A strategic approach for efficient cryo-EM grid optimization using design of experiments.

Area of Science:

• Structural Biology
• Biophysics
• Biochemistry

Background:

• Cryo-electron microscopy (cryo-EM) is crucial for high-resolution structure determination.
• Sample preparation, specifically grid optimization, is a significant bottleneck in the cryo-EM workflow.
• Current methods require multiple, time-consuming iterations of grid vitrification and screening.

Purpose of the Study:

• To develop a strategic and efficient approach to expedite cryo-EM grid optimization.
• To reduce the number of iterations required for successful grid preparation.
• To improve the quality of ice thickness and particle distribution for data collection.

Main Methods:

• Implementation of Design of Experiments (DOE), specifically Fractional Factorial Design (FFD).
• Systematic screening of limited experimental conditions to model the parameter space.
• Quantitative scoring of ice thickness and particle distribution based on a qualitative rubric.
• Generation of a least-squares regression model using JMP software.

Main Results:

• The DOE approach successfully identified optimal grid conditions for apoferritin and L-glutamate dehydrogenase.
• Optimized grids exhibited high-quality ice and particle distribution suitable for data collection.
• The method was validated on both Vitrobot Mark IV and Leica GP2 plunge freezers.
• The approach reliably yielded grids for overnight data collection on a Krios microscope.

Conclusions:

• DOE provides a cost-effective and time-saving strategy for cryo-EM grid preparation.
• This approach significantly streamlines the optimization process, accelerating research.
• DOE enables researchers to achieve high-quality samples more efficiently.