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

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.

UPLC-MS/MS-Based Profiling of Eicosanoids in RAW264.7 Cells Treated with Lipopolysaccharide.

While both the pro- and anti-inflammatory effects of several eicosanoids have been widely studied, the degree of inflammation in cells that results from various eicosanoids has yet to be comprehensively studied. The objective of this study was to assess the effect of lipopolysaccharide (LPS) treatment on eicosanoid content in RAW264.7 cells. An Ultra performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS)-based profiling method was used to analyze the eicosanoid contents of RAW264.7 cells treated with different LPS concentrations. The profiling data were subjected to statistical analyses, such as principal component analysis (PCA) and hierarchical clustering analysis. LPS treatment increased nitric oxide production and secretion of pro-inflammatory cytokines, such as tumor necrosis factor-α and interleukin-6, in a concentration-dependent manner. In total, 79 eicosanoids were identified in the cells. RAW264.7 cells treated with different LPS concentrations were well differentiated in the PCA score plot. A heatmap was used to identify the eicosanoids that were up- or down-regulated according to the degree of inflammation and LPS concentration. Thirty-nine eicosanoids were upregulated and seven were down-regulated by LPS treatment in a concentration-dependent manner. Our novel UPLC-MS/MS technique can profile eicosanoids, and can evaluate the correlations between inflammation and eicosanoid metabolism.

Small polyanion recognition of a triazolium cyclodextrin click cluster in water.

In order to detect small polyanions (sPAs), which play important roles in many biological systems, a triazolium cyclodextrin click cluster (5, hexakis{6-(3-methyl-4-hydroxymethyl-1H-1,2,3-triazolium-1-yl)-6-deoxy}-α-cyclodextrin iodide) was synthesized and characterized. The competition binding to 5 occupied by 5-carboxyfluorescein of inositol-1,4,5-trisphosphate (IP3), phytic acid, adenosine triphosphate (ATP), ethylenediaminetetraacetic acid (EDTA), glucose, and glucose-6-phosphate was evaluated by UV/vis titration in HEPES (10 mM, pH 7.4) : methanol (1 : 1, v/v). We obtained the binding constants of IP3 and phytic acid to 5 (1.4 × 10(6) and 1.9 × 10(6) M(-1), respectively); however, the binding constants of ATP and EDTA were significantly lower (2.1 × 10(5) and 4.5 × 10(4) M(-1), respectively). Moreover, glucose and glucose-6-phosphate did not show any detectable binding. In addition, the sPA recognition of the triazolium cyclodextrin click cluster in water was confirmed by fluorescence titration.