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Evaluation of lipid quantification accuracy using HILIC and RPLC MS on the example of NIST® SRM® 1950 metabolites in human plasma

Lipidomics analysis for large-scale studies aiming at the identification and quantification of natural lipidomes is often performed using LC–MS-based data acquisition. However, the choice of suitable LC–MS method for accurate lipid quantification remains a matter of debate. Here, we performed the sy...

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Detalles Bibliográficos
Autores principales: Lange, Mike, Fedorova, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220885/
https://www.ncbi.nlm.nih.gov/pubmed/32240327
http://dx.doi.org/10.1007/s00216-020-02576-x
Descripción
Sumario:Lipidomics analysis for large-scale studies aiming at the identification and quantification of natural lipidomes is often performed using LC–MS-based data acquisition. However, the choice of suitable LC–MS method for accurate lipid quantification remains a matter of debate. Here, we performed the systematic comparison between two HRAM-MS-based quantification workflows based on HILIC and RPLC MS by quantifying 191 lipids from five lipid classes in human blood plasma using deuterated standards in the “one ISTD-per-lipid class” approach. Lipid quantification was performed considering all necessary isotopic corrections, and obtained correction factors are illustrated. Concentrations of lipids in NIST® SRM® 1950 human blood plasma determined by the two methods were comparable for most of the studied lipid species except for highly unsaturated phosphatidylcholines (PC). A comparison of lipid concentrations to consensus values determined in a previously published multi-laboratory study illustrated possible “overestimation” of concentrations for these highly unsaturated lipids by HILIC MS. We evaluated the influence of lipid loading amounts as well as the difference between quantified lipid and internal standard concentrations on the HILIC MS quantification results. We conclude that both HILIC and RPLC HRAM-MS workflows can be equally used for accurate lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), and sphingomyelin (SM) lipid quantification, despite significant differences in the concentration of highly unsaturated PC lipids which need to be addressed by establishing response factors to account for the differences in degree of lipid unsaturation. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-020-02576-x) contains supplementary material, which is available to authorized users.