Case studiesDiscover our selection of volume EM related case studies!
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vEM reveals the cellular composition of the Blood Nerve Barrier
DOI: 10.5281/zenodo.13912395
Authors: Giulia Casal*, Ian White*, Jemima Burden* & Alison C. Lloyd*
*Laboratory for Molecular Cell Biology, University College London, UK
Authors: Giulia Casal*, Ian White*, Jemima Burden* & Alison C. Lloyd*
*Laboratory for Molecular Cell Biology, University College London, UK
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CHALLENGE
The blood barriers of the nervous system are essential for protecting neural tissues and maintaining homeostasis. While the blood-brain barrier (BBB) of the central nervous system (CNS) is well characterized, comprising a monolayer of endothelial cells supported by nearly complete pericyte and astrocyte coverage, there is a lack of comparable understanding in the peripheral nervous system (PNS). In the CNS, the microenvironment of the BBB is critical for its barrier properties1. However, the structure and regulation of the blood-nerve barrier (BNB) in the PNS remain poorly understood. The BNB plays a crucial role in PNS function, yet its vascular component (EndoVs) and its cellular composition have not been described to date, despite the importance of the BNB for PNS function, with disruption associated with disorders such as diabetes and neuropathies2,3. TECHNIQUE: AT-SEM Array Tomography-SEM (AT-SEM)5 provides 3D ultrastructural information about a sample by sequentially imaging a region of interest (ROI) in a series of ultrathin sections of that sample. The sections are cut from a heavy metal stained and resin embedded sample, and are collected in series order onto a solid conductive substrate such as silicon wafer or ITO coated coverslip for imaging in the SEM5. The resulting data stack can then be analysed for 3D information such as surface areas, blood vessel coverage and the extent of cell to cell interactions. Unlike other vEM techniques AT-SEM is non destructive so samples can be reinterrogated as often as required, at different resolutions and multiple ROI imaged. AT-SEM is particularly useful when following structures that meander through a sample, e.g. blood vessels, as their locations are visible at the onset of imaging and can be easily tracked. REFERENCES
(1) Nolan et al., 2013 Developmental Cell (2) Kanda, 2013 Journal of Neurology, Neurosurgery, and Psychiatry (3) Richner et al., 2019 Frontiers in Neuroscience (4) Micheva and Smith., 2007 Neuron (5) White and Burden, 2023 Methods in Cell Biology (6) Denk and Horstmann, 2004 PLoS Biology (7) Malong, Napoli, Casal et al., 2023 Developmental Cell |
RESEARCH
Using Serial Block-Face-SEM6 and AT-SEM, we characterized the cellular composition and interactions along EndoBVs7. Unlike the BBB, we observed that the vasculature within the endoneurium is not completely covered. Upon closer examination of the cells in contact with EndoBVs, we identified three distinct cell types frequently interacting with the vasculature. Pericytes were found embedded within the basement membrane, while two other cell types were closely associated with the BM. Using correlative light and electron microscopy (CLEM), we identified these cells as fibroblast-like tactocytes and macrophages, confirmed by their canonical markers. In conclusion, our application of vEM provided an unbiased characterization of the cellular composition of the vascular unit in the BNB. 
Endothelial cells (left EM cross section: blue, right EM reconstruction: white) surrounded by cells of the vascular unit.
IMPACT
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Kidney elastic fiber network changes in Marfan’s Syndrome
DOI: https://doi.org/10.1242/focalplane.21066
Authors: de Souza RB*, Meek KM#, Lewis PN#, Pereira LV*.
*Department of Genetics and Evolutionary Biology, University of São Paulo, Brazil
#StructuralbBiophysics Research Group, School of Optometry and Vision Sciences of the United Kingdom, Cardiff University, UK
Authors: de Souza RB*, Meek KM#, Lewis PN#, Pereira LV*.
*Department of Genetics and Evolutionary Biology, University of São Paulo, Brazil
#StructuralbBiophysics Research Group, School of Optometry and Vision Sciences of the United Kingdom, Cardiff University, UK
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CHALLENGE
Marfan’s syndrome (MFS) is an autosomal dominant disorder that affects the connective tissue, resulting from a mutation in the FBN1 gene. This gene encodes fibrillin-1, a major structural component of the extracellular matrix, specifically the elastic fiber system. Our research discovered that in MFS mouse models, the kidney glomerulus (the filtering unit of the kidney) exhibited a smaller size and reduced hemodynamic capillary flow. Our challenge was to investigate the potential contribution of changes in the fibers of the elastic fiber system (FEFS) to this kidney phenotype. This necessitated the visualization of the entire functional unit of the mouse glomerulus capillary network.
