Reproducible mass spectrometry data processing and compound annotation in MZmine 3

Area of Science:

• Analytical Chemistry
• Computational Chemistry
• Bioinformatics

Background:

• Untargeted mass spectrometry (MS) generates complex data requiring computational tools for analysis.
• Manual investigation of multidimensional MS data is impractical.
• Software solutions are crucial for extracting meaningful information from raw spectral data.

Purpose of the Study:

• To present MZmine 3, an open-source software for processing untargeted MS data.
• To describe three distinct procedures for feature detection and annotation.
• To support various MS platforms including liquid chromatography-MS, gas chromatography-MS, MS-imaging, and ion mobility spectrometry (IMS) data.

Main Methods:

• Utilized MZmine 3, an open-source software package.
• Developed three specific protocols for feature detection and annotation.
• Included example datasets and configuration batch files for user training and workflow replication.
• Detailed descriptions and optimization recommendations for all processing parameters were provided.

Main Results:

• MZmine 3 supports processing of diverse MS data, including LC-MS, GC-MS, MS-imaging, and IMS-MS.
• Provided three distinct, replicable workflows for untargeted MS data analysis.
• Generated aligned feature tables and fragmentation spectra lists for downstream analysis.
• Anticipated processing time of 2-24 hours for new users.

Conclusions:

• MZmine 3 enhances the analysis of untargeted MS data across various platforms.
• The software facilitates metabolomics, lipidomics, and other MS-based research.
• The provided protocols and examples lower the barrier for new users to analyze complex MS data.