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Extracellular vesicles (EVs) play pivotal roles in intercellular communication and are implicated in numerous physiological and pathological processes. Here, we introduce a quantitative technique using total internal reflection fluorescence microscopy (TIRFm)-based single vesicle analysis (SVA) to assess EV aggregation, a critical factor influencing their biological functionality. Employing two-colored fluorescent recombinant EV mixtures, this method enables precise discrimination between aggregated and non-aggregated EVs. It allows for calculating an aggregation ratio from the colocalization of fluorescence signals. We evaluate the impact of isolation methods, storage conditions, and biochemical environments on EV aggregation, including salt and pH variations and the presence of antibodies. Additionally, we quantitatively assess the efficacy of aggregation removal techniques, revealing significant variability in removal methods depending on the type of aggregates. This analytical approach is expected to enhance our understanding of EV aggregation dynamics and set a new standard for the characterization and functional analysis of EVs.

Stiffness-related eye diseases such as keratoconus require comprehensive visualization of the complex morphological matrix changes. The aim of this study was to use three-dimensional (3D) light sheet fluorescence microscopy (LSFM) to analyze unlabeled corneal tissue samples, qualitatively visualizing changes in corneal stiffness. Isolated porcine corneal tissue samples were treated with either NaCl or 0.1% glutaraldehyde (GTA) prior to clearing with benzyl alcohol/benzyl benzoate (BABB) and subsequently scanned with LSFM. After analysis of the LSFM data sets, the samples were embedded in paraffin to validate the results by conventional planar microscopy. In the unlabeled corneal tissue samples the 2D/3D morphology of the entire tissue volume was identified by specific autofluorescence signals. An enhancement of collagen crosslinking was induced by applying GTA to the corneal tissue. Subsequent LSFM scans showed specific morphological changes due to altered autofluorescence signals of the corneal stroma, which were confirmed by conventional histology. Therefore, LSFM analysis of corneal tissue samples allowed label-free 3D autofluorescence assessment of the corneal morphology in its anatomical context. It provides the technical basis for the examination of the pathologically altered cornea and facilitates ophthalmologic examinations of corneal diseases based on the altered tissue stiffness., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Routine histochemical techniques are capable of producing vast amount of information from diverse sample types, but these techniques are limited in their ability to generate 3D information. Autofluorescence imaging can be used to analyse samples in 3D but it suffers from weak/low signal intensities. Here, we describe a simple chemical treatment with glutaraldehyde to enhance autofluorescence for 3D fluorescence imaging and to generate detailed morphological images on whole-mount samples. This methodology is straightforward and cost-effective to implement, suitable for a wide range of organisms and sample types. Furthermore, it can be readily integrated with standard confocal and fluorescence microscopes for analysis. This approach has the potential to facilitate the analysis of biological 3D structures and research in developmental biology, including studies on model and non-model organisms., Competing Interests: Competing interests University of Turku has registered a trademark 3DFLUOHISTO®. University of Turku, IP and MN are preparing commercialization of the 3DFLUOHISTO® method for 3D morphological imaging of biological samples., (© 2024. Published by The Company of Biologists Ltd.)

A nucleoid protein Cren7 compacts DNA, contributing to the living of Crenarchaeum in high temperature environment. In this study, we investigated the dynamic behavior of Cren7 on DNA and its functional relation using single-molecule fluorescence microscopy. We found two mobility modes of Cren7, sliding along DNA and pausing on it, and the rapid dissociation kinetics from DNA. The salt dependence analysis suggests a sliding with continuous contact to DNA, rather than hopping/jumping. The mutational analysis demonstrates that Cren7 slides along DNA while Trp (W26) residue interacts with the DNA. Furthermore, Cren7 does not impede the target search by a model transcription factor p53, implying no significant interference to other DNA-binding proteins on DNA. At high concentration of Cren7, the molecules form large clusters on DNA via bridging, which compacts DNA. We discuss how the dynamic behavior of Cren7 on DNA enables DNA-compaction and protein-bypass functions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Post-translational modifications of histones play a crucial role in chromatin structure maintenance and epigenetic regulation. The LiveMIEL (Live-cell Microscopic Imaging of Epigenetic Landscape) method represents a promising approach for tracking histone modifications. It involves visualization of epigenetic modifications using genetically encoded fluorescent sensors and further analysis of the obtained intranuclear patterns by multiparametric image analysis. In this study, we designed three new red fluorescent sensors-MPP8-Red, AF9-Red and DPF3-Red-for live-cell visualization of patterns of H3K9me3, H3K8ac and H3K4me1, respectively. The observed fluorescent patterns were visually distinguishable, and LiveMIEL analysis clearly classified them into three corresponding groups. We propose that these sensors can be used for live-cell dynamic analysis of changes in organization of three epigenetic types of chromatin., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Konstantin A. Lukyanov is in Editorial Board of the BBRC journal. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Fluorescence in Situ Hybridization (FISH) is a technique for macromolecule identification that utilizes the complementarity of DNA or DNA/RNA double strands. Probes, crafted from selected DNA strands tagged with fluorophore-coupled nucleotides, hybridize to complementary sequences within the cells and tissues under examination. These are subsequently visualized through fluorescence microscopy or imaging systems. However, the vast number of cells and disorganized nucleic acid sequences in FISH images present significant challenges. The manual processing and analysis of these images are not only time-consuming but also prone to human error due to visual fatigue. To overcome these challenges, we propose the integration of medical imaging with deep learning to develop an automated detection system for FISH images. This system features an algorithm capable of quickly detecting fluorescent spots and capturing their coordinates, which is crucial for evaluating cellular characteristics in cancer diagnosis. Traditional models struggle with the small size, low resolution, and noise prevalent in fluorescent points, leading to significant performance declines. This paper offers a detailed examination of these issues, providing insights into why traditional models falter. Comparative tests between the YOLO series models and our proposed method affirm the superior accuracy of our approach in identifying fluorescent dots in FISH images., (© 2024. The Author(s).)

The mammalian plasma membrane is known to contain domains with varying lipid composition and biophysical properties. However, studying these membrane lipid domains presents challenges due to their predicted morphological similarity to the bulk membrane and their scale being below the classical resolution limit of optical microscopy. To address this, we combine the solvatochromic probe di-4-ANEPPDHQ, which reports on its biophysical environment through changes in its fluorescence emission, with spectrally resolved single-molecule localisation microscopy. The resulting data comprises nanometre-precision localisation coordinates and a generalised polarisation value related to the probe's environment - a marked point pattern. We introduce quantification algorithms based on topological data analysis (PLASMA) to detect and map nano-domains in this marked data, demonstrating their effectiveness in both artificial membranes and live cells. By leveraging environmentally sensitive fluorophores, multi-modal single molecule localisation microscopy, and advanced analysis methods, we achieve nanometre scale mapping of membrane properties and assess changes in response to external perturbation with methyl-β-cyclodextrin. This integrated methodology represents an integrated toolset for investigating marked point pattern data at nanometre spatial scales., (© 2024. The Author(s).)

