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Electron Tomography
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Updated: Mar 26, 2026

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

Published on: January 30, 2016

Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography.

Dustin R Morado¹, Bo Hu¹, Jun Liu²

¹Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston.

Journal of Visualized Experiments : Jove

|February 11, 2016

Summary

This summary is machine-generated.

A new high-throughput cryo-electron tomography (Cryo-ET) protocol streamlines 3-D imaging of macromolecular complexes. This method, utilizing advanced hardware and software, overcomes data processing challenges for enhanced molecular visualization.

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Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

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Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

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Published on: July 12, 2022

Area of Science:

Structural Biology
Microscopy Techniques
Biophysics

Background:

Cryo-electron tomography (Cryo-ET) enables molecular-level 3-D visualization of biological samples in their native state.
Low signal-to-noise ratios in raw cryo-tomograms necessitate advanced image processing techniques like sub-tomogram averaging.
Acquiring large datasets for Cryo-ET is often a bottleneck in structural analysis.

Purpose of the Study:

To present a high-throughput cryo-electron tomography (Cryo-ET) protocol designed to overcome data acquisition and processing challenges.
To demonstrate the application of this protocol for visualizing complex biological systems at high resolution.
To provide a broadly applicable method for researchers utilizing Cryo-ET.

Main Methods:

Implementation of a high-throughput Cryo-ET workflow using a 300kV cryo-electron microscope and a direct detection device (DDD) camera.
Development and application of an in-house, semi-automated image-processing pipeline software library called tomoauto.
Collection of large tilt-series datasets crucial for averaging and classification of macromolecular complexes.

Main Results:

Successfully visualized the intact type III secretion system (T3SS) in Shigella flexneri minicells using the developed protocol.
The protocol significantly enhances throughput for Cryo-ET data acquisition and processing.
Demonstrated the effectiveness of the semi-automated software pipeline in managing large datasets.

Conclusions:

The described high-throughput Cryo-ET protocol offers an efficient solution for molecular imaging challenges.
This method facilitates detailed structural analysis of macromolecular complexes, including the T3SS.
The protocol is adaptable for diverse research projects requiring advanced Cryo-ET analysis.