Applications for Array TomographyCourtesy of D. Sherrier, J. Caplan, and S. Modla, University of Delaware, USA
Courtesy of D. Sherrier, J. Caplan, and S. Modla, University of Delaware, USA
Overview

Applications for Array Tomography

Explore inspiring examples

Array tomography (AT) is a powerful approach for generating 3D datasets with nanoscale resolution. The sample is sectioned into many hundreds of individual slices and each is imaged at high resolution using scanning electron microscopy.

As a non-destructive approach, the thin sections of the sample are maintained on the imaging substrate and can be further studied using other methods such as fluorescence microscopy or other analytical approaches.

There is no requirement for specialized equipment, making this volume EM (vEM) approach widely accessible to any lab with a standard scanning electron microscope (SEM) and ultramicrotome. These characteristics of AT make it a valuable approach for the exploration of samples as diverse as cells, tissues and plants as demonstrated by these examples.

Understanding Connectivity in Brain Tissue

Exploring millions of neural connections to better understand the signaling pathways in the brain.

Overview image of monkey brain captured using AT.

Overview image of monkey brain captured using AT.

The brain is a complex organ with millions of neural connections and signalling pathways. Understanding the relationship between structure and function of neural tissue helps in unravelling some of this complexity to better understand how the brain works and in the long term how to treat malfunctions with medical interventions.

High resolution image of monkey brain captured using SEM.

High resolution image of monkey brain captured using SEM.

When looking to explore the millions of neural connections, a high-resolution 3D imaging approach is required. For small brain specimens, the time required to capture a full 3D dataset is substantial but achievable. However, when the tissue size is significantly increased, such is the case with the brain of a mouse or a monkey, there is a need to scale up the imaging to generate the high-resolution 3D datasets in a realistic timeframe. This is enabled by AT.

Monkey brain vasculature captured using AT.

Monkey brain vasculature captured using AT.

ZEISS Atlas 5 Array Tomography is a hardware/software tool that can automatically image the serial sections on the substrate down to nanometer resolution. This unique workflow is easy-to-use and has been specifically designed for automated imaging to enable the 3D visualization of the large volumes necessary for understanding the vast connections in brain tissue.

Automatically acquired, large scale image of monkey brain specimen showing brain vasculature. Image captured using Atlas 5 Array Tomography. Field of view: 3700 mm.

Stitched mosaic of >1000 images showing the brain of a monkey. Each tile image is 4096 x 4096 pixels, with a pixel size of 150 nm.

Automated stitching of these tile images to calculate one image of the monkey brain with a large field of view.

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

Using computer-assisted tools in Atlas 5 Array Tomography, you can define unlimited regions of interest with any shape over hundreds of serial sections. This is particularly useful in experiments such as capturing monkey brain or neuronal connections in mouse brain.

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

This image is a large-scale SEM image of an ultrathin section of a mouse brain mounted on a substrate. It has been acquired using Atlas 5 Array Tomography to assist in automating the acquisition.

Subcellular details such as the nucleus and mitochondria can be identified and when reconstructed in 3D the connections between the different neurons can be mapped.

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

This image shows a number of brain slices mounted on tape ready for imaging. Atlas 5 Array Tomography identifies each of the Cerebellum sections for subsequent acquisition with high resolution SEM and all of the useful information about each slice is contained within the software platform.

Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

This video demonstrates the great value of using Atlas 5 Array Tomography to streamline your AT workflows. As the video progresses you can see how high-resolution data is captured from each slice can be combined to ultimately generate a 3D dataset.

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section
Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.
Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

To capture the optic nerve with high resolution SEM, single sections need to be imaged and then reconstructed. Using Array Tomography, these sections can be automatically located and subsequently imaged to ensure the acquisition process is quick and straightforward.  

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section

Ultrathin Mouse Brain Section
Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.
Ultrathin mouse brain section. Sample: courtesy of J. Lichtman, Harvard, USA.

The image shows the individual sections of the Optic Nerve, mounted on a wafer and awaiting imaging using the Atlas 5 software.

Mouse optic nerve imaged using array tomography. Sample: courtesy of J. Lichtman, Harvard, USA.

When imaging brain using Array Tomography you have many hundreds and sometimes thousands of slices available that need to be located and imaged. Manual identification of each of these slices is laborious and time consuming. Atlas 5 automatically and quickly identifies each of the slices such that subsequent imaging can begin quickly and efficiently and all of the high-resolution information about each slice is registered in the software.

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.

Understanding the Impact of Bacteria in Root Nodules on the Health and Condition of Plants

Visualizing the distribution of root nodules and bacteria by overlaying fluorescence and structural data using Correlative Array Tomography (CAT).

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root nodules showing the distribution of plasmodesmata. Courtesy of D. Sherrier, J. Caplan, and S. Modla, University of Delaware, USA.

Root nodules showing the distribution of plasmodesmata. Courtesy of D. Sherrier, J. Caplan, and S. Modla, University of Delaware, USA.

The root network of a plant provides access to the water and nutrients that are crucial components for all plant growth. Exploring the whole root network as well as understanding the influence of external microbes is important for optimizing plant health and yield.

Investigating the symbiotic relationship between plants and bacteria in root nodules requires knowledge of root nodule and bacteria distribution and a combination of both fluorescence and high-resolution structural assessment is vital to understand this in detail.

Correlative array tomography enables the overlay of both fluorescence and structural data to enable visualization of root nodule and bacteria distribution.

The combination of high-resolution structural information and precise fluorescence information is key for a thorough understanding of how the bacteria in the root nodules impact plant condition.

