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Lipidomics

What is Lipidomics?

As a branch of metabolomics, lipidomics is a research model based on high-throughput analysis and counting to systematically analyze changes in the composition and expression of lipids in organisms. As the main components of cell membranes and lipid droplets, lipids play important roles in a wide range of biological processes, such as signal transduction, transport, and the selection of biological macromolecules with different biochemical properties.

Lipidomic analysisFig. 1. Lipidomic analysis (Anal. Chem. 2018, 90(7): 4249-4257).

Lipidomics Analysis Technology

Advanced analytical methods capable of capturing their structural variety and estimating their abundance are needed for a thorough investigation of lipids in biological materials. Several techniques, such as chromatography, nuclear magnetic resonance (NMR) spectroscopy, and mass spectrometry (MS), have been developed over time to analyze lipids.

Mass Spectrometry (MS)

The most used method in lipidomics is mass spectrometry because of its great sensitivity, specificity, and capacity to evaluate numerous lipid classes at once. Ionization of lipids precedes separation based on mass-to-charge ratio (m/z) and detection in MS-based lipidomics. Several ionization methods, such as electrospray ionization (ESI) and matrix-assisted laser desorption/ionization, might be utilized depending on the kind of lipid and the needed analysis (MALDI). The content, saturation, and positional isomers of fatty acids as well as other details regarding lipid species may be obtained through MS.

Nuclear Magnetic Resonance (NMR) Spectroscopy

In lipidomics, NMR spectroscopy is yet another potent method. It offers comprehensive structural data on the lipid, including its connectivity, coupling constants, and chemical changes. Although NMR may be used to analyze lipids quantitatively as well as qualitatively, its sensitivity is often lower than MS.

Chromatography

To separate and identify lipids, chromatographic methods like liquid chromatography (LC) and gas chromatography (GC) are frequently used with MS or NMR. While GC-MS is better suited for the analysis of volatile and thermally stable lipids, LC-MS is particularly well suited for the investigation of complex lipid mixtures. The relative abundance of different lipid classes and subclasses may be determined using chromatographic methods.

Applications of Lipidomics

Lipidomics has broad applications in various fields, including biomedical research, nutrition, and drug discovery. By providing detailed understanding of lipid composition and dynamics, lipidomics helps identify lipid biomarkers of disease and develop therapeutic interventions.

Biomedical Research

Lipidomics is used in cancer research to identify possible targets for anticancer treatment by revealing changes in lipid metabolism in cancer cells. For instance, the development of breast cancer is linked to increased levels of certain lipids, such as phosphatidylcholine and sphingomyelin. Lipidomics has also shown alterations in lipid metabolism in various disorders, such as metabolic syndrome, neurological diseases, and cardiovascular diseases.

Nutrition Research

Lipidomics is essential for comprehending how diet affects health. Researchers can find certain lipids linked to health advantages or disease risks by examining the lipid profiles of various diets. Omega-3 fatty acids, which are present in fatty fish, have been connected, for instance, to lowered inflammation and enhanced cardiovascular health. Lipidomics can be used to clarify underlying processes and pinpoint prospective dietary intervention targets.

Drug Discovery

Lipidomics also contributes significantly to the identification and development of new drugs. Lipids can act as medication transporters or therapeutic drug targets. Researchers can create medications that particularly target lipid-related processes by comprehending the lipid composition of cell membranes and lipid-protein interactions. Moreover, lipidomics may be used to assess the efficacy and toxicity of medications by tracking how they affect lipid metabolism.

Reference

  1. Holčapek, M. et al. Lipidomic Analysis. Anal. Chem. 2018, 90(7): 4249-4257.

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