TY - JOUR
T1 - Structure elucidation of unknown metabolites in metabolomics by combined NMR and MS/MS prediction
AU - Boiteau, Rene M.
AU - Hoyt, David W.
AU - Nicora, Carrie D.
AU - Kinmonth-Schultz, Hannah A.
AU - Ward, Joy K.
AU - Bingol, Kerem
N1 - Publisher Copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2018/3
Y1 - 2018/3
N2 - We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.
AB - We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.
KW - Arabidopsis thaliana metabolome
KW - Chemical shift prediction
KW - Hybrid MS/NMR method
KW - In silico fragmentation
KW - Metabolite identification
KW - Metabolomics
UR - http://www.scopus.com/inward/record.url?scp=85041028005&partnerID=8YFLogxK
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U2 - 10.3390/metabo8010008
DO - 10.3390/metabo8010008
M3 - Article
AN - SCOPUS:85041028005
SN - 2218-1989
VL - 8
JO - Metabolites
JF - Metabolites
IS - 1
M1 - 8
ER -