaging of Magnetic Nanostructures.

The anomalous Nernst effect (ANE) gives rise to an electrical response transverse to magnetization and an applied temperature gradient in a magnetic metal. A nanoscale temperature gradient can be generated by the use of a laser beam applied to the apex of an atomic force microscope tip, thereby allowing for spatially resolved ANE measurements beyond the optical diffraction limit. Such a method has been previously used to map in-plane magnetized magnetic textures. However, the spatial distribution of the out-of-plane temperature gradient, which is needed to fully interpret such ANE-based imaging, was not studied. We therefore use a well-known magnetic texture, a magnetic vortex core, to demonstrate the reliability of the ANE method for imaging of magnetic domains with nanoscale resolution. Moreover, since the ANE signal is directly proportional to the temperature gradient, we can also consider the inverse problem and deduce information about the nanoscale temperature distribution. Our results together with finite element modeling indicate that besides the out-of-plane temperature gradients there are even larger in-plane temperature gradients. Thus, we extend the ANE imaging to study the out-of-plane magnetization in a racetrack nanowire by detecting the ANE signal generated by in-plane temperature gradients. In all cases, a spatial resolution of ≈70 nm is obtained. These results are significant for the rapidly growing field of thermoelectric imaging of antiferromagnetic spintronic device structures.

Application of Advanced Microscopy Techniques to the Characterization of Mixed Matrix Membranes.

Mixed matrix membranes (MMMs) have emerged as promising materials for various separation processes due to their tunable properties, enhanced separation performance and reproducibility. In this review paper, we provide a comprehensive overview of the methodologies, challenges, and applications associated with the characterization of MMMs using two advanced imaging techniques: Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) and Transmission Electron Microscopy (TEM). We begin by outlining the principles and capabilities of FIB-SEM and TEM, emphasizing their suitability for studying the microstructure, morphology, and composition of MMMs at nanoscale resolution. Subsequently, we discuss the specific challenges and limitations encountered in the characterization of MMMs using these techniques, including sample preparation, image acquisition, and data interpretation. Furthermore, we review the diverse applications of FIB-SEM and TEM in elucidating the structure-property relationships of MMMs. Through illustrative examples, we highlight the valuable insights gained from these imaging techniques in optimizing MMMs for various separation applications. Finally, we propose future directions and emerging trends in MMM characterization, including the integration of lasers into FIB-SEM and in situ characterization techniques, to address current challenges and push the boundaries of MMM design and performance. Overall, this review provides a comprehensive overview of the state-of-the-art methodologies for characterizing MMMs using FIB-SEM and TEM, identifies key challenges, and offers insights into future research directions aimed at harnessing the full potential of MMMs for sustainable separation technologies.

Single-vesicle imaging reveals actin-dependent spatial restriction of vesicles at the active zone, essential for sustained transmission

Synaptic-vesicle (SV) recruitment is thought to maintain reliable neurotransmitter release during high-frequency signaling. However, the mechanism underlying the SV reloading for sustained neurotransmission at central synapses remains unknown. To elucidate this, we performed direct observations of SV reloading and mobility at a single-vesicle level near the plasma membrane in cerebellar mossy fiber terminals using total internal reflection fluorescence microscopy, together with simultaneous recordings of membrane fusion by capacitance measurements. We found that actin disruption abolished the rapid SV recruitment and reduced sustained release. In contrast, induction of actin polymerization and stabilization did not affect vesicle recruitment and release, suggesting that the presence of actin filaments, rather than actin dynamics, was required for the rapid recruitment. Single-particle tracking experiments of quantum dot-labeled vesicles, which allows nanoscale resolution of vesicle mobility, revealed that actin disruption caused vesicles to diffuse more rapidly. Hidden Markov modeling with Bayesian inference revealed that SVs had two diffusion states under normal conditions: free-diffusing and trapped. After disruption of the actin filament, vesicles tended to have only the free-diffusing state. F-actin staining showed that actin filaments were localized outside the active zones (AZs) and surrounded some SV trajectories. Perturbation of SV mobility, possibly through interference with biomolecular condensates, also suggested that the restricted diffusion state determined the rate of SV recruitment. We propose that actin filaments confined SVs near the AZ to achieve rapid and efficient recruitment followed by priming and sustained synaptic transmission.

