Background
Eicosanoids are vital lipid mediators involved in inflammation but are highly volatile
and prone to evaporation during sample preparation steps such as solid-phase
extraction (SPE). Their volatility, driven by low molecular weight, reactive functional
groups, and vacuum-induced evaporation, compromises their accurate quantification
in LC-MS analysis. To address this, ethylene glycol was evaluated as a vacuum
additive to stabilize eicosanoids during evaporation, aiming to enhance recovery and
reliability in LC-MS workflows.
Methodology
Solid-phase extraction (SPE) was employed to isolate and concentrate eicosanoids
from plasma samples. Six experimental conditions (Exp A–F) were tested to examine
the effects of mixing, sonication, pH adjustments, and ethylene glycol addition on
eicosanoid stability. These included controls with no additives or stabilization steps
(Exp A–C) and conditions incorporating ethylene glycol as a vacuum additive (Exp D
and Exp F) or pH adjustment (Exp E and Exp F). This systematic design allowed the
evaluation of ethylene glycol’s effectiveness in reducing volatilization and improving
stability during drying steps.
Results
Log-transformed LC-MS peak areas across the experimental conditions demonstrated
that Experiment D (with ethylene glycol) consistently produced the highest and most
stable peak areas for all tested eicosanoids, including 16-HETE, 5(6)-EET, and 17-
HDHA. Control experiments (Exp A and Exp B) exhibited significantly lower and more
variable peak areas, indicating substantial analyte loss during sample preparation. The
superior stabilization achieved with ethylene glycol underscores its efficacy in
preventing eicosanoid volatilization, offering a simple and effective solution to enhance
their quantification in LC-MS analysis.
Conclusion
Ethylene glycol proves to be a promising vacuum additive, effectively preventing lipid
mediator evaporation and ensuring reproducibility and accuracy in biomarker
quantification. This approach significantly improves the robustness and reliability of
LC-MS workflows for studying eicosanoids and oxidative stress biomarkers, with
critical implications for clinical applications.