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Related Concept Videos

Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

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...
Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Cryo-electron Microscopy01:28

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 21, 2026

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
08:55

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

Contrast transfer function correction applied to cryo-electron tomography and sub-tomogram averaging.

Giulia Zanetti1, James D Riches, Stephen D Fuller

  • 1Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.

Journal of Structural Biology
|August 12, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces improved methods for correcting the contrast transfer function (CTF) in cryo-electron tomography. These advancements enhance the resolution of protein structures obtained through sub-tomogram averaging, even with low signal-to-noise data.

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Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography
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Preparing Lamellae from Vitreous Biological Samples Using a Dual-Beam Scanning Electron Microscope for Cryo-Electron Tomography
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Preparing Lamellae from Vitreous Biological Samples Using a Dual-Beam Scanning Electron Microscope for Cryo-Electron Tomography

Published on: August 5, 2021

Related Experiment Videos

Last Updated: Jun 21, 2026

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
08:55

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Published on: July 12, 2022

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Preparing Lamellae from Vitreous Biological Samples Using a Dual-Beam Scanning Electron Microscope for Cryo-Electron Tomography
07:00

Preparing Lamellae from Vitreous Biological Samples Using a Dual-Beam Scanning Electron Microscope for Cryo-Electron Tomography

Published on: August 5, 2021

Area of Science:

  • Structural Biology
  • Biophysics
  • Microscopy

Background:

  • Cryo-electron tomography (Cryo-ET) with sub-tomogram averaging reveals native protein structures.
  • Microscope contrast transfer function (CTF) limits Cryo-ET resolution.
  • Routine CTF correction is challenging due to low signal-to-noise and spatially variant CTF.

Purpose of the Study:

  • To simulate CTF effects on Cryo-ET reconstruction resolution.
  • To develop and validate methods for CTF correction in low signal-to-noise Cryo-ET data.
  • To improve structural resolution of protein complexes using sub-tomogram averaging.

Main Methods:

  • Simulations of CTF effects on resolution before and after correction.
  • Development of methods for CTF parameter determination in low signal-to-noise tilted images.
  • Monitoring defocus variations and applying CTF correction prior to reconstruction.
  • Application to bacteriophage PRD1 for validation.

Main Results:

  • CTF correction significantly improves reconstruction resolution.
  • Errors in defocus determination are well-tolerated with a range of defocus values.
  • Developed methods effectively determine CTF parameters and correct for spatial variations.
  • Demonstrated improved structure of bacteriophage PRD1.

Conclusions:

  • Effective CTF correction is crucial for high-resolution Cryo-ET.
  • The developed methods overcome common challenges in CTF correction for Cryo-ET.
  • This approach enhances the structural analysis of biological macromolecules in their native state.