Laser-Induced Self-Limiting Welding of Ag Nanowires with High Mechanical and Electrical Performance.

The high-efficiency and high-precision welding technology of Ag nanowires is of great engineering significance for the integration of new-generation micro- and nanodevices, and the mechanical behavior of its interconnect joints is also essential for their reliable application, especially for some flexible device. In this paper, based on the nano-focusing and localized plasma enhancement properties of Ag nanowires under laser irradiation, Ag nanowire self-limiting joints with mechanical and electrical properties comparable to those of the base material are obtained. At the same time, the local plasma enhancement characteristics of Ag nanowire joints are scanned and analyzed with nanoscale resolution by using cathodoluminescence technology, and the local multi-physical field coupling regulation mechanism of Ag nanowire joints induced by different laser parameters is systematically investigated by combining theoretical simulations. Meanwhile, based on the in situ laser welding and nanomechanical tensile experiments, the mechanical properties of single Ag nanowires and their welded joints are systematically analyzed, and the characteristics of the interfacial atomic behaviors and the evolution process during the welding and tensile processes are investigated.

Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst.

Tomographic imaging of time-evolving samples is a challenging yet important task for various research fields. At the nanoscale, current approaches face limitations of measurement speed or resolution due to lengthy acquisitions. We developed a dynamic nanotomography technique based on sparse dynamic imaging and 4D tomography modeling. We demonstrated the technique, using ptychographic x-ray computed tomography as its imaging modality, on resolving the in situ hydration process of polymer electrolyte fuel cell (PEFC) catalyst. The technique provides a 40-time increase in temporal resolution compared to conventional approaches, yielding 28 nm half-period spatial and 12 min temporal resolution. The results allow a quantitative characterization of the water intake process inside PEFC catalysts with nanoscale resolution, which is crucial for understanding their electrochemical mechanisms and optimizing their performance. Our technique enables high-speed operando nanotomography studies and paves the way for wider application of dynamic tomography at the nanoscale.

Exploring Transient States of PAmKate to Enable Improved Cryogenic Single-Molecule Imaging.

Super-resolved cryogenic correlative light and electron microscopy is a powerful approach which combines the single-molecule specificity and sensitivity of fluorescence imaging with the nanoscale resolution of cryogenic electron tomography. Key to this method is active control over the emissive state of fluorescent labels to ensure sufficient sparsity to localize individual emitters. Recent work has identified fluorescent proteins (FPs) that photoactivate or photoswitch efficiently at cryogenic temperatures, but long on-times due to reduced quantum yield of photobleaching remain a challenge for imaging structures with a high density of localizations. In this work, we explore the photophysical properties of the red photoactivatable FP PAmKate and identify a 2-color process leading to enhanced turn-off of active emitters, improving localization rate. Specifically, after excitation of ground state molecules, we find that a transient state forms with a lifetime of ∼2 ms under cryogenic conditions, which can be bleached by exposure to a second wavelength. We measure the response of the transient state to different wavelengths, demonstrate how this mechanism can be used to improve imaging, and provide a blueprint for the study of other FPs at cryogenic temperatures.

Observation of Brownian elastohydrodynamic forces acting on confined soft colloids

Confined motions in complex environments are ubiquitous in microbiology. These situations invariably involve the intricate coupling between fluid flow, soft boundaries, surface forces, and fluctuations. In the present study, such a coupling is investigated using a method combining holographic microscopy and advanced statistical inference. Specifically, the Brownian motion of soft micrometric oil droplets near rigid walls is quantitatively analyzed. All the key statistical observables are reconstructed with high precision, allowing for nanoscale resolution of local mobilities and femtonewton inference of conservative or nonconservative forces. Strikingly, the analysis reveals the existence of a novel, transient, but large, soft Brownian force. The latter might be of crucial importance for microbiological and nanophysical transport, target finding, or chemical reactions in crowded environments, and hence the whole life machinery.

Super-Resolution Surface-Enhanced Raman Scattering: Perspectives on the Past, Present, and Future.

