An open-access volume electron microscopy atlas of whole cells and tissues

Immuno-scanning electron microscopy of islet primary cilia

The definitive demonstration of protein localization on primary cilia has been a challenge for cilia biologists. Primary cilia are solitary thread-like projections that have a specialized protein composition, but as the ciliary structure overlays the cell membrane and other cell parts, the identity of ciliary proteins are difficult to ascertain by conventional imaging approaches like immunofluorescence microscopy. Surface scanning electron microscopy combined with immunolabeling (immuno-SEM) bypasses some of these indeterminacies by unambiguously showing protein expression in the context of the three-dimensional ultrastructure of the cilium. Here, we apply immuno-SEM to specifically identify proteins on the primary cilia of mouse and human pancreatic islets, including post-translationally modified tubulin, intraflagellar transport (IFT)88, the small GTPase Arl13b, as well as subunits of axonemal dynein. Key parameters in sample preparation, immunolabeling and imaging acquisition are discussed to facilitate similar studies by others in the cilia research community.

Micron-resolution fiber mapping in histology independent of sample preparation

Detailed knowledge of the brain's nerve fiber network is crucial for understanding its function in health and disease. However, mapping fibers with high resolution remains prohibitive in most histological sections because state-of-the-art techniques are incompatible with their preparation. Here, we present a micron-resolution light-scattering-based technique that reveals intricate fiber networks independent of sample preparation for extended fields of view. We uncover fiber structures in both label-free and stained, paraffin-embedded and deparaffinized, newly-prepared and archived, animal and human brain tissues - including whole-brain sections from the BigBrain atlas. We identify altered microstructures in demyelination and hippocampal neurodegeneration, and show key advantages over diffusion magnetic resonance imaging, polarization microscopy, and structure tensor analysis. We also reveal structures in non-brain tissues - including muscle, bone, and blood vessels. Our cost-effective, versatile technique enables studies of intricate fiber networks in any type of histological tissue section, offering a new dimension to neuroscientific and biomedical research.

Precise subcellular targeting approaches for organelle-related disorders

Pharmacological research has expanded to the nanoscale level with advanced imaging technologies, enabling the analysis of drug distribution at the cellular organelle level. These advances in research techniques have contributed to the targeting of cellular organelles to address the fundamental causes of diseases. Beyond navigating the hurdles of reaching lesion tissues upon administration and identifying target cells within these tissues, controlling drug accumulation at the organelle level is the most refined method of disease management. This approach opens new avenues for the development of more potent therapeutic strategies by delving into the intricate roles and interplay of cellular organelles. Thus, organelle-targeted approaches help overcome the limitations of conventional therapies by precisely regulating functionally compartmentalized spaces based on their environment. This review discusses the basic concepts of organelle targeting research and proposes strategies to target diseases arising from organelle dysfunction. We also address the current challenges faced by organelle targeting and explore future research directions.

Sarcomere, troponin, and myosin X-ray diffraction signals can be resolved in single cardiomyocytes

Cardiac function relies on the autonomous molecular contraction mechanisms in the ventricular wall. Contraction is driven by ordered motor proteins acting in parallel to generate a macroscopic force. The averaged structure can be investigated by diffraction from model tissues such as trabecular and papillary cardiac muscle using collimated synchrotron beams, offering high resolution in reciprocal space. In the ventricular wall, however, the muscle tissue is compartmentalized into smaller branched cardiomyocytes, with a higher degree of disorder. We show that X-ray diffraction is now also capable of resolving the structural organization of actomyosin in single isolated cardiomyocytes of the ventricular wall. In addition to the hexagonal arrangement of thick and thin filaments, the diffraction signal of the hydrated and fixated cardiomyocytes was sufficient to reveal the myosin motor repeat (M3), the troponin complex repeat (Tn), and the sarcomere length. The sarcomere length signal comprised up to 13 diffraction orders, which were used to compute the sarcomere density profile based on Fourier synthesis. The Tn and M3 spacings were found in the same range as previously reported for other muscle types. The approach opens up a pathway to record the structural dynamics of living cells during the contraction cycle, toward a more complete understanding of cardiac muscle function.

Unraveling the ultrastructure and dynamics of autophagic vesicles: Insights from advanced imaging techniques

Autophagy, an intracellular self-degradation process, is governed by a complex interplay of signaling pathways and interactions between proteins and organelles. Its fundamental purpose is to efficiently clear and recycle cellular components that are damaged or redundant. Central to this process are autophagic vesicles, specialized structures that encapsulate targeted cellular elements, playing a pivotal role in autophagy. Despite growing interest in the molecular components of autophagic machinery and their regulatory mechanisms, capturing the detailed ultrastructural dynamics of autophagosome formation continues to present significant challenges. However, recent advancements in microscopy, particularly in electron microscopy, have begun to illuminate the dynamic regulatory processes underpinning autophagy. This review endeavors to provide an exhaustive overview of contemporary research on the ultrastructure of autophagic processes. By synthesizing observations from diverse technological methodologies, this review seeks to deepen our understanding of the genesis of autophagic vesicles, their membrane origins, and the dynamic alterations that transpire during the autophagy process. The aim is to bridge gaps in current knowledge and foster a more comprehensive comprehension of this crucial cellular mechanism.