We have developed a method combining microinjection and automated fluorescence microscopy to continuously assess the degradation rate, subcellular localization and intracellular concentration of protein analytes at the single-cell level. Cells are unperturbed and grown in unaltered environmental conditions and show high viability. The injection of analytes at defined ratios and concentrations allows for a clearly defined starting point of degradation, without the entanglement of biosynthesis/uptake, often encountered in existing methods. The possibility to evaluate, add, or remove post-translational modifications prior to injection represents a powerful tool to assess minute protein degradation rate changes with high precision and allowed us to determine the absolute degradation rates caused by N-degron pathway engagement, with a focus on the role of acetylation. The low degradation rate of eGFP was found to be caused by inefficient N-terminal proteasomal unfolding. We moreover quantified the surprisingly strong influences of commonly used peptide tags and detected high variation between fluorescent proteins with regard to both protein degradation and subcellular localization. Furthermore, we have validated the use of chemically coupled dyes as robust reporters for protein degradation, and elucidated the significance of their membrane-permeability, thereby extending the applicability of our method to any protein of interest., (© 2024. The Author(s).)

Fluorescent proteins (FPs) are indispensable tools used for molecular imaging, single-cell dynamics, imaging in infection models, and more. However, next-generation FPs have yet to be characterized in Aspergillus . Here, we characterize 18 FPs in the pathogenic filamentous fungus Aspergillus fumigatus spanning the visible light spectrum. We report on in vivo FP brightness in hyphal and spore morphotypes and show how a fluoropyrimidine-based selection system can be used to iteratively introduce four distinct FPs enabling the simultaneous visualization of the cell membrane, mitochondria, peroxisomes, and vacuoles. Using this strain, we describe and compare the dynamic responses of organelles to stresses induced by voriconazole, amphotericin B, and the novel antifungal drugs olorofim and manogepix. The expansion to the fluorescent genetic toolbox will overcome boundaries in research applications that involve fluorescence imaging in filamentous fungi., Competing Interests: The authors declare no conflict of interest.

Expansion microscopy (ExM) is in increasingly widespread use throughout biology because its isotropic physical magnification enables nanoimaging on conventional microscopes. To date, ExM methods either expand specimens to a limited range (~4-10× linearly) or achieve larger expansion factors through iterating the expansion process a second time (~15-20× linearly). Here, we present an ExM protocol that achieves ~20× expansion (yielding <20-nm resolution on a conventional microscope) in a single expansion step, achieving the performance of iterative expansion with the simplicity of a single-shot protocol. This protocol, which we call 20ExM, supports postexpansion staining for brain tissue, which can facilitate biomolecular labeling. 20ExM may find utility in many areas of biological investigation requiring high-resolution imaging., (© 2024. The Author(s).)

Light-sheet fluorescence microscopy (LSFM) combined with tissue clearing has emerged as a powerful technology in drug discovery. LSFM is applicable to a variety of samples, from rodent organs to clinical tissue biopsies, and has been used for characterizing drug targets in tissues, demonstrating the biodistribution of pharmaceuticals and determining their efficacy and mode of action. LSFM is scalable to high-throughput analysis and provides resolution down to the single cell level. In this review, we describe the advantages of implementing LSFM into the drug discovery pipeline and highlight recent advances in this field., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Fe 2 + plays a crucial role in biological systems as an essential trace element in the body. Iron is absorbed by the body through food and Fe 2+ is also an important component of living cells; therefore, quantitative testing of Fe 2+ in food and in living cells is of great importance. This paper presents the development of a novel π-bridge EDOT-based N-oxide turn-on fluorescent probe, designated as FeE, for the detection of Fe 2+ . The probe has been shown to exhibit excellent sensitivity, a favorable linear relationship between fluorescence signal intensity and Fe 2+ concentration, and an effective immunity to interference. The probe has low cytotoxicity and has been successfully used to detect Fe 2+ in cells using laser confocal fluorescence microscopy. It is also possible to determine the presence of Fe 2+ in animal blood, spinach, apple juice, red wine, mineral water and metal cans., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

Cell imaging assays utilising fluorescence stains are essential for observing sub-cellular organelles and their responses to perturbations. Immunofluorescent staining process is routinely in labs, however the recent innovations in generative AI is challenging the idea of wet lab immunofluorescence (IF) staining. This is especially true when the availability and cost of specific fluorescence dyes is a problem to some labs. Furthermore, staining process takes time and leads to inter-intra-technician and hinders downstream image and data analysis, and the reusability of image data for other projects. Recent studies showed the use of generated synthetic IF images from brightfield (BF) images using generative AI algorithms in the literature. Therefore, in this study, we benchmark and compare five models from three types of IF generation backbones-CNN, GAN, and diffusion models-using a publicly available dataset. This paper not only serves as a comparative study to determine the best-performing model but also proposes a comprehensive analysis pipeline for evaluating the efficacy of generators in IF image synthesis. We highlighted the potential of deep learning-based generators for IF image synthesis, while also discussed potential issues and future research directions. Although generative AI shows promise in simplifying cell phenotyping using only BF images with IF staining, further research and validations are needed to address the key challenges of model generalisability, batch effects, feature relevance and computational costs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

