Determination of Monounsaturated Fatty Acid Isomers in Biological Systems by Modeling MS Product Ion Patterns.

Unsaturated free fatty acids are natively present in biological samples as isomers, where double bonds can be situated on different carbons in the acyl chain. While these isomers can have different actions and impacts on biological systems, they are inherently difficult to identify and differentiate by mass spectrometry alone. To address this challenge, several techniques for derivatization of the double bond or metal cationization at the carboxylic group have yielded diagnostic product ions for the respective isomer in tandem mass spectrometry. However, diagnostic product ions do not necessarily reflect quantitative isomeric ratios since fatty acid isomers have different ionization and fragmentation efficiencies. Here, we introduce a simple and rapid approach to predict the quantitative ratio of isomeric monounsaturated fatty acids. Specifically, empirically derived MS product ion patterns from fatty acid silver adducts are modeled using a stepwise linear model. This model is then applied to predict the proportion oleic and vaccenic acid in chemically complex samples at individual concentrations between 0.45 and 5.25 μM, with an average accuracy and precision below 2 and 5 mol %, respectively. We show that by simply including silver ions in the electrospray solvent, isomeric ratios are rapidly predicted in neat standards, rodent plasma, and tissue extract. Furthermore, we use the method to directly map isomeric ratios in tissue sections using nanospray desorption electrospray ionization MS imaging without any sample preparation or modification to the instrumental setup. Ultimately, this approach provides a simple and rapid solution to differentiate monounsaturated fatty acids using commonly available commercial mass spectrometers without any instrumental modifications.