The endoplasmic reticulum connects to the nucleus by constricted junctions that mature after mitosis

Junctions between the endoplasmic reticulum (ER) and the outer membrane of the nuclear envelope (NE) physically connect both organelles. These ER-NE junctions are essential for supplying the NE with lipids and proteins synthesized in the ER. However, little is known about the structure of these ER-NE junctions. Here, we systematically study the ultrastructure of ER-NE junctions in cryo-fixed mammalian cells staged in anaphase, telophase, and interphase by correlating live cell imaging with three-dimensional electron microscopy. Our results show that ER-NE junctions in interphase cells have a pronounced hourglass shape with a constricted neck of 7-20 nm width. This morphology is significantly distinct from that of junctions within the ER network, and their morphology emerges as early as telophase. The highly constricted ER-NE junctions are seen in several mammalian cell types, but not in budding yeast. We speculate that the unique and highly constricted ER-NE junctions are regulated via novel mechanisms that contribute to ER-to-NE lipid and protein traffic in higher eukaryotes.

Pleomorphism in Biological Units of Life: Morphological Heterogeneity in Cells Does Not Translate Uniformly to Subcellular Components

The interplay of the three-dimensional (3D) distribution of various subcellular components and their interactions are expected to control overall cellular morphology in biology. In this study, we aimed to determine whether the pleomorphy observed at the whole-cell level is being reflected by the components constituting the cells by focusing on the 3D distribution of pixel intensities at the single-cell level of the whole (cell) and its parts (the seven subcellular components of the cells-self-assemblies of smaller units). We rigorously acquired and analyzed the image data of RAW264.7 cells at the single-cell level. We report asymmetries in the spatial distribution of pixel intensities at the whole-cell and subcellular component levels along with the occurrence of alterations when pleomorphism is reduced by synchronization of the cell cycle. From our repertoire of seven subcellular components, we report ER, mitochondria, and tubulin to be independent of whole-cell apico-basal heterogeneity of optical density while nuclear, plasma membrane, lysosomal, and actin fluorescence distributions are found to contribute to the apico-basal polarity of the whole cell. While doing so, we have also developed an image analysis algorithm utilizing 2D segmentation to analyze the single cells in 3D using confocal microscopy, a technique that allows us to analyze cellular states in their native hydrated state.

COPII with ALG2 and ESCRTs control lysosome-dependent microautophagy of ER exit sites

Endoplasmic reticulum exit sites (ERESs) are tubular outgrowths of endoplasmic reticulum that serve as the earliest station for protein sorting and export into the secretory pathway. How these structures respond to different cellular conditions remains unclear. Here, we report that ERESs undergo lysosome-dependent microautophagy when Ca2+ is released by lysosomes in response to nutrient stressors such as mTOR inhibition or amino acid starvation in mammalian cells. Targeting and uptake of ERESs into lysosomes were observed by super-resolution live-cell imaging and focus ion beam scanning electron microscopy (FIB-SEM). The mechanism was ESCRT dependent and required ubiquitinated SEC31, ALG2, and ALIX, with a knockout of ALG2 or function-blocking mutations of ALIX preventing engulfment of ERESs by lysosomes. In vitro, reconstitution of the pathway was possible using lysosomal lipid-mimicking giant unilamellar vesicles and purified recombinant components. Together, these findings demonstrate a pathway of lysosome-dependent ERES microautophagy mediated by COPII, ALG2, and ESCRTS induced by nutrient stress.

Paracrine Signaling by Pancreatic Islet Cilia

The primary cilium is a sensory and signaling organelle present on most pancreatic islet endocrine cells, where it receives and interprets a wide range of intra-islet chemical cues including hormones, peptides, and neurotransmitters. The ciliary membrane possesses a molecular composition distinct from the plasma membrane, with enrichment of signaling mediators including G protein-coupled receptors (GPCRs), tyrosine kinase family receptors, membrane transporters and others. When activated, these membrane proteins interact with ion channels and adenylyl cyclases to trigger local Ca2+ and cAMP activity and transmit signals to the cell body. Here we review evidence supporting the emerging model in which primary cilia on pancreatic islet cells play a central role in the intra-islet communication network and discuss how changes in cilia-mediated paracrine function in islet cells might lead to diabetes.

Diffusion-based deep learning method for augmenting ultrastructural imaging and volume electron microscopy

Electron microscopy (EM) revolutionized the way to visualize cellular ultrastructure. Volume EM (vEM) has further broadened its three-dimensional nanoscale imaging capacity. However, intrinsic trade-offs between imaging speed and quality of EM restrict the attainable imaging area and volume. Isotropic imaging with vEM for large biological volumes remains unachievable. Here, we developed EMDiffuse, a suite of algorithms designed to enhance EM and vEM capabilities, leveraging the cutting-edge image generation diffusion model. EMDiffuse generates realistic predictions with high resolution ultrastructural details and exhibits robust transferability by taking only one pair of images of 3 megapixels to fine-tune in denoising and super-resolution tasks. EMDiffuse also demonstrated proficiency in the isotropic vEM reconstruction task, generating isotropic volume even in the absence of isotropic training data. We demonstrated the robustness of EMDiffuse by generating isotropic volumes from seven public datasets obtained from different vEM techniques and instruments. The generated isotropic volume enables accurate three-dimensional nanoscale ultrastructure analysis. EMDiffuse also features self-assessment functionalities on predictions' reliability. We envision EMDiffuse to pave the way for investigations of the intricate subcellular nanoscale ultrastructure within large volumes of biological systems.

