Journal of Microscopy

Backscattered electron scanning electron microscopy (BSE-SEM) provides compositional image contrast but has found limited application to biological samples due to the low atomic number difference between constituent elements, the thickness of the surrounding environment, and the need for complex sample preparation. Here, we demonstrate the use of room temperature liquid phase BSE-SEM (LPBSEM) for imaging Bacillus subtilis spores encapsulated in graphene liquid cells, preserving native hydration and reducing the thickness of the sample environment. This approach eliminates the need for staining and enables high-contrast visualisation of subcellular structures. Distinct structural layers within B. subtilis spores have been observed with a contrast similar to conventional thin-section transmission electron microscopy but without the need for sample preparation that potentially compromises sample integrity. We further investigate the influence of beam energy on the interaction volume depth and image contrast and propose optimal conditions for subsurface visualisation. Monte Carlo simulations have been used to validate our experimental observations and provide a quantitative framework for understanding BSE generation from hydrated, low atomic number specimens.

The ability to detect host cell factors during Staphylococcus aureus infection in vitro by immunofluorescence microscopy is severely hampered by staphylococcal protein A (SpA), a cell wall-anchored protein that binds the fragment crystallizable (Fc) region of immunoglobulins. This interaction generates strong nonspecific fluorescent signals on the bacterial surface, complicating data interpretation and limiting the accuracy of quantitative image analysis. Several measures have been put forward to overcome this obstacle, most importantly the pre-incubation with an anti-SpA antibody (SpA) and the use of human serum (HS) as blocking agent and antibody diluent. To highlight this feature to general fluorescence microscopy users, we here systematically evaluated these two strategies. Using S. aureus coated on coverslips and S. aureus-infected A549 cells, we highlight the efficiencies of both approaches to markedly reduce nonspecific fluorescence, with HS treatment yielding the most profound suppression. Notably, HS, containing high levels of human immunoglobulins, offered a robust, cost-effective and broadly applicable solution for minimizing SpA-driven artifacts, thereby improving immunofluorescence microscopy in S. aureus infection models in vitro.

Dragonfly and cicada wing-inspired titanium nanopillar surfaces show promising bactericidal properties for antibacterial medical implant applications, but the precise mechanisms of bacteria-nanopillar interactions under hydrated conditions remain unclear. Cryo-electron tomography (cryo-ET) enables the visualisation of cellular organelles within their native hydrated cellular environment at molecular resolution. Visualising the bacteria-material interface on nanostructured surfaces by cryo transmission electron microscopy (cryo-TEM) requires the preparation of thin lamellae. Obtaining lamellae of bacteria directly on metal substrates while in a non-fixed and hydrated state requires cryo-focused ion beam (cryo-FIB) milling to isolate the targeted bacteria from the bulk sample. This approach faces additional challenges compared to tissues or cells on TEM grids, as titanium samples require a simultaneous cross-section of soft and hard materials at the same position and require vitrification, which embeds the sample in a thick layer of ice. Nonetheless, we demonstrate how to target a specific bacterium interacting with a titanium nanopillar surface using correlative cryo-fluorescence imaging, and how lamellae can still be prepared from vitrified samples by extracting the targeted bacterium and its surrounding as a small volume and transferring it to a receptor grid for thin lamella preparation, called targeted cryo-lift-out. Here, we outline the workflows and discuss their advantages and limitations for producing lamellae through lift-out techniques under cryogenic conditions, using methods that do not involve gas injection systems (GIS) for the lift-out transfer. These advances enhance cryo-ET applications, enabling in situ investigations of the interface between bacteria and nanopillars to effectively study the bactericidal mechanisms of biomimetic nature-inspired nanotopographies in a hydrated environment.

In contemporary bio-imaging-based research, computer-based assessment is becoming crucial for the characterisation of biological structures, as it minimises the need for time-consuming human annotation, which is prone to human error. Furthermore, it allows for the use of optical techniques that use lower photon intensities, thereby reducing reliance on high-intensity excitation and mitigating adverse effects on their activities. This study details the development and evaluation of sophisticated deep-learning models for amoeba detection using phase-contrast imaging. Using a single-class annotated dataset comprising 88 images and 4,131 annotations, we developed nine object detection models based on Detectron 2 and six variants based on YOLO v10. The diversity of the dataset, acquired under varying setup parameters, facilitated a comprehensive evaluation of the strengths and limitations of each model. A comparative analysis of speed and accuracy was performed to identify the most efficient models for real-time detection, providing critical insights for future microscopic analyses.