In the field of photosynthesis, only a limited number of approaches of super-resolution fluorescence microscopy can be used, as the functional architecture of the thylakoid membrane in chloroplasts is probed through the natural fluorescence of chlorophyll molecules. In this work, we have used a custom-built fluorescence microscopy method called Single Pixel Reconstruction Imaging (SPiRI) that yields a 1.4 gain in lateral and axial resolution relative to confocal fluorescence microscopy, to obtain 2D images and 3D-reconstucted volumes of isolated chloroplasts, obtained from pea (Pisum sativum), spinach (Spinacia oleracea) and Arabidopsis thaliana. In agreement with previous studies, SPiRI images exhibit larger thylakoid grana diameters when extracted from plants under low-light regimes. The three-dimensional thylakoid architecture, revealing the complete network of the thylakoid membrane in intact, non-chemically-fixed chloroplasts can be visualized from the volume reconstructions obtained at high resolution. From such reconstructions, the stromal connections between each granum can be determined and the fluorescence intensity in the stromal lamellae compared to those of neighboring grana., Competing Interests: Declaration of competing interest Cristian Ilioaia, Dmitrij Frolov, Andrew Gall, Bruno Robert reports financial support was provided by I2BC through the French Infrastructure for Integrated Structural Biology. Cristian Ilioaia, Andrew Gall, Bruno Robert reports financial support was provided by Infrastructures en Biologie Santé et Agronomie. Simona Streckaite, Jevgenij Chmeliov, Andrius Gelzinis, Leonas Valkunas reports financial support was provided by Research Council of Lithuania. Cristian Ilioaia, Dmitrij Frolov, Andrew Gall, Igor Chaussavoine, Bruno Robert reports a relationship with Eloquant Nanoimaging that includes: board membership, employment, and equity or stocks. Bruno Robert, Andrew Gall, Dmitrij FROLOV has patent #Imaging method, and system, for obtaining a super-resolution image of an object (US10527837B2) issued to Centre National de la Recherche Scientifique CNRS Commissariat a lEnergie Atomique et aux Energies Alternatives CEA. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

We have demonstrated high-speed, super-resolution infrared (IR) spectroscopy and chemical imaging of autofluorescent biomaterials and organisms using camera-based widefield photothermal detection that takes advantage of temperature-dependent modulations of autofluorescent emission. A variety of biological materials and photosynthetic organisms exhibit strong autofluorescence emission under ultraviolet excitation and the autofluorescent emission has a very strong temperature dependence, of order 1%/K. Illuminating a sample with pulses of IR light from a wavelength-tunable laser source causes periodic localized sample temperature increases that result in a corresponding transient decrease in autofluorescent emission. A low-cost light-emitting diode-based fluorescence excitation source was used in combination with a conventional fluorescence microscopy camera to detect localized variations in autofluorescent emission over a wide area as an indicator of localized IR absorption. IR absorption image stacks were acquired over a range of IR wavelengths, including the fingerprint spectral range, enabling extraction of localized IR absorption spectra. We have applied widefield fluorescence detected photothermal IR (FL-PTIR) to an analysis of autofluorescent biological materials including collagen, leaf tissue, and photosynthetic organisms including diatoms and green microalgae cells. We have also demonstrated the FL-PTIR on live microalgae in water, demonstrating the potential for label-free dynamic chemical imaging of autofluorescent cells., Competing Interests: Declaration of Conflicting InterestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: CP, DG, KK, and AS are employees and/or shareholders of Photothermal Spectroscopy Corp., a company that sells O-PTIR instrumentation including the instrument used for this study. Other authors declare no conflicts.

The analysis of membrane vesicles at the nanoscale level is crucial for advancing the understanding of intercellular communication and its implications for health and disease. Despite their significance, the nanoscale analysis of vesicles at the single particle level faces challenges owing to their small size and the complexity of biological fluids. This new vesicle analysis tool leverages the single-molecule sensitivity of super-resolution microscopy (SRM) and the high-throughput analysis capability of deep-learning algorithms. By comparing classical clustering methods (k-means, DBSCAN, and SR-Tesseler) with deep-learning-based approaches (YOLO, DETR, Deformable DETR, and Faster R-CNN) for the analysis of super-resolution fluorescence images of exosomes, we identified the deep-learning algorithm, Deformable DETR, as the most effective. It showed superior accuracy and a reduced processing time for detecting individual vesicles from SRM images. Our findings demonstrate that image-based deep-learning-enhanced methods from SRM images significantly outperform traditional coordinate-based clustering techniques in identifying individual vesicles and resolving the challenges related to misidentification and computational demands. Moreover, the application of the combined Deformable DETR and ConvNeXt-S algorithms to differently labeled exosomes revealed its capability to differentiate between them, indicating its potential to dissect the heterogeneity of vesicle populations. This breakthrough in vesicle analysis suggests a paradigm shift towards the integration of AI into super-resolution imaging, which is promising for unlocking new frontiers in vesicle biology, disease diagnostics, and the development of vesicle-based therapeutics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Single-molecule localisation microscopy (SMLM) has the potential to reveal the underlying organisation of specific molecules within supramolecular complexes and their conformations, which is not possible with conventional microscope resolution. However, the detection efficiency for fluorescent molecules in cells can be limited in SMLM, even to below 1% in thick and dense samples. Segmentation of individual complexes can also be challenging. To overcome these problems, we have developed a software package termed PERPL: Pattern Extraction from Relative Positions of Localisations. This software assesses the relative likelihoods of models for underlying patterns behind incomplete SMLM data, based on the relative positions of pairs of localisations. We review its principles and demonstrate its use on the 3D lattice of Z-disk proteins in mammalian cardiomyocytes. We find known and novel features at ~20 nm with localisations of less than 1% of the target proteins, using mEos fluorescent protein constructs., (© 2023 The Author(s). Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.)

Correlative super-resolution microscopy has the potential to accurately visualize and validate new biological structures past the diffraction limit. However, combining different super-resolution modalities, such as deterministic stimulated emission depletion (STED) and stochastic single-molecule localization microscopy (SMLM), is a challenging endeavour. For correlative STED and SMLM, the following poses a significant challenge: (1) the photobleaching of the fluorophores in STED; (2) the subsequent reactivation of the fluorophores for SMLM and (3) finding the right fluorochrome and imaging buffer for both imaging modalities. Here, we highlight how the deep ultraviolet (DBUE) wavelengths of the Mercury (Hg) arc lamp can help recover STED bleaching and allow for the reactivation of single molecules for SMLM imaging. We also show that Alexa Fluor 594 and the commercially available Prolong Diamond to be excellent fluorophores and imaging media for correlative STED and SMLM., (© 2023 The Author(s). Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.)

In 2015, we reported primed conversion, a novel way to convert green-to-red photoconvertible fluorescent proteins, which emerges as a powerful tool for precision optical imaging. Primed conversion uses the intercept of blue and red-to-far-red light instead of traditional violet or near-UV light illumination which offers a series of advantages. Here, we review the fundamental principles and applications of primed conversion with a focus on its use in single-cell labelling and lineage tracing. We provide a historical perspective of lineage tracing techniques, thereby covering basic principles of fluorescence, photoconvertible fluorescent proteins, and eventually primed conversion. We then present the molecular requirements for primed conversion to take place and showcase how it can be used for dual-colour high-fidelity lineage tracing. Further, we discuss potential future developments of the primed conversion imaging toolkit that can benefit the study of both development and disease progression., (© 2023 The Author(s). Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.)

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., Competing Interests: Competing interests statement:The authors declare no competing interest.

