Abstract
In this study, both conventional one-dimensional liquid chromatography (1DLC) and comprehensive two-dimensional liquid chromatography (2DLC) coupled to a high-resolution time-of-flight mass spectrometer (HR-TOF MS) were used for full-scale lipid characterization of lipid extracts from zebrafish embryos. We investigated the influence on annotated lipids and different separation mechanisms (HILIC, C18, and PFP), and their different orders arranged in the first and the second dimensions. As a result, the number of lipid species annotated by conventional one-dimensional LC-MS was between 212 and 448. In contrast, the number of individual lipids species annotated by C18×HILIC, HILIC×C18, and HILIC×PFP were 1784, 1059, and 1123, respectively. Therefore, it was evident that the performance of comprehensive 2DLC, especially the C18×HILIC method, considerably exceeded 1DLC. Interestingly, a comparison of the HILIC×C18 and C18×HILIC approaches showed, under the optimized conditions, similar orthogonality, but the effective separation power of the C18×HILIC was much higher. A comparison of the HILIC×C18 and the HILIC×PFP methods demonstrated that the HILIC×PFP separation had superior orthogonality with a small increase on its effective peak capacity, indicating that the HILIC×PFP combination maybe a promising platform for untargeted lipidomics in complex samples. Finally, from the comprehensive lipid profiling respective, the C18×HILIC was selected for further studies.
Highlights
Lipidomics is a fast-growing field, which aims to study the full spectrum of lipid species and the interaction among lipids in biological system
A good separation of compounds in a complex wastewater samples was achieved by liquid chromatography (LC)×LC with a combination of C18 and PFP, which enriches the versatility in developing online RPLC×RPLC methods [37]
The performance of comprehensive twodimensional LC-MS greatly overtook that of the conventional 1D LC-MS in untargeted lipidomic studies of zebrafish embryo samples
Summary
Lipidomics is a fast-growing field, which aims to study the full spectrum of lipid species and the interaction among lipids in biological system. Lipids play an essential role in energy storage, structural composition and cell signaling. The link between lipids and cancer, kidney diseases, diabetes, cardiovascular diseases, neurological disorders, obesity, and depression or anxiety has been previously reviewed [1,2,3,4,5,6]. Comprehensive analysis of lipids is gaining more attention in many fields, ranging from biomedical to environmental studies
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