Can we Trust Untargeted Metabolomics: Results of the Metabo-ring Initiative, a Large-scale Multi-instruments Inter-laboratoire Study

Archive ouverte : Article de revue

Martin, Jean-Charles | Maillot, Mathieu | Mazerolles, Gerard | Verdu, Alexandre | Lyan, Bernard | Migné, Carole | Defoort, Catherine | Canlet, Cécile | Junot, Christophe | Guillou, Claude | Manach, Claudine | Jacob, Daniel | Jouan-Rimbaud Bouveresse, Delphine | Paris, Estelle | Pujos-Guillot, Estelle | Jourdan, Fabien | Giacomoni, Franck | Courant, Frédérique | Fave, Gaelle | Le Gall, Gwenaëlle | Chassaigne, Hubert | Tabet, Jean-Claude | Martin, Jean-Francois | Antignac, Jean-Philippe | Shintu, Laetitia | Defernez, Marianne | Philo, Mark | Alexandre Gouaubau, Marie-Cécile | Amiot-Carlin, Marie Josephe | Bossis, Mathilde | Triba, Mohamed | Stojilkovic, Nathali | Banzet, Nathalie | Molinié, Roland | Bott, Romain | Goulitquer, Sophie | Caldarelli, Stefano | Rutledge, Douglas

Edité par HAL CCSD ; Springer Verlag

This article is published with open access at Springerlink.com. International audience. The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11different mass spectrometers with the objective of assessing the reliability of untargeted metabolomics approaches in obtaining comparable metabolomics profiles. This was estimated by measuring the proportion of common spectral information extracted from the different LCMS and NMR platforms. Biological samples obtained from 2 different conditions were analysed by the partners using their own inhouse protocols. Test #1 examined urine samples from adult volunteers either spiked or not spiked with 32 metabolite standards. Test #2 involved a low biological contrast situation comparing the plasma of rats fed a diet either supplementedor not with vitamin D. The spectral information from each instrument was assembled into separate statisticalblocks. Correlations between blocks (e.g., instruments) were examined (RV coefficients) along with the structure of the common spectral information (common components and specific weights analysis). In addition, in Test #1, an outlier individual was blindly introduced, and its identification by the various platforms was evaluated. Despite large differences in the number of spectral features produced after post-processing and the heterogeneity of the analytical conditions and the data treatment, the spectral information both within (NMR and LCMS) and across methods (NMR vs. LCMS) was highly convergent (from 64 to 91 % on average). No effect of the LCMS instrumentation (TOF, QTOF, LTQ-Orbitrap) was noted. The outlier individual was best detected and characterised by LCMS instruments. In conclusion, untargeted metabolomics analyses report consistent information within and across instruments of various technologies, even without prior standardisation.

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