Energy filtering enables macromolecular MicroED data at sub-atomic resolution

Area of Science:

• * Correlative microscopy and structural biology.
• * Advanced electron crystallography techniques.

Background:

• * Obtaining high-resolution data in macromolecular crystallography is limited by fading diffraction intensities and radiation damage.
• * Direct electron detectors and electron counting enable MicroED data collection at low flux, but inelastic scattering remains a significant noise source.
• * Noise from inelastic scattering hinders accurate measurement of faint, high-resolution reflections.

Purpose of the Study:

• * To investigate the impact of energy filtering on MicroED data quality and resolution.
• * To assess the combined benefits of energy filtering and electron counting for macromolecular structure determination.
• * To explore novel structural information from diffuse scattering phenomena.

Main Methods:

• * Utilized electron counting with direct electron detectors for MicroED data acquisition.
• * Implemented an energy filter to remove inelastically scattered electrons.
• * Collected and processed MicroED data from proteinase K crystals.

Main Results:

• * Energy filtering significantly improved the signal-to-noise ratio by reducing background noise from inelastic scattering.
• * Achieved sub-atomic resolution MicroED data, enabling accurate structure modeling and visualization of fine details.
• * Observed and characterized diffuse scattering phenomena previously obscured by noise.

Conclusions:

• * Combining energy filtering with electron counting in MicroED enhances data accuracy and resolution.
• * This approach facilitates precise protein structure refinement and deeper understanding of protein function.
• * Diffuse scattering, revealed by noise reduction, offers potential for additional structural insights.