Volume scanning electron microscopy for imaging biological ultrastructure

The advent of preventive high-resolution structural histopathology by artificial-intelligence-powered cryogenic electron tomography

Advances in cryogenic electron microscopy (cryoEM) single particle analysis have revolutionized structural biology by facilitating the in vitro determination of atomic- and near-atomic-resolution structures for fully hydrated macromolecular complexes exhibiting compositional and conformational heterogeneity across a wide range of sizes. Cryogenic electron tomography (cryoET) and subtomogram averaging are rapidly progressing toward delivering similar insights for macromolecular complexes in situ, without requiring tags or harsh biochemical purification. Furthermore, cryoET enables the visualization of cellular and tissue phenotypes directly at molecular, nanometric resolution without chemical fixation or staining artifacts. This forward-looking review covers recent developments in cryoEM/ET and related technologies such as cryogenic focused ion beam milling scanning electron microscopy and correlative light microscopy, increasingly enhanced and supported by artificial intelligence algorithms. Their potential application to emerging concepts is discussed, primarily the prospect of complementing medical histopathology analysis. Machine learning solutions are poised to address current challenges posed by "big data" in cryoET of tissues, cells, and macromolecules, offering the promise of enabling novel, quantitative insights into disease processes, which may translate into the clinic and lead to improved diagnostics and targeted therapeutics.

Zooming into lipid droplet biology through the lens of electron microscopy

Electron microscopy (EM), in its various flavors, has significantly contributed to our understanding of lipid droplets (LD) as central organelles in cellular metabolism. For example, EM has illuminated that LDs, in contrast to all other cellular organelles, are uniquely enclosed by a single phospholipid monolayer, revealed the architecture of LD contact sites with different organelles, and provided near-atomic resolution maps of key enzymes that regulate neutral lipid biosynthesis and LD biogenesis. In this review, we first provide a brief history of pivotal findings in LD biology unveiled through the lens of an electron microscope. We describe the main EM techniques used in the context of LD research and discuss their current capabilities and limitations, thereby providing a foundation for utilizing suitable EM methodology to address LD-related questions with sufficient level of structural preservation, detail, and resolution. Finally, we highlight examples where EM has recently been and is expected to be instrumental in expanding the frontiers of LD biology.

Unambiguous identification of asymmetric and symmetric synapses using volume electron microscopy

The brain contains thousands of millions of synapses, exhibiting diverse structural, molecular, and functional characteristics. However, synapses can be classified into two primary morphological types: Gray's type I and type II, corresponding to Colonnier's asymmetric (AS) and symmetric (SS) synapses, respectively. AS and SS have a thick and thin postsynaptic density, respectively. In the cerebral cortex, since most AS are excitatory (glutamatergic), and SS are inhibitory (GABAergic), determining the distribution, size, density, and proportion of the two major cortical types of synapses is critical, not only to better understand synaptic organization in terms of connectivity, but also from a functional perspective. However, several technical challenges complicate the study of synapses. Potassium ferrocyanide has been utilized in recent volume electron microscope studies to enhance electron density in cellular membranes. However, identifying synaptic junctions, especially SS, becomes more challenging as the postsynaptic densities become thinner with increasing concentrations of potassium ferrocyanide. Here we describe a protocol employing Focused Ion Beam Milling and Scanning Electron Microscopy for studying brain tissue. The focus is on the unequivocal identification of AS and SS types. To validate SS observed using this protocol as GABAergic, experiments with immunocytochemistry for the vesicular GABA transporter were conducted on fixed mouse brain tissue sections. This material was processed with different concentrations of potassium ferrocyanide, aiming to determine its optimal concentration. We demonstrate that using a low concentration of potassium ferrocyanide (0.1%) improves membrane visualization while allowing unequivocal identification of synapses as AS or SS.

The application and development of electron microscopy for three-dimensional reconstruction in life science: a review

Imaging technologies have played a pivotal role in advancing biological research by enabling visualization of biological structures and processes. While traditional electron microscopy (EM) produces two-dimensional images, emerging techniques now allow high-resolution three-dimensional (3D) characterization of specimens in situ, meeting growing needs in molecular and cellular biology. Combining transmission electron microscopy (TEM) with serial sectioning inaugurated 3D imaging, attracting biologists seeking to explore cell ultrastructure and driving advancement of 3D EM reconstruction. By comprehensively and precisely rendering internal structure and distribution, 3D TEM reconstruction provides unparalleled ultrastructural insights into cells and molecules, holding tremendous value for elucidating structure-function relationships and broadly propelling structural biology. Here, we first introduce the principle of 3D reconstruction of cells and tissues by classical approaches in TEM and then discuss modern technologies utilizing TEM and on new SEM-based as well as cryo-electron microscope (cryo-EM) techniques. 3D reconstruction techniques from serial sections, electron tomography (ET), and the recent single-particle analysis (SPA) are examined; the focused ion beam scanning electron microscopy (FIB-SEM), the serial block-face scanning electron microscopy (SBF-SEM), and automatic tape-collecting lathe ultramicrotome (ATUM-SEM) for 3D reconstruction of large volumes are discussed. Finally, we review the challenges and development prospects of these technologies in life science. It aims to provide an informative reference for biological researchers.

High-resolution 3D ultrastructural analysis of developing mouse neocortex reveals long slender processes of endothelial cells that enter neural cells

The development of the neocortex involves an interplay between neural cells and the vasculature. However, little is known about this interplay at the ultrastructural level. To gain a 3D insight into the ultrastructure of the developing neocortex, we have analyzed the embryonic mouse neocortex by serial block-face scanning electron microscopy (SBF-SEM). In this study, we report a first set of findings that focus on the interaction of blood vessels, notably endothelial tip cells (ETCs), and the neural cells in this tissue. A key observation was that the processes of ETCs, located either in the ventricular zone (VZ) or subventricular zone (SVZ)/intermediate zone (IZ), can enter, traverse the cytoplasm, and even exit via deep plasma membrane invaginations of the host cells, including apical progenitors (APs), basal progenitors (BPs), and newborn neurons. More than half of the ETC processes were found to enter the neural cells. Striking examples of this ETC process "invasion" were (i) protrusions of apical progenitors or newborn basal progenitors into the ventricular lumen that contained an ETC process inside and (ii) ETC process-containing protrusions of neurons that penetrated other neurons. Our observations reveal a - so far unknown - complexity of the ETC-neural cell interaction.

Correlative light-electron microscopy methods to characterize the ultrastructural features of the replicative and dormant liver stages of Plasmodium parasites

BACKGROUND

The infection of the liver by Plasmodium parasites is an obligatory step leading to malaria disease. Following hepatocyte invasion, parasites differentiate into replicative liver stage schizonts and, in the case of Plasmodium species causing relapsing malaria, into hypnozoites that can lie dormant for extended periods of time before activating. The liver stages of Plasmodium remain elusive because of technical challenges, including low infection rate. This has been hindering experimentations with well-established technologies, such as electron microscopy. A deeper understanding of hypnozoite biology could prove essential in the development of radical cure therapeutics against malaria.