Fluorescent reporters such as fluorescent proteins or chemigenetic indicators are indispensable tools for studying biological processes using light microscopy. Choosing an appropriate fluorescent tag is a crucial step in experimental design not only for imaging but also for quantitative measurements such as fluorescence fluctuation spectroscopy. Two key parameters should be considered: Fluorescent brightness and photo-bleaching. Change to fluorescence intensity due to photobleaching is relatively easy to assess in different biological environments, while brightness is more elusive. Here, we develop and employ a fluorescence correlation spectroscopy (FCS) based excitation scan assay that determines fluorescent protein performance and validate it in tissue culture and zebrafish embryos. We employ our FCS pipeline to compare a set of 10 established fluorescent proteins as well as HALO and SNAP tags for both cellular imaging and measurements of diffusion dynamics with FCS. We show that mNeonGreen outperforms mEGFP in tissue culture and zebrafish embryos. We also compare StayGold variants against other green fluorescent proteins and chemigenetic reporters in tissue culture. Overall, we present a broadly applicable approach for determining fluorescent reporter brightness in the living system of interest.

Fourier ptychographic microscopy (FPM) uses sequential multi-angle illumination and iterative phase retrieval to recover a high-resolution complex image from a series of low-resolution brightfield and darkfield images. We present OpenFPM, an open-source FPM platform in which conventional and optomechanical hardware is replaced with compact, low-cost 3D printed components. Illumination, sample and objective positioning, and camera triggering are controlled using a Python-based interface on a Raspberry Pi microcomputer. With a 10 x /0.25 NA objective lens and 636 nm illumination, OpenFPM experimentally achieves amplitude and phase reconstructions with an effective synthetic NA of 0.90 over a 1 mm field-of-view. This platform gives researchers accessible and affordable hardware for developing and testing LED-array microscopy techniques for a range of biomedical imaging applications.

Digital holographic microscopy systems in a common-path configuration, compared to systems with a separate reference arm, offer a compact design and resistance to disturbances. They can operate with partially coherent illumination, reducing speckle noise. However, they are limited by the overlapping of the object beam and its laterally shifted replica. As a result, images from different regions of the object overlap on the detector, preventing imaging of dense samples. We present the wavelength-scanning replica-removal method, which solves this problem by enabling the separation of information from both replicas and thereby doubling the effective field of view (FOV). The wavelength-scanning multi-shear replica removal algorithm plays a key role in reconstructing the undisturbed phase from a series of holograms recorded with variable shears. The shear value is controlled by changing the illumination wavelength. This enabled the development of two measurement modes: time-domain wavelength scanning for high-quality imaging, and a single-shot mode with frame division into color channels to improve temporal resolution. The method was validated using resolution tests and biological samples - neurons and dynamic yeast cultures. By combining the advantages of the common-path configuration with dense-structure imaging and dynamic processes, the proposed method constitutes a versatile tool for quantitative phase microscopy.

Single-molecule localization microscopy (SMLM) methods enable fluorescence imaging of biological specimens with nanometer-scale resolution. Although fluorophore localization precision is theoretically limited only by photon statistics, in practice the resolution of SMLM images is often degraded by physical drift of the sample and/or the microscope during data acquisition. At present, correcting this effect requires either specialized stabilization systems or computationally intensive post-processing, and established drift correction algorithms based on image cross-correlation suffer from limited temporal resolution. In this study we introduce COMET, a new method for SMLM drift estimation which achieves a substantially higher precision, accuracy, and temporal resolution compared with existing algorithmic approaches. We demonstrate that improved drift estimation translates directly into higher SMLM image resolution, limited by localization precision rather than drift artifacts. COMET is applicable to all types of SMLM data, operating directly on 2D or 3D localization datasets, and is readily integrated into analysis workflows. We benchmark its performance using both simulations and experiments, including STORM, MINFLUX, and Sequential OligoSTORM measurements, where long acquisition times make drift correction particularly challenging. COMET is published as an open-source, Python-based software project and is also available on open cloud-computing platforms.

