ObjectivesBovine milk is rich in sphingomyelin (SM), a class of polar lipids which may affect the gut microbiome and have anti-inflammatory properties. Infusion mass spectrometry rapidly yields valuable information about the structure of SM, but quantitation is confounded by isobaric phosphatidylcholine (PC) lipids. Using previously established Li-induced fragmentation chemistry, we developed a quantitative method for analysis of SM species using selective multiple reaction monitoring (MRM) transitions.MethodsPolar lipids were extracted from milk samples using organic solvents followed by silicic acid solid phase extraction (SPE) to remove triacylglycerol (TAG). Extracts were dissolved in methanol with 0.2 mM lithium acetate and analyzed on an AB Sciex 5500 QTRAP hybrid mass spectrometer in an infusion-based manner. SM species were identified by a characteristic 207 Da loss, representing the loss of [Li + H2O + (CH3)3NC2H4PO4] allowing for separation from PC species. Commercially available SM standards were used where possible to verify identity. A total SM profile was determined through neutral loss (NL) 207 Da scans, SM fine structure with MS3 scans, and individual SM species were quantified utilizing MRM.ResultsUse of the Li- mediated fragmentation and the NL 207 Da scans allowed for selective quantitation of SM, but not PC species, with limits of detection >1 nM and limits of quantitation >10 nM for individual SM species. Milk matrix TAG suppressed MRM intensities by 10-fold requiring SPE removal of TAG. In bovine milk, 30 individual SM species were detected ranging from SM 28:1 to SM 44:2. SM were predominately 16:1 and 18:1 sphingoid bases with fatty acid tails ranging from 10 to 26 carbons. Utilizing this method, we determined the SM content of fluid dairy products including whole bovine milk (37 μM), half and half (70 μM), whipping cream (130 μM), and goat milk (56 μM).ConclusionsA rapid, infusion-based MS approach was developed to selectivity identify and quantify SM species that avoids isobaric overlap with PC. This method is robust and could potentially be applied to other SM-containing samples.Funding SourcesThis work was funded by USDA-ARS Projects 3062-53,000-001-00D and supported by the USDA-ARS Grand Challenge Synergy project “Dairy Agriculture for People and Planet”.
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