Super-resolution surface-enhanced Raman scattering (SERS) allows researchers to overcome the resolution limit of far field optical microscopy and peer into electromagnetic hot spots with nanoscale resolution. By localizing the signal from single (or few) molecules on the surface of plasmonic nanoparticle aggregates, relationships between the spatial origin of the SERS signal, local electromagnetic field enhancements, and SERS intensity can be determined. This Perspective describes the successes and challenges of super-resolution SERS, from the earliest mapping of single-molecule SERS hot spots to the current state-of-the-art, while highlighting open questions and future opportunities to advance the field. Comparisons with fluorescence-based super-resolution imaging are discussed to help frame the unique challenges associated with performing SERS in the super-resolution regime.

Optical Nanoscopy of Cytokine-Induced Structural Alterations of the Endoplasmic Reticulum and Golgi Apparatus in Insulin-Secreting Cells.

Pro-inflammatory cytokines play a role in the failure of β cells in type 1 and type 2 diabetes. While existing data from 'omics' experiments allow for some understanding of the molecular mechanisms behind cytokine-induced dysfunction in β cells, no report thus far has provided information on the direct imaging of the β cell landscape with nanoscale resolution following cytokine exposure. In this study, we use Airyscan-based optical super-resolution microscopy of Insulinoma 1E (INS-1E) cells to investigate the structural properties of two subcellular membranous compartments involved in the production, maturation and secretion of insulin-containing granules, the endoplasmic reticulum (ER) and the Golgi apparatus (GA). Our findings reveal that exposure of INS-1E cells to IL-1β and IFN-γ for 24 h leads to significant structural alterations of both compartments. In more detail, both the ER and the GA fragment and give rise to vesicle-like structures with markedly reduced characteristic area and perimeter and increased circularity with respect to the original structures. These findings complement the molecular data collected thus far on these compartments and their role in β cell dysfunction and lay the groundwork for future optical microscopy-based ex vivo and in vivo investigations.

Combined Confocal‐Atomic‐Force Microscope Setup for Quantum Sensing Applications with Sub‐diffractional Spatial Resolution

Quantum sensors find applications ranging from material science to biophysics. Nitrogen‐vacancy (NV) center in diamond has been successfully implemented for measuring various types of signals. Optical NV center readout, routinely used in confocal microscopes, allows achieving high spatial resolution down to the diffraction limit. This work describes in detail the combined confocal‐atomic‐force microscope (confocal‐AFM), which takes advantage of sharp AFM cantilevers, and shows its possible applications for nanoscale resolution. It demonstrates the sub‐diffractional localization of NV centers with platinum‐coated cantilevers and the ability to separately address optically unresolved sensors using cantilevers with ferromagnetic coating. The presented setup exhibits a lateral resolution of 13 nm, providing a tool for nanoscale quantum sensing.

Automated analysis framework of strain partitioning and deformation mechanisms via multimodal fusion and computer vision

Simultaneously investigating strain partitioning and the underlying deformation mechanisms for both the grain interior and the grain boundary (GB) is essential for understanding the complex plastic deformation of hexagonal close-packed metals. To this end, an automated analysis framework based on high-resolution digital image correlation (HRDIC) and electron backscatter diffraction (EBSD) data fusion and computer vision, integrating nanoscale resolution and a large field of view, is proposed. This framework consists of: (1) HRDIC-EBSD data fusion; (2) Segmenting the strain field into individual grains each with a core and a mantle; (3) Data clustering of the Matrix and slip bands (SBs) for each grain; (4) Full slip system (SS) identification and SS assignment to the SBs. The capabilities of this framework were demonstrated on Mg-10Y during compression. The strain field data, which was segmented into different clusters, including grain mantle, grain core, Matrix, and SBs, was analyzed statistically and quantitatively. The pixel-based slip activity, which considers the SB morphology, was obtained from a statistical perspective. Inter-granular accommodating mechanisms, including GB strain, slip transfer, and GB sliding, were quantitatively analyzed. Overall, this analysis framework, which can be applied to other materials, can automatically and statistically evaluate both nanoscale strain fields and underlying intra- and inter-granular deformation mechanisms grain-by-grain. This work provides valuable experimental insights into plastic deformation and accommodation mechanisms for polycrystals.

Exploring transient states of PAmKate to enable improved cryogenic single-molecule imaging.

