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Electron Microscope Tomography and Single-particle Reconstruction

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Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...

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Updated: Jan 5, 2026

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

A complete data processing workflow for cryo-ET and subtomogram averaging.

Muyuan Chen¹, James M Bell^1,2, Xiaodong Shi^1,3

¹Verna Marrs and McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA.

|October 16, 2019

Summary

This summary is machine-generated.

We developed an automated workflow for electron cryotomography data processing, improving resolution and reducing bias in structural analysis of cells and macromolecules.

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Last Updated: Jan 5, 2026

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

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Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Published on: March 19, 2021

Area of Science:

Structural Biology
Cell Biology
Microscopy

Background:

Electron cryotomography (cryo-ET) offers 3D nanoscale visualization of cells.
Current cryo-ET data processing is labor-intensive and limits results.
High-resolution structural information is often lost during manual processing.

Purpose of the Study:

To present an integrated, automated workflow for cryo-ET data processing.
To enhance resolution and reduce human bias in subtomogram averaging.
To enable near data-limited resolution for structural analysis.

Main Methods:

Automated tilt series alignment for cryo-ET data.
Subnanometer resolution subtomogram averaging pipeline.
Per-particle, per-tilt contrast transfer function correction and alignment.

Main Results:

The workflow significantly reduces human bias in data processing.
Increased throughput for analyzing large tomography datasets.
Achieved resolution closer to data limits for macromolecules and cells.

Conclusions:

The integrated workflow streamlines cryo-ET data analysis.
Automated processing enhances structural resolution and reproducibility.
Enables more accurate nanoscale structural insights from cellular cryo-ET data.