Automated data collection and real-time data analysis suite for serial synchrotron crystallography

Area of Science:

• Structural Biology
• Crystallography
• Biophysics

Background:

• Macromolecular crystallography (MX) is crucial for determining protein structures.
• Serial synchrotron crystallography (SSX) enables high-throughput structure determination from microcrystals.
• Efficient data acquisition and processing are essential for SSX success.

Purpose of the Study:

• To present the DA+ software suite for enhanced serial synchrotron crystallography (SSX) data collection and analysis.
• To highlight the integration of automated data processing and merging for MX experiments.
• To improve the efficiency and throughput of SSX experiments at the Swiss Light Source.

Main Methods:

• Development and implementation of the DA+ data acquisition and analysis software suite.
• Utilizing a 2D grid scan method for microcrystal localization.
• Employing the CY+ GUI for assessment and automated data collection (minisets).
• Adapting automated data processing (adp) and automatic data merging (adm) routines for SSX data.
• Integration with MX MongoDB database and web-based tracker for real-time feedback.

Main Results:

• The SSX suite facilitates easy, efficient, and high-throughput measurements.
• Automated data processing (adp) provides near real-time analysis of SSX data.
• Automatic data merging (adm) with the sxdm package optimizes data quality.
• On-the-fly experimental feedback is provided through a web-based tracker.

Conclusions:

• The DA+ software suite significantly improves SSX data collection and analysis efficiency.
• Automated processing and merging enhance the throughput and quality of structural data.
• Real-time feedback mechanisms empower users to optimize SSX experiments effectively.