MS-DIAL 5 multimodal mass spectrometry data mining unveils lipidome complexities

MS-DIAL 5 多模态质谱数据挖掘揭示脂质组的复杂性

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Abstract

Lipidomics and metabolomics communities comprise various informatics tools; however, software programs handling multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 for in-depth lipidome structural elucidation through electron-activated dissociation (EAD)-based tandem MS and determining their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section values. With the optimized EAD settings using 14 eV kinetic energy, the program correctly delineated lipid structures for 96.4% of authentic standards, among which 78.0% had the sn-, OH-, and/or C = C positions correctly assigned at concentrations exceeding 1 μM. We showcased our workflow by annotating the sn- and double-bond positions of eye-specific phosphatidylcholines containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and n-3-VLC-PUFA-supplemented HeLa cells, we identified glycerol 3-phosphate acyltransferase as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into the sn1 position of phospholipids in mammalian cells, which was confirmed using EAD-MS/MS and recombinant proteins in a cell-free system. Therefore, the MS-DIAL 5 environment, combined with optimized MS data acquisition methods, facilitates a better understanding of lipid structures and their localization, offering insights into lipid biology.

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