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Establishing an untargeted lipidomics workflow for cellular analysis: insights into endothelial cell function in
María Isabel Delgado Dolset1,2, Andrea Escolar-Peña2, Sergio Fernández-Bravo3
1Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Spain.
Frontiers in Immunology
|March 20, 2026
Summary
This study introduces a novel cell lipidomics workflow to analyze limited cell populations. The method effectively distinguishes intracellular lipids from external sources, enabling accurate metabolic profiling in conditions like anaphylaxis.
Area of Science:
- * Biochemistry and Molecular Biology
- * Metabolomics and Lipidomics
- * Immunology and Cell Signaling
Background:
- * Cell metabolomics, particularly lipidomics, faces challenges in analyzing small cell numbers and differentiating cellular metabolites from external signals.
- * Existing methods struggle with background noise from stimuli or treatments, complicating the analysis of intracellular metabolic changes.
Purpose of the Study:
- * To develop and validate a novel workflow for untargeted cell lipidomics analysis.
- * To establish a method for distinguishing cell-derived lipid signals from background noise.
- * To apply the workflow to investigate lipidomic alterations in human microvascular dermal endothelial cells during anaphylaxis.
Main Methods:
- * Analysis of varying cell counts (50k-1M) of CD3+ cells using liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS) in positive and negative electrospray ionization modes.
- * Application of Spearman correlation analyses to identify cell-derived chemical signals (ρ ≥ 0.7, p-value < 0.05).
- * Development of a cell number calibration curve for human microvascular dermal endothelial cells (HMVEC-d) and analysis of lipid responses during anaphylaxis stages.
Main Results:
- * Correlation analysis enabled clear clustering by cell number in CD3+ cells (50k-1M), with principal component analysis (PCA) explaining over 90% of variance.
- * For HMVEC-d, 157 and 278 correlated lipid signals were identified in positive and negative modes, respectively.
- * 193 significantly altered lipid signals differentiated acute anaphylaxis from baseline, with 75 unique lipids annotated (fatty acids, acyl carnitines, glycerophospholipids, sphingolipids) showing increased levels in the acute phase.
Conclusions:
- * The developed workflow successfully selects intracellular lipids, regardless of external sources.
- * This method supports specific intracellular metabolism profiling, overcoming limitations in analyzing small cell populations.
- * The findings provide insights into lipidomic changes associated with anaphylaxis, highlighting pathways like sphingolipid metabolism and signaling.
