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Retention behavior of lipids in reversed-phase ultrahigh-performance liquid chromatography-electrospray ionization mass spectrometry
M. Ovčačíková, M. Lísa, E. Cífková, M. Holčapek,
Language English Country Netherlands
Document type Journal Article
- MeSH
- Time Factors MeSH
- Chromatography, Reverse-Phase methods MeSH
- Erythrocytes chemistry MeSH
- Spectrometry, Mass, Electrospray Ionization methods MeSH
- Humans MeSH
- Lipids analysis blood chemistry urine MeSH
- Brain Chemistry MeSH
- Swine MeSH
- Chromatography, Supercritical Fluid MeSH
- Tandem Mass Spectrometry methods MeSH
- Chromatography, High Pressure Liquid MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
Reversed-phase ultrahigh-performance liquid chromatography (RP-UHPLC) method using two 15cm sub-2μm particles octadecylsilica gel columns is developed with the goal to separate and unambiguously identify a large number of lipid species in biological samples. The identification is performed by the coupling with high-resolution tandem mass spectrometry (MS/MS) using quadrupole - time-of-flight (QTOF) instrument. Electrospray ionization (ESI) full scan and tandem mass spectra are measured in both polarity modes with the mass accuracy better than 5ppm, which provides a high confidence of lipid identification. Over 400 lipid species covering 14 polar and nonpolar lipid classes from 5 lipid categories are identified in total lipid extracts of human plasma, human urine and porcine brain. The general dependences of relative retention times on relative carbon number or relative double bond number are constructed and fit with the second degree polynomial regression. The regular retention patterns in homologous lipid series provide additional identification point for UHPLC/MS lipidomic analysis, which increases the confidence of lipid identification. The reprocessing of previously published data by our and other groups measured in the RP mode and ultrahigh-performance supercritical fluid chromatography on the silica column shows more generic applicability of the polynomial regression for the description of retention behavior and the prediction of retention times. The novelty of this work is the characterization of general trends in the retention behavior of lipids within logical series with constant fatty acyl length or double bond number, which may be used as an additional criterion to increase the confidence of lipid identification.
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