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Cryo-electron Microscopy

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Related Experiment Video

Updated: Jun 30, 2025

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

Recent advances in data collection for Cryo-EM methods.

Anchi Cheng¹, Yue Yu¹

¹Chan Zuckerberg Institute for Advanced Biological Imaging (CZ Imaging Institute), 3400 Bridge Parkway, Redwood City CA 94065, USA.

Current Opinion in Structural Biology

|March 14, 2024

Summary

This summary is machine-generated.

Automating transmission electron microscopy (TEM) data collection enhances biological structure resolution. Advancements in conventional TEM, single particle analysis (SPA), and cryo-electron tomography (cryo-ET) improve throughput and efficiency.

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Last Updated: Jun 30, 2025

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

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Published on: March 16, 2022

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

Single-Particle Cryo-EM Data Collection with Stage Tilt using Leginon

Published on: July 1, 2022

Area of Science:

Microscopy
Structural Biology
Biophysics

Background:

Transmission electron microscopy (TEM) is crucial for visualizing vitrified biological specimens.
Both single particle analysis (SPA) and cryo-electron tomography (cryo-ET) are key TEM methods.
Automation in TEM data collection is essential for increasing throughput and user convenience.

Purpose of the Study:

To review the progress and applications of automated data collection in various TEM methods.
To highlight the benefits of automation for SPA, cryo-ET, and scanning TEM (STEM).
To discuss the impact of machine learning and new hardware on TEM automation.

Main Methods:

Review of automated data collection strategies in conventional TEM, SPA, and cryo-ET.
Application of beam-image shift strategies for improved data acquisition.
Integration of machine learning for target selection, path planning, and automated screening in SPA.
Development of new hardware, such as square apertures, for enhanced data collection.

Main Results:

Automation in conventional TEM data collection has advanced significantly.
Beam-image shift strategies are effective for both SPA and cryo-ET.
Machine learning enables efficient target selection and automated screening for SPA.
Progress in scanning TEM automation promises increased throughput for cryo-applications.

Conclusions:

Automation is rapidly advancing across various transmission electron microscopy techniques.
These advancements are crucial for improving the efficiency and accessibility of high-resolution structural analysis of biological specimens.
Continued development in automation, including machine learning and hardware, will further enhance the capabilities of cryo-TEM.