RESULTS

The liver stages of the rodent parasite Plasmodium berghei, causing non-relapsing malaria, and the simian parasite Plasmodium cynomolgi, causing relapsing malaria, were characterized in human Huh7 cells or primary non-human primate hepatocytes using Correlative Light-Electron Microscopy (CLEM). Specifically, CLEM approaches that rely on GFP-expressing parasites (GFP-CLEM) or on an immunofluorescence assay (IFA-CLEM) were used for imaging liver stages. The results from P. berghei showed that host and parasite organelles can be identified and imaged at high resolution using both CLEM approaches. While IFA-CLEM was associated with more pronounced extraction of cellular content, samples' features were generally well preserved. Using IFA-CLEM, a collection of micrographs was acquired for P. cynomolgi liver stage schizonts and hypnozoites, demonstrating the potential of this approach for characterizing the liver stages of Plasmodium species causing relapsing malaria.

CONCLUSIONS

A CLEM approach that does not rely on parasites expressing genetically encoded tags was developed, therefore suitable for imaging the liver stages of Plasmodium species that lack established protocols to perform genetic engineering. This study also provides a dataset that characterizes the ultrastructural features of liver stage schizonts and hypnozoites from the simian parasite species P. cynomolgi.

Beyond the surface: Investigation of tumorsphere morphology using volume electron microscopy

The advent of volume electron microscopy (vEM) has provided unprecedented insights into cellular and subcellular organization, revolutionizing our understanding of cancer biology. This study presents a previously unexplored comparative analysis of the ultrastructural disparities between cancer cells cultured as monolayers and tumorspheres. By integrating a robust workflow that incorporates high-pressure freezing followed by freeze substitution (HPF/FS), serial block face scanning electron microscopy (SBF-SEM), manual and deep learning-based segmentation, and statistical analysis, we have successfully generated three-dimensional (3D) reconstructions of monolayer and tumorsphere cells, including their subcellular organelles. Our findings reveal a significant degree of variation in cellular morphology in tumorspheres. We observed the increased prevalence of nuclear envelope invaginations in tumorsphere cells compared to monolayers. Furthermore, we detected a diverse range of mitochondrial morphologies exclusively in tumorsphere cells, as well as intricate cellular interconnectivity within the tumorsphere architecture. These remarkable ultrastructural differences emphasize the use of tumorspheres as a superior model for cancer research due to their relevance to in vivo conditions. Our results strongly advocate for the utilization of tumorsphere cells in cancer research studies, enhancing the precision and relevance of experimental outcomes, and ultimately accelerating therapeutic advancements.

Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey

Electron microscopy (EM) enables high-resolution imaging of tissues and cells based on 2D and 3D imaging techniques. Due to the laborious and time-consuming nature of manual segmentation of large-scale EM datasets, automated segmentation approaches are crucial. This review focuses on the progress of deep learning-based segmentation techniques in large-scale cellular EM throughout the last six years, during which significant progress has been made in both semantic and instance segmentation. A detailed account is given for the key datasets that contributed to the proliferation of deep learning in 2D and 3D EM segmentation. The review covers supervised, unsupervised, and self-supervised learning methods and examines how these algorithms were adapted to the task of segmenting cellular and sub-cellular structures in EM images. The special challenges posed by such images, like heterogeneity and spatial complexity, and the network architectures that overcame some of them are described. Moreover, an overview of the evaluation measures used to benchmark EM datasets in various segmentation tasks is provided. Finally, an outlook of current trends and future prospects of EM segmentation is given, especially with large-scale models and unlabeled images to learn generic features across EM datasets.

Nanoemulsion-based piperine to enhance bioavailability for the treatment of LPS-induced depression-like behaviour in mice

In the present study, the objective was to encapsulate piperine in nanoform by solvent evaporation method and to investigate the antidepressant-like activity of nanopiperine in lipopolysaccharide (LPS) induced depression in mice. LPS-induced depression in mice was reversed by repeated treatment of nanopiperine at dosages of 5 and 10 mg/kg body weight for 14 days. After 24 h of LPS injection, the animals were exposed to a (TST) tail suspension test and (FST) forced swim test. A sequence of behaviours was measured on days 0, 7, and 14. On day 14, the animals were euthanized, and the blood was collected; biochemical analysis was performed for the measurement of inflammatory and oxidative stress markers. Within the same period, nanopiperine improved hippocampal progenitor cell proliferation and increased brain-derived neurotrophic factor (BDNF) levels in the hippocampus of mice subjected to LPS-induced stress. In addition, the neurotransmitter estimation by the HPLC method showed that nanopiperine increased the levels of neurotransmitters. In summary, the nanopiperine showed potent neuroprotective and antidepressant activity, and stability relating to the elevated level of hippocampal BDNF level and as compared to pure piperine, the nanopiperine showed better oral bioavailability and stability.

An intelligent workflow for sub-nanoscale 3D reconstruction of intact synapses from serial section electron tomography

BACKGROUND

As an extension of electron tomography (ET), serial section electron tomography (serial section ET) aims to align the tomographic images of multiple thick tissue sections together, to break through the volume limitation of the single section and preserve the sub-nanoscale voxel size. It could be applied to reconstruct the intact synapse, which expands about one micrometer and contains nanoscale vesicles. However, there are several drawbacks of the existing serial section ET methods. First, locating and imaging regions of interest (ROIs) in serial sections during the shooting process is time-consuming. Second, the alignment of ET volumes is difficult due to the missing information caused by section cutting and imaging. Here we report a workflow to simplify the acquisition of ROIs in serial sections, automatically align the volume of serial section ET, and semi-automatically reconstruct the target synaptic structure.

RESULTS

We propose an intelligent workflow to reconstruct the intact synapse with sub-nanometer voxel size. Our workflow includes rapid localization of ROIs in serial sections, automatic alignment, restoration, assembly of serial ET volumes, and semi-automatic target structure segmentation. For the localization and acquisition of ROIs in serial sections, we use affine transformations to calculate their approximate position based on their relative location in orderly placed sections. For the alignment of consecutive ET volumes with significantly distinct appearances, we use multi-scale image feature matching and the elastic with belief propagation (BP-Elastic) algorithm to align them from coarse to fine. For the restoration of the missing information in ET, we first estimate the number of lost images based on the pixel changes of adjacent volumes after alignment. Then, we present a missing information generation network that is appropriate for small-sample of ET volume using pre-training interpolation network and distillation learning. And we use it to generate the missing information to achieve the whole volume reconstruction. For the reconstruction of synaptic ultrastructures, we use a 3D neural network to obtain them quickly. In summary, our workflow can quickly locate and acquire ROIs in serial sections, automatically align, restore, assemble serial sections, and obtain the complete segmentation result of the target structure with minimal manual manipulation. Multiple intact synapses in wild-type rat were reconstructed at a voxel size of 0.664 nm/voxel to demonstrate the effectiveness of our workflow.

CONCLUSIONS

Our workflow contributes to obtaining intact synaptic structures at the sub-nanometer scale through serial section ET, which contains rapid ROI locating, automatic alignment, volume reconstruction, and semi-automatic synapse reconstruction. We have open-sourced the relevant code in our workflow, so it is easy to apply it to other labs and obtain complete 3D ultrastructures which size is similar to intact synapses with sub-nanometer voxel size.

