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Optimizing Lipidomics Analysis Workflows for Biological Fluids and Extracellular Vesicles with Integrated Liquid Chromatography Tandem Mass Spectrometry Approaches

Vilela, A. F. L.; Patricio, M. R.; Defelippo-Felippe, T. V.; Nardini, V.; Pontes, N. N. H.; Carvalho, J. C.; Nobre-Azevedo, P.; Rodrigues, D. L.; Oliveira, B. T. M.; da Silva-Neto, P. V.; Fernandes, A. P. M.; Almeida, F.; Faccioli, L. H.; Sorgi, C. A.

2024-11-08 biochemistry
10.1101/2024.11.08.622653 bioRxiv
Show abstract

Lipidomics, a subfield of metabolomics, involves the comprehensive analysis of lipids within biological systems and has become a cornerstone of biomedical research, driven by recent technological advancements. Lipids are crucial biomolecules in cellular functions and have been increasingly recognized for their roles in physiological and pathological processes. This study focuses on innovative strategies for developing, validating, and applying comprehensive analytical methods for untargeted lipidomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in human plasma and extracellular vesicles (EVs). We describe improvements based on analytical validation parameters, including inter-day repeatability, limit of quantification, precision, accuracy, recovery, and matrix effects. Plasma samples were used as a proof-of-concept study, and the method was ultimately applied to human macrophage-derived EVs. Samples preparations were achieved through four liquid-liquid extraction methods for lipids in order to achieve a broad coverage of lipid classes as well as high recovery and repeatability. Additionally, we demonstrated that a sonication-assisted homogenization step effectively facilitates lipid extraction from EVs. Through untargeted lipidomics, our study identifies and quantifies a diverse range of lipid species in human plasma (225 molecular lipids) and macrophage-derived EVs (124 molecular lipids) within different classes. Overall, we present an innovative methodology that combines pre-analytical lipid extraction techniques with high-resolution LC-MS/MS to enhance lipidomics research. This approach holds promise for personalized medicine and the discovery of novel lipid cargo associated with the various biological pathways involved with EVs biogenesis.

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