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Scalable Analysis of Untargeted LC-HRMS Data by Means of SQL Database Archiving
Marie Mardal1,2, Petur W Dalsgaard1, Brian S Rasmussen1
1Department of Forensic Medicine, University of Copenhagen, Frederik V's vej 11, Ø Copenhagen, Denmark.
Analytical Chemistry
|February 21, 2023
Summary
A new database strategy, ScreenDB, improves analysis of complex forensic drug screening data from liquid chromatography-high-resolution mass spectrometry (LC-HRMS). This scalable approach enhances long-term monitoring and retrospective analysis for biomonitoring projects.
Area of Science:
- Forensic Chemistry
- Analytical Chemistry
- Biomonitoring
Background:
- Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is crucial for analyzing complex biological samples.
- Current LC-HRMS data analysis methods face scalability challenges due to data complexity and amplitude.
Purpose of the Study:
- To introduce a novel, scalable data analysis strategy for untargeted LC-HRMS data.
- To develop a structured query language database (ScreenDB) for archiving and analyzing large-scale LC-HRMS datasets.
Main Methods:
- Implemented a structured query language database (ScreenDB) to archive parsed, untargeted LC-HRMS data after peak deconvolution.
- Utilized data acquired over 8 years from approximately 40,000 forensic drug screening files and quality control samples.
- Developed methods for slicing and dicing data across multiple layers within the database.
Main Results:
- ScreenDB successfully archives and organizes extensive LC-HRMS data from forensic drug screening.
- The database facilitates long-term system performance monitoring and retrospective analysis for new targets.
- Identified alternative analytical targets for poorly ionized analytes, demonstrating enhanced analytical capabilities.
Conclusions:
- ScreenDB offers a significant improvement for forensic services by providing a scalable data analysis solution for LC-HRMS.
- The database concept holds substantial potential for broad application in large-scale biomonitoring projects utilizing untargeted LC-HRMS data.