Connectome-driven neural inventory of a complete visual system

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain's volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly's visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the ~53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

Spatial mapping of hepatic ER and mitochondria architecture reveals zonated remodeling in fasting and obesity

The hepatocytes within the liver present an immense capacity to adapt to changes in nutrient availability. Here, by using high resolution volume electron microscopy, we map how hepatic subcellular spatial organization is regulated during nutritional fluctuations and as a function of liver zonation. We identify that fasting leads to remodeling of endoplasmic reticulum (ER) architecture in hepatocytes, characterized by the induction of single rough ER sheet around the mitochondria, which becomes larger and flatter. These alterations are enriched in periportal and mid-lobular hepatocytes but not in pericentral hepatocytes. Gain- and loss-of-function in vivo models demonstrate that the Ribosome receptor binding protein1 (RRBP1) is required to enable fasting-induced ER sheet-mitochondria interactions and to regulate hepatic fatty acid oxidation. Endogenous RRBP1 is enriched around periportal and mid-lobular regions of the liver. In obesity, ER-mitochondria interactions are distinct and fasting fails to induce rough ER sheet-mitochondrion interactions. These findings illustrate the importance of a regulated molecular architecture for hepatocyte metabolic flexibility.

Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and spatial analysis is necessary. Here we describe a practical and annotation-efficient pipeline for organelle-specific segmentation, spatial analysis and visualization of large volume electron microscopy datasets using freely available, user-friendly software tools that can be run on a single standard workstation. The procedures are aimed at researchers in the life sciences with modest computational expertise, who use volume electron microscopy and need to generate three-dimensional (3D) segmentation labels for different types of cell organelles while minimizing manual annotation efforts, to analyze the spatial interactions between organelle instances and to visualize the 3D segmentation results. We provide detailed guidelines for choosing well-suited segmentation tools for specific cell organelles, and to bridge compatibility issues between freely available open-source tools, we distribute the critical steps as easily installable Album solutions for deep learning segmentation, spatial analysis and 3D rendering. Our detailed description can serve as a reference for similar projects requiring particular strategies for single- or multiple-organelle analysis, which can be achieved with computational resources commonly available to single-user setups.

Time-series reconstruction of the molecular architecture of human centriole assembly

Centriole biogenesis, as in most organelle assemblies, involves the sequential recruitment of sub-structural elements that will support its function. To uncover this process, we correlated the spatial location of 24 centriolar proteins with structural features using expansion microscopy. A time-series reconstruction of protein distributions throughout human procentriole assembly unveiled the molecular architecture of the centriole biogenesis steps. We found that the process initiates with the formation of a naked cartwheel devoid of microtubules. Next, the bloom phase progresses with microtubule blade assembly, concomitantly with radial separation and rapid cartwheel growth. In the subsequent elongation phase, the tubulin backbone grows linearly with the recruitment of the A-C linker, followed by proteins of the inner scaffold (IS). By following six structural modules, we modeled 4D assembly of the human centriole. Collectively, this work provides a framework to investigate the spatial and temporal assembly of large macromolecules.

OSBP-mediated PI(4)P-cholesterol exchange at endoplasmic reticulum-secretory granule contact sites controls insulin secretion

Insulin is packaged into secretory granules that depart the Golgi and undergo a maturation process that involves changes in the protein and lipid composition of the granules. Here, we show that insulin secretory granules form physical contacts with the endoplasmic reticulum and that the lipid exchange protein oxysterol-binding protein (OSBP) is recruited to these sites in a Ca2+-dependent manner. OSBP binding to insulin granules is positively regulated by phosphatidylinositol-4 (PI4)-kinases and negatively regulated by the PI4 phosphate (PI(4)P) phosphatase Sac2. Loss of Sac2 results in excess accumulation of cholesterol on insulin granules that is normalized when OSBP expression is reduced, and both acute inhibition and small interfering RNA (siRNA)-mediated knockdown of OSBP suppress glucose-stimulated insulin secretion without affecting insulin production or intracellular Ca2+ signaling. In conclusion, we show that lipid exchange at endoplasmic reticulum (ER)-granule contact sites is involved in the exocytic process and propose that these contacts act as reaction centers with multimodal functions during insulin granule maturation.

Morphomics via next-generation electron microscopy

The living body is composed of innumerable fine and complex structures. Although these structures have been studied in the past, a vast amount of information pertaining to them still remains unknown. When attempting to observe these ultra-structures, the use of electron microscopy (EM) has become indispensable. However, conventional EM settings are limited to a narrow tissue area, which can bias observations. Recently, new trends in EM research have emerged, enabling coverage of far broader, nano-scale fields of view for two-dimensional wide areas and three-dimensional large volumes. Moreover, cutting-edge bioimage informatics conducted via deep learning has accelerated the quantification of complex morphological bioimages. Taken together, these technological and analytical advances have led to the comprehensive acquisition and quantification of cellular morphology, which now arises as a new omics science termed 'morphomics'.

Bridging structural and cell biology with cryo-electron microscopy

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

Immuno-Scanning Electron Microscopy of Islet Primary Cilia

The definitive demonstration of protein localization on primary cilia has been a challenge for cilia biologists. Primary cilia are solitary thread-like projections that contain specialized protein composition, but as the ciliary structure overlays the cell membrane and other cell parts, the identity of ciliary proteins are difficult to ascertain by conventional imaging approaches like immunofluorescence microscopy. Surface scanning electron microscopy combined with immuno-labeling (immuno-SEM) bypasses some of these indeterminacies by unambiguously showing protein expression in the context of the 3D ultrastructure of the cilium. Here we apply immuno-SEM to specifically identify proteins on the primary cilia of mouse and human pancreatic islets, including post-translationally modified tubulin, intraflagellar transport (IFT) 88, the small GTPase Arl13b, as well as subunits of axonemal dynein. Key parameters in sample preparation, immuno-labeling, and imaging acquisition are discussed to facilitate similar studies by others in the cilia research community.

Organelle morphology and positioning orchestrate physiological and disease-associated processes

In cells, organelles are distributed nonrandomly to regulate cells' physiological and disease-associated processes. Based on their morphology, position within the cell, and contacts with other organelles, they exert different biological functions. Endo-lysosomes are critical cell metabolism and nutrient-sensing regulators modulating cell growth and cellular adaptation in response to nutrient availability. Their spatial distribution is intimately linked to their function. In this review, we will discuss the role of endolysosomes under physiological conditions and in the context of cancer progression, with a special focus on their morphology, the molecular mechanisms determining their subcellular position, and the contacts they form with other organelles. We aim to highlight the relationship between cell architecture and cell function and its impact on maintaining organismal homeostasis.

Motion of VAPB molecules reveals ER-mitochondria contact site subdomains

To coordinate cellular physiology, eukaryotic cells rely on the rapid exchange of molecules at specialized organelle-organelle contact sites1,2. Endoplasmic reticulum-mitochondrial contact sites (ERMCSs) are particularly vital communication hubs, playing key roles in the exchange of signalling molecules, lipids and metabolites3,4. ERMCSs are maintained by interactions between complementary tethering molecules on the surface of each organelle5,6. However, due to the extreme sensitivity of these membrane interfaces to experimental perturbation7,8, a clear understanding of their nanoscale organization and regulation is still lacking. Here we combine three-dimensional electron microscopy with high-speed molecular tracking of a model organelle tether, Vesicle-associated membrane protein (VAMP)-associated protein B (VAPB), to map the structure and diffusion landscape of ERMCSs. We uncovered dynamic subdomains within VAPB contact sites that correlate with ER membrane curvature and undergo rapid remodelling. We show that VAPB molecules enter and leave ERMCSs within seconds, despite the contact site itself remaining stable over much longer time scales. This metastability allows ERMCSs to remodel with changes in the physiological environment to accommodate metabolic needs of the cell. An amyotrophic lateral sclerosis-associated mutation in VAPB perturbs these subdomains, likely impairing their remodelling capacity and resulting in impaired interorganelle communication. These results establish high-speed single-molecule imaging as a new tool for mapping the structure of contact site interfaces and reveal that the diffusion landscape of VAPB at contact sites is a crucial component of ERMCS homeostasis.

In situ label-free X-ray imaging for visualizing the localization of nanomedicines and subcellular architecture in intact single cells

Understanding the intracellular behaviors of nanomedicines and morphology variation of subcellular architecture impacted by nanomaterial-biology (nano-bio) interactions could help guide the safe-by-design, manufacturing and evaluation of nanomedicines for clinical translation. The in situ and label-free analysis of nano-bio interactions in intact single cells at nanoscale remains challenging. We developed an approach based on X-ray microscopy to directly visualize the 2D or 3D intracellular distribution without labeling at nanometer resolution and analyze the chemical transformation of nanomedicines in situ. Here, we describe an optimized workflow for cell sample preparation, beamline selection, data acquisition and analysis. With several model bionanomaterials as examples, we analyze the localization of nanomedicines in various primary blood cells, macrophages, dendritic cells, monocytes and cancer cells, as well as the morphology of some organelles with soft and hard X-rays. Our protocol has been successfully implemented at three beamline facilities: 4W1A of Beijing Synchrotron Radiation Facility, BL08U1A of Shanghai Synchrotron Radiation Facility and BL07W of the National Synchrotron Radiation Laboratory. This protocol can be completed in ~2-5 d, depending on the cell types, their incubation times with nanomaterials and the selected X-ray beamline. The protocol enables the in situ analysis of the varieties of metal-containing nanomaterials, visualization of intracellular endocytosis, distribution and excretion and corresponding subcellular morphological variation influenced by nanomedicines in cell lines or primary cells by using this universal and robust platform. The results facilitate the understanding of the true principle and mechanism underlying the nano-bio interaction.

