Issue 20, 2025

Single-cell lipidomics: performance evaluation across four liquid chromatography mass spectrometry (LC-MS) systems

Abstract

Single-cell lipidomics holds tremendous promise for understanding a wide range of pathological conditions involving heterogenous cell populations, including infection, cancer, diabetes, and cardiovascular disease and yet its widespread adoption has been hitherto limited. Although Liquid Chromatography Mass Spectrometry (LC-MS) is a globally established method for lipidomics, its application to single cells has been considered particularly challenging, if not impossible, due to the very low sample volume and the high dynamic range and structural complexity of cellular lipids. Recent advances have shown that LC-MS-based single-cell lipidomics is achievable, offering the benefit of sampling cells in their native state, as well as chromatographic separation to reduce matrix effects and enhance peak annotation. In this study, we advocate for wider adoption of single-cell lipidomics by demonstrating that a range of widely accessible LC-MS platforms can successfully generate single-cell lipid profiles. Using four distinct instrumental configurations, we provide a perspective on the achievable depth of coverage and annotation. We show that polarity switching, ion mobility spectrometry, and electron-activated dissociation significantly enhance both lipidome coverage and confidence in lipid identification from single cells.

Graphical abstract: Single-cell lipidomics: performance evaluation across four liquid chromatography mass spectrometry (LC-MS) systems

Supplementary files

Article information

Article type
Communication
Submitted
08 Aug 2025
Accepted
19 Sep 2025
First published
23 Sep 2025
This article is Open Access
Creative Commons BY license

Analyst, 2025,150, 4525-4534

Single-cell lipidomics: performance evaluation across four liquid chromatography mass spectrometry (LC-MS) systems

J. von Gerichten, K. D. G. Saunders, M. Spick and M. J. Bailey, Analyst, 2025, 150, 4525 DOI: 10.1039/D5AN00851D

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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