UPLC-QqQ/MS-Based Lipidomics Approach To Characterize Lipid Alterations in Inflammatory Macrophages.
Jae Won LeeHyuck Jun MokDae Young LeeSeung Cheol ParkGeum-Soog KimSeung-Eun LeeYoung-Seob LeeKwang Pyo KimHyung Don KimPublished in: Journal of proteome research (2017)
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.
Keyphrases
- anti inflammatory
- inflammatory response
- fatty acid
- oxidative stress
- induced apoptosis
- ms ms
- lps induced
- cell cycle arrest
- transcription factor
- simultaneous determination
- toll like receptor
- signaling pathway
- endoplasmic reticulum stress
- electronic health record
- newly diagnosed
- cell proliferation
- cancer therapy
- artificial intelligence
- climate change
- human health