Development and Validation of Methodologies for the Identification of Specialized Pro-Resolving Lipid Mediators and Classic Eicosanoids in Biological Matrices

Lipid mediators, which include specialized pro-resolving mediators and classic eicosanoids, are pivotal in both initiating and resolving inflammation. The regulation of these molecules determines whether inflammation resolves naturally or persists. However, our understanding of how these mediators are regulated over time in various inflammatory contexts is limited. This gap hinders our grasp of the mechanisms underlying the disease onset and progression. Due to their localized action and low endogenous levels in many tissues, developing robust and highly sensitive methodologies is imperative for assessing their endogenous regulation in diverse inflammatory settings. These methodologies will help us gain insight into their physiological roles. Here, we establish methodologies for extracting, identifying, and quantifying these mediators. Using our methods, we identified a total of 37 lipid mediators. Additionally, by employing a reverse-phase HPLC method, we successfully separated both double-bond and chiral isomers of select lipid mediators, including Lipoxin (LX) A₄, 15-epi-LXA₄, Protectin (PD) D1, PDX, and 17R-PD1. Validation of the method was performed in both solvent and surrogate matrix for linearity of the standard curves, lower limits of quantitation (LLOQ), accuracy, and precision. Results from these studies demonstrated that linearity was good with r² values > 0.98, and LLOQ for the mediators ranged from 0.01 to 0.9 pg in phase and from 0.1 to 8.5 pg in surrogate matrix. The relative standard deviation (RSD) for inter- and intraday precision in solvent ranged from 5% to 12% at low, intermediate, and high concentrations, whereas the RSD for the inter- and intraday variability in the accuracy ranged from 95% to 87% at low to high concentrations. The recovery in biological matrices (plasma and serum) for the internal standards used ranged from 60% to 118%. We observed a marked ion suppression for molecules evaluated in negative ionization mode, while there was an ion enhancement effect by the matrix for molecules evaluated in positive ionization mode. Comparison of the integration algorithms, namely, AutoPeak and MQ4, and approaches for calculating signal-to-noise ratios (i.e., US Pharmacopeia, relative noise, peak to peak, and standard deviation) demonstrated that different integration algorithms tested had little influence on signal-to-noise ratio calculations. In contrast, the method used to calculate the signal-to-noise ratio had a more significant effect on the results, with the relative noise approach proving to be the most robust. The methods described herein provide a platform to study the SPM and classic eicosanoids in biological tissues that will help further our understanding of disease mechanisms.