Abstract
Surfactant lipid metabolism is closely related to pulmonary diseases. Lipid metabolism disorder can cause lung diseases, vice versa. With this rationale, a useful method was established in this study to determine the lipidome in bronchoalveolar lavage fluid (BALF) of mice. The lipid components in BALF were extracted by liquid–liquid extraction (methanol and methyl tert-butyl ether, and water). Ultra-high-performance liquid chromatography coupled to hybrid Quadrupole-Exactive Orbitrap mass spectrometry was used to analyze the extracted samples, which showed a broad scanning range of 215–1800 m/z. With MS-DIAL software and built-in LipidBlast database, we identified 38 lipids in positive, and 31 lipids in negative, ion mode, including lysophosphatidylcholine (lysoPC), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), etc. Then, the changes of lipids in BALF of mice with acute lung injury (ALI) induced by lipopolysaccharide (LPS) was investigated, which may contribute to further exploration of the pathogenesis of ALI.
Highlights
Lipidomics is an important branch of metabolomics, aiming at the comprehensive analysis of lipids in biological systems
The necrotic cells and exudate were seen in the cavity
The results show that there is a significant difference between control group and acute lung injury (ALI) model group (p < 0.05 or p < 0.01)
Summary
Lipidomics is an important branch of metabolomics, aiming at the comprehensive analysis of lipids in biological systems. It is a useful research tool that can be applied in lipid biochemistry, lipid-related clinical biomarker discovery, disease pathology study and disease diagnosis. By comparing the changes in lipid metabolism networks under different physiological conditions, lipidomics assay can be used to identify the biomarkers in metabolic regulation, revealing the mechanism of lipid action in various life activities. Lipidomics technology mainly includes the research of lipid extraction, isolation, analysis, identification and bioinformatics technology. Software is usually required to analyze sample similarities and differences to identify significant regulated molecules between samples or groups, which can further undergoe in-depth analysis of metabolic pathways, biomarker identification, and biological significance assessment [1,2,3,4,5].
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