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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: Oct 21, 2025

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency

Published on: May 10, 2024

Cryo-EM density maps adjustment for subtraction, consensus and sharpening.

E Fernández-Giménez¹, M Martínez², R Sánchez-García²

¹Centro Nac. Biotecnología (CSIC), c/Darwin, 3, 28049 Cantoblanco, Madrid, Spain; Univ. Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain.

Journal of Structural Biology

|September 1, 2021

Summary

This summary is machine-generated.

A new method enhances electron cryomicroscopy (cryo-EM) data comparison by refining volume adjustments. This improves structural biology insights by enabling more reliable map subtraction, sharpening, and combination for advanced analysis.

Keywords:

Cryo-EM Map fusion SPA Sharpening Subtomogram averaging Subtraction

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A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

Electron cryomicroscopy (cryo-EM) is crucial for determining near-atomic 3D structures.
A lack of robust comparison tools hinders the analysis of cryo-EM density maps.
Existing comparison methods use basic grey-level adjustments, limiting reliability.

Purpose of the Study:

To develop a sophisticated volume adjustment method for cryo-EM data comparison.
To enable more reliable quantitative analysis of cryo-EM reconstructions.
To provide a foundation for advanced cryo-EM data processing applications.

Main Methods:

A novel algorithm adjusts grey level scale and spectrum energy of cryo-EM volumes.
Phases are preserved within a defined mask, and volumes are constrained to be strictly positive.
The method ensures volumes are in the same numeric frame for accurate operations.

Main Results:

The proposed adjustment method allows for more reliable comparison of cryo-EM density maps.
This technique facilitates applications like map subtraction, sharpening, and consensus map generation.
The algorithm can also serve as a model-based sharpening method.

Conclusions:

The developed adjustment algorithm significantly enhances the reliability of cryo-EM data comparison.
This method supports advanced applications in structural biology, improving data analysis.
The algorithm is integrated into the Xmipp software and accessible via Scipion.