Datasets from the prepared specimens were acquired using a Sigma Zeiss SEM equipped with a Gatan 3view system. Data sets consisting of up to 1000 4k x 4k images were acquired every 75nm at a pixel resolution of 7.3nm. Amira 3D visualization software was employed for 3D modeling of the data.
RESEARCH
Our study revealed that in the normal wild-type mouse (WT a and b), the FEFS is organized in a tubular-shaped network within a capillary. MFS mouse model (MFS c and d) exhibited FEFS fragmentation with a loss of capillary structure. These 3D observations were crucial evidence supporting our conclusion that the loss of capillary elasticity leads to reduced hemodynamic flow². |
3D structural organization of the FEFS of the glomerulus. FEFS are shown in red; capillary in yellow dotted line and cells in blue. WT group presents FEFS arranged in a tubular-shaped network (white arrow WTb) within the capillary. MFS group showed fractured FEFS (black arrow MFSd). WTa and MFSc superior plane; WTb and MFSd lateral plane.
IMPACT
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REFERENCES
(1) Lewis et al. Contrast-enhansed tissue processing of fibrallin-rich elastic fibres for 3D visulisation by volume scanning electron microscopy Methods Protoc. 2021, 4(3), 56; https://doi.org/10.3390/mps4030056
(2) de Souza RB, et al. Extracellular matrix and vascular dynamics in the kidney of a murine model for Marfan syndrome. PLoS One. 2023. 9;18(5):e0285418.
(1) Lewis et al. Contrast-enhansed tissue processing of fibrallin-rich elastic fibres for 3D visulisation by volume scanning electron microscopy Methods Protoc. 2021, 4(3), 56; https://doi.org/10.3390/mps4030056
(2) de Souza RB, et al. Extracellular matrix and vascular dynamics in the kidney of a murine model for Marfan syndrome. PLoS One. 2023. 9;18(5):e0285418.
Targeted vCLEM of heterogeneous samples
DOI: https://doi.org/10.1242/focalplane.18165
Authors: Karel Mocaer* and Paolo Ronchi#
*Schwab Team and #EMCF, EMBL Heidelberg, Germany
Authors: Karel Mocaer* and Paolo Ronchi#
*Schwab Team and #EMCF, EMBL Heidelberg, Germany
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CHALLENGE
Studying cells or events within their biological context (i.e. in tissues, ecosystem etc…) is highly relevant. However, volume EM techniques are limited in the volume that can be acquired. Therefore, targeting approaches are needed to characterize specific regions of interest. This is particularly important when investigating rare events in a heterogeneous sample. To overcome this bottleneck we have developed a targeting approach based on the fluorescence of exogenously tagged proteins¹, organic dyes², or autofluorescence³. TECHNIQUE: LM GUIDED FIB-SEM IMAGING
Focused ion beam – scanning electron microscopy (FIB-SEM) allows the acquisition of vEM data by combining iterative block surface imaging and ablation of thin layers of resin with an ion beam, thus providing 3D subcellular information. In order to target specific fluorescent events in an heterogeneous sample, we have developed a workflow that relies on the preservation of fluorescence when processing the sample for EM. We can then acquire a fluorescent 3D map of the resin block using a confocal microscope (e.g. Fig.1, reproduced from ³) and use it to efficiently target the vEM acquisition. As light microscopy and EM are performed on the same block post embedding, we can overlay the 2 datasets with high precision, thus associating molecular information with morphology (e.g. in Fig. 1, chlorophyll fluorescence in magenta overlaps with the chloroplast in a dinoflagellate. Reproduced from ³) REFERENCES
¹Ronchi et al, JCB, 2021; ²D’imprima et al, Dev Cell, 2023, ³Mocaer et al, JCS, 2023 |
RESEARCH
Using this method we could acquire a specific cell of interest from an heterogeneous marine environmental sample (Fig. 1) and perform a morphometric analysis of various organelles (Fig. 2, chloroplast in red and mitochondrion in green). The same workflow has also been applied to target fluorescent cells in Drosophila tissues¹ and organoids¹,².
IMPACT
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Deciphering cardiac multiscale organization
DOI: https://doi.org/10.1242/focalplane.17654
Authors: Sandra Rugonyi, Claudia López
Oregon Health & Science University, Portland Oregon, USA
Authors: Sandra Rugonyi, Claudia López
Oregon Health & Science University, Portland Oregon, USA
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CHALLENGE
The morphology, microstructure, and ultrastructure of heart tissues is exquisitely organized to optimize cardiac efficiency. In cases of cardiac malformations, known as congenital heart disease (CHD), spatially heterogeneous and abnormal ultrastructural patterns emerge as early as fetal stages that worsen heart performance. To spatially survey ultrastructural changes in CHD, we developed a technique that allows us to precisely select regions of interest (ROIs) for vEM, while keeping track of the location of the ROI within the heart. TECHNIQUE: MicroCT FOLLOWED BY SBF-SEM
Our workflow allows for correlative micro-CT of the whole heart followed by vEM of selected cardiac ROIs. 
