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Decoding the Oxylipin Chemical Space Using Ion Identity Molecular Networking.

Sandra M Camunas-Alberca¹, Francesco Bartolini², Hana Cermakova¹

¹Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Madrid 28660, Spain.

Analytical Chemistry

|April 17, 2026

Summary

This summary is machine-generated.

This study introduces Ion Identity Molecular Networking (IIMN) to map oxylipin chemical space, improving identification of these bioactive lipid mediators in complex biological samples. The developed workflow enhances oxylipin characterization and discovery, creating a valuable resource for redox lipidomics research.

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Area of Science:

Lipidomics
Bioactive Lipid Mediators
Mass Spectrometry

Background:

Oxylipins are crucial bioactive lipid mediators involved in various biological and pathological processes.
The chemical diversity of oxylipins presents significant challenges for identification using untargeted LC-MS/MS analyses.
Current methods for comprehensive oxylipin characterization are limited.

Purpose of the Study:

To implement and evaluate the Ion Identity Molecular Networking (IIMN) strategy for mapping the chemical space of oxylipins.
To systematically assess factors affecting accurate annotation of MS/MS datasets for oxylipins.
To develop a robust bioinformatic tool for decoding oxylipin diversity and discovering novel mediators.

Main Methods:

Implementation of a fully local IIMN analysis strategy using mzmine software.
Creation of a high-quality MS/MS spectral library from 67 oxylipin standards.
Integration of ion species characterization into IIMN and application of a modified cosine algorithm.
Analysis of mouse spleen extracts using IIMN with combined spectral libraries.

Main Results:

The IIMN strategy effectively mapped the oxylipin chemical space, reducing network complexity by integrating ion species characterization.
The modified cosine algorithm successfully separated oxylipin forms and clustered structurally related compounds.
Application to biological samples facilitated oxylipin organization into molecular families, aiding structural characterization and novel species discovery.
A publicly available reference spectral library was generated.

Conclusions:

Ion Identity Molecular Networking (IIMN) is established as a robust bioinformatic tool for oxylipin analysis.
The developed workflow significantly improves the interpretability and understanding of oxylipin MS/MS data.
This approach provides a successful strategy for characterizing oxylipins and discovering novel mediators in biological matrices, advancing redox lipidomics research.