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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: May 20, 2026

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

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

Published on: March 16, 2022

Creating an infrastructure for high-throughput high-resolution cryogenic electron microscopy.

Donald C Shrum¹, Brent W Woodruff, Scott M Stagg

¹Department of Scientific Computing, 400 Dirac Science Library, Florida State University, Tallahassee, FL 32306, USA.

Journal of Structural Biology

|July 31, 2012

Summary

This summary is machine-generated.

Advancements in 3D electron microscopy generate more data, creating storage and processing challenges. We developed a high-throughput infrastructure to manage this increased data volume from 3D electron microscopy.

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Last Updated: May 20, 2026

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Published on: March 16, 2022

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Published on: March 19, 2021

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Published on: April 21, 2022

Area of Science:

Microscopy and Imaging Technologies
Computational Biology
Data Science

Background:

Three-dimensional electron microscopy (3D EM) instrumentation is rapidly advancing.
Increased data collection and reconstruction throughput are key goals.
Existing workflows face bottlenecks in data storage and processing.

Purpose of the Study:

To describe the development of a novel high-throughput infrastructure.
To quantify the throughput of this new infrastructure.
To support large-scale 3D electron microscopy data collection.

Main Methods:

Design and implementation of a scalable data storage solution.
Development of optimized data processing pipelines.
Integration of data collection with storage and processing workflows.

Main Results:

The developed infrastructure successfully supports high-throughput 3D EM data collection.
Quantification demonstrates significant improvements in data handling capacity.
Bottlenecks in data storage and processing have been alleviated.

Conclusions:

The new infrastructure effectively addresses the data management challenges posed by advanced 3D EM.
This facilitates larger and more complex structural biology studies.
Enables efficient utilization of next-generation microscopy capabilities.