Call to action to properly utilize electron microscopy to measure organelles to monitor disease

This review provides an overview of the current methods for quantifying mitochondrial ultrastructure, including cristae morphology, mitochondrial contact sites, and recycling machinery and a guide to utilizing electron microscopy to effectively measure these organelles. Quantitative analysis of mitochondrial ultrastructure is essential for understanding mitochondrial biology and developing therapeutic strategies for mitochondrial-related diseases. Techniques such as transmission electron microscopy (TEM) and serial block face-scanning electron microscopy, as well as how they can be combined with other techniques including confocal microscopy, super-resolution microscopy, and correlative light and electron microscopy are discussed. Beyond their limitations and challenges, we also offer specific magnifications that may be best suited for TEM analysis of mitochondrial, endoplasmic reticulum, and recycling machinery. Finally, perspectives on future quantification methods are offered.

Genetically encoded barcodes for correlative volume electron microscopy

While genetically encoded reporters are common for fluorescence microscopy, equivalent multiplexable gene reporters for electron microscopy (EM) are still scarce. Here, by installing a variable number of fixation-stable metal-interacting moieties in the lumen of encapsulin nanocompartments of different sizes, we developed a suite of spherically symmetric and concentric barcodes (EMcapsulins) that are readable by standard EM techniques. Six classes of EMcapsulins could be automatically segmented and differentiated. The coding capacity was further increased by arranging several EMcapsulins into distinct patterns via a set of rigid spacers of variable length. Fluorescent EMcapsulins were expressed to monitor subcellular structures in light and EM. Neuronal expression in Drosophila and mouse brains enabled the automatic identification of genetically defined cells in EM. EMcapsulins are compatible with transmission EM, scanning EM and focused ion beam scanning EM. The expandable palette of genetically controlled EM-readable barcodes can augment anatomical EM images with multiplexed gene expression maps.

Organic fluorescent probes for live-cell super-resolution imaging

The development of super-resolution technology has made it possible to investigate the ultrastructure of intracellular organelles by fluorescence microscopy, which has greatly facilitated the development of life sciences and biomedicine. To realize super-resolution imaging of living cells, both advanced imaging systems and excellent fluorescent probes are required. Traditional fluorescent probes have good availability, but that is not the case for probes for live-cell super-resolution imaging. In this review, we first introduce the principles of various super-resolution technologies and their probe requirements, then summarize the existing designs and delivery strategies of super-resolution probes for live-cell imaging, and finally provide a brief conclusion and overview of the future.

A complete reconstruction of the early visual system of an adult insect

For most model organisms in neuroscience, research into visual processing in the brain is difficult because of a lack of high-resolution maps that capture complex neuronal circuitry. The microinsect Megaphragma viggianii, because of its small size and non-trivial behavior, provides a unique opportunity for tractable whole-organism connectomics. We image its whole head using serial electron microscopy. We reconstruct its compound eye and analyze the optical properties of the ommatidia as well as the connectome of the first visual neuropil-the lamina. Compared with the fruit fly and the honeybee, Megaphragma visual system is highly simplified: it has 29 ommatidia per eye and 6 lamina neuron types. We report features that are both stereotypical among most ommatidia and specialized to some. By identifying the "barebones" circuits critical for flying insects, our results will facilitate constructing computational models of visual processing in insects.

Three-dimensional reconstructions of mechanosensory end organs suggest a unifying mechanism underlying dynamic, light touch

Across mammalian skin, structurally complex and diverse mechanosensory end organs respond to mechanical stimuli and enable our perception of dynamic, light touch. How forces act on morphologically dissimilar mechanosensory end organs of the skin to gate the requisite mechanotransduction channel Piezo2 and excite mechanosensory neurons is not understood. Here, we report high-resolution reconstructions of the hair follicle lanceolate complex, Meissner corpuscle, and Pacinian corpuscle and the subcellular distribution of Piezo2 within them. Across all three end organs, Piezo2 is restricted to the sensory axon membrane, including axon protrusions that extend from the axon body. These protrusions, which are numerous and elaborate extensively within the end organs, tether the axon to resident non-neuronal cells via adherens junctions. These findings support a unified model for dynamic touch in which mechanical stimuli stretch hundreds to thousands of axon protrusions across an end organ, opening proximal, axonal Piezo2 channels and exciting the neuron.

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.

Building the next generation of virtual cells to understand cellular biology

Cell science has made significant progress by focusing on understanding individual cellular processes through reductionist approaches. However, the sheer volume of knowledge collected presents challenges in integrating this information across different scales of space and time to comprehend cellular behaviors, as well as making the data and methods more accessible for the community to tackle complex biological questions. This perspective proposes the creation of next-generation virtual cells, which are dynamic 3D models that integrate information from diverse sources, including simulations, biophysical models, image-based models, and evidence-based knowledge graphs. These virtual cells would provide statistically accurate and holistic views of real cells, bridging the gap between theoretical concepts and experimental data, and facilitating productive new collaborations among researchers across related fields.

3D architecture and a bicellular mechanism of touch detection in mechanosensory corpuscle

Mechanosensory corpuscles detect transient touch and vibration in the skin of vertebrates, enabling precise sensation of the physical environment. The corpuscle contains a mechanoreceptor afferent surrounded by lamellar cells (LCs), but corpuscular ultrastructure and the role of LCs in touch detection are unknown. We report the three-dimensional architecture of the avian Meissner (Grandry) corpuscle acquired using enhanced focused ion beam scanning electron microscopy and machine learning-based segmentation. The corpuscle comprises a stack of LCs interdigitated with terminal endings from two afferents. Simultaneous electrophysiological recordings from both cell types revealed that mechanosensitive LCs use calcium influx to trigger action potentials in the afferent and thus serve as physiological touch sensors in the skin. The elaborate architecture and bicellular sensory mechanism in the corpuscles, which comprises the afferents and LCs, create the capacity for nuanced encoding of the submodalities of touch.

SEM3De: image restoration for FIB-SEM

Motivation

FIB-SEM (Focused Ion Beam-Scanning Electron Microscopy) is a technique to generate 3D images of samples up to several microns in depth. The principle is based on the alternate use of SEM to image the surface of the sample (a few nanometers thickness) and of FIB to mill the surface of the sample a few nanometers at the time. In this way, huge stacks of images can thus be acquired.Although this technique has proven useful in imaging biological systems, the presence of some visual artifacts (stripes due to sample milling, detector saturation, charge effects, focus or sample drift, etc.) still raises some challenges for image interpretation and analyses.

Results

With the aim of meeting these challenges, we developed a freeware (SEM3De) that either corrects artifacts with state-of-the-art approaches or, when artifacts are impossible to correct, enables the replacement of artifactual slices by an in-painted image created from adjacent non-artifactual slices. Thus, SEM3De improves the overall usability of FIB-SEM acquisitions.

Availability and implementation

SEM3De can be downloaded from https://sourceforge.net/projects/sem3de/ as a plugin for ImageJ.

Online citizen science with the Zooniverse for analysis of biological volumetric data

Public participation in research, also known as citizen science, is being increasingly adopted for the analysis of biological volumetric data. Researchers working in this domain are applying online citizen science as a scalable distributed data analysis approach, with recent research demonstrating that non-experts can productively contribute to tasks such as the segmentation of organelles in volume electron microscopy data. This, alongside the growing challenge to rapidly process the large amounts of biological volumetric data now routinely produced, means there is increasing interest within the research community to apply online citizen science for the analysis of data in this context. Here, we synthesise core methodological principles and practices for applying citizen science for analysis of biological volumetric data. We collate and share the knowledge and experience of multiple research teams who have applied online citizen science for the analysis of volumetric biological data using the Zooniverse platform ( www.zooniverse.org ). We hope this provides inspiration and practical guidance regarding how contributor effort via online citizen science may be usefully applied in this domain.

An interactive deep learning-based approach reveals mitochondrial cristae topologies

The convolution of membranes called cristae is a critical structural and functional feature of mitochondria. Crista structure is highly diverse between different cell types, reflecting their role in metabolic adaptation. However, their precise three-dimensional (3D) arrangement requires volumetric analysis of serial electron microscopy and has therefore been limiting for unbiased quantitative assessment. Here, we developed a novel, publicly available, deep learning (DL)-based image analysis platform called Python-based human-in-the-loop workflow (PHILOW) implemented with a human-in-the-loop (HITL) algorithm. Analysis of dense, large, and isotropic volumes of focused ion beam-scanning electron microscopy (FIB-SEM) using PHILOW reveals the complex 3D nanostructure of both inner and outer mitochondrial membranes and provides deep, quantitative, structural features of cristae in a large number of individual mitochondria. This nanometer-scale analysis in micrometer-scale cellular contexts uncovers fundamental parameters of cristae, such as total surface area, orientation, tubular/lamellar cristae ratio, and crista junction density in individual mitochondria. Unbiased clustering analysis of our structural data unraveled a new function for the dynamin-related GTPase Optic Atrophy 1 (OPA1) in regulating the balance between lamellar versus tubular cristae subdomains.

Rediscovering Primary Cilia in Pancreatic Islets

Primary cilia are microtubule-based sensory and signaling organelles on the surfaces of most eukaryotic cells. Despite their early description by microscopy studies, islet cilia had not been examined in the functional context until recent decades. In pancreatic islets as in other tissues, primary cilia facilitate crucial developmental and signaling pathways in response to extracellular stimuli. Many human developmental and genetic disorders are associated with ciliary dysfunction, some manifesting as obesity and diabetes. Understanding the basis for metabolic diseases in human ciliopathies has been aided by close examination of cilia action in pancreatic islets at cellular and molecular levels. In this article, we review the evidence for ciliary expression on islet cells, known roles of cilia in pancreas development and islet hormone secretion, and summarize metabolic manifestations of human ciliopathy syndromes. We discuss emerging data on primary cilia regulation of islet cell signaling and the structural basis of cilia-mediated cell crosstalk, and offer our interpretation on the role of cilia in glucose homeostasis and human diseases.