Minimal resin embedding of SBF-SEM samples reduces charging and facilitates finding a surface-linked region of interest

BACKGROUND

For decoding the mechanism of how cells and organs function information on their ultrastructure is essential. High-resolution 3D imaging has revolutionized morphology. Serial block face scanning electron microscopy (SBF-SEM) offers non-laborious, automated imaging in 3D of up to ~ 1 mm3 large biological objects at nanometer-scale resolution. For many samples there are obstacles. Quality imaging is often hampered by charging effects, which originate in the nonconductive resin used for embedding. Especially, if the imaged region of interest (ROI) includes the surface of the sample and neighbours the empty resin, which insulates the object. This extra resin also obscures the sample's morphology, thus making navigation to the ROI difficult.

RESULTS

Using the example of small arthropods and a fish roe we describe a workflow to prepare samples for SBF-SEM using the minimal resin (MR) embedding method. We show that for imaging of surface structures this simple approach conveniently tackles and solves both of the two major problems-charging and ROI localization-that complicate imaging of SBF-SEM samples embedded in an excess of overlying resin. As the surface ROI is not masked by the resin, samples can be precisely trimmed before they are placed into the imaging chamber. The initial approaching step is fast and easy. No extra trimming inside the microscope is necessary. Importantly, charging is absent or greatly reduced meaning that imaging can be accomplished under good vacuum conditions, typically at the optimal high vacuum. This leads to better resolution, better signal to noise ratio, and faster image acquisition.

CONCLUSIONS

In MR embedded samples charging is minimized and ROI easily targeted. MR embedding does not require any special equipment or skills. It saves effort, microscope time and eventually leads to high quality data. Studies on surface-linked ROIs, or any samples normally surrounded by the excess of resin, would benefit from adopting the technique.

New Insights into RPE-Photoreceptor Complex Ultrastructure using Focused Ion Beam-Scanning Election Microscopy (FIB-SEM)

Photoreceptors in the retina are specialized neuronal cells that perceive light and play a central role in the visual system. Damage to photoreceptors is a clinical feature often associated with various retinal degenerative disorders. The photoreceptor bed comprises a unique extracellular matrix (ECM) scaffold often described as the interphotoreceptor matrix (IPM) in the subretinal space, vital during retinal development and homeostasis. In this study, we used focused ion beam scanning electron microscopy (FIB-SEM) and transmission electron microscopy (TEM) to analyze the ultrastructural architecture of the retinal pigmented epithelium (RPE)-photoreceptor complex in mice. Additionally, we describe methods for retinal preparation in EM imaging. TEM images display ultrastructural retina layers, including Bruch's membrane and the interdigitation zone (IZ). The 3-dimensional reconstruction of the outer retina revealed individual photoreceptors, the connection between their inner and outer segment via the photoreceptor cilia, and photoreceptor interaction with the RPE ciliary processes. Our findings highlight the importance of FIB-SEM in deciphering the ultrastructural details of RPE-photoreceptor interactions in the IPM complex which are essential for the maintenance of retinal architecture.

Three-dimensional structural analysis of papillary thyroid carcinoma nuclei with serial block-face scanning electron microscopy (SBF-SEM)

Nuclear morphology of carcinoma cells is critical for the pathological diagnosis of papillary thyroid carcinoma (PTC). However, three-dimensional architecture of PTC nuclei is still elusive. In this study, we analyzed the three-dimensional ultrastructure of PTC nuclei using serial block-face scanning electron microscopy which takes advantage of the high-throughput acquisition of serial electron microscopic images and three-dimensional reconstruction of subcellular structures. En bloc-stained and resin-embedded specimens were prepared from surgically removed PTCs and normal thyroid tissues. We acquired two-dimensional images from serial block-face scanning electron microscopy and reconstructed three-dimensional nuclear structures. Quantitative comparisons showed that the nuclei of carcinoma cells were larger and more complex than those of normal follicular cells. The three-dimensional reconstruction of carcinoma nuclei divided intranuclear cytoplasmic inclusions into "open intranuclear cytoplasmic inclusions" connecting to cytoplasm outside the nucleus and "closed intranuclear cytoplasmic inclusions" without that connection. Cytoplasm with abundant organelles was observed in open inclusions, but closed inclusions contained fewer organelles with or without degeneration. Granules with a dense core were only observed in closed inclusions. Our observations suggested that open inclusions originate from nuclear invaginations, and disconnection from cytoplasm leads to closed inclusions.

Serial Block Face-Scanning Electron Microscopy as a Burgeoning Technology

Serial block face scanning electron microscopy (SBF-SEM), also referred to as serial block-face electron microscopy, is an advanced ultrastructural imaging technique that enables three-dimensional visualization that provides largerx- and y-axis ranges than other volumetric EM techniques. While SEM is first introduced in the 1930s, SBF-SEM is developed as a novel method to resolve the 3D architecture of neuronal networks across large volumes with nanometer resolution by Denk and Horstmann in 2004. Here, the authors provide an accessible overview of the advantages and challenges associated with SBF-SEM. Beyond this, the applications of SBF-SEM in biochemical domains as well as potential future clinical applications are briefly reviewed. Finally, the alternative forms of artificial intelligence-based segmentation which may contribute to devising a feasible workflow involving SBF-SEM, are also considered.

Systematic Transmission Electron Microscopy-Based Identification and 3D Reconstruction of Cellular Degradation Machinery

Various intracellular degradation organelles, including autophagosomes, lysosomes, and endosomes, work in tandem to perform autophagy, which is crucial for cellular homeostasis. Altered autophagy contributes to the pathophysiology of various diseases, including cancers and metabolic diseases. This paper aims to describe an approach to reproducibly identify and distinguish subcellular structures involved in macroautophagy. Methods are provided that help avoid common pitfalls. How to distinguish between lysosomes, lipid droplets, autolysosomes, autophagosomes, and inclusion bodies are also discussed. These methods use transmission electron microscopy (TEM), which is able to generate nanometer-scale micrographs of cellular degradation components in a fixed sample. Serial block face-scanning electron microscopy is also used to visualize the 3D morphology of degradation machinery using the Amira software. In addition to TEM and 3D reconstruction, other imaging techniques are discussed, such as immunofluorescence and immunogold labeling, which can be used to classify cellular organelles, reliably and accurately. Results show how these methods may be used to accurately quantify cellular degradation machinery under various conditions, such as treatment with the endoplasmic reticulum stressor thapsigargin or ablation of the dynamin-related protein 1.

A Convenient All-Cell Optical Imaging Method Compatible with Serial SEM for Brain Mapping

The mammalian brain, with its complexity and intricacy, poses significant challenges for researchers aiming to understand its inner workings. Optical multilayer interference tomography (OMLIT) is a novel, promising imaging technique that enables the mapping and reconstruction of mesoscale all-cell brain atlases and is seamlessly compatible with tape-based serial scanning electron microscopy (SEM) for microscale mapping in the same tissue. However, currently, OMLIT suffers from imperfect coatings, leading to background noise and image contamination. In this study, we introduced a new imaging configuration using carbon spraying to eliminate the tape-coating step, resulting in reduced noise and enhanced imaging quality. We demonstrated the improved imaging quality and validated its applicability through a correlative light-electron imaging workflow. Our method successfully reconstructed all cells and vasculature within a large OMLIT dataset, enabling basic morphological classification and analysis. We also show that this approach can perform effectively on thicker sections, extending its applicability to sub-micron scale slices, saving sample preparation and imaging time, and increasing imaging throughput. Consequently, this method emerges as a promising candidate for high-speed, high-throughput brain tissue reconstruction and analysis. Our findings open new avenues for exploring the structure and function of the brain using OMLIT images.

