Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data

Area of Science:

• Analytical Chemistry
• Biochemistry
• Computational Biology

Background:

• Lipid identification is essential for lipidomics, influencing data interpretation and biological insights.
• Mass spectrometry (MS) coupled with liquid chromatography (LC) is the primary technique for lipidomics, offering detailed identification.
• Ion mobility spectrometry (IMS) coupled with MS (IMS-MS) provides an additional separation dimension and structural information for enhanced lipid identification.

Purpose of the Study:

• To review available software tools for analyzing ion mobility spectrometry-mass spectrometry (IMS-MS) lipidomics data.
• To evaluate the performance of these software tools in lipid identification, particularly for isomers.
• To assess the integration of IMS-MS data analysis with MS-based imaging.

Main Methods:

• Survey of existing software tools for IMS-MS lipidomics data analysis.
• Evaluation of lipid identification accuracy using open-access data from peer-reviewed literature.
• Assessment of software capabilities for isomer identification, including double bond positioning.

Main Results:

• The adoption of IMS in lipidomics is limited, reflected in the scarcity of dedicated software tools.
• Software support for IMS-MS lipidomics data analysis, especially for isomer identification, remains underdeveloped.
• Performance evaluation of available tools using real-world data highlights areas for improvement.

Conclusions:

• There is a need for more robust and specialized software solutions for IMS-MS lipidomics data analysis.
• Improved software is critical for advancing lipid identification accuracy, particularly for complex lipid structures and isomers.
• Further development is required to fully leverage the potential of IMS-MS in lipidomics research and imaging.