Fluorescence lifetime imaging microscopy (FLIM) provides quantitative readouts of biochemical microenvironments, holding great promise for biomedical imaging. However, conventional FLIM relies on slow photon counting routines to accumulate sufficient photon statistics, restricting acquisition speeds. Here we demonstrate SparseFLIM, an intelligent paradigm for achieving high-fidelity FLIM reconstruction from sparse photon measurements. We develop a coupled bidirectional propagation network that enriches photon counts and recovers hidden spatial-temporal information. Quantitative analysis shows over tenfold photon enrichment, dramatically improving signal-to-noise ratio, lifetime accuracy, and correlation compared to the original sparse data. SparseFLIM enables reconstructing spatially and temporally undersampled FLIM at full resolution and channel count. The model exhibits strong generalization across experimental modalities including multispectral FLIM and in vivo endoscopic FLIM. This work establishes deep learning as a promising approach to enhance fluorescence lifetime imaging and transcend limitations imposed by the inherent codependence between measurement duration and information content., (© 2024. The Author(s).)

Droplet digital PCR (ddPCR) is recognized as a high-precision method for nucleic acid quantification, extensively utilized in biomedical research and clinical diagnostics. This technique employs microfluidic technology to partition the nucleic acid-containing reaction mixture into discrete droplets for amplification, achieving absolute quantification by identifying and enumerating the number of fluorescent droplets. The accuracy of droplet quantification is pivotal to the success of the assay. However, current image-processing tools are operationally complex, and commercial instruments are costly. Moreover, the designed algorithms exhibit a need for enhanced accuracy and are often restricted to use by trained personnel with specific microscopy equipment. In response to these challenges, we introduce an automated device (A-MMD), capable of detecting fluorescent droplets in ddPCR images captured by multiple microscopes. The device integrates three distinct algorithms tailored for the image processing of Laser Scanning Confocal Microscopy (LSCM), inverted microscopy, and self-assembled microscopy. Experimental validation using λ DNA demonstrated a 100.00% identification rate for positive droplets across all three image types, and the average identification rates for total droplets being 99.27% for LSCM, 98.96% for inverted microscopy, and 99.08% for self-assembled microscopy. Furthermore, the A-MMD is equipped with a user-friendly interface (UI) that streamlines the operational process, enabling non-specialists to efficiently perform droplet detection tasks. Our device not only has good environmental adaptability and identification accuracy, but also significantly reduces costs and operational complexity. It offers an economical, efficient, and user-friendly solution for ddPCR image analysis, thereby further propelling the advancement and application of nucleic acid detection technology.

Single-molecule Förster Resonance Energy Transfer (smFRET) excels in studying dynamic biomolecules by allowing precise observation of their conformational changes over time. To monitor RNA dynamics with smFRET, we developed a method to covalently label RNAs at their termini with a FRET pair of fluorophores. This direct end-labeling strategy targets the 5'-phosphate by carbodiimide (EDC)/N-hydroxysuccinimide (NHS) activation and the 3'-ribose by periodate oxidation, which can be adapted to other RNAs regardless of their size and sequence to study them independently of artificial modifications. Furthermore, the 5'-EDC/NHS activation is of general interest to all nucleic acids with a 5'-phosphate. The use of commercially available chemicals eliminates the need to synthesize RNA-specific probes. Total Internal Reflection Fluorescence (TIRF) microscopy requires the surface-immobilized molecules of interest to be within the evanescent field to be illuminated. A sophisticated way of keeping the RNA molecules within the evanescent field is to encapsulate them in phospholipid vesicles. Encapsulation benefits from the best of both worlds, tethering the molecule to the surface while enabling free diffusion of the molecule. We ensure that each vesicle contains only a single RNA molecule, enabling single-molecule imaging. Upon dual-end labeling and encapsulation of the RNA of interest, smFRET measurements offer a dynamic and detailed view of RNA behavior.

Fluorescence lifetime imaging microscopy is sensitive to molecular interactions and environments. In homo-dyne frequency-domain fluorescence lifetime imaging microscopy, images of fluorescence objects are acquired at different phase settings of the detector. The detected intensity as a function of detector phase is a sinusoidal function that is sensitive to the lifetime of the fluorescent species. In this paper, the theory of phase-sensitive fluorescence image correlation spectroscopy is described. In this version of lifetime imaging, image correlation spectroscopy analysis (i.e., spatial autocorrelation) is applied to successive fluorescence images acquired at different phase settings of the detector. Simulations of different types of lifetime distributions reveal that the phase-dependent density of fluorescent objects is dependent on the heterogeneity of lifetimes present in the objects. We provide an example of this analysis workflow to a cervical cancer cell stained with a fluorescent membrane probe.

Serum amyloid A (SAA) is one of the most important precursor amyloid proteins discovered during the study of amyloidosis, but its underlying aggregation mechanism has not yet been well elucidated. Since SAA aggregation is a key step in the pathogenesis of AA amyloidosis, amyloid inhibitors can be used as a tool to study its pathogenesis. Previously, we reported a novel microliter-scale high-throughput screening (MSHTS) system for screening amyloid β (Aβ) aggregation inhibitors based on quantum dot (QD) fluorescence imaging technology. In this study, we report the aggregation of human SAA (hSAA) in phosphate-buffered saline, in which we successfully visualized hSAA aggregation by QD using fluorescence microscopy and confocal microscopy. Two-dimensional and three-dimensional image analyses showed that most aggregations were observed at 40 μM hSAA, which was the optimal aggregation concentration in vitro. The accuracy of this finding was verified by a Thioflavin T assay. The transmission electron microscopy results showed that QD uniformly bound to hSAA aggregation. hSAA aggregation inhibitory activity was also evaluated by rosmarinic acid (RA). The results showed that RA, which is a compound with high inhibitory activity against Aβ aggregation, also exhibited high inhibitory activity against 40 μM hSAA. These results indicate that the MSHTS system is an effective tool for visualizing hSAA aggregation and for screening highly active inhibitors.

Expansion Microscopy (ExM) is an innovative and cost-effective super-resolution microscopy technique that has become popular in cell biology research. It achieves super-resolution by physically expanding specimens. Since its introduction, ExM has undergone continuous methodological developments to enhance its resolution and labeling capabilities. However, ExM imaging often encounters sample drift during image acquisition due to the physical movement of the expanded hydrogel, posing a significant challenge for accurate image reconstruction. Despite many proposed experimental solutions to mitigate sample drift, a universal solution has yet to be established. In response to this challenge, we developed 3D-Aligner, an advanced and user-friendly image analysis tool designed to computationally correct drift in ExM images for precise three-dimensional image reconstruction and downstream quantification. We demonstrate that 3D-Aligner effectively determines and corrects drift in ExM images with different expansion rates and various fluorescently labeled biological targets, showcasing its capabilities and robustness in drift correction. Additionally, we validate the precision of 3D-Aligner by comparing drift values across different labeled targets and highlight the importance of drift correction in quantification of biological structures., (© 2024. The Author(s).)

