Résumé
Oxylipins are bioactive lipid mediators that play key roles in biological and pathological processes. Their remarkable chemical diversity makes their identification by untargeted LC-MS/MS analyses challenging. To date, effective solutions for their comprehensive characterization remain unavailable. Here, we present the first implementation of the recently refined Ion Identity Molecular Networking (IIMN) strategy to map the chemical space of oxylipins, together with a systematic evaluation of factors that hinder accurate annotation in MS/MS datasets. Building on recent mzmine software developments, we implemented a fully local strategy to perform the IIMN analysis without requiring web platforms or external tools. We established a high-quality MS/MS spectral library from 67 commercially available oxylipin standards using LC-MS data obtained in data-dependent acquisition mode. Integrating the detailed characterization of ion species generated during electrospray ionization into IIMN reduced network complexity. Across configurations, the modified cosine algorithm proved most effective for separating full-length from cyclized forms and for clustering oxylipins through structurally coherent relationships. Application of the IIMN workflow to mouse spleen extracts, in combination with our in-house and publicly available experimental MS/MS libraries, enabled the organization of oxylipins into molecular families, facilitating their structural characterization and the discovery of novel species. Although manual curation remained necessary for certain coeluting isomers and ambiguous fragments, the IIMN-based approach significantly improved network interpretability and understanding. Overall, this study establishes IIMN as a robust bioinformatic tool for decoding oxylipin diversity and provides a successful strategy for mapping their chemical space, characterizing them within samples, and discovering novel mediators in biological matrices. The new combined reference spectral library has been made publicly available and will serve as a valuable resource for future redox lipidomics research.