OR 06 - Ion Identity Molecular Networking as a tool to characterize oxylipin structural diversity

Francesco Bartolinia, Sandra M. Camunas-Albercab, Hana Cermakovab, Ángel Sánchez-Illanac, David Perez-Guaitac, Pablo Cañadas-Miqueld, Alberto Gil-de-la-Fuenteb, Jean-Marie Galanoe, Thierry Durande, Ana Gradillasb, Coral Barbasb

aSapienza University of Rome, Department of Chemistry, 00185, Rome, RM, Italy,
bCentro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, 28660, Boadilla del Monte, Madrid, Spain,
cDepartment of Analytical Chemistry, University of Valencia, 46100 Burjassot, Valencia. Spain,
dDepartamento de Tecnologías de la Información, Escuela Politécnica Superior, Universidad San Pablo-CEU, CEU Universities, 28660, Boadilla del Monte, Madrid, Spain,
eInstitut des Biomolécules Max Mousseron (IBMM), UMR 5247, Pôle Chimie Balard Recherche, CNRS, Université de Montpellier, ENSCM, 34293, Montpellier, France

Oxylipins are bioactive lipid mediators derived from the oxidation of polyunsaturated fatty acids (PUFA). In vivo, oxylipins are involved in key processes such as the regulation of blood flow, cell signalling, and play a central role in the modulation of inflammation processes, among others. Their high chemical diversity makes their identification in untargeted LC-MS/MS analyses challenging. 

In this study, 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 multidimensional database with oxylipin names, retention times (RT), exact mass (m/z), and characterized adduct, cluster and in-source fragmentation profiles; together with an 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 and implementation of 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. 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. 

Keywords: Oxylipins; Redox Lipidomics; Ion Identity Molecular Networking (IIMN); Untargeted LC-MS/MS