Cryo-Focused Ion Beam Scanning Electron Microscopy (cryoFIB-SEM) using samples fixed by high-pressure freezing uniquely enables high resolution cryo-volume Electron Microscope (cvEM) images of cell ultrastructure to be obtained from whole cells and complex tissues in their near native state. As the freezing process also preserves fluorescence, the link between three-dimensional (3D) ultrastructure and biological process is also enabled by targeted cryo-Correlative Light and Electron Microscopy (CLEM). However, the overall viability of cvEM is challenged by sample preparation, charge balance during imaging, sample sensitivity to beam damage, contamination, and very long acquisition times. Here we detail new experimental workflows to significantly reduce each of these effects and demonstrate the improvement in resolution possible with results from the nematode Caenorhabditis elegans and the ciliated protozoon Paramecium bursaria containing many endosymbiotic algae. These results demonstrate the versatility and potential wide-ranging utility of cvEM for 3D ultrastructural imaging of whole multicellular and unicellular organisms.

Investigating single-cell dynamics and morphology in tissues and embryos requires highly accurate quantitative analysis of microscopy images. Despite significant advances in the field of bioimage analysis, even the most sophisticated segmentation and tracking algorithms inevitably produce errors (e.g. : over segmentation, missing objects, miss-connected objects). Although error rate may be small, their propagation throughout a time-lapse sequence has catastrophic effects on the accuracy of tracking and extraction of single cell parameters. Extracting single cell temporal information in the context of tissue/embryo requires thus expert curation to identify and correct segmentation errors. In the movies commonly used in developmental biology and stem cell research, both the number of imaged cells and the duration of recording are large, making this manual correction task extremely time-consuming. This has now become a major bottleneck in the fields of development, stem cell biology and bioimage analysis. We present here EpiCure (Epithelial Curation), a versatile tool designed to streamline and accelerate manual curation of segmentation and tracking in 2D movies of large epithelial tissues. EpiCure uses temporal information and morphometric parameters to automatically identify segmentation and tracking errors and provides user-friendly tools to correct them. It focuses on ergonomics and offers several visualization options to help navigating in movies of tissue covering a large number of cells, speeding up the detection of errors and their curation. EpiCure is highly interoperable and supports input from a wide range of segmentation tools. It also includes multiple export filters, enabling seamless integration with downstream analysis pipelines. In this paper, using movies from several animal models, we highlight the importance of curating cell segmentation and tracking for accurate downstream analysis, and demonstrate how EpiCure helps the curation process for extracting accurate single cell dynamics and cellular events detection, making it faster and amenable on large dataset.

It is an essential element of mechanobiology to measure the forces of biological cells. In microparticle traction force microscopy, they are inferred from the deformation of elastic microparticles. Two complementary variants have been introduced before: the volume method, which reconstructs surface stresses from the displacements of fiducial markers embedded inside the particles, and the surface method, which infers stresses directly from the deformation of the particle surface. However, a systematic comparison of the two methods has been lacking. Here, we quantitatively compare both approaches using simulated traction fields representing biologically relevant loading scenarios. We find that the surface method consistently reconstructs traction profiles with substantially lower errors than the volume method, which suffers from displacement tracking and stress calculation at the surface. At high noise levels, however, the performance gap becomes smaller. To compare the performance of the two methods in a realistic experimental setting, we developed DNA-based hydrogel microparticles equipped with both fluorescent surface labels and embedded fluorescent nanoparticles, enabling the direct comparison of the two methods within the same system. Compression experiments produced traction profiles consistent with Hertzian contact mechanics and confirmed the trends observed in the simulations. While our computational workflow establishes a framework to apply both methods, our experimental workflow establishes DNA microparticles as versatile and biocompatible probes for measuring cellular forces.

