UPLC-QqQ/MS-Based Lipidomics Approach to Characterize Lipid Alterations in Inflammatory Macrophages

Jae Won Lee, Hyuck Jun Mok, Dae Young Lee, Seung Cheol Park, Geum Soog Kim, Seung Eun Lee, Young Seob Lee, Kwang Pyo Kim, Hyung Don Kim

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

In this study, UPLC-QqQ/MS-based lipidomics was applied to profile various lipids from RAW264.7 macrophages treated with different concentrations of lipopolysaccharide (LPS). The degree of inflammation increased with the LPS concentration. To elucidate the altered lipid metabolism of inflammatory macrophages, we targeted to analyze 25 lipid classes from LPS-treated RAW264.7 cells. As a result, 523 lipid species were successfully profiled by using the optimal UPLC and MRM. Statistical data analyses such as PCA, PLS-DA, and HCA differentiated five RAW264.7 cells treated with different concentrations of LPS. VIP plot, heat map, and bar plot also provided lists of up- or down-regulated lipids according to the LPS concentration. From the results, 11 classes of lipids, TG, DG, ChE, PE, PS, PI, PA, LyPC, LyPE, Cer, and dCer, were increased, and three classes, cholesterol, PC, and LyPA, were decreased in an LPS concentration-dependent manner. Furthermore, the treatment of an anti-inflammatory compound recovered the levels of PC, PE, PI, PA, LyPE, LyPA, and Cer from the activated macrophages. Finally, these results demonstrate the correlation between inflammation and lipid metabolism in macrophages. The differentially regulated lipids also have the potential to be used as biomarkers for inflammation.

Original languageEnglish
Pages (from-to)1460-1469
Number of pages10
JournalJournal of Proteome Research
Volume16
Issue number4
DOIs
StatePublished - 7 Apr 2017

Keywords

  • inflammation
  • lipidomics
  • lipopolysaccharide
  • macrophages
  • UPLC-QqQ/MS

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