Super-resolved cryogenic correlative light and electron microscopy is a powerful approach which combines the single-molecule specificity and sensitivity of fluorescence imaging with the nanoscale resolution of cryogenic electron tomography. Key to this method is active control over the emissive state of fluorescent labels to ensure sufficient sparsity to localize individual emitters. Recent work has identified fluorescent proteins (FPs) which photoactivate or photoswitch efficiently at cryogenic temperatures, but long on-times due to reduced quantum yield of photobleaching remains a challenge for imaging structures with a high density of localizations. In this work, we explore the photophysical properties of the red photoactivatable FP PAmKate and identify a 2-color process leading to enhanced turn-off of active emitters, improving localization rate. Specifically, after excitation of ground state molecules, we find a transient state forms with a lifetime of ~2 ms under cryogenic conditions which can be bleached by exposure to a second wavelength. We measure the response of the transient state to different wavelengths, demonstrate how this mechanism can be used to improve imaging, and provide a blueprint for study of other FPs at cryogenic temperatures.

Genome-wide analysis of the biophysical properties of chromatin and nuclear proteins in living cells with Hi-D.

To understand the dynamic nature of the genome, the localization and rearrangement of DNA and DNA-binding proteins must be analyzed across the entire nucleus of single living cells. Recently, we developed a computational light microscopy technique, called high-resolution diffusion (Hi-D) mapping, which can accurately detect, classify and map diffusion dynamics and biophysical parameters such as the diffusion constant, the anomalous exponent, drift velocity and model physical diffusion from the data at a high spatial resolution across the genome in living cells. Hi-D combines dense optical flow to detect and track local chromatin and nuclear protein motion genome-wide and Bayesian inference to characterize this local movement at nanoscale resolution. Here we present the Python implementation of Hi-D, with an option for parallelizing the calculations to run on multicore central processing units (CPUs). The functionality of Hi-D is presented to the users via user-friendly documented Python notebooks. Hi-D reduces the analysis time to less than 1 h using a multicore CPU with a single compute node. We also present different applications of Hi-D for live-imaging of DNA, histone H2B and RNA polymerase II sequences acquired with spinning disk confocal and super-resolution structured illumination microscopy.

Trifunctional sphingomyelin derivatives enable nanoscale resolution of sphingomyelin turnover in physiological and infection processes via expansion microscopy

Sphingomyelin is a key molecule of sphingolipid metabolism, and its enzymatic breakdown is associated with various infectious diseases. Here, we introduce trifunctional sphingomyelin derivatives that enable the visualization of sphingomyelin distribution and sphingomyelinase activity in infection processes. We demonstrate this by determining the activity of a bacterial sphingomyelinase on the plasma membrane of host cells using a combination of Förster resonance energy transfer and expansion microscopy. We further use our trifunctional sphingomyelin probes to visualize their metabolic state during infections with Chlamydia trachomatis and thereby show that chlamydial inclusions primarily contain the cleaved forms of the molecules. Using expansion microscopy, we observe that the proportion of metabolized molecules increases during maturation from reticulate to elementary bodies, indicating different membrane compositions between the two chlamydial developmental forms. Expansion microscopy of trifunctional sphingomyelins thus provides a powerful microscopy tool to analyze sphingomyelin metabolism in cells at nanoscale resolution.

A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features

Cellular phenotypic heterogeneity is an important hallmark of many biological processes and understanding its origins remains a substantial challenge. This heterogeneity often reflects variations in the chromatin structure, influenced by factors such as viral infections and cancer, which dramatically reshape the cellular landscape. To address the challenge of identifying distinct cell states, we developed artificial intelligence of the nucleus (AINU), a deep learning method that can identify specific nuclear signatures at the nanoscale resolution. AINU can distinguish different cell states based on the spatial arrangement of core histone H3, RNA polymerase II or DNA from super-resolution microscopy images. With only a small number of images as the training data, AINU correctly identifies human somatic cells, human-induced pluripotent stem cells, very early stage infected cells transduced with DNA herpes simplex virus type 1 and even cancer cells after appropriate retraining. Finally, using AI interpretability methods, we find that the RNA polymerase II localizations in the nucleoli aid in distinguishing human-induced pluripotent stem cells from their somatic cells. Overall, AINU coupled with super-resolution microscopy of nuclear structures provides a robust tool for the precise detection of cellular heterogeneity, with considerable potential for advancing diagnostics and therapies in regenerative medicine, virology and cancer biology.