Ever since Robert Hooke's 17th century discovery of the cell using a humble compound microscope, light-matter interactions have continuously redefined our understanding of cell biology. Fluorescence microscopy has been particularly transformative and remains an indispensable tool for many cell biologists. The subcellular localization of biomolecules is now routinely visualized simply by manipulating the wavelength of light. Fluorescence polarization microscopy (FPM) extends these capabilities by exploiting another optical property - polarization - allowing researchers to measure not only the location of molecules, but also their organization or alignment within larger cellular structures. With only minor modifications to an existing fluorescence microscope, FPM can reveal the nanoscale architecture, orientational dynamics, conformational changes and interactions of fluorescently labeled molecules in their native cellular environments. Importantly, FPM excels at imaging systems that are challenging to study through traditional structural approaches, such as membranes, membrane proteins, cytoskeletal networks and large macromolecular complexes. In this Review, we discuss key discoveries enabled by FPM, compare and contrast the most common optical setups for FPM, and provide a theoretical and practical framework for researchers to apply this technique to their own research questions., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Nonmuscle myosin II (NMII) generates cytoskeletal forces that drive cell division, embryogenesis, muscle contraction and many other cellular functions. However, at present there is no method that can directly measure the forces generated by myosins in living cells. Here, we describe a Förster resonance energy transfer (FRET)-based tension sensor that can detect myosin-associated force along the filamentous actin network. Fluorescence lifetime imaging microscopy (FLIM)-FRET measurements indicate that the forces generated by NMII isoform B (NMIIB) exhibit significant spatial and temporal heterogeneity as a function of donor lifetime and fluorophore energy exchange. These measurements provide a proxy for inferred forces that vary widely along the actin cytoskeleton. This initial report highlights the potential utility of myosin-based tension sensors in elucidating the roles of cytoskeletal contractility in a wide variety of contexts., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Unambiguous targeting of cellular structures for in situ cryo-electron microscopy in the heterogeneous, dense and compacted environment of the cytoplasm remains challenging. Here, we have developed a cryogenic correlative light and electron microscopy (cryo-CLEM) workflow that utilizes thin cells grown on a mechanically defined substratum for rapid analysis of organelles and macromolecular complexes by cryo-electron tomography (cryo-ET). We coupled these advancements with optogenetics to redistribute perinuclear-localised organelles to the cell periphery, allowing visualisation of organelles that would otherwise be positioned in cellular regions too thick for cryo-ET. This reliable and robust workflow allows for fast in situ analyses without the requirement for cryo-focused ion beam milling. Using this protocol, cells can be frozen, imaged by cryo-fluorescence microscopy and be ready for batch cryo-ET within a day., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Fluorescence microscopy, which employs fluorescent tags to label and observe cellular structures and their dynamics, is a powerful tool for life sciences. However, due to the spectral overlap between different dyes, a limited number of structures can be separately labeled and imaged for live-cell applications. In addition, the conventional sequential channel imaging procedure is quite time consuming, as it needs to switch either different lasers or filters. Here, we propose a novel double-structure network (DBSN) that consists of multiple connected models, which can extract six distinct subcellular structures from three raw images with only two separate fluorescent labels. DBSN combines the intensity-balance model to compensate for uneven fluorescent labels for different structures and the structure-separation model to extract multiple different structures with the same fluorescent labels. Therefore, DBSN breaks the bottleneck of the existing technologies and holds immense potential applications in the field of cell biology., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Exocytosis is a dynamic physiological process that enables the release of biomolecules to the surrounding environment via the fusion of membrane compartments to the plasma membrane. Understanding its mechanisms is crucial, as defects can compromise essential biological functions. The development of pH-sensitive optical reporters alongside fluorescence microscopy enables the assessment of individual vesicle exocytosis events at the cellular level. Manual annotation represents, however, a time-consuming task that is prone to selection biases and human operational errors. Here, we introduce ExoJ, an automated plugin based on Fiji/ImageJ2 software. ExoJ identifies user-defined genuine populations of exocytosis events, recording quantitative features including intensity, apparent size and duration. We designed ExoJ to be fully user-configurable, making it suitable for studying distinct forms of vesicle exocytosis regardless of the imaging quality. Our plugin demonstrates its capabilities by showcasing distinct exocytic dynamics among tetraspanins and vesicular SNARE protein reporters. Assessment of performance on synthetic data shows that ExoJ is a robust tool that is capable of correctly identifying exocytosis events independently of signal-to-noise ratio conditions. We propose ExoJ as a standard solution for future comparative and quantitative studies of exocytosis., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Optical investigations of nanometer distances between proteins, their subunits, or other biomolecules have been the exclusive prerogative of Förster resonance energy transfer (FRET) microscopy for decades. In this work, we show that MINFLUX fluorescence nanoscopy measures intramolecular distances down to 1 nanometer-and in planar projections down to 1 angstrom-directly, linearly, and with angstrom precision. Our method was validated by quantifying well-characterized 1- to 10-nanometer distances in polypeptides and proteins. Moreover, we visualized the orientations of immunoglobulin subunits, applied the method in human cells, and revealed specific configurations of a histidine kinase PAS domain dimer. Our results open the door for examining proximities and interactions by direct position measurements at the intramacromolecular scale.

Fluorescence microscopy has long been a transformative technique in biological sciences. Nevertheless, most implementations are limited to a few targets, which have been revealed using primary antibodies and fluorescently conjugated secondary antibodies. Super-resolution techniques such as Exchange-PAINT and, more recently, SUM-PAINT have increased multiplexing capabilities, but they require specialized equipment, software, and knowledge. To enable multiplexing for any imaging technique in any laboratory, we developed NanoPlex, a streamlined method based on conventional antibodies revealed by engineered secondary nanobodies that allow the selective removal of fluorescence signals. We develop three complementary signal removal strategies: OptoPlex (light-induced), EnzyPlex (enzymatic), and ChemiPlex (chemical). We showcase NanoPlex reaching 21 targets for 3D confocal analyses and 5-8 targets for dSTORM and STED super-resolution imaging. NanoPlex has the potential to revolutionize multi-target fluorescent imaging methods, potentially redefining the multiplexing capabilities of antibody-based assays., (© 2024. The Author(s).)

