期刊
ANALYTICAL CHEMISTRY
卷 79, 期 24, 页码 9385-9390出版社
AMER CHEMICAL SOC
DOI: 10.1021/ac071583z
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资金
- NCRR NIH HHS [P41 RR02301, P41 RR002301, P41 RR002301-15] Funding Source: Medline
- NHGRI NIH HHS [1T32HG002760, T32 HG002760, T32 HG002760-05] Funding Source: Medline
- NIDDK NIH HHS [R21 DK070297-01, R21 DK070297] Funding Source: Medline
- NIGMS NIH HHS [P41 GM066326, P41 GM066326-05, P41 GM GM66326] Funding Source: Medline
One-dimensional (1D) H-1 nuclear magnetic resonance (NMR) spectroscopy is used extensively for high-throughput analysis of metabolities in biological fluids and tissue extracts. Typically, such spectra are treated as multivariate statistical objects rather than as collections of quantifiable metabolites. We report here a two-dimensional (2D) H-1- C-13 NMR strategy (fast metabolite quantification, FMQ, by NMR) for identifying and quantifying the similar to 40 most abundant metabolites in biological samples. To validate this technique, we prepared mixtures of synthetic compounds and extracts from Arabidopsis thaliana, Saccharomyces cerevisiae, and Medicago sativa. We show that accurate (technical error 2.7%) molar concentrations can be determined in 12 min using our quantitative 2D H-1-C-13 NMR strategy. In contrast, traditional 1D H-1 NMR analysis resulted in 16.2% technical error under nearly ideal conditions. We propose FMQ by NMR as a practical alternative to 1D H-1 NMR for metabolomics studies in which 50-mg (extract dry weight) samples can be obtained.
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