This study demonstrated the performances of top-down and bottom-up approaches in lipidomic analysis of lipoproteins from rabbits raised under different metabolic conditions: healthy controls, carrageenan-induced inflammation, dehydration, high cholesterol (HC) diet, and highest cholesterol diet with inflammation (HCI). In the bottom-up approach, the high density lipoproteins (HDL) and the low density lipoproteins (LDL) were size-sorted and collected on a semi-preparative scale using a multiplexed hollow fiber flow field-flow fractionation (MxHF5), followed by nanoflow liquid chromatography-ESI-MS/MS (nLC-ESI-MS/MS) analysis of the lipids extracted from each lipoprotein fraction. In the top-down method, size-fractionated lipoproteins were directly infused to MS for quantitative analysis of targeted lipids using chip-type asymmetrical flow field-flow fractionation-electrospray ionization-tandem mass spectrometry (cAF4-ESI-MS/MS) in selected reaction monitoring (SRM) mode. The comprehensive bottom-up analysis yielded 122 and 104 lipids from HDL and LDL, respectively. Rabbits within the HC and HCI groups had lipid patterns that contrasted most substantially from those of controls, suggesting that HC diet significantly alters the lipid composition of lipoproteins. Among the identified lipids, 20 lipid species that exhibited large differences (>10-fold) were selected as targets for the top-down quantitative analysis in order to compare the results with those from the bottom-up method. Statistical comparison of the results from the two methods revealed that the results were not significantly different for most of the selected species, except for those species with only small differences in concentration between groups. The current study demonstrated that top-down lipid analysis using cAF4-ESI-MS/MS is a powerful high-speed analytical platform for targeted lipidomic analysis that does not require the extraction of lipids from blood samples.
Bibliographical noteFunding Information:
This study was supported by the Bio & Medical Technology Development Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science, ICT & Future Planning ( NRF-2013M3A9B6046413 ), and in part by a grant NRF-2015R1A2A1A01004677 .
© 2015 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Analytical Chemistry
- Organic Chemistry