Functional characterization of endo-lysosomal compartments by correlative live-cell and volume electron microscopy

Fluorescent biosensors are valuable tools to monitor protein activities and the functional state of organelles in live cells. However, the information provided by fluorescent microscopy (FM) is mostly limited in resolution and lacks ultrastructural context information. Protein activities are confined to organelle zones with a distinct membrane morphology, which can only be seen by electron microscopy (EM). EM, however, intrinsically lacks information on protein activities. The lack of methods to integrate these two imaging modalities has hampered understanding the functional organization of cellular organelles. Here we introduce "functional correlative microscopy" (functional CLEM) to directly infer functional information from live cells to EM with nanometer resolution. We label and visualize live cells with fluorescent biosensors after which they are processed for EM and imaged using a volume electron microscopy technique. Within a single dataset we correlate hundreds of fluorescent spots enabling quantitative analysis of the functional-ultrastructural data. We employ our method to monitor essential functional parameters of late endo-lysosomal compartments, i.e., pH, calcium, enzyme activities and cholesterol content. Our data reveal a steep functional difference in enzyme activity between late endosomes and lysosomes and unexpectedly high calcium levels in late endosomes. The presented CLEM workflow is compatible with a large repertoire of probes and paves the way for large scale functional studies of all types of cellular structures.

Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy

Stereological methods for estimating the 3D particle size and density from 2D projections are essential to many research fields. These methods are, however, prone to errors arising from undetected particle profiles due to sectioning and limited resolution, known as 'lost caps'. A potential solution developed by Keiding, Jensen, and Ranek in 1972, which we refer to as the Keiding model, accounts for lost caps by quantifying the smallest detectable profile in terms of its limiting 'cap angle' (ϕ), a size-independent measure of a particle's distance from the section surface. However, this simple solution has not been widely adopted nor tested. Rather, model-independent design-based stereological methods, which do not explicitly account for lost caps, have come to the fore. Here, we provide the first experimental validation of the Keiding model by comparing the size and density of particles estimated from 2D projections with direct measurement from 3D EM reconstructions of the same tissue. We applied the Keiding model to estimate the size and density of somata, nuclei and vesicles in the cerebellum of mice and rats, where high packing density can be problematic for design-based methods. Our analysis reveals a Gaussian distribution for ϕ rather than a single value. Nevertheless, curve fits of the Keiding model to the 2D diameter distribution accurately estimate the mean ϕ and 3D diameter distribution. While systematic testing using simulations revealed an upper limit to determining ϕ, our analysis shows that estimated ϕ can be used to determine the 3D particle density from the 2D density under a wide range of conditions, and this method is potentially more accurate than minimum-size-based lost-cap corrections and disector methods. Our results show the Keiding model provides an efficient means of accurately estimating the size and density of particles from 2D projections even under conditions of a high density.

Bringing synapses into focus: Recent advances in synaptic imaging and mass-spectrometry for studying synaptopathy

Synapses are integral for healthy brain function and are becoming increasingly recognized as key structures in the early stages of brain disease. Understanding the pathological processes driving synaptic dysfunction will unlock new therapeutic opportunities for some of the most devastating diseases of our time. To achieve this we need a solid repertoire of imaging and molecular tools to interrogate synaptic biology at greater resolution. Synapses have historically been examined in small numbers, using highly technical imaging modalities, or in bulk, using crude molecular approaches. However, recent advances in imaging techniques are allowing us to analyze large numbers of synapses, at single-synapse resolution. Furthermore, multiplexing is now achievable with some of these approaches, meaning we can examine multiple proteins at individual synapses in intact tissue. New molecular techniques now allow accurate quantification of proteins from isolated synapses. The development of increasingly sensitive mass-spectrometry equipment means we can now scan the synaptic molecular landscape almost in totality and see how this changes in disease. As we embrace these new technical developments, synapses will be viewed with clearer focus, and the field of synaptopathy will become richer with insightful and high-quality data. Here, we will discuss some of the ways in which synaptic interrogation is being facilitated by methodological advances, focusing on imaging, and mass spectrometry.

Liver inter-organelle membrane contact sites revealed by serial section electron tomography

Inter-organelle membrane contact sites (MCSs) are defined as areas of close proximity between the membranes of two organelles (10-80nm). They have been implicated in many physiological processes such as Ca++, lipids or small molecules transfer, organelles biogenesis or dynamic and have an important role in many cellular processes such as apoptosis, autophagy, and signaling. Since the distance and the extent of these contacts are in the nanometer range, high resolution techniques are ideal for imaging these structures. It is for this reason that transmission electron microscopy (TEM) has been considered the gold standard for MCSs visualization and the first technique that described them. However, often TEM analysis is limited to 2D lacking information on the 3D association between the organelles involved in MCSs. To fully describe the complex architecture of MSCs and to unveil their role in cellular physiology a 3D analysis is required. This chapter provides a method for the analysis of MCSs using serial section electron tomography (ssET), a technique able to reconstruct in 3D at nanometer resolution cellular and subcellular structures. By applying this procedure, it was possible to elucidate the role of the contacts between Endoplasmic Reticulum (ER) and other organelles in liver lipid metabolism.

A novel technique of STEM observation of TEM section using LVSEM and application of pathological diagnosis of renal biopsy

The usefulness of the transmission electron microscope (TEM) for pathological diagnosis is apparent. However, high operating costs and other disadvantages have limited the ability to maintain and operate a TEM. In recent years, a general-purpose benchtop low-vacuum scanning electron microscope (LVSEM), which is inexpensive and easy to operate, has been developed and is expected to be applied in electron microscopic pathological diagnosis. To date, we have previously observed TEM ultrathin sections of Immunoglobulin A (IgA) nephropathy with a benchtop LVSEM using an ultra variable-pressure detector (UVD) and a newly developed holder for observing scanning transmission electron microscope (STEM) images (UVD-STEM holder) and compared the images with those obtained with typical TEM observations. We reported the results in the 53rd Annual Meeting of the Japanese Society for Clinical Molecular Morphology and the 64th Symposium of The Japanese Society of Microscopy and discussed the validity of the methods in the pathological diagnosis of IgA nephropathy and other renal diseases. As a result, we demonstrated the potential for pathological diagnosis using benchtop LVSEM. In this study, we similarly examined typical kidney diseases such as membranous nephropathy, lupus nephritis and amyloidosis. We could obtain sufficient data for the pathological diagnosis of IgA nephropathy, membranous nephropathy and lupus nephritis. However, it is difficult to detect amyloid fibres that are characteristic of amyloidosis. The development of this method is expected to expand the possibilities for pathological diagnosis using electron microscopy, including its application to other diseases.

Mesoscopic structural analysis via deep learning processing, with a special reference to in vitro alteration in collagen fibre induced by a gap junction inhibitor

Dense connective tissue, including the ligament, tendon, fascia and cornea, is formed by regularly arranged collagen fibres synthesized by fibroblasts (Fbs). The mechanism by which fibre orientation is determined remains unclear. Periodontal ligament Fbs consistently communicate with their surroundings via gap junctions (GJs), leading to the formation of a wide cellular network. A method to culture Fb-synthesized collagen fibres was previously reported by Schafer et al. ('Ascorbic acid deficiency in cultured human fibroblasts'. J. Cell Biol. 34: 83-95, 1967). This method has been applied to investigate the ability and activity of Fb collagen synthesis/phagocytosis using conventional electron microscopy (EM). However, the three-dimensional mesoscopic architecture of collagen fibres and the influence of GJ inhibitors on collagen fibre formation in vitro are poorly understood. In this study, three-dimensional mesoscopic analysis was used to elucidate the mechanism of directional fibre formation. We investigated the influence of GJ inhibitors on collagen formation driven by periodontal ligament Fbs in vitro, histomorphometrically, and the structural properties of in vitro collagen fibre on a mesoscale quantitatively, using correlative light and EM optimized for picrosirius red staining and focused ion beam-scanning EM tomography. Our results indicate that under culture conditions, in the presence of a GJ inhibitor, the orientation of collagen fibres becomes more disordered than that in the control group. This suggests that the GJ might be involved in determining fibre orientation during collagen fibre formation. Elucidation of this mechanism may help develop novel treatment strategies for connective tissue orientation disorders. Graphical Abstract.

Spatial proteomics of vesicular trafficking: coupling mass spectrometry and imaging approaches in membrane biology

In plants, membrane compartmentalization requires vesicle trafficking for communication among distinct organelles. Membrane proteins involved in vesicle trafficking are highly dynamic and can respond rapidly to changes in the environment and to cellular signals. Capturing their localization and dynamics is thus essential for understanding the mechanisms underlying vesicular trafficking pathways. Quantitative mass spectrometry and imaging approaches allow a system-wide dissection of the vesicular proteome, the characterization of ligand-receptor pairs and the determination of secretory, endocytic, recycling and vacuolar trafficking pathways. In this review, we highlight major proteomics and imaging methods employed to determine the location, distribution and abundance of proteins within given trafficking routes. We focus in particular on methodologies for the elucidation of vesicle protein dynamics and interactions and their connections to downstream signalling outputs. Finally, we assess their biological applications in exploring different cellular and subcellular processes.

Light and focused ion beam microscopy workflow for resin-embedded tissues

Although the automated image acquisition with the focused ion beam scanning electron microscope (FIB-SEM) provides volume reconstructions, volume analysis of large samples remains challenging. Here, we present a workflow that combines a modified sample protocol of the classical transmission electron microscope with FIB-SEM volume imaging. The proposed workflow enables efficient 3D structural surveys of rabbit ovaries collected at consecutive developmental stages. The precise trimming of the region of interest adds the time dimension to the volume, constructing a virtual 4D electron microscopy. We found filopodia-like processes emitted by oocyte cysts allowing contact between oocytes not previously observed.

Instance segmentation of mitochondria in electron microscopy images with a generalist deep learning model trained on a diverse dataset

Mitochondria are extremely pleomorphic organelles. Automatically annotating each one accurately and precisely in any 2D or volume electron microscopy (EM) image is an unsolved computational challenge. Current deep learning-based approaches train models on images that provide limited cellular contexts, precluding generality. To address this, we amassed a highly heterogeneous ∼1.5 × 10⁶ image 2D unlabeled cellular EM dataset and segmented ∼135,000 mitochondrial instances therein. MitoNet, a model trained on these resources, performs well on challenging benchmarks and on previously unseen volume EM datasets containing tens of thousands of mitochondria. We release a Python package and napari plugin, empanada, to rapidly run inference, visualize, and proofread instance segmentations. A record of this paper's transparent peer review process is included in the supplemental information.

Deep learning-based synapse counting and synaptic ultrastructure analysis of electron microscopy images

BACKGROUND

Synapses are the connections between neurons in the central nervous system (CNS) or between neurons and other excitable cells in the peripheral nervous system (PNS), where electrical or chemical signals rapidly travel through one cell to another with high spatial precision. Synaptic analysis, based on synapse numbers and fine morphology, is the basis for understanding neurological functions and diseases. Manual analysis of synaptic structures in electron microscopy (EM) images is often limited by low efficiency and subjective bias.

NEW METHOD

We developed a multifunctional synaptic analysis system based on several advanced deep learning (DL) models. The system achieved synapse counting in low-magnification EM images and synaptic ultrastructure analysis in high-magnification EM images.

RESULTS

The synapse counting system based on ResNet18 and a Faster R-CNN model had a mean average precision (mAP) of 92.55%. For synaptic ultrastructure analysis, the Faster R-CNN model based on ResNet50 achieved a mAP of 91.60%, the DeepLab v3 + model based on ResNet50 enabled high performance in presynaptic and postsynaptic membrane segmentation with a global accuracy of 0.9811, and the Faster R-CNN model based on ResNet18 achieved a mAP of 91.41% for synaptic vesicle detection.

CONCLUSIONS

The proposed multifunctional synaptic analysis system may help to overcome the experimental bias inherent in manual analysis, thereby facilitating EM image-based synaptic function studies.

Exploiting volume electron microscopy to investigate structural plasticity and stability of the postsynaptic compartment of central synapses

Volume reconstruction from electron microscopy datasets is a tool increasingly used to study the ultrastructure of the synapse in the broader context of neuronal network and brain organization. Fine modifications of synapse structure, such as activity-dependent dendritic spine enlargement and changes in the size and shape of the postsynaptic density, occur upon maturation and plasticity. The lack of structural plasticity or the inability to stabilize potentiated synapses are associated with synaptic and neuronal functional impairment. Mapping these rearrangements with the high resolution of electron microscopy proved to be essential in order to establish precise correlations between the geometry of synapses and their functional states. In this review we discuss recent discoveries on the substructure of the postsynaptic compartment of central excitatory synapses and how those are correlated with functional states of the neuronal network. The added value of volume electron microscopy analyses with respect to conventional transmission electron microscopy studies is highlighted considering that some limitations of volume-based methods imposed several adjustments to describe the geometry of this synaptic compartment and new parameters-that are good indicators of synapses strength and activity-have been introduced.

CLEMSite, a software for automated phenotypic screens using light microscopy and FIB-SEM

In recent years, Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) has emerged as a flexible method that enables semi-automated volume ultrastructural imaging. We present a toolset for adherent cells that enables tracking and finding cells, previously identified in light microscopy (LM), in the FIB-SEM, along with the automatic acquisition of high-resolution volume datasets. We detect the underlying grid pattern in both modalities (LM and EM), to identify common reference points. A combination of computer vision techniques enables complete automation of the workflow. This includes setting the coincidence point of both ion and electron beams, automated evaluation of the image quality and constantly tracking the sample position with the microscope's field of view reducing or even eliminating operator supervision. We show the ability to target the regions of interest in EM within 5 µm accuracy while iterating between different targets and implementing unattended data acquisition. Our results demonstrate that executing volume acquisition in multiple locations autonomously is possible in EM.

Studying Golgi Structure and Function by Thin Section TEM

Here, we describe protocols for chemical fixation and flat embedding to study the Golgi structure by thin section transmission electron microscopy (TEM) and for 3,3'-diaminobenzidine (DAB) cytochemical staining and pre-embedding immunolabelling to localize specific Golgi proteins. Furthermore, we demonstrate how the Golgi morphology can be elucidated by classifying the Golgi membranes using Microscopy Image Browser-a software that provides anonymization, modelling, and annotation.

Algorithm for Modern Electron Microscopic Examination of the Golgi Complex

The Golgi complex (GC) is an essential organelle of the eukaryotic exocytic pathway. It has a very complexed structure and thus localization of its resident proteins is not trivial. Fast development of microscopic methods generates a huge difficulty for Golgi researchers to select the best protocol to use. Modern methods of light microscopy, such as super-resolution light microscopy (SRLM) and electron microscopy (EM), open new possibilities in analysis of various biological structures at organelle, cell, and organ levels. Nowadays, new generation of EM methods became available for the study of the GC; these include three-dimensional EM (3DEM), correlative light-EM (CLEM), immune EM, and new estimators within stereology that allow realization of maximal goal of any morphological study, namely, to achieve a three-dimensional model of the sample with optimal level of resolution and quantitative determination of its chemical composition. Methods of 3DEM have partially overlapping capabilities. This requires a careful comparison of these methods, identification of their strengths and weaknesses, and formulation of recommendations for their application to cell or tissue samples. Here, we present an overview of 3DEM methods for the study of the GC and some basics for how the images are formed and how the image quality can be improved.

Imaging tools for plant nanobiotechnology

The successful application of nanobiotechnology in biomedicine has greatly changed the traditional way of diagnosis and treating of disease, and is promising for revolutionizing the traditional plant nanobiotechnology. Over the past few years, nanobiotechnology has increasingly expanded into plant research area. Nanomaterials can be designed as vectors for targeted delivery and controlled release of fertilizers, pesticides, herbicides, nucleotides, proteins, etc. Interestingly, nanomaterials with unique physical and chemical properties can directly affect plant growth and development; improve plant resistance to disease and stress; design as sensors in plant biology; and even be used for plant genetic engineering. Similarly, there have been concerns about the potential biological toxicity of nanomaterials. Selecting appropriate characterization methods will help understand how nanomaterials interact with plants and promote advances in plant nanobiotechnology. However, there are relatively few reviews of tools for characterizing nanomaterials in plant nanobiotechnology. In this review, we present relevant imaging tools that have been used in plant nanobiotechnology to monitor nanomaterial migration, interaction with and internalization into plants at three-dimensional lengths. Including: 1) Migration of nanomaterial into plant organs 2) Penetration of nanomaterial into plant tissues (iii)Internalization of nanomaterials by plant cells and interactions with plant subcellular structures. We compare the advantages and disadvantages of current characterization tools and propose future optimal characterization methods for plant nanobiotechnology.

Three-dimensional imaging of biological cells using surface plasmon coupled emission

SIGNIFICANCE

Biological cell imaging has become one of the most crucial research interests because of its applications in biomedical and microbiology studies. However, three-dimensional (3D) imaging of biological cells is critically challenging and often involves prohibitively expensive and complex equipment. Therefore, a low-cost imaging technique with a simpler optical arrangement is immensely needed.

AIM

The proposed approach will provide an accurate cell image at a low cost without needing any microscope or extensive processing of the collected data, often used in conventional imaging techniques.

APPROACH

We propose that patterns of surface plasmon coupled emission (SPCE) features from a fluorescently labeled biological cell can be used to image the cell. An imaging methodology has been developed and theoretically demonstrated to create 3D images of cells from the detected SPCE patterns. The 3D images created from the different SPCE properties at the far-field closely match the actual cell structures.

RESULTS

The developed technique has been applied to different regular and irregular cell shapes. In each case, the calculated root-mean-square error (RMSE) of the created images from the cell structures remains within a few percentages. Our work recreates the base of a circular-shaped cell with an RMSE of ≲1.4 % . In addition, the images of irregular-shaped cell bases have an RMSE of ≲2.8 % . Finally, we obtained a 3D image with an RMSE of ≲6.5 % for a random cellular structure.

CONCLUSIONS

Despite being in its initial stage of development, the proposed technique shows promising results considering its simplicity and the nominal cost it would require.

Combined nanometric and phylogenetic analysis of unique endocytic compartments in Giardia lamblia sheds light on the evolution of endocytosis in Metamonada

Background

Giardia lamblia, a parasitic protist of the Metamonada supergroup, has evolved one of the most diverged endocytic compartment systems investigated so far. Peripheral endocytic compartments, currently known as peripheral vesicles or vacuoles (PVs), perform bulk uptake of fluid phase material which is then digested and sorted either to the cell cytosol or back to the extracellular space.

Results

Here, we present a quantitative morphological characterization of these organelles using volumetric electron microscopy and super-resolution microscopy (SRM). We defined a morphological classification for the heterogenous population of PVs and performed a comparative analysis of PVs and endosome-like organelles in representatives of phylogenetically related taxa, Spironucleus spp. and Tritrichomonas foetus. To investigate the as-yet insufficiently understood connection between PVs and clathrin assemblies in G. lamblia, we further performed an in-depth search for two key elements of the endocytic machinery, clathrin heavy chain (CHC) and clathrin light chain (CLC), across different lineages in Metamonada. Our data point to the loss of a bona fide CLC in the last Fornicata common ancestor (LFCA) with the emergence of a protein analogous to CLC (GlACLC) in the Giardia genus. Finally, the location of clathrin in the various compartments was quantified.

Conclusions

Taken together, this provides the first comprehensive nanometric view of Giardia’s endocytic system architecture and sheds light on the evolution of GlACLC analogues in the Fornicata supergroup and, specific to Giardia, as a possible adaptation to the formation and maintenance of stable clathrin assemblies at PVs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01402-3.

Mem3DG: Modeling membrane mechanochemical dynamics in 3D using discrete differential geometry

Biomembranes adopt varying morphologies that are vital to cellular functions. Many studies use computational modeling to understand how various mechanochemical factors contribute to membrane shape transformations. Compared with approximation-based methods (e.g., finite element method [FEM]), the class of discrete mesh models offers greater flexibility to simulate complex physics and shapes in three dimensions; its formulation produces an efficient algorithm while maintaining coordinate-free geometric descriptions. However, ambiguities in geometric definitions in the discrete context have led to a lack of consensus on which discrete mesh model is theoretically and numerically optimal; a bijective relationship between the terms contributing to both the energy and forces from the discrete and smooth geometric theories remains to be established. We address this and present an extensible framework, Mem3DG, for modeling 3D mechanochemical dynamics of membranes based on discrete differential geometry (DDG) on triangulated meshes. The formalism of DDG resolves the inconsistency and provides a unifying perspective on how to relate the smooth and discrete energy and forces. To demonstrate, Mem3DG is used to model a sequence of examples with increasing mechanochemical complexity: recovering classical shape transformations such as 1) biconcave disk, dumbbell, and unduloid; and 2) spherical bud on spherical, flat-patch membrane; investigating how the coupling of membrane mechanics with protein mobility jointly affects phase and shape transformation. As high-resolution 3D imaging of membrane ultrastructure becomes more readily available, we envision Mem3DG to be applied as an end-to-end tool to simulate realistic cell geometry under user-specified mechanochemical conditions.