Mitochondrial membrane potential ({Delta}{Psi}m) is central to ATP production, ion homeostasis, and cell survival, reflecting the functional state of the inner mitochondrial membrane and oxidative phosphorylation. Accurate assessment of {Delta}{Psi}m is therefore essential for understanding mitochondrial physiology and dysfunction in health, ageing, and disease. Lipophilic cationic fluorescent dyes, such as TMRM and TMRE, are widely used to monitor {Delta}{Psi}m in live cells, enabling high-temporal-resolution imaging of both steady-state membrane potential and dynamic fluctuations. Beyond stable bioenergetic measurements, live-cell imaging reveals transient, reversible depolarisation events, known as mitochondrial "flickers." These events, observed across multiple cell types and imaging platforms, are often associated with brief openings of the mitochondrial permeability transition pore (mPTP) and may represent regulated mitochondrial excitability, rather than irreversible damage. While excessive or synchronised depolarisations may signal mitochondrial injury, transient flickers are increasingly viewed as potential signalling mechanisms within the mitochondrial network. This work discusses methodological considerations for {Delta}{Psi}m imaging, the biological significance of mitochondrial flickers, and the importance of distinguishing physiological events from probe- and light-induced artefacts, highlighting the emerging concept of mitochondria as dynamic and communicative bioenergetic networks.

Accurate quantification of transplanted cardiac spheroids requires three-dimensional localisation within intact myocardium, yet this remains technically challenging. Optical clearing and light-sheet microscopy enable volumetric imaging of injection sites, but automated segmentation is difficult when transplanted spheroids and host tissue are labelled with the same fluorescent markers and cannot be separated by simple thresholding. We developed a random forest based pixel classification workflow for 3D detection of injected hiPSC derived cardiomyocyte and H9c2 spheroids in optically cleared rabbit myocardium. A supervised classifier trained on intensity, edge, and texture features generated a segmentation then grouped pixels via connected component analysis to reconstruct individual spheroids. The method showed good agreement with manual annotation and enabled automated extraction of spheroid size and spatial metrics. This accessible workflow enables reproducible three-dimensional quantification of transplanted spheroids in large light-sheet microscopy datasets and provides a practical route from volumetric imaging to spatial metrics in cardiac regeneration studies.

Quantitative histological analysis of skeletal muscle morphometry provides critical insights into muscle physiology but remains labor-intensive and technically demanding. While recent developments in machine-learning-based image segmentation techniques have facilitated large-scale tissue analysis, existing tools that automate muscle morphometry analysis are largely tailored to mammalian models, with limited applicability to teleosts. Moreover, there is a lack of effective tools for visualizing spatial organization and morphometric variability of teleost muscle fibers, a feature that is important for understanding hyperplastic muscle growth dynamics in teleosts. In this study, we show that cytoplasmic staining combined with deep learning-based cell segmentation offers a robust and accurate approach for automated muscle morphometry analysis in developing zebrafish. We also introduce a FIJI2 plugin, implemented in Jython, that streamlines both morphometric analysis and visualization. This tool accommodates shallow and deep learning-based segmentation techniques and incorporates novel quantification and visualization methods suited to teleost-specific muscle features, including mosaic hyperplasia dynamics. The plugin features an intuitive graphical user interface and is designed for flexibility, with minimal constraints regarding species, image quality, or staining protocol. Its modular architecture allows it to be used as a baseline for automated muscle morphometry analysis, while permitting integration with other tools and workflows.

