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Lipid Wizard: Analysis Software for Comprehensive Two-Dimensional Liquid Chromatography-Mass Spectrometry-Based Lipid
Raobo Xu1,2,3,4, Huan Liu5, Fang Yuan1,2,3,4
1Department of Chemistry, University of Louisville, Louisville, Kentucky 40292, United States.
Analytical Chemistry
|March 25, 2024
Summary
Lipid Wizard software simplifies lipid identification from complex 2DLC-MS data. This tool aids researchers in accurately analyzing lipid profiles, crucial for understanding biological processes and disease states.
Area of Science:
- Biochemistry and Molecular Biology
- Analytical Chemistry
- Bioinformatics
Background:
- Lipids are vital molecules involved in numerous biological functions.
- Comprehensive two-dimensional liquid chromatography-mass spectrometry (2DLC-MS) is a powerful technique for lipid profiling.
- Accurate lipid identification and quantification from 2DLC-MS data present significant analytical challenges.
Purpose of the Study:
- To develop and validate open-source software, Lipid Wizard, for automated lipid assignment and isotopic peak stripping in 2DLC-MS data.
- To enhance the accuracy and efficiency of lipidomic data analysis.
- To facilitate the study of lipid alterations in biological systems, such as alcohol-induced liver changes.
Main Methods:
- Lipid Wizard utilizes precursor ion m/z matching against the LIPID MAPS database for initial lipid assignment.
- Lipid candidates are filtered using first-dimension (1D RT) and predicted second-dimension retention times (2D RT) based on an equivalent carbon number (ECN) model.
- Isotopic peak stripping is performed using an iterative linear regression algorithm.
Main Results:
- Lipid Wizard demonstrated robust performance in lipid identification and isotopic peak stripping using lipid standards.
- The software was successfully applied to analyze lipidomic changes in the livers of alcohol-fed mice (fat-1).
- The study successfully identified and quantified lipid alterations associated with alcohol consumption.
Conclusions:
- Lipid Wizard provides an effective and open-source solution for challenging lipid identification and quantification from 2DLC-MS data.
- The software significantly improves the analysis of complex lipidomic datasets.
- This tool will advance lipidomic research, particularly in areas like metabolic diseases and toxicology.
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