Development and validation of a modified QuEChERS protocol coupled to UHPLC-APCI-MS/MS for the simple and rapid quantification of 16 heterocyclic aromatic amines in cooked beef

International audienceHeterocyclic aromatic amines (HAAs) are neo-formed compounds generated during the cooking of meats and are known or suspected to be mutagenic and carcinogenic. In this study, a novel, simple, and fast methodology combining salting-out liquid-liquid microextraction, solid-phase extraction (SPE), and UHPLC-APCI-MS/MS was developed for the analysis of 16 HAAs. The QuEChERS extraction (quick, easy, cheap, efficient, rugged, and safe) was revisited and modified using mixed-mode SPE purification to adapt the method to the particular physicochemical properties of HAAs and the fatty nature of the beef matrix. The UHPLC-MS/MS analysis was performed on a C8 column in less than 4 min using positive APCI ionisation and an internal standard. The method was validated according to the European Medicines Agency and Eurachem guidelines and was successfully applied to beef samples of various cooking degrees, showing HAA levels similar to those shown by previous studies

Metabolism of versicolorin A, a genotoxic precursor of aflatoxin B1: Characterization of metabolites using in vitro production of standards

International audienceThe toxicity of mycotoxins containing bisfuranoid structures such as aflatoxin B1 (AFB1) depends largely on biotransformation processes. While the genotoxicity and mutagenicity of several bisfuranoid mycotoxins including AFB1 and sterigmatocystin have been linked to in vivo bioactivation of these molecules into reactive epoxide forms, the metabolites of genotoxic and mutagenic AFB1 precursor versicolorin A (VerA) have not yet been characterized. Because this molecule is not available commercially, our strategy was to produce a library of metabolites derived from the biotransformation of in-house purified VerA, following incubation with human liver S9 fractions, in presence of appropriate cofactors. The resulting chromatographic and mass-spectrometric data were used to identify VerA metabolites produced by intestinal cell lines as well as intestinal and liver tissues exposed ex vivo. In this way, we obtained a panel of metabolites suggesting the involvement of phase I (M + O) and phase II (glucuronide and sulfate metabolites) enzymes, the latter of which is implicated in the detoxification process. This first qualitative description of the metabolization products of VerA suggests bioactivation of the molecule into an epoxide form and provides qualitative analytic data to further conduct a precise metabolism study of VerA required for the risk assessment of this emerging mycotoxin

Preliminary results of the first NMR ring test inside MetaboHUB IA project on NMR acquisition and annotation of the NIST standard reference material of human plasma (SRM1950)

Preliminary results of the first NMR ring test inside MetaboHUB IA project on NMR acquisition and annotation of the NIST standard reference material of human plasma (SRM1950). 10. journées scientifiques du Réseau Francophone de Métabolomique et Fluxomique RFMF 201

Vers une annotation RMN 1D et 2D ciblée à partir de matrices de référence

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PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management

International audienceIntroduction Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories. Objectives To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management. Methods We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles. Results PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases. Conclusion PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest