TY - JOUR
T1 - Can we trust untargeted metabolomics? Results of the metabo-ring initiative, a large-scale, multi-instrument inter-laboratory study
AU - Martin, Jean-Charles
AU - Maillot, Matthieu
AU - Mazerolles, Gérard
AU - Verdu, Alexandre
AU - Lyan, Bernard
AU - Migné, Carole
AU - Defoort, Catherine
AU - Canlet, Cecile
AU - Junot, Christophe
AU - Guillou, Claude
AU - Manach, Claudine
AU - Jabob, Daniel
AU - Bouveresse, Delphine Jouan-Rimbaud
AU - Paris, Estelle
AU - Pujos-Guillot, Estelle
AU - Jourdan, Fabien
AU - Giacomoni, Franck
AU - Courant, Frédérique
AU - Favé, Gaëlle
AU - Le Gall, Gwenaëlle
AU - Chassaigne, Hubert
AU - Tabet, Jean-Claude
AU - Martin, Jean-Francois
AU - Antignac, Jean-Philippe
AU - Shintu, Laetitia
AU - Defernez, Marianne
AU - Philo, Mark
AU - Alexandre-Gouaubau, Marie-Cécile
AU - Amiot-Carlin, Marie-Josephe
AU - Bossis, Mathilde
AU - Triba, Mohamed N.
AU - Stojilkovic, Natali
AU - Banzet, Nathalie
AU - Molinié, Roland
AU - Bott, Romain
AU - Goulitquer, Sophie
AU - Caldarelli, Stefano
AU - Rutledge, Douglas N.
PY - 2015/8
Y1 - 2015/8
N2 - The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different 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 in-house 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 supplemented or not with vitamin D. The spectral information from each instrument was assembled into separate statistical blocks. 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.
AB - The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different 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 in-house 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 supplemented or not with vitamin D. The spectral information from each instrument was assembled into separate statistical blocks. 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.
KW - Inter-laboratory
KW - Mass spectrometry
KW - Metabolic fingerprinting
KW - Nuclear magnetic resonance
KW - Untargeted metabolomics
UR - http://www.scopus.com/inward/record.url?scp=84931575490&partnerID=8YFLogxK
U2 - 10.1007/s11306-014-0740-0
DO - 10.1007/s11306-014-0740-0
M3 - Article
AN - SCOPUS:84931575490
SN - 1573-3882
VL - 11
SP - 807
EP - 821
JO - Metabolomics
JF - Metabolomics
IS - 4
ER -