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RESEARCH
In an avian model of CHD, we compared a normal and a malformed heart (Tetralogy of Fallot, TOF). Along with anatomical differences, evident from micro-CT images, quantification of vEM uncovered a lower density of cells and myofibrils in the TOF heart, suggesting that in TOF tissues cardiac contraction might be impaired. 
IMPACT
This research will help inform patients with CHD, from fetal stages to adulthood. Importantly, we hope it will provide a rationale for planning treatments that account for the unique nature of CHD cardiac tissues. 
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REFERENCES
1. G. Rykiel, C.S. López, J.L. Riesterer, I. Fries, S. Deosthali, K. Courchaine, A. Maloyan, K. Thornburg, S. Rugonyi 2020, Multiscale cardiac imaging spanning the whole heart and its internal cellular architecture in a small animal model. eLife 2020; 9:e58138, DOI: 10.7554/eLife.58138d
1. G. Rykiel, C.S. López, J.L. Riesterer, I. Fries, S. Deosthali, K. Courchaine, A. Maloyan, K. Thornburg, S. Rugonyi 2020, Multiscale cardiac imaging spanning the whole heart and its internal cellular architecture in a small animal model. eLife 2020; 9:e58138, DOI: 10.7554/eLife.58138d
Insights into the leaky Blood Brain Barrier by vEM
DOI: 10.1242/focalplane.15936
Author: Martina Schifferer
German Center for Neurodegenerative Diseases, Munich Cluster for Systems Neurology SyNergy, Germany
Author: Martina Schifferer
German Center for Neurodegenerative Diseases, Munich Cluster for Systems Neurology SyNergy, Germany
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CHALLENGE
The Blood Brain Barrier (BBB) controls the exchange between blood and the brain parenchyme. Its structural determinants comprise tight junctions and endothelial vesicles which require resolution at the nanometer scale. In disease like stroke or traumatic brain injury the BBB is locally disrupted. The morphological hallmarks of BBB leakiness are, however, poorly understood. In our study¹ we aimed at the identification of sites of BBB disruption in a mouse model of traumatic brain injury. These spots were visualized at the ultrastructural level by correlated light and volume electron microscopy (vEM). 
TECHNIQUE: ATUM CLEM
The idea of tissue slicing has been carried over from the Greek word ‘anatomy’ (‘through’ ‘cutting’) to modern volume electron microscopy (vEM). Among them, array tomography (AT)³ approaches are based on serial ultramicrotomy, collection onto solid support and serial scanning EM. |
The AT method automated tape-collecting ultramicrotomy (ATUM) was initially developed for large-scale neural circuit reconstruction⁴ while vEM of more confined volumes has broadened investigation of a wide range of biological systems. ATUM enables the creation of a tissue section library that can be inspected by scanning electron microscopy (SEM) at different resolution regimes. Hierarchical imaging and the modular character of ATUM provide flexibility. Therefore, ATUM is not only valuable for the volume rendering of biological structures at the nanoscale but provides beneficial features for correlative light and electron microscopy (CLEM). We used 30 nm sized fluorescent and electron-dense nanoparticles to localize vessels of leaky BBB¹. These target sites were relocated in the ultrastructural volume, generated by ATUM-SEM¹. We observed nanoparticles within pericytes and abluminally¹. Moreover, the ultrastructural volume captures the entire tissue context including all cells involved in an unbiased fashion.
