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Related Experiment Video

Updated: Jul 8, 2025

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques
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Cryo-Electron Microscopy Screening Automation across Multiple Grids using Smart Leginon.

Anjelique Sawh-Gopal1, Aygul Ishemgulova2, Eugene Y D Chua2

  • 1Simons Electron Microscopy Center, New York Structural Biology Center; Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology.

Journal of Visualized Experiments : Jove
|December 18, 2023
PubMed
Summary

Automating cryo-electron microscopy (cryoEM) grid screening with Smart Leginon Autoscreen significantly reduces operator time and microscope usage. This AI-powered system streamlines the optimization process for high-resolution structural biology research.

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Area of Science:

  • Structural Biology
  • Biophysics
  • Microscopy

Background:

  • Cryo-electron microscopy (cryoEM) enables near-atomic resolution of protein complexes.
  • The cryoEM workflow involves iterative sample preparation and grid screening, which is a major bottleneck.
  • Manual screening is time-consuming, operator-dependent, and limited by microscope accessibility.

Purpose of the Study:

  • To automate the cryo-electron microscopy (cryoEM) grid screening process.
  • To reduce the significant operator time and resources currently required for cryoEM grid optimization.
  • To demonstrate the utility of Leginon and Smart Leginon Autoscreen for unattended grid screening.

Main Methods:

  • Implementation of Leginon software for automated microscope control.
  • Utilizing Smart Leginon Autoscreen, which integrates machine learning and computer vision.
  • Employing an automated specimen-exchange cassette system for unattended loading and imaging of multiple grids.

Main Results:

  • Smart Leginon Autoscreen autonomously screens grids, reducing operator time from ~6 hours to ~10 minutes for 12 grids.
  • The automated system effectively handles multi-scale imaging and particle behavior analysis in ice.
  • Unattended screening of an entire cassette of grids is achieved, minimizing manual intervention.

Conclusions:

  • Automated cryoEM grid screening using Smart Leginon Autoscreen drastically improves efficiency.
  • This automation overcomes the limitations of manual screening, including variability between grids and operator time.
  • The protocol provides a step-by-step guide for setting up and running automated screening sessions.