A compact, in-house developed ultraviolet germicidal irradiation (UVGI) system adaptable to static, mobile, or robotic platforms was developed for the effective sterilization of bacteria and fungi using a wireless mode of operation. Under controlled laboratory conditions, its efficacy was evaluated against three representative biofilm-forming pathogens: Bacillus subtilis (Gram-positive, spore-forming, motile bacterium), Escherichia coli K12 (Gram-negative, non-spore-forming, non-motile bacterium), and Candida albicans M-207 (multi-drug-resistant, clinical yeast isolate). Microbial viability following UVGI exposure was assessed using colony-forming unit (CFU) and MTT assays, and morphological alterations were characterized by scanning electron microscopy (SEM). Cultures were exposed to UV-C radiation at distances of 1-5 m for 15-90 min. CFU assay demonstrated 100% kill of all tested organisms at 1 m and 15 min, corresponding to doses of 600.3, 576 & 697.5 mJ/cm{superscript 2}. Although MTT assays indicated residual metabolic activity under the same conditions, CFU results confirmed that surviving cells were unable to proliferate, highlighting the robustness of UV treatment for long-term inactivation. SEM confirmed distinct morphological alterations such as complete destruction of extracellular matrix & reduction in number of cells indicating cell death with increase in UV dose as compared to controls. A dose & time-dependent inactivation of biofilm-forming bacteria & fungi was observed on exposure to UVGI. Therefore, this pilot study validates the effectiveness of the newly developed UVGI surface sterilizer against biofilm-forming bacterial and fungal pathogens. Overall, the system demonstrates proof-of-concept efficacy under laboratory conditions and holds strong potential for future development and validation in hospitals and other contaminated public spaces. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/715580v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@150cefcorg.highwire.dtl.DTLVardef@450831org.highwire.dtl.DTLVardef@1cfd6borg.highwire.dtl.DTLVardef@1419ba8_HPS_FORMAT_FIGEXP M_FIG C_FIG IMPORTANCEMicroorganisms that form biofilms on surfaces are difficult to eliminate and contribute to the spread of infections in healthcare and indoor environments. There is a need for practical, easy-to-use disinfection technologies that can effectively reduce such contamination. In this study, we developed a compact, in-house, wireless UV-C disinfection system designed for flexible operation across different surface types. The system was evaluated under controlled laboratory conditions using representative biofilm-forming bacterial and fungal pathogens. Our findings show that the system can effectively reduce microbial contamination, demonstrating proof-of-concept efficacy. This work highlights the potential of accessible, non-chemical UV-based technologies and supports their further validation for applications in real-world disinfection settings.

Space-based platforms currently represent the most accurate means to experimentally assess the influence of the space environment on biological systems. However, performing such experiments remains technically challenging and requires highly specialized instrumentation. This study describes the current development and hardware qualification of ExocubeBio, a miniaturized experimental platform for in-situ biological space exposure. This experiment is scheduled for installation on the exterior of the International Space Station in 2027, as part of Exobio, the European Space Agencys new generation exobiology exposure facility. ExocubeBio will expose live microbial samples to the low Earth orbit environment, and combine autonomous in-situ optical density and fluorescence measurements, with the capacity to return preserved samples to Earth. Achieving these experimental goals requires a specialized, robust and reliable hardware system. The ExocubeBio hardware testing described here includes assessment of material biocompatibility and durability, functional validation of the miniaturized fluidic system, and optimization of the integrated optical subsystem for optical density and fluorescence measurements. These results demonstrate that the ExocubeBio experimental hardware components can each execute their core functional and operational requirements; subsystems allow for sample exposure, in-situ measurements of microbial cultures, and the chemical preservation of samples for post-flight analysis. As ExocubeBio transitions from hardware development to mission readiness, the results presented here validate the overall design and engineering approaches utilized. By combining the strengths of in-situ monitoring and sample return, ExocubeBio represents a significant advancement in space-based experimentation, and will provide new insights into microbial responses to the space environment.

When honeybee colonies reproduce by fission, several thousand bees and their queen depart the parental nest and temporarily form a dense cluster on a tree branch or other surface while searching for a new nest site. Once the new nest site is selected, the swarm disassembles and flies toward it. How honeybees transition rapidly between dispersed flight and an aggregated cluster remains an open question. Here, we develop an experimental system and three-dimensional imaging pipeline to track individual flying bees together with the evolving morphology of the swarm during formation and dissolution. We report results from a representative swarming event. During assembly, swarms rapidly form low-density clusters before undergoing a slower contraction to a more dense steady state configuration. In contrast, disassembly occurs significantly faster than assembly and is characterized by strongly divergent flight, with bees departing the swarm in all directions. Overall, this method is able to demonstrate the coupled flight and morphological dynamics that underlie honeybee swarm assembly. Because the system is relatively low-cost and low-power, it is readily adaptable for three-dimensional imaging of other biological collectives in naturalistic environments.