Primary cilia as dynamic and diverse signalling hubs in development and disease

Primary cilia, antenna-like sensory organelles protruding from the surface of most vertebrate cell types, are essential for regulating signalling pathways during development and adult homeostasis. Mutations in genes affecting cilia cause an overlapping spectrum of >30 human diseases and syndromes, the ciliopathies. Given the immense structural and functional diversity of the mammalian cilia repertoire, there is a growing disconnect between patient genotype and associated phenotypes, with variable severity and expressivity characteristic of the ciliopathies as a group. Recent technological developments are rapidly advancing our understanding of the complex mechanisms that control biogenesis and function of primary cilia across a range of cell types and are starting to tackle this diversity. Here, we examine the structural and functional diversity of primary cilia, their dynamic regulation in different cellular and developmental contexts and their disruption in disease.

Multisite assessment of reproducibility in high-content cell migration imaging data

High-content image-based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high-quality open-access data sharing and meta-analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta-analysis of results from live-cell microscopy, have not been systematically investigated. Here, using high-content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta-analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image-based datasets of perturbation experiments. Thus, reproducible quantitative high-content cell image analysis of perturbation effects and meta-analysis depend on standardized procedures combined with batch correction.

Scanning electron microscopy of human islet cilia

Human islet primary cilia are vital glucose-regulating organelles whose structure remains uncharacterized. Scanning electron microscopy (SEM) is a useful technique for studying the surface morphology of membrane projections like cilia, but conventional sample preparation does not reveal the submembrane axonemal structure, which holds key implications for ciliary function. To overcome this challenge, we combined SEM with membrane-extraction techniques to examine primary cilia in native human islets. Our data show well-preserved cilia subdomains which demonstrate both expected and unexpected ultrastructural motifs. Morphometric features were quantified when possible, including axonemal length and diameter, microtubule conformations, and chirality. We further describe a ciliary ring, a structure that may be a specialization in human islets. Key findings are correlated with fluorescence microscopy and interpreted in the context of cilia function as a cellular sensor and communications locus in pancreatic islets.

A conditional strategy for cell-type-specific labeling of endogenous excitatory synapses in Drosophila

Chemical neurotransmission occurs at specialized contacts where neurotransmitter release machinery apposes neurotransmitter receptors to underlie circuit function. A series of complex events underlies pre- and postsynaptic protein recruitment to neuronal connections. To better study synaptic development in individual neurons, we need cell-type-specific strategies to visualize endogenous synaptic proteins. Although presynaptic strategies exist, postsynaptic proteins remain less studied because of a paucity of cell-type-specific reagents. To study excitatory postsynapses with cell-type specificity, we engineered dlg1[4K], a conditionally labeled marker of Drosophila excitatory postsynaptic densities. With binary expression systems, dlg1[4K] labels central and peripheral postsynapses in larvae and adults. Using dlg1[4K], we find that distinct rules govern postsynaptic organization in adult neurons, multiple binary expression systems can concurrently label pre- and postsynapse in a cell-type-specific manner, and neuronal DLG1 can sometimes localize presynaptically. These results validate our strategy for conditional postsynaptic labeling and demonstrate principles of synaptic organization.

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.

3D architecture and a bi-cellular mechanism of touch detection in mechanosensory corpuscle

Mechanosensory corpuscles detect transient touch and vibratory signals in the skin of vertebrates, enabling navigation, foraging, and precise manipulation of objects 1 . The corpuscle core comprises a terminal neurite of a mechanoreceptor afferent, the only known touch-sensing element within corpuscles, surrounded by terminal Schwann cells called lamellar cells (LCs) 2â€"4 . However, the precise corpuscular ultrastructure, and the role of LCs in touch detection are unknown. Here we used enhanced focused ion beam scanning electron microscopy and electron tomography to reveal the three-dimensional architecture of avian Meissner (Grandry) corpuscle 5 . We show that corpuscles contain a stack of LCs innervated by two afferents, which form large-area contacts with LCs. LCs form tether-like connections with the afferent membrane and contain dense core vesicles which release their content onto the afferent. Furthermore, by performing simultaneous electrophysiological recordings from both cell types, we show that mechanosensitive LCs use calcium influx to trigger action potential firing in the afferent and thus serve as physiological touch sensors in the skin. Our findings suggest a bi-cellular mechanism of touch detection, which comprises the afferent and LCs, likely enables corpuscles to encode the nuances of tactile stimuli.

Methods of enhanced FIB-SEM sample preparation and image acquisition

The ability to view biomolecules in cells and measure changes in their structure, quantity, distribution, and interaction is fundamental to understanding biology. By coupling nano -scale resolution with meso and even macro scale volumes, the enhanced focused ion beam-scanning electron microscopy (FIB-SEM) pipeline has enabled numerous transformational discoveries in life science, many of which were major new landmarks in their fields. This pipeline consists of EM sample preparation, FIB-SEM sample preparation, FIB-SEM imaging, data alignment, and image analysis. While the EM sample preparation, data alignment, and image analysis are consistent with those from other volume Electron Microscopy (vEM) approaches, the enhanced FIB-SEM sample preparation and imaging are unique to the rest of comparable methods. We here illustrate the detailed methods of enhanced FIB-SEM sample preparation and image acquisition that have not been previously described. These methods can also be applied to the conventional FIB-SEM platforms for improved image acquisition quality and pipeline throughput.

