Oxylipins are a class of low-abundance lipids formed via oxygenation of fatty acids. These compounds include potent signaling molecules (e.g., octadecanoids, eicosanoids) that can exert essential functions in the pathophysiology of inflammatory diseases including asthma. While some oxylipin signaling cascades have been unraveled using LC-MS/MS-based methods, measurements in homogenate samples do not represent the spatial heterogeneity of lipid metabolism. Mass spectrometry imaging (MSI) directly detects analytes from a surface, which enables spatial mapping of oxylipin biosynthesis and migration within the tissue. MSI has lacked the sensitivity to routinely detect low-abundance oxylipins; however, new multiple-reaction-monitoring (MRM)-based MSI technologies show increased sensitivity. In this study, we developed a workflow to apply desorption electrospray ionization coupled to a triple quadrupole mass spectrometer (DESI-MRM) to spatially map oxylipins in pulmonary tissue. The targeted MSI workflow screened guinea pig lung extracts using LC-MS/MS to filter oxylipin targets based on their detectability by DESI-MRM. A panel of 5 oxylipins was then selected for DESI-MRM imaging derived from arachidonic acid (TXB(2), 11-HETE, 12-HETE), linoleic acid (12,13-DiHOME), and α-linolenic acid (16-HOTrE). To parse this new data type, a custom-built R package (quantMSImageR) was developed with functionality to label regions of interest as well as quantify and analyze lipid distributions. The spatial distributions quantified by DESI-MRM were supported by LC-MS/MS analysis, with both indicating that 16-HOTrE and 12-HETE were associated with airways, while 12,13-DiHOME and arachidonic acid were mapped to parenchyma. This study realizes the potential of targeted MSI to routinely map low-abundance oxylipins with high specificity at scale.
Development of a Desorption Electrospray Ionization-Multiple-Reaction-Monitoring Mass Spectrometry (DESI-MRM) Workflow for Spatially Mapping Oxylipins in Pulmonary Tissue.
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作者:Smith Matthew J, Nie Mu, Adner Mikael, Säfholm Jesper, Wheelock Craig E
| 期刊: | Analytical Chemistry | 影响因子: | 6.700 |
| 时间: | 2024 | 起止号: | 2024 Nov 12; 96(45):17950-17959 |
| doi: | 10.1021/acs.analchem.4c02350 | ||
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