Jake D. Johnston

This paper introduces a pipeline for high-resolution cryo-ET imaging using square electron beams, demonstrating improved resolution and field-of-view by reducing radiation damage and overlap.

This paper introduces a method to reduce air-water interface artifacts in cryo-EM by encapsulating proteins in hydrophilic shells, demonstrating its effectiveness with three protein examples.

This paper develops a platform for creating protein nanoparticles using electrostatic interactions between globular proteins and intrinsically disordered polypeptides, enabling controlled delivery of functional proteins.

This study shows that cationic amino acid identity and net charge affect condensate properties in E. coli, with arginine promoting better encapsulation and stability than lysine.

The paper introduces cryoDRGN-AI, a method for ab initio 3D reconstruction of cryo-EM and cryo-ET datasets, revealing new conformational states and unresolved motions.

TARDIS is a deep learning framework that rapidly and accurately segments membranes and filaments in electron microscopy data, enabling large-scale biophysical analysis.

This paper introduces CryoCycle, a method for blotting, vitrifying, and reusing clipped cryoEM grids to reduce costs and improve access to cryoEM.