Decoding the Oxylipin Chemical Space using Ion Identity Molecular Networking

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 characterization remain unavailable. Here we present the first implementation of the recently refined Ion Identity Molecular Networking (IIMN) methodology to map the chemical space of oxylipins, together with a systematic evaluation of factors that hinder accurate annotation in MS/MS datasets. Our approach leverages recent enhancements to the mzmine software, offering an alternative GNPS-independent method of connecting oxylipins in molecular networks. 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. Detailed characterization of ion species generated during electrospray ionization 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. Although manual curation remained necessary for certain co-eluting 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 and characterizing these 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.