nextPYP: a comprehensive and scalable platform for characterizing protein variability in situ using single-particle...

Area of Science:

• Structural Biology
• Biophysics
• Cell Biology

Background:

• Single-particle cryo-electron tomography (cryo-ET) offers molecular resolution of proteins within native cellular contexts.
• High-throughput cryo-ET data generation is advancing, but complex analysis and computational demands hinder widespread adoption.
• Current limitations include intricate data processing pipelines and substantial storage/computational needs.

Purpose of the Study:

• To develop a scalable, end-to-end data analysis framework for single-particle cryo-ET.
• To overcome barriers in data processing, storage, and computation for cryo-ET.
• To facilitate high-resolution structural studies of proteins in situ.

Main Methods:

• Developed a comprehensive framework for cryo-ET data analysis, from pre-processing to refinement and classification.
• Implemented on-the-fly pre-processing of tilt series for efficient data handling.
• Designed for analysis of large datasets, including hundreds of tilt series and hundreds of thousands of particles.

Main Results:

• Demonstrated a scalable framework for efficient analysis and visualization of large cryo-ET datasets.
• Achieved high-resolution structural determination using both in vitro and cellular data.
• Successfully revealed in situ conformational heterogeneity of proteins.

Conclusions:

• The presented framework significantly enhances the efficiency and accessibility of cryo-ET data analysis.
• nextPYP facilitates high-resolution structural insights into protein dynamics within native cellular environments.
• The framework's availability as an intuitive application promotes broader adoption of cryo-ET technology.