IMPACT
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REFERENCES
¹Khalin et al., Small, 2022; ²Peddie et al., Nat Rev Methods Primer; ³Micheva and Smith, Neuron, 2007; ⁴Kasthuri et al., Cell, 2015
¹Khalin et al., Small, 2022; ²Peddie et al., Nat Rev Methods Primer; ³Micheva and Smith, Neuron, 2007; ⁴Kasthuri et al., Cell, 2015
Inputs and Outputs of vEM in a Sensory System
DOI: 10.1242/focalplane.14809
Author: Federica Mangione
The Francis Crick Institute, UK
Author: Federica Mangione
The Francis Crick Institute, UK
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CHALLENGE
The sense of touch enables organisms to interact with their environment by perceiving physical forces and guiding complex behaviors. Touch sensing is mediated by sensory neurons that innervate the body surface of animals and, together with surrounding cells, form specialized structures known as tactile organs ¹, ². Accessing the structure of a tactile organ at different scales would provide crucial insights into the cellular basis of touch. A major challenge towards this goal is to image whole cell volumes with enough resolution for their subsequent assembly in 3D. Volume electron microscopy (vEM) techniques can be applied to acquire and render the volume of the cells in tactile organs, providing precious insights into the cellular architecture of the sensory system of touch and its biological function. TECHNIQUE: SBF-SEM
Serial blockface scanning electron microscopy (SBF-SEM) provides high resolution access to cells and tissues and allows 3D rendering of cellular structures³,⁴. With SBF-SEM, the 3D morphology of cells and tissues is acquired through the serial imaging of a sectioned sample, which is prepared ad hoc by encasing the stained cells/tissues in specialized resins, then sliced with a diamond knife³, ⁴. RESEARCH
Using SBF-SEM, the cellular assembly of the tactile organs of the fruit fly Drosophila melanogaster have been recently defined². |
The sensory neuron of each tactile organ is surrounded by cells that show unique morphologies and interactions with one another². The proper assembly of the tactile organ is essential for touch sensing and for guiding complex behaviors².
IMPACT
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REFERENCES
[1] Handler and Ginty, 2021, Nat Rev Neurosci
[2] Mangione et al., 2023, Nat Cell Biol
[3] Denk and Horstmann, 2004, Plos Biol
[4] Peddie et al., 2022, Nat Rev Methods Primers
[1] Handler and Ginty, 2021, Nat Rev Neurosci
[2] Mangione et al., 2023, Nat Cell Biol
[3] Denk and Horstmann, 2004, Plos Biol
[4] Peddie et al., 2022, Nat Rev Methods Primers
How volumeEM (vEM) can help map neuronal circuits
DOI: 10.5281/zenodo.6320414
Author: Nadine Randel
University of Cambridge, UK
Author: Nadine Randel
University of Cambridge, UK
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CHALLENGE
The nervous system processes sensory information and generates different behavioural outputs accordingly. Synaptic resolution wiring diagrams form a basis for our understanding of how the brain works. Such a connectome provides the synaptic connectivity between all neurons and allows to identify all potential neuronal pathways which mediate different behaviours. This “road map” can then be combined with cell-specific molecular information, neuronal dynamics, targeted manipulation and behavioural experiments. A main challenge is the acquisition of large, continuous EM volumes with sufficient resolution. Several volume EM (vEM) techniques can be applied to generate these volumes, which form the basis for whole nervous system wiring diagrams; only such diagrams will allow comprehensive exploration and understanding of sensory computation and the evoked behavioural outputs. TECHNIQUE: SERIAL SECTION TEM/SEM
Large, continuous EM volumes with synaptic resolution can be acquired using ssTEM on grids or ssSEM on glass slides¹. Both methods are also compatible with serial sections mounted on grid and ATUM tape²,³. Furthermore, serial blockface (SBF) SEM⁴ and modified focused ion beam (FIB) SEM⁵ can be used to image samples en bloc. 
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RESEARCH
Currently, the largest existing whole animal connectome has been generated in Platynereis⁶. Using vEM, all cells and connections of the entire sensory-motor pathways have been mapped⁷,⁸. The researchers used the connectome to identify how information is transmitted from the brain to global or local segment-specific areas in the ventral nerve cord, and vice versa. They also could link specific neuronal circuits with different behaviors: For example, they discovered how the nervous system coordinates whole-body ciliary activity for locomotion, visual phototaxis and predator escape response⁹ - ¹¹.
IMPACT
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REFERENCES
1. Burel et al. 2018 Development, 2. Graham et al. 2019 bioRxiv, 3. Hayworth et al. 2014 Front Neural Circuits, 4. Denk and Hostmann 2004 PLoS Biol, 5. Xu et al. 2017 eLife, 6. https://catmaid.jekelylab.ex.ac.uk, 7. Verasztó et al. 2020 bioRxiv, 8. Jasek et al. 2021 bioRxiv, 9. Bezares-Calderón et al. 2018 eLife, 10. Randel et al. 2014 eLife, 11. Verasztó et al. 2017 eLife
1. Burel et al. 2018 Development, 2. Graham et al. 2019 bioRxiv, 3. Hayworth et al. 2014 Front Neural Circuits, 4. Denk and Hostmann 2004 PLoS Biol, 5. Xu et al. 2017 eLife, 6. https://catmaid.jekelylab.ex.ac.uk, 7. Verasztó et al. 2020 bioRxiv, 8. Jasek et al. 2021 bioRxiv, 9. Bezares-Calderón et al. 2018 eLife, 10. Randel et al. 2014 eLife, 11. Verasztó et al. 2017 eLife