Abstract
BackgroundIdentification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies. NMR spectroscopy is an excellent technique for analysis of mixtures of organic compounds and gives a detailed chemical fingerprint of most individual components above the detection limit. For the identification of individual metabolites in metabolomics, correlation or covariance between peaks in 1H NMR spectra has previously been successfully employed. Similar correlation of 2D 1H-13C Heteronuclear Single Quantum Correlation spectra was recently applied to investigate the structure of heparine. In this paper, we demonstrate how a similar approach can be used to identify metabolites in human biofluids (post-prostatic palpation urine).ResultsFrom 50 1H-13C Heteronuclear Single Quantum Correlation spectra, 23 correlation plots resembling pure metabolites were constructed. The identities of these metabolites were confirmed by comparing the correlation plots with reported NMR data, mostly from the Human Metabolome Database.ConclusionsCorrelation plots prepared by statistically correlating 1H-13C Heteronuclear Single Quantum Correlation spectra from human biofluids provide unambiguous identification of metabolites. The correlation plots highlight cross-peaks belonging to each individual compound, not limited by long-range magnetization transfer as conventional NMR experiments.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-014-0413-z) contains supplementary material, which