Cyclic fluorescence microscopy enables multiple targets to be detected simultaneously. This, in turn, has deepened our understanding of tissue composition, cell-to-cell interactions, and cell signaling. Unfortunately, analysis of these datasets can be time-prohibitive due to the sheer volume of data. In this paper, we present CycloNET, a computational pipeline tailored for analyzing raw fluorescent images obtained through cyclic immunofluorescence. The automated pipeline pre-processes raw image files, quickly corrects for translation errors between imaging cycles, and leverages a pre-trained neural network to segment individual cells and generate single-cell molecular profiles. We applied CycloNET to a dataset of 22 human samples from head and neck squamous cell carcinoma patients and trained a neural network to segment immune cells. CycloNET efficiently processed a large-scale dataset (17 fields of view per cycle and 13 staining cycles per specimen) in 10 min, delivering insights at the single-cell resolution and facilitating the identification of rare immune cell clusters. We expect that this rapid pipeline will serve as a powerful tool to understand complex biological systems at the cellular level, with the potential to facilitate breakthroughs in areas such as developmental biology, disease pathology, and personalized medicine., (© 2024. The Author(s).)

Deciphering the dynamic mechanism of ferroptosis can provide insights into pathogenesis, which is valuable for disease diagnosis and treatment. However, due to the lack of suitable time-resolved mechanosensitive tools, researchers have been unable to determine the membrane tension and morphology of the plasma membrane and the nuclear envelope during ferroptosis. With this research, we propose a rational strategy to develop robust mechanosensitive fluorescence lifetime probes which can facilitate simultaneous fluorescence lifetime imaging of the plasma membrane and nuclear envelope. Fluorescence lifetime imaging microscopy using the unique mechanosensitive probes reveal a dynamic mechanism for ferroptosis: The membrane tension of both the plasma membrane and the nuclear envelope decreases during ferroptosis, and the nuclear envelope exhibits budding during the advanced stage of ferroptosis. Significantly, the membrane tension of the plasma membrane is always larger than that of the nuclear envelope, and the membrane tension of the nuclear envelope is slightly larger than that of the nuclear membrane bubble. Meanwhile, the membrane lesions are repaired in the low-tension regions through exocytosis., Competing Interests: Competing interests statement:The authors declare no competing interest.

Patterns of lineal descent play a critical role in the development of metazoan embryos. In eutelic organisms that generate a fixed number of somatic cells, invariance in the topology of their cell lineage provides a powerful opportunity to interrogate developmental events with empirical repeatability across individuals. Studies of embryonic development using the nematode Caenorhabditis elegans have been drivers of discovery. These studies have depended heavily on high-throughput lineage tracing enabled by 4D fluorescence microscopy and robust computer vision pipelines. For a range of applications, computer-aided yet manual lineage tracing using 4D label-free microscopy remains an essential tool. Deep learning approaches to cell detection and tracking in fluorescence microscopy have advanced significantly in recent years, yet solutions for automating cell detection and tracking in 3D label-free imaging of dense tissues and embryos remain inaccessible. Here, we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time-lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance, and generalizes well to images acquired in multiple labs on multiple instruments. We characterize embGAN's performance using lineage tracing in the C. elegans embryo as a benchmark. embGAN achieves near-state-of-the-art performance in cell detection and tracking, enabling high-throughput studies of cell lineage without the need for fluorescent reporters or transgenics., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)

Super-resolution (SR) microscopy provides a revolutionary optical imaging approach by breaking the diffraction limit of light, while the commonly required special instrumentation with complex optical setup hampers its popularity. Here, we present a scanning switch-off microscopy (SSM) concept that exploits the omnipresent switch-off response of fluorophores to enable super-resolution imaging using a commercial confocal microscope. We validated the SSM model with theoretical calculations and experiments. An imaging resolution of ∼100 nm was obtained for DNA origami nanostructures and cellular cytoskeletons using fluorescent labels of Alexa 405, Alexa 488, Cy3, and Atto 488. Notably, super-resolution imaging of live cells was realized with SSM, by employing a dronpa fluorescent protein as the fluorescent label. In principle, this SSM method can be applied to any excitation laser scanning-based microscope.

Immunofluorescence analysis of individual extracellular vesicles (EVs) in common fluorescence microscopes is gaining popularity due to its accessibility and high fluorescence sensitivity; however, EV number and size are only measurable using fluorescent stains requiring extensive sample manipulations. Here we introduce highly sensitive label-free EV size photometry (SP) based on interferometric scattering (iSCAT) imaging of immersed EVs immobilized on a glass coverslip. We implement SP on a common inverted epifluorescence microscope with LED illumination and a simple 50:50 beamsplitter, permitting seamless integration of SP with fluorescence imaging (SPFI). We present a high-throughput SPFI workflow recording >10,000 EVs in 7 min over ten 88 × 88 µm 2 fields of view, pre- and post-incubation imaging to suppress background, along with automated image alignment, aberration correction, spot detection and EV sizing. We achieve an EV sizing range from 37 to ∼220 nm in diameter with a dual 440 and 740 nm SP illumination scheme, and suggest that this range can be extended by more advanced image analysis or additional hardware customization. We benchmark SP to flow cytometry using calibrated silica nanoparticles and demonstrate superior, label-free sensitivity. We showcase SPFI's potential for EV analysis by experimentally distinguishing surface and volumetric EV dyes, observing the deformation of EVs adsorbed to a surface, and by uncovering distinct subpopulations in <100 nm-in-diameter EVs with fluorescently tagged membrane proteins., (© 2024 The Author(s). Journal of Extracellular Vesicles published by Wiley Periodicals LLC on behalf of International Society for Extracellular Vesicles.)

Current methods for single-molecule orientation localization microscopy (SMOLM) require optical setups and algorithms that can be prohibitively slow and complex, limiting widespread adoption for biological applications. We present POLCAM, a simplified SMOLM method based on polarized detection using a polarization camera, which can be easily implemented on any wide-field fluorescence microscope. To make polarization cameras compatible with single-molecule detection, we developed theory to minimize field-of-view errors, used simulations to optimize experimental design and developed a fast algorithm based on Stokes parameter estimation that can operate over 1,000-fold faster than the state of the art, enabling near-instant determination of molecular anisotropy. To aid in the adoption of POLCAM, we developed open-source image analysis software and a website detailing hardware installation and software use. To illustrate the potential of POLCAM in the life sciences, we applied our method to study α-synuclein fibrils, the actin cytoskeleton of mammalian cells, fibroblast-like cells and the plasma membrane of live human T cells., (© 2024. The Author(s).)

