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Related Concept Videos

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...
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...

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Do's and Don'ts of Cryo-electron Microscopy: A Primer on Sample Preparation and High Quality Data Collection for Macromolecular 3D Reconstruction
09:25

Do's and Don'ts of Cryo-electron Microscopy: A Primer on Sample Preparation and High Quality Data Collection for Macromolecular 3D Reconstruction

Published on: January 9, 2015

Image formation modeling in cryo-electron microscopy.

Miloš Vulović1, Raimond B G Ravelli, Lucas J van Vliet

  • 1Quantitative Imaging Group, Faculty of Applied Sciences, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands.

Journal of Structural Biology
|May 29, 2013
PubMed
Summary

This study introduces a new cryo-electron microscopy forward model for accurate image simulation. The model accurately predicts image formation by considering specimen properties, microscope optics, and detector response, improving quantitative analysis.

Keywords:
Amplitude contrastCryo-electron microscopyImage simulationInSilicoTEMInteraction potentialPhase contrast

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Do's and Don'ts of Cryo-electron Microscopy: A Primer on Sample Preparation and High Quality Data Collection for Macromolecular 3D Reconstruction
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Area of Science:

  • Structural Biology
  • Microscopy Techniques
  • Computational Imaging

Background:

  • Accurate modeling of image formation is crucial for quantitative interpretation and optimization in cryo-electron microscopy (cryo-EM).
  • Existing models often lack comprehensive inclusion of specimen scattering, microscope optics, and detector response.

Purpose of the Study:

  • To develop and validate a comprehensive forward model for cryo-electron microscopy image simulation.
  • To accurately predict image formation by integrating specimen properties, microscope optics, and detector response.

Main Methods:

  • Calculated specimen interaction potential using the isolated atom superposition approximation (IASA), incorporating solvent dielectric/ionic properties and molecular electrostatics via the Poisson-Boltzmann approach.
  • Propagated electron waves through the specimen using the multislice approach and included optical effects via the contrast transfer function.
  • Incorporated camera detective quantum efficiency (DQE) instead of solely relying on the modulation transfer function (MTF).

Main Results:

  • The IASA-based potential dominates the interaction potential, with charge redistribution contributing less than 10%.
  • Simulations accurately predicted experimental images of 20S proteasome, hemoglobin, and GroEL.
  • The model successfully predicted effects of phase contrast, electron flux, thickness, inelastic scattering, DQE, and acceleration voltage.

Conclusions:

  • Beam-induced specimen movements are significant in experimental cryo-EM, while solvent amorphousness effects can be neglected.
  • The developed forward model provides a robust tool for quantitative image interpretation and data acquisition optimization in cryo-EM.
  • Simulation parameters are grounded in physical principles and experimental data.