Automation in single-particle electron microscopy connecting the pieces

Area of Science:

• Structural biology
• Microscopy techniques

Background:

• Single-particle electron microscopy (EM) faces challenges from increasing data volumes and user diversity.
• Sophisticated specimen preparation, data processing, and quality assessment tools are now available.
• An influx of new users necessitates advanced automation.

Purpose of the Study:

• To define and review key advances in automated techniques for single-particle electron microscopy.
• To illustrate automation as a comprehensive strategy for large-scale biological data acquisition.
• To contrast manual and automated approaches, highlighting breakthroughs and limitations.

Main Methods:

• Review of automated approaches in specimen preparation, grid handling, robotic screening, and microscope calibration.
• Discussion of automation in data acquisition, image processing, and computational infrastructure.
• Examples from the National Resource for Automated Molecular Microscopy (NRAMM) are provided.

Main Results:

• Automation addresses challenges in modern single-particle electron microscopy.
• Automated techniques cover specimen preparation through data analysis.
• Specific processing packages and NRAMM approaches are highlighted.

Conclusions:

• Automation is essential for managing the scale and complexity of modern single-particle EM.
• Automated strategies significantly enhance the capacity for biological information discovery.
• Future improvements in automation promise further advancements in the field.