Significance: Autofluorescence characteristics of the reduced nicotinamide adenine dinucleotide and oxidized flavin cofactors are important for the evaluation of the metabolic status of the cells. The approaches that involve a detailed analysis of both spectral and time characteristics of the autofluorescence signals may provide additional insights into the biochemical processes in the cells and biological tissues and facilitate the transition of spectral fluorescence lifetime imaging into clinical applications., Aim: We present the experiments on multispectral fluorescence lifetime imaging with a detailed analysis of the fluorescence decays and spectral profiles of the reduced nicotinamide adenine dinucleotide and oxidized flavin under a single excitation wavelength aimed at understanding whether the use of multispectral detection is helpful for metabolic imaging of cancer cells., Approach: We use two-photon spectral fluorescence lifetime imaging microscopy. Starting from model solutions, we switched to cell cultures treated by metabolic inhibitors and then studied the metabolism of cells within tumor spheroids., Results: The use of a multispectral detector in combination with an excitation at a single wavelength of 750 nm allows the identification of fluorescence signals from three components: free and bound NAD(P)H, and flavins based on the global fitting procedure. Multispectral data make it possible to assess not only the lifetime but also the spectral shifts of emission of flavins caused by chemical perturbations. Altogether, the informative parameters of the developed approach are the ratio of free and bound NAD(P)H amplitudes, the decay time of bound NAD(P)H, the amplitude of flavin fluorescence signal, the fluorescence decay time of flavins, and the spectral shift of the emission signal of flavins. Hence, with multispectral fluorescence lifetime imaging, we get five independent parameters, of which three are related to flavins., Conclusions: The approach to probe the metabolic state of cells in culture and spheroids using excitation at a single wavelength of 750 nm and a fluorescence time-resolved spectral detection with the consequent global analysis of the data not only simplifies image acquisition protocol but also allows to disentangle the impacts of free and bound NAD(P)H, and flavin components evaluate changes in their fluorescence parameters (emission spectra and fluorescence lifetime) upon treating cells with metabolic inhibitors and sense metabolic heterogeneity within 3D tumor spheroids., (© 2024 The Authors.)

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging technique that enables the visualization of biological samples at the molecular level by measuring the fluorescence decay rate of fluorescent probes. This provides critical information about molecular interactions, environmental changes, and localization within biological systems. However, creating high-resolution lifetime maps using conventional FLIM systems can be challenging, as it often requires extensive scanning that can significantly lengthen acquisition times. This issue is further compounded in three-dimensional (3D) imaging because it demands additional scanning along the depth axis. To tackle this challenge, we developed a computational imaging technique called light-field tomographic FLIM (LIFT-FLIM). Our approach allows for the acquisition of volumetric fluorescence lifetime images in a highly data-efficient manner, significantly reducing the number of scanning steps required compared to conventional point-scanning or line-scanning FLIM imagers. Moreover, LIFT-FLIM enables the measurement of high-dimensional data using low-dimensional detectors, which are typically low cost and feature a higher temporal bandwidth. We demonstrated LIFT-FLIM using a linear single-photon avalanche diode array on various biological systems, showcasing unparalleled single-photon detection sensitivity. Additionally, we expanded the functionality of our method to spectral FLIM and demonstrated its application in high-content multiplexed imaging of lung organoids. LIFT-FLIM has the potential to open up broad avenues in both basic and translational biomedical research., Competing Interests: Competing interests statement:Edoardo Charbon holds the position of Chief Scientific Officer at Fastree3D, a company that specializes in the manufacturing of LiDARs for the automotive market. Claudio Bruschini and Edoardo Charbon are also cofounders of Pi Imaging Technology. Additionally, Liang Gao has a financial interest in Lift Photonics, which commercializes the LIFT technology for FLIM applications. However, it is important to note that none of these companies were involved in the research presented in this paper. The authors disclose UCLA provisional patent filing. Research support was provided by the National Institutes of Health (R01HL165318 and RF1NS128488).

Genetically encoded fluorescent calcium indicators allow cellular-resolution recording of physiology. However, bright, genetically targetable indicators that can be multiplexed with existing tools in vivo are needed for simultaneous imaging of multiple signals. Here we describe WHaloCaMP, a modular chemigenetic calcium indicator built from bright dye-ligands and protein sensor domains. Fluorescence change in WHaloCaMP results from reversible quenching of the bound dye via a strategically placed tryptophan. WHaloCaMP is compatible with rhodamine dye-ligands that fluoresce from green to near-infrared, including several that efficiently label the brain in animals. When bound to a near-infrared dye-ligand, WHaloCaMP shows a 7× increase in fluorescence intensity and a 2.1-ns increase in fluorescence lifetime upon calcium binding. We use WHaloCaMP1a to image Ca 2+ responses in vivo in flies and mice, to perform three-color multiplexed functional imaging of hundreds of neurons and astrocytes in zebrafish larvae and to quantify Ca 2+ concentration using fluorescence lifetime imaging microscopy (FLIM)., (© 2024. The Author(s).)

Lipid droplets (LDs) are organelles associated with lipid storage and energy metabolism, thus, their morphology and quantity are of significant research interest. While commercially available BODIPY dye effectively labels LDs in various cell types, it also labels lysosome-related organelles (LROs) in C. elegans, leading to non-specific LD quantification. Here, we report that the fluorescent signals of BODIPY exhibit distinct fluorescence lifetime patterns for LROs and LDs, which can be captured, visualized, and filtered by fluorescence lifetime imaging microscopy. Furthermore, we proposed and validated a method based on fluorescence lifetime that can improve the accuracy of fat storage quantification in BODIPY vital-staining worms, which holds broad applications, including rapid and accurate LD quantification in forward genetic screening. Additionally, our method enables observing dynamic LD-LRO interactions in living worms, a unique capability of BODIPY vital staining. Our findings highlight distinct BODIPY fluorescence lifetime characteristics of LDs and LROs, providing a valuable tool for future research on LDs, LROs, or their interactions., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Motivation: Intracellular organelle networks (IONs) such as the endoplasmic reticulum (ER) network and the mitochondrial (MITO) network serve crucial physiological functions. The morphology of these networks plays a critical role in mediating their functions. Accurate image segmentation is required for analyzing the morphology and topology of these networks for applications such as molecular mechanism analysis and drug target screening. So far, however, progress has been hindered by their structural complexity and density., Results: In this study, we first establish a rigorous performance baseline for accurate segmentation of these organelle networks from fluorescence microscopy images by optimizing a baseline U-Net model. We then develop the multi-resolution encoder (MRE) and the hierarchical fusion loss (Lhf) based on two inductive components, namely low-level features and topological self-similarity, to assist the model in better adapting to the task of segmenting IONs. Empowered by MRE and Lhf, both U-Net and Pyramid Vision Transformer (PVT) outperform competing state-of-the-art models such as U-Net++, HR-Net, nnU-Net, and TransUNet on custom datasets of the ER network and the MITO network, as well as on public datasets of another biological network, the retinal blood vessel network. In addition, integrating MRE and Lhf with models such as HR-Net and TransUNet also enhances their segmentation performance. These experimental results confirm the generalization capability and potential of our approach. Furthermore, accurate segmentation of the ER network enables analysis that provides novel insights into its dynamic morphological and topological properties., Availability and Implementation: Code and data are openly accessible at https://github.com/cbmi-group/MRE., (© The Author(s) 2024. Published by Oxford University Press.)