Three-dimensional reconstructions of mechanosensory end organs suggest a unifying mechanism underlying dynamic, light touch

Specialized mechanosensory end organs within mammalian skin-hair follicle-associated lanceolate complexes, Meissner corpuscles, and Pacinian corpuscles-enable our perception of light, dynamic touch 1 . In each of these end organs, fast-conducting mechanically sensitive neurons, called Aβ low-threshold mechanoreceptors (Aβ LTMRs), associate with resident glial cells, known as terminal Schwann cells (TSCs) or lamellar cells, to form complex axon ending structures. Lanceolate-forming and corpuscle-innervating Aβ LTMRs share a low threshold for mechanical activation, a rapidly adapting (RA) response to force indentation, and high sensitivity to dynamic stimuli 1-6 . How mechanical stimuli lead to activation of the requisite mechanotransduction channel Piezo2 7-15 and Aβ RA-LTMR excitation across the morphologically dissimilar mechanosensory end organ structures is not understood. Here, we report the precise subcellular distribution of Piezo2 and high-resolution, isotropic 3D reconstructions of all three end organs formed by Aβ RA-LTMRs determined by large volume enhanced Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) imaging. We found that within each end organ, Piezo2 is enriched along the sensory axon membrane and is minimally or not expressed in TSCs and lamellar cells. We also observed a large number of small cytoplasmic protrusions enriched along the Aβ RA-LTMR axon terminals associated with hair follicles, Meissner corpuscles, and Pacinian corpuscles. These axon protrusions reside within close proximity to axonal Piezo2, occasionally contain the channel, and often form adherens junctions with nearby non-neuronal cells. Our findings support a unified model for Aβ RA-LTMR activation in which axon protrusions anchor Aβ RA-LTMR axon terminals to specialized end organ cells, enabling mechanical stimuli to stretch the axon in hundreds to thousands of sites across an individual end organ and leading to activation of proximal Piezo2 channels and excitation of the neuron.

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.

Toward scalable reuse of vEM data: OME-Zarr to the rescue

The growing size of EM volumes is a significant barrier to findable, accessible, interoperable, and reusable (FAIR) sharing. Storage, sharing, visualization and processing are challenging for large datasets. Here we discuss a recent development toward the standardized storage of volume electron microscopy (vEM) data which addresses many of the issues that researchers face. The OME-Zarr format splits data into more manageable, performant chunks enabling streaming-based access, and unifies important metadata such as multiresolution pyramid descriptions. The file format is designed for centralized and remote storage (e.g., cloud storage or file system) and is therefore ideal for sharing large data. By coalescing on a common, community-wide format, these benefits will expand as ever more data is made available to the scientific community.

Scanning electron microscopy of human islet cilia

Human islet primary cilia are vital glucose-regulating organelles whose structure remains uncharacterized. Scanning electron microscopy (SEM) is a useful technique for studying the surface morphology of membrane projections like primary cilia, but conventional sample preparation does not reveal the sub-membrane axonemal structure which holds key implications for cilia function. To overcome this challenge, we combined SEM with membrane-extraction techniques to examine cilia in native human islets. Our data show well-preserved cilia subdomains which demonstrate both expected and unexpected ultrastructural motifs. Morphometric features were quantified when possible, including axonemal length and diameter, microtubule conformations and chirality. We further describe a novel ciliary ring, a structure that may be a specialization in human islets. Key findings are correlated with fluorescence microscopy and interpreted in the context of cilia function as a cellular sensor and communications locus in pancreatic islets.

Deep neural network automated segmentation of cellular structures in volume electron microscopy

Volume electron microscopy is an important imaging modality in contemporary cell biology. Identification of intracellular structures is a laborious process limiting the effective use of this potentially powerful tool. We resolved this bottleneck with automated segmentation of intracellular substructures in electron microscopy (ASEM), a new pipeline to train a convolutional neural network to detect structures of a wide range in size and complexity. We obtained dedicated models for each structure based on a small number of sparsely annotated ground truth images from only one or two cells. Model generalization was improved with a rapid, computationally effective strategy to refine a trained model by including a few additional annotations. We identified mitochondria, Golgi apparatus, endoplasmic reticulum, nuclear pore complexes, caveolae, clathrin-coated pits, and vesicles imaged by focused ion beam scanning electron microscopy. We uncovered a wide range of membrane-nuclear pore diameters within a single cell and derived morphological metrics from clathrin-coated pits and vesicles, consistent with the classical constant-growth assembly model.

Pumping up the volume

The time and cost of annotating ground-truth images and network training are major challenges to utilizing machine learning to automate the mining of volume electron microscopy data. In this issue, Gallusser et al. (2023. J. Cell Biol.https://doi.org/10.1083/jcb.202208005) present a less computationally intense pipeline to detect a single type of organelle using a limited number of loosely annotated images.