Raman spectroscopy offers a uniquely rich window into molecular structure and composition, making it a powerful tool across fields ranging from materials science to biology. However, the reproducibility of Raman data analysis remains a fundamental bottleneck. In practice, transforming raw spectra into meaningful results is far from standardized: workflows are often complex, fragmented, and implemented through highly customized, case-specific code. This challenge is compounded by the lack of unified open-source pipelines and the diversity of acquisition systems, each introducing its own file formats, calibration schemes, and correction requirements. Consequently, researchers must frequently rely on manual, ad hoc reconciliation of processing steps. To address this gap, we introduce TRaP (Toolbox for Reproducible Raman Processing), an open-source, GUI-based Python toolkit designed to bring reproducibility, transparency, and portability to Raman spectral analysis. TRaP unifies the entire preprocessing-to-analysis pipeline within a single, coherent framework that operates consistently across heterogeneous instrument platforms (e.g., Cart, Portable, Renishaw, and MANTIS). Central to its design is the concept of fully shareable, declarative workflows: users can encode complete processing pipelines into a single configuration file (e.g., JSON), enabling others to reproduce results instantly without reimplementing code or reverse-engineering undocumented steps. Beyond convenience, TRaP integrates configuration management, X-axis calibration, spectral response correction, interactive processing, and batch execution into a workflow-driven architecture that enforces deterministic, repeatable operations. Every transformation is explicitly recorded, making the full processing history transparent, inspectable, and reproducible. This eliminates ambiguity in how results are generated and ensures that identical protocols can be applied consistently across datasets and experimental contexts. Through representative use cases, we show that TRaP enables seamless, reproducible preprocessing of Raman spectra acquired from diverse platforms within a unified environment. We hope TRaP can empower Raman data processing as a reproducible, shareable, and systematized scientific practice, aligning it with modern standards for computational research. TRaP is released as an open-source software at https://github.com/hrlblab/TRaP

The performance of a laser scanning microscope inevitably depends on the performance of the point detector. As laser scanning approaches aim to penetrate deeper in tissue, there is a commensurate need for detectors that can operate with high sensitivity, bandwidth, and dynamic range at near-infrared wavelengths where scattering is reduced. Here, we demonstrate that fiber optical parametric amplification can be used to boost low-power microscopy signals to levels that can be detected by near-infrared photodiodes without introducing prohibitive noise. We construct amplifiers that achieve >50 dB of parametric gain at wavelengths within the third near-infrared transparency window and have similar sensitivity to near-infrared photomultiplier tubes. Furthermore, these amplifiers outperform detection with a photodiode and subsequent electrical amplification, providing a factor of 10-100-fold improvement in sensitivity. We demonstrate amplifier bandwidths up to ~1.6 GHz, a factor of 10 faster than conventional detectors, including near-infrared photo-multiplier tubes, with sensitivity of ~8 nW (corresponding to ~20 photons/pixel). Finally, the increased performance of the optical amplifier is confirmed in diagnostic imaging experiments where >10x less power is required to achieve the same signal-to-noise ratio and contrast as images using electrical amplification. Accordingly, fiber optical parametric amplification is a new path forward for extending the performance of laser scanning microscopes in the near infrared.

As human space exploration expands to the Moon, Mars, and beyond, there is a growing need to study the effects of altered gravity on the microbial systems that we will bring with us for life support. Because spaceflight experiment opportunities are rare and resource-intensive, most space biology experiments are conducted using ground-based simulators. The most common microgravity simulator for microbial experiments, the rotating wall vessel, can approximate the low-shear and low-turbulence conditions that characterize microgravity. However, current designs do not allow for real-time measurement of growth or metabolic activity during rotation: experiments require destructive sampling or disruption of the microgravity simulation conditions. Here, we describe the development of an in situ spectroscopy system compatible with the Cell Spinpod rotating wall vessel, which enables measurement of both optical absorbance and fluorescence with high temporal resolution, producing growth curves similar to those from an off-the-shelf plate reader. These results are validated using two common microbial hosts: Escherichia coli and Saccharomyces cerevisiae. The Spinpod Optical System has the potential to diversify the types of microbiology experiments possible in simulated microgravity, allowing the measurement of not only growth curve parameters but also metabolic activity, gene expression, or community dynamics. It thus has the potential to improve the quality of experiments seeking to characterize microbial responses to spaceflight conditions.