Root nodules showing the distribution of plasmodesmata. Courtesy of D. Sherrier, J. Caplan, and S. Modla, University of Delaware, USA.

The images are either 3D reconstructions or single slices of fluorescence data from serial sections from root nodules showing the distribution of plasmodesmata. The stack can be overlaid with the SEM data to investigate the relationship of bacterial infection and distribution of plasmodesmata.

The sample was embedded in Epon and cut with an ultramicrotome. The serial sections were transferred on ITO-coated cover glasses by means of a micromanipulator. Cell walls were stained with Calcofluor White (blue) and the plasmodesmata were stained against Callose with Alexa Fluor 647. The sample was post-stained for imaging in the SEM.

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata
Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata
Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata
Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata
Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata
Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

Root Nodules Showing the Distribution of Plasmodesmata

How to Set up an Array Tomography Acquisition

This video illustrates the workflow utilized by ZEISS Atlas 5 Array Tomography to generate a correlative dataset with fluorescence and SEM data. One of the examples shown in the video is of a yeast specimen to demonstrate how this can be configured.

The yeast sample shown in the video was embedded in Epon and cut with an ultramicrotome. The serial sections were transferred on ITO-coated cover glasses by means of a micromanipulator. The sample was first imaged with the light microscope and then post-stained for imaging in the SEM.

Courtesy of D. Sherrier, J. Caplan, and S. Modla, University of Delaware, USA.
  

Understanding the Biology and Progression of Huntington's Disease

Visualizing the development of protein plaques in macrophages using Correlative Array Tomography (CAT).

Macrophages Exhibiting Protein Plaques Induced by Mutant Huntingtin Protein Aggregation

Macrophages Exhibiting Protein Plaques Induced by Mutant Huntingtin Protein Aggregation

Macrophages Exhibiting Protein Plaques Induced by Mutant Huntingtin Protein Aggregation

Macrophages exhibiting protein plaques induced by mutant huntingtin protein aggregation. The image is a fluorescence dataset taken from one section and showing protein plaques in the macrophages. DNA: blue (DAPI), huntingtin protein: red (Alexa Fluor 647). Courtesy of Jeff Caplan, University of Delaware, USA.

Macrophages exhibiting protein plaques induced by mutant huntingtin protein aggregation. The image is a fluorescence dataset taken from one section and showing protein plaques in the macrophages. DNA: blue (DAPI), huntingtin protein: red (Alexa Fluor 647). Courtesy of Jeff Caplan, University of Delaware, USA.

Huntington’s Disease is an incurable, progressive neurodegenerative disease that is caused by a defective gene on chromosome 4 that codes for the huntingtin protein. The defective gene leads to the formation of mutant huntingtin protein which misfolds and aggregates causing protein plaque development in the brain. Such deterioration in the brain leads to disruption of movement, behavior, thinking and emotions.
  

Overexpression of Huntingtin Results in an Aggregation of the Protein Clearly Visible within the Z-Stack

Overexpression of Huntingtin Results in an Aggregation of the Protein Clearly Visible within the Z-Stack

Overexpression of Huntingtin Results in an Aggregation of the Protein Clearly Visible within the Z-Stack

An overexpression of huntingtin results in an aggregation of the protein clearly visible within the Z-stack. An antibody was used against GFP-Huntington to locate plaques of huntingtin within the cells (Alexa Fluor 647, red). The nucleus is shown in blue (Hoechst). Correlation of the LM z-stack with the SEM z-stack shows the distribution of the huntingtin plaques and the location of the nucleus in 3D. Courtesy of J. Caplan, E. Kmiec and S. Modla, University of Delaware, USA.

An overexpression of huntingtin results in an aggregation of the protein clearly visible within the Z-stack. An antibody was used against GFP-Huntington to locate plaques of huntingtin within the cells (Alexa Fluor 647, red). The nucleus is shown in blue (Hoechst). Correlation of the LM z-stack with the SEM z-stack shows the distribution of the huntingtin plaques and the location of the nucleus in 3D. Courtesy of J. Caplan, E. Kmiec and S. Modla, University of Delaware, USA.

Visualizing the development of protein plaques in macrophages, which are used as a model system for the investigation of this disease, and understanding how these relate to ultrastructural cellular details is important for understanding the biology and progression of Huntington's disease.

Correlative Array Tomography provides the opportunity to explore both ultrastructural information and fluorescence data from serial sections of this macrophage.

Correlation of the LM Z-Stack with the SEM Z-Stack Shows the Distribution of the Huntingtin Plaques and the Location of the Nucleus in 3D

Correlation of the LM Z-Stack with the SEM Z-Stack Shows the Distribution of the Huntingtin Plaques and the Location of the Nucleus in 3D

Correlation of the LM Z-Stack with the SEM Z-Stack Shows the Distribution of the Huntingtin Plaques and the Location of the Nucleus in 3D

Correlation of the LM z-stack with the SEM z-stack shows the distribution of the huntingtin plaques and the location of the nucleus in 3D. Courtesy of J. Caplan, E. Kmiec and S. Modla, University of Delaware, USA.

Correlation of the LM z-stack with the SEM z-stack shows the distribution of the huntingtin plaques and the location of the nucleus in 3D. Courtesy of J. Caplan, E. Kmiec and S. Modla, University of Delaware, USA.

The correlation of high-resolution ultrastructural information and fluorescence data is important to thoroughly understand the biology and progression of Huntington’s disease.

The image on the left/above show a schematic representation of the information gained in 3D through combining the serial LM and SEM images of macrophages expressing the protein huntingtin resulting from a ZEISS ZEN Correlative Array Tomography experiment.

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