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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...

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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Related Experiment Video

Updated: Oct 21, 2025

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

Computational Methods for Single-Particle Electron Cryomicroscopy.

Amit Singer¹, Fred J Sigworth²

¹Department of Mathematics and Program in Applied and Computational Mathematics, Princeton University, Princeton, NJ 08544, USA.

Annual Review of Biomedical Data Science

|September 6, 2021

Summary

This summary is machine-generated.

Single-particle cryo-electron microscopy (cryo-EM) determines 3D protein structures from noisy 2D images. This review explores computational methods for structure determination and analyzing molecular flexibility.

Keywords:

Electron cryomicroscopy conformational heterogeneity contrast transfer function image alignment and classification statistical estimation three-dimensional tomographic reconstruction

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Area of Science:

Structural biology
Biophysics
Computational biology

Background:

Single-particle cryo-electron microscopy (cryo-EM) is a powerful technique for near-atomic resolution 3D structure determination.
Unlike X-ray crystallography, cryo-EM does not require crystallization and visualizes molecules in native states.

Purpose of the Study:

To review computational methods for single-particle cryo-EM structure determination.
To discuss the application of statistical inference, machine learning, and signal processing in cryo-EM data analysis.
To highlight challenges in reconstructing structures from noisy 2D projections and inferring conformational flexibility.

Main Methods:

Computational reconstruction of 3D structures from noisy 2D tomographic projections.
Statistical inference for determining molecular structures and orientations.
Machine learning and signal processing techniques applied to cryo-EM data.

Main Results:

Computational challenges in cryo-EM include high noise levels and unknown particle orientations (pose parameters).
Inferring structural variability and dynamics from heterogeneous conformational states is particularly complex.
The review consolidates guiding principles from diverse computational fields.

Conclusions:

Computational methods are crucial for advancing single-particle cryo-EM.
Techniques from statistical inference, machine learning, and signal processing are vital for overcoming cryo-EM challenges.
Understanding these methods aids in analyzing complex biological structures and dynamics.