Current state-of-the-art of separation methods used in LC-MS based metabolomics and lipidomics

Metabolomics deals with the large-scale analysis of metabolites, belonging to numerous compound classes and showing an extremely high chemical diversity and complexity. Lipidomics, being a subcategory of metabolomics, analyzes the cellular lipid species. Both require state-of-the-art analytical methods capable of accessing the underlying chemical complexity. One of the major techniques used for the analysis of metabolites and lipids is Liquid Chromatography-Mass Spectrometry (LC-MS), offering both different selectivities in LC separation and high sensitivity in MS detection. Chromatography can be divided into different modes, based on the properties of the employed separation system. The most popular ones are Reversed-Phase (RP) separation for non- to mid polar molecules and Hydrophilic Interaction Liquid Chromatography (HILIC) for polar molecules. So far, no single analysis method exists that can cover the entire range of metabolites or lipids, due to the huge chemical diversity. Consequently, different separation methods have been used for different applications and research questions. In this review, we explore the current use of LC-MS in metabolomics and lipidomics. As a proxy, we examined the use of chromatographic methods in the public repositories EBI MetaboLights and NIH Metabolomics Workbench. We extracted 1484 method descriptions, collected separation metadata and generated an overview on the current use of columns, eluents, etc. Based on this overview, we reviewed current practices and identified potential future trends as well as required improvements that may allow us to increase metabolite coverage, throughput or both simultaneously.

Automated summary

Metabolomics and lipidomics involve the large-scale analysis of metabolites, requiring advanced analytical methods. Liquid Chromatography-Mass Spectrometry (LC-MS) is a commonly used technique that provides different selectivities in separation and high sensitivity in detection. Due to the huge chemical diversity, there is no single analysis method that can cover the entire range of metabolites or lipids, leading to the use of different separation methods. This review explores the current use of LC-MS in metabolomics and lipidomics using data from public databases, and highlights potential future trends and improvements needed.