TYSON: robust searching, sorting, and selecting of single particles in electron micrographs.

Area of Science:

• Structural Biology
• Biophysics
• Microscopy

Background:

• Accurate particle selection is crucial for high-resolution cryo-electron microscopy (cryo-EM).
• Manual particle selection is time-consuming and subjective.

Purpose of the Study:

• To introduce TYSON, a novel software tool for automated and semi-automated particle selection in electron micrographs.
• To provide an efficient and user-friendly solution for processing large cryo-EM datasets.

Main Methods:

• TYSON utilizes a three-step strategy: searching, sorting, and selecting single particles.
• Particle identification employs local averaging, template matching, or local variance methods.
• Automated sorting based on probability of true positives and an interactive step for false positive removal.

Main Results:

• TYSON demonstrated efficiency in selecting particles from both spherical virus and asymmetric particle cryo-EM datasets.
• The software enables rapid particle selection, with up to 20,000 particles processed in a single day.
• The interactive step allows for quick elimination of false positives.

Conclusions:

• TYSON offers a fast and effective solution for particle selection in cryo-EM.
• The program streamlines the initial stages of cryo-EM data processing, facilitating higher throughput.
• TYSON is suitable for both spherical and asymmetric particle analysis.