Serial Block-Face SEM
Explore inspiring examples
Serial block-face scanning electron microscopy (SBF-SEM) utilizes an ultramicrotome inside the SEM chamber to image the ultrastructure of a resin-embedded biological sample in 3D over a large area.
A diamond knife slices sections from the sample block and the exposed sample surface is imaged by the electron beam and backscatter electron detector. The cutting and imaging process is automatically repeated until the desired – or entire - stack is acquired in the z direction of the sample.
The individual 2D images are stitched and aligned to create a 3D volume of the sample.
Understanding the Neuronal Connections inside the Brain and the Morphology of Neuronal Cells
The brain is a complex organ with millions of neuronal connections and signaling pathways. Understanding the relationship between structure and function of brain tissue helps in unravelling some of this complexity to better understand how neural networks are organized and, in the long term, how to treat certain pathologies with medical interventions. SBF-SEM is an ideal solution to image and follow neurons with long and thin protrusions such as dendrites and axons.
The video shows the cross sections from a mouse brain specimen captured using SBF-SEM. The high resolution achieved using this approach can be clearly seen in each of the single block-face images allowing identification of the different structures. Courtesy of Prof. Mark Ellisman, University of California, San Diego, USA.
This image shows a stack from a mouse brain that has been embedded in resin and then imaged using a BSE detector and SBF-SEM device as part of an automated run to generate a high-resolution 3D volume. Courtesy of Naomi Kamasawa, Max Planck Florida Institute, R. Shigemoto, Nation Institute for Physiological Sciences Okazaki, Japan.
The animation shows a run through single slices (x-y) taken from a 3D dataset of brain tissue. As the 3D volume is completely reconstructed it also allows the visualization of planes which were not imaged directly (x-z, y-z). 75 images were captured in total with 7 nm pixels and 15 nm section thickness. Courtesy of Naomi Kamasawa – Max Planck Florida Institute, Jupiter, USA, and Ryuichi Shigemoto – National Institute for Physiological Sciences Okazaki, Japan.
Single neurons and cellular compartments can be easily identified and followed along the z-dimension.
Mouse brain
Studying the Neuronal Network and Synapses of Neurobiological Samples
Since SBF-SEM provides high resolution imaging in 3D, samples such as this mouse brain can be imaged to reveal single neurons and cellular compartments. This sample was imaged using SBF-SEM with a stack of 75 images with 7 nm pixels, and microtome set to remove 15 nm/slice.
Mouse brain (cultured hippocampal neurons expressing PSD95-APEX2 to stain post-synaptic densities)
Exploring Cultured Hippocampal Neurons to Understand Neuronal Morphologies and Networks
High resolution imaging of features such as thin dendrites, axons, cell protrusions and connections between single neurons is key for fundamental understanding of neuronal morphologies and networks.
The images show a single slice from a 3D dataset of cultured hippocampal neurons expressing PSD95-APEX2 to stain post-synaptic densities (arrows). The image was acquired using SBF-SEM and Focal Charge Compensation. Ultrastructure such as thin dendrites and connections are visible with high resolution due to the removal of charging effects. Courtesy of National Center for Microscopy and Imaging Research NCMIR, University of California, San Diego, USA.
New Discoveries from the Ultrastructure of Life Virtual Seminar Series | January – June 2024
In a series of six webinars, explore the technological underpinnings of Volume EM imaging and its growing number of application areas in neurobiology, cancer research, developmental biology, plant science, and more.
Learn about vEM-specific sample preparation and technologies (array tomography, serial block-face SEM, and FIB-SEM), advanced image processing, data analysis, and result visualization capabilities of workflow-oriented software solutions.
Investigation of Axon Myelinization to Understand Multiple Sclerosis and Parkinson’s Disease
Axon myelinization is altered in diseases such as Multiple Sclerosis and Parkinson’s Disease. Electron micrographs provide high resolution information sufficient to count the number of single myelin lamellae and measure overall sheath thickness. The sparse nature of structures in these samples means there are large areas of non-conductive, bare resin which leads to significant charging effects. Using Focal Charge Compensation eliminates these effects – meaning you can image with highest resolution in all three dimensions.
Charging effects can cause significant issues when imaging life science specimens using the SEM as they greatly reduce image quality. When this rat axon bundle is imaged in high vacuum and without focal charge compensation, it is clear to see charging effects. In contrast, when the images are captured using Focal Charge Compensation, no charging effects can be seen, even in large expanses of bare resin. The images show a ~300 micron diameter axon bundle at different magnifications (courtesy of National Center for Microscopy and Imaging Research (NCMIR), University of California, San Diego, USA).
The animation shows a run through of single slices (x-y) of rat spinal cord using SBF and Focal Charge Compensation. Single lamellae within the myelin sheaths of the axons are clearly visible as well as microtubules and other cellular organelles in the original data set.
Myelin lamellae
This SBF-SEM image provides high resolution information sufficient to count the number of single myelin lamellae and measure overall sheath thickness. Images taken with Focal Charge Compensation, which show no charging effects even in large expanses of bare resin.
Identification of Astrocytes in a Brain Sample
This brain sample has been imaged using SBF-SEM. Astrocytes (turquoise) can be easily identified, visualized and segmented in 3D. Courtesy of P. Munro and H. Armer, UCL - Institute of Ophthalmology, London, UK.