ARRAY TOMOGRAPHY: 15 YEARS OF SYNAPTIC ANALYSIS

Synapses are minuscule, intricate structures crucial for the correct communication between neurons. In the 125 years since the term synapse was first coined, we have advanced a long way when it comes to our understanding of how they work and what they do. Most of the fundamental discoveries have been invariably linked to advances in technology. However, due to their size, delicate structural integrity and their sheer number, our knowledge of synaptic biology has remained somewhat elusive and their role in neurodegenerative diseases still remains largely unknown. Here, we briefly discuss some of the imaging technologies used to study synapses and focus on the utility of the high-resolution imaging technique array tomography (AT). We introduce the AT technique and highlight some of the ways it is utilised with a particular focus on its power for analysing synaptic composition and pathology in human post-mortem tissue. We also discuss some of the benefits and drawbacks of techniques for imaging synapses and highlight some recent advances in the study of form and function by combining physiology and high-resolution synaptic imaging.

Electron microscopy of cellular ultrastructure in three dimensions

Electron microscopy in three dimensions (3D) of cells and tissues can be essential for understanding the ultrastructural aspects of biological processes. The quest for 3D information reveals challenges at many stages of the workflow, from sample preparation, to imaging, data analysis and segmentation. Here, we outline several available methods, including volume SEM imaging, cryo-TEM and cryo-STEM tomography, each one occupying a different domain in the basic tradeoff between field-of-view and resolution. We discuss the considerations for choosing a suitable method depending on research needs and highlight recent developments that are essential for making 3D volume imaging of cells and tissues a standard tool for cellular and structural biologists.

A versatile enhanced freeze-substitution protocol for volume electron microscopy

Volume electron microscopy, a powerful approach to generate large three-dimensional cell and tissue volumes at electron microscopy resolutions, is rapidly becoming a routine tool for understanding fundamental and applied biological questions. One of the enabling factors for its adoption has been the development of conventional fixation protocols with improved heavy metal staining. However, freeze-substitution with organic solvent-based fixation and staining has not realized the same level of benefit. Here, we report a straightforward approach including osmium tetroxide, acetone and up to 3% water substitution fluid (compatible with traditional or fast freeze-substitution protocols), warm-up and transition from organic solvent to aqueous 2% osmium tetroxide. Once fully hydrated, samples were processed in aqueous based potassium ferrocyanide, thiocarbohydrazide, osmium tetroxide, uranyl acetate and lead acetate before resin infiltration and polymerization. We observed a consistent and substantial increase in heavy metal staining across diverse and difficult-to-fix test organisms and tissue types, including plant tissues (Hordeum vulgare), nematode (Caenorhabditis elegans) and yeast (Saccharomyces cerevisiae). Our approach opens new possibilities to combine the benefits of cryo-preservation with enhanced contrast for volume electron microscopy in diverse organisms.

Automatic segmentation and reconstruction of intracellular compartments in volumetric electron microscopy data

BACKGROUND AND OBJECTIVES

In recent years, electron microscopy is enabling the acquisition of volumetric data with resolving power to directly observe the ultrastructure of intracellular compartments. New insights and knowledge about cell processes that are offered by such data require a comprehensive analysis which is limited by the time-consuming manual segmentation and reconstruction methods.

METHOD

We present methods for automatic segmentation, reconstruction, and analysis of intracellular compartments from volumetric data obtained by the dual-beam electron microscopy. We specifically address segmentation of fusiform vesicles and the Golgi apparatus, reconstruction of mitochondria and fusiform vesicles, and morphological analysis of the reconstructed mitochondria.

RESULTS AND CONCLUSION

Evaluation on the public UroCell dataset demonstrated high accuracy of the proposed methods for segmentation of fusiform vesicles and the Golgi apparatus, as well as for reconstruction of mitochondria and analysis of their shapes, while reconstruction of fusiform vesicles proved to be more challenging. We published an extension of the UroCell dataset with all of the data used in this work, to further contribute to research on automatic analysis of the ultrastructure of intracellular compartments.

How innovations in methodology offer new prospects for volume electron microscopy

Detailed knowledge of biological structure has been key in understanding biology at several levels of organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, the throughput rate of conventional electron microscopes has limited the volume size and number of samples that can be imaged. Recent improvements in methodology are currently driving a revolution in volume EM, making possible the structural imaging of whole organs and small organisms. In turn, these recent developments in image acquisition have created or stressed bottlenecks in other parts of the pipeline, like sample preparation, image analysis and data management. While the progress in image analysis is stunning due to the advent of automatic segmentation and server‐based annotation tools, several challenges remain. Here we discuss recent trends in volume EM, emerging methods for increasing throughput and implications for sample preparation, image analysis and data management.

Volume electron microscopy

Life exists in three dimensions, but until the turn of the century most electron microscopy methods provided only 2D image data. Recently, electron microscopy techniques capable of delving deep into the structure of cells and tissues have emerged, collectively called volume electron microscopy (vEM). Developments in vEM have been dubbed a quiet revolution as the field evolved from established transmission and scanning electron microscopy techniques, so early publications largely focused on the bioscience applications rather than the underlying technological breakthroughs. However, with an explosion in the uptake of vEM across the biosciences and fast-paced advances in volume, resolution, throughput and ease of use, it is timely to introduce the field to new audiences. In this Primer, we introduce the different vEM imaging modalities, the specialized sample processing and image analysis pipelines that accompany each modality and the types of information revealed in the data. We showcase key applications in the biosciences where vEM has helped make breakthrough discoveries and consider limitations and future directions. We aim to show new users how vEM can support discovery science in their own research fields and inspire broader uptake of the technology, finally allowing its full adoption into mainstream biological imaging.

