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Related Experiment Video

Updated: Nov 6, 2025

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

Global Lipidomics Profiling by a High Resolution LC-MS Platform.

Thomas Züllig¹, Martin Trötzmüller¹, Harald C Köfeler²

¹Core Facility Mass Spectrometry, Medical University of Graz, Graz, Austria.

Methods in Molecular Biology (Clifton, N.J.)

|May 6, 2021

Summary

This summary is machine-generated.

This study details a lipidomics protocol using high-resolution mass spectrometry for lipid identification. It covers extraction, Orbitrap mass spectrometry data acquisition, and analysis with open-source software.

Keywords:

Chromatography LC-MS Lipid data analyzer Lipidomics Lipids Mass spectrometry

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Shotgun Lipidomics of Rodent Tissues

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Last Updated: Nov 6, 2025

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Published on: March 14, 2013

Shotgun Lipidomics of Rodent Tissues

Shotgun Lipidomics of Rodent Tissues

Published on: November 18, 2022

Area of Science:

Biochemistry
Analytical Chemistry
Mass Spectrometry

Background:

Lipidomics involves characterizing lipid profiles using mass spectrometry.
Accurate lipid identification relies on mass, fragmentation, and retention time data.

Purpose of the Study:

To present a comprehensive protocol for lipidomics analysis.
To detail lipid extraction, LC-MS data acquisition, and data processing.

Main Methods:

Lipid extraction from biological samples.
Liquid chromatography coupled with high-resolution Orbitrap mass spectrometry (LC-MS).
Data processing using the open-source Lipid Data Analyzer software.

Main Results:

Successful identification of lipids based on exact mass, fragment spectra, and retention time.
Demonstration of a complete workflow from sample to analyzed data.

Conclusions:

The presented protocol enables robust lipid identification and quantification.
The open-source Lipid Data Analyzer facilitates efficient lipidomics data processing.