Software tool for mining liquid chromatography/multi-stage mass spectrometry data for comprehensive...

Area of Science:

• Biochemistry
• Analytical Chemistry
• Computational Biology

Background:

• Lipidomics research relies heavily on mass spectrometry techniques.
• Limited availability of user-friendly software hinders comprehensive lipid analysis.
• Automated data processing is crucial for efficient lipid identification and quantification.

Purpose of the Study:

• To develop a computational tool for processing raw data from liquid chromatography/mass spectrometry (LC/MS) experiments.
• To create a software package that aids in lipid identification and relative quantification.
• To accelerate manual data evaluation in lipidomics studies.

Main Methods:

• Development of the Profiler-Merger-Viewer software package implemented in Java.
• Utilizing high-performance liquid chromatography hyphenated to electrospray ionization hybrid linear ion trap Fourier transform mass spectrometry (FTICR-MS and Orbitrap).
• Processing raw data for lipid identification, summarizing replicate measurements, and visualizing results.

Main Results:

• The Profiler-Merger-Viewer tool automates the processing of LC/MS data for lipidomics.
• The software facilitates lipid identification and relative quantification through its Profiler, Merger, and Viewer modules.
• The tool supports data-dependent experiments and is compatible with FTICR-MS and Orbitrap instruments.

Conclusions:

• The developed software significantly supports and accelerates manual data evaluation in lipidomics.
• The Profiler-Merger-Viewer tool provides a user-friendly approach to analyzing complex lipidomics datasets.
• This tool enhances the efficiency of lipid analysis, focusing on glycerophospholipids, lyso-glycerophospholipids, and free fatty acids.