Every collected photon is precious in live-cell super-resolution (SR) microscopy. Here, we describe a data-efficient, deep learning-based denoising solution to improve diverse SR imaging modalities. The method, SN2N, is a Self-inspired Noise2Noise module with self-supervised data generation and self-constrained learning process. SN2N is fully competitive with supervised learning methods and circumvents the need for large training set and clean ground truth, requiring only a single noisy frame for training. We show that SN2N improves photon efficiency by one-to-two orders of magnitude and is compatible with multiple imaging modalities for volumetric, multicolor, time-lapse SR microscopy. We further integrated SN2N into different SR reconstruction algorithms to effectively mitigate image artifacts. We anticipate SN2N will enable improved live-SR imaging and inspire further advances., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Single-molecule localization microscopy (SMLM) has gained widespread use for visualizing the morphology of subcellular organelles and structures with nanoscale spatial resolution. However, analysis tools for automatically quantifying and classifying SMLM images have lagged behind. Here we introduce Enhanced Classification of Localized Point clouds by Shape Extraction (ECLiPSE), an automated machine learning analysis pipeline specifically designed to classify cellular structures captured through two-dimensional or three-dimensional SMLM. ECLiPSE leverages a comprehensive set of shape descriptors, the majority of which are directly extracted from the localizations to minimize bias during the characterization of individual structures. ECLiPSE has been validated using both unsupervised and supervised classification on datasets, including various cellular structures, achieving near-perfect accuracy. We apply two-dimensional ECLiPSE to classify morphologically distinct protein aggregates relevant for neurodegenerative diseases. Additionally, we employ three-dimensional ECLiPSE to identify relevant biological differences between healthy and depolarized mitochondria. ECLiPSE will enhance the way we study cellular structures across various biological contexts., (© 2024. The Author(s).)

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., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Metastasis driven by cancer cell migration is the leading cause of cancer-related deaths. It involves significant changes in the organization of the cytoskeleton, which includes the actin microfilaments and the vimentin intermediate filaments. Understanding how these filament change cells from normal to invasive offers insights that can be used to improve cancer diagnosis and therapy. We have developed a computational, transparent, large-scale and imaging-based pipeline, that can distinguish between normal human cells and their isogenically matched, oncogenically transformed, invasive and metastasizing counterparts, based on the spatial organization of actin and vimentin filaments in the cell cytoplasm. Due to the intricacy of these subcellular structures, manual annotation is not trivial to automate. We used established deep learning methods and our new multi-attention channel architecture. To ensure a high level of interpretability of the network, which is crucial for the application area, we developed an interpretable global explainable approach correlating the weighted geometric mean of the total cell images and their local GradCam scores. The methods offer detailed, objective and measurable understanding of how different components of the cytoskeleton contribute to metastasis, insights that can be used for future development of novel diagnostic tools, such as a nanometer level, vimentin filament-based biomarker for digital pathology, and for new treatments that significantly can increase patient survival., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024. Published by Elsevier Ltd. All rights reserved.)

There is interest in studying microbes that colonize maize silks (style tissue, critical for reproduction) including the fungal pathogen Fusarium graminearum (Fg) and its interactions with the microbiome and biocontrol agents. In planta imaging of these interactions on living silks using confocal fluorescence microscopy would provide key insights. However, newly discovered microbes have unknown effects on human health, and there are regulatory requirements to prevent the release of fluorescently tagged microbes into the environment. Therefore, the microbe infection, colonization, and interaction stages on silks prior to microscopy must be contained. At the same time, silk viability must be maintained and experiments conducted that are biologically relevant (e.g. silks should remain attached to the cob), yet the silk tissue must be accessible to the researcher (i.e. not within husk leaves) and allow for multiple replicates. Here we present methods that meet these five contrasting criteria. We tested these methods using Fg and four silk-derived bacterial endophytes. The endophytes were previously known to have anti-Fg activity in vitro, but in planta observations were lacking. In Method 1, a portion of the tip of a cob was dissected, and silks remained attached to the cob in a Petri dish. The cob was placed on a water agar disc to maintain hydration. DsRed-tagged bacteria and GFP-tagged Fg were inoculated onto the silks and incubated, allowing the two microbes to grow towards one another before staining with propidium iodide for confocal microscopy. A variation of the protocol was presented in Method 2, where detached silk segments were placed directly on water agar where they were inoculated with bacteria and Fg to promote dense colonization, and to allow for many replicates and interventions such as silk wounding. The bacterial endophytes were successfully observed colonizing Fg hyphae, silk trichomes, and entering silks via cut ends and wounds. These protocols can be used to study other silk-associated microbes including several globally important fungal pathogens that enter maize grain through silks., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Expansion Microscopy (ExM) and Light-Sheet Fluorescence Microscopy (LSFM) are forefront imaging techniques that enable high-resolution visualization of biological specimens. ExM enhances nanoscale investigation using conventional fluorescence microscopes, while LSFM offers rapid, minimally invasive imaging over large volumes. This review explores the joint advancements of ExM and LSFM, focusing on the excellent performance of the integrated modality obtained from the combination of the two, which is refer to as ExLSFM. In doing so, the chemical processes required for ExM, the tailored optical setup of LSFM for examining expanded samples, and the adjustments in sample preparation for accurate data collection are emphasized. It is delve into various specimen types studied using this integrated method and assess its potential for future applications. The goal of this literature review is to enrich the comprehension of ExM and LSFM, encouraging their wider use and ongoing development, looking forward to the upcoming challenges, and anticipating innovations in these imaging techniques., (© 2024 The Author(s). Small Methods published by Wiley‐VCH GmbH.)