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.

Authors

Institutions

Publication Details

Journal
Metabolomics
Published
2026-08-26
DOI
https://doi.org/10.1007/s11306-026-02481-x
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Vinicius Verri Hernandes, Dr Monika Ehling-Schulz, Benedikt Warth, Ellen L. Zechner et al.
Metabolomics
Metabolomics and Mass Spectrometry Studies
article

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

Vinicius Verri Hernandes, Dr Monika Ehling-Schulz, Benedikt Warth, Ellen L. Zechner, Emily P. Balskus, Hannes Mikula, Philipp Fruhmann, Miguel A. Aguilar Ramos, Rolf Breinbauer
article en

Abstract

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.

MetabolomicsVol. 22(5)
University of Vienna (AT), Statistics Austria (AT), Harvard University (US), TU Wien (AT), University of Veterinary Medicine Vienna (AT), Graz University of Technology (AT), BioTechMed-Graz (AT)
Universität Wien, Bundesministerium für Bildung, Wissenschaft und Forschung
Openalex Percentile: Top 17%
Metabolomics and Mass Spectrometry Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.