One for All, All for One: A Close Look at In-Resin Fluorescence Protocols for CLEM

Sample preparation is the novel bottleneck for high throughput correlative light and electron microscopy (CLEM). Protocols suitable for both imaging methods must therefore balance the requirements of each technique. For fluorescence light microscopy, a structure of interest can be targeted using: 1) staining, which is often structure or tissue specific rather than protein specific, 2) dye-coupled proteins or antibodies, or 3) genetically encoded fluorescent proteins. Each of these three methods has its own advantages. For ultrastructural investigation by electron microscopy (EM) resin embedding remains a significant sample preparation approach, as it stabilizes the sample such that it withstands the vacuum conditions of the EM, and enables long-term storage. Traditionally, samples are treated with heavy metal salts prior to resin embedding, in order to increase imaging contrast for EM. This is particularly important for volume EM (vEM) techniques. Yet, commonly used contrasting agents (e.g., osmium tetroxide, uranyl acetate) tend to impair fluorescence. The discovery that fluorescence can be preserved in resin-embedded specimens after mild heavy metal staining was a game changer for CLEM. These so-called in-resin fluorescence protocols present a significant leap forward for CLEM approaches towards high precision localization of a fluorescent signal in (volume) EM data. Integrated microscopy approaches, combining LM and EM detection into a single instrument certainly require such an “all in one” sample preparation. Preserving, or adding, dedicated fluorescence prior to resin embedding requires a compromise, which often comes at the expense of EM imaging contrast and membrane visibility. Especially vEM can be strongly hampered by a lack of heavy metal contrasting. This review critically reflects upon the fundamental aspects of resin embedding with regard to 1) specimen fixation and the physics and chemistry underlying the preservation of protein structure with respect to fluorescence and antigenicity, 2) optimization of EM contrast for transmission or scanning EM, and 3) the choice of embedding resin. On this basis, various existing workflows employing in-resin fluorescence are described, highlighting their common features, discussing advantages and disadvantages of the respective approach, and finally concluding with promising future developments for in-resin CLEM.

Single-Neuron Labeling in Fixed Tissue and Targeted Volume Electron Microscopy

The structural complexity of nervous tissue makes it very difficult to unravel the connectivity between neural elements at different scales. Numerous methods are available to trace long-range projections at the light microscopic level, and to identify the actual synaptic connections at the electron microscopic level. However, correlating mesoscopic and nanoscopic scales in the same cell, cell population or brain region is a problematic, laborious and technically demanding task. Here we present an effective method for the 3D reconstruction of labeled subcellular structures at the ultrastructural level, after single-neuron labeling in fixed tissue. The brain is fixed by intracardial perfusion of aldehydes and thick vibratome sections (250 μm) are obtained. Single cells in these vibratome sections are intracellularly injected with horseradish peroxidase (HRP), so that the cell body and its processes can be identified. The thick sections are later flat-embedded in epoxy resin and re-sectioned into a series of thinner (7 μm) sections. The sections containing the regions of interest of the labeled cells are then imaged with automated focused ion beam milling and scanning electron microscopy (FIB-SEM), acquiring long series of high-resolution images that can be reconstructed, visualized, and analyzed in 3D. With this methodology, we can accurately select any cellular segment at the light microscopic level (e.g., proximal, intermediate or distal dendrites, collateral branches, axonal segments, etc.) and analyze its synaptic connections at the electron microscopic level, along with other ultrastructural features. Thus, this method not only facilitates the mapping of the synaptic connectivity of single-labeled neurons, but also the analysis of the surrounding neuropil. Since the labeled processes can be located at different layers or subregions, this method can also be used to obtain data on the differences in local synaptic organization that may exist at different portions of the labeled neurons.

Microscopic Visualization of Cell-Cell Adhesion Complexes at Micro and Nanoscale

Considerable progress has been made in our knowledge of the morphological and functional varieties of anchoring junctions. Cell-cell adhesion contacts consist of discrete junctional structures responsible for the mechanical coupling of cytoskeletons and allow the transmission of mechanical signals across the cell collective. The three main adhesion complexes are adherens junctions, tight junctions, and desmosomes. Microscopy has played a fundamental role in understanding these adhesion complexes on different levels in both physiological and pathological conditions. In this review, we discuss the main light and electron microscopy techniques used to unravel the structure and composition of the three cell-cell contacts in epithelial and endothelial cells. It functions as a guide to pick the appropriate imaging technique(s) for the adhesion complexes of interest. We also point out the latest techniques that have emerged. At the end, we discuss the problems investigators encounter during their cell-cell adhesion research using microscopic techniques.

X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs

Capturing complete internal anatomies of plant organs and tissues within their relevant morphological context remains a key challenge in plant science. While plant growth and development are inherently multiscale, conventional light, fluorescence, and electron microscopy platforms are typically limited to imaging of plant microstructure from small flat samples that lack a direct spatial context to, and represent only a small portion of, the relevant plant macrostructures. We demonstrate technical advances with a lab-based X-ray microscope (XRM) that bridge the imaging gap by providing multiscale high-resolution three-dimensional (3D) volumes of intact plant samples from the cell to the whole plant level. Serial imaging of a single sample is shown to provide sub-micron 3D volumes co-registered with lower magnification scans for explicit contextual reference. High-quality 3D volume data from our enhanced methods facilitate sophisticated and effective computational segmentation. Advances in sample preparation make multimodal correlative imaging workflows possible, where a single resin-embedded plant sample is scanned via XRM to generate a 3D cell-level map, and then used to identify and zoom in on sub-cellular regions of interest for high-resolution scanning electron microscopy. In total, we present the methodologies for use of XRM in the multiscale and multimodal analysis of 3D plant features using numerous economically and scientifically important plant systems.

Deciphering tumour tissue organization by 3D electron microscopy and machine learning

Despite recent progress in the characterization of tumour components, the tri-dimensional (3D) organization of this pathological tissue and the parameters determining its internal architecture remain elusive. Here, we analysed the spatial organization of patient-derived xenograft tissues generated from hepatoblastoma, the most frequent childhood liver tumour, by serial block-face scanning electron microscopy using an integrated workflow combining 3D imaging, manual and machine learning-based semi-automatic segmentations, mathematics and infographics. By digitally reconstituting an entire hepatoblastoma sample with a blood capillary, a bile canaliculus-like structure, hundreds of tumour cells and their main organelles (e.g. cytoplasm, nucleus, mitochondria), we report unique 3D ultrastructural data about the organization of tumour tissue. We found that the size of hepatoblastoma cells correlates with the size of their nucleus, cytoplasm and mitochondrial mass. We also found anatomical connections between the blood capillary and the planar alignment and size of tumour cells in their 3D milieu. Finally, a set of tumour cells polarized in the direction of a hot spot corresponding to a bile canaliculus-like structure. In conclusion, this pilot study allowed the identification of bioarchitectural parameters that shape the internal and spatial organization of tumours, thus paving the way for future investigations in the emerging onconanotomy field.

de Senneville et al. demonstrate an integrated workflow combining 3D imaging, manual and machine learning-based semi-automatic segmentation, mathematics and infographics to study the spatial organization of patient-derived hepatoblastoma xenograft tissues. Their approach potentially assists investigations of this childhood liver tumour and other types of tumour tissues.

Aligned Organization of Synapses and Mitochondria in Auditory Hair Cells

Recent studies have revealed great functional and structural heterogeneity in the ribbon-type synapses at the basolateral pole of the isopotential inner hair cell (IHC). This feature is believed to be critical for audition over a wide dynamic range, but whether the spatial gradient of ribbon morphology is fine-tuned in each IHC and how the mitochondrial network is organized to meet local energy demands of synaptic transmission remain unclear. By means of three-dimensional electron microscopy and artificial intelligence-based algorithms, we demonstrated the cell-wide structural quantification of ribbons and mitochondria in mature mid-cochlear IHCs of mice. We found that adjacent IHCs in staggered pairs differ substantially in cell body shape and ribbon morphology gradient as well as mitochondrial organization. Moreover, our analysis argues for a location-specific arrangement of correlated ribbon and mitochondrial function at the basolateral IHC pole.