ExpoLib: a framework for an MS/MS exposome library of anthropogenic and natural toxicants and their biotransformation products

Introduction: Despite technological advancements over the last three decades in small-molecule omics, compound annotation remains a major bottleneck in untargeted metabolomics and non-targeted environmental analysis. This is especially true for exposomics applications, which remain significantly affected by the limited chemical space coverage. Objectives: This work aims at describing the development of an MS/MS spectral library containing > 170 relevant xenobiotics from different classes of food, environmental, and microbial toxicants. Methods: LC–MS/MS data was acquired using collision-induced dissociation in data dependent acquisition mode under 13 different single collision energies with four additional collision energy spread experiments. A diverse set of compounds including natural toxins produced by bacteria, fungi (mycotoxins), and plants (phytotoxins), as well as anthropogenic chemicals such as bisphenols, phthalates, PFAS chemicals, drugs, consumer care products ingredients, and pesticides, and additional toxicologically relevant chemical classes were screened. Metabolic products for which commercially available reference standards and/or MS/MS spectra are not available in any public or commercial database have been included (e.g. colibactin-DNA-adduct, cereulide, deoxynivalenol-3-glucuronide). Library generation was performed in mzmine. Results: Open-format data based on representative spectra are provided.This new resource, available at https://zenodo.org/records/20715576, is aimed at providing a ready-to-use tool for the annotation of key exogenous compounds which are frequently overlooked in clinical metabolomics but may exert potent biological effects. A detailed discussion from a user perspective is provided regarding the library generation workflow in mzmine, aiming at facilitating the work of fellow researchers in the creation of their own in-house libraries. Conclusion: We intend to provide the metabolomics community with better tools for exposomics research and to reduce perceived barriers in developing specialized MS/MS libraries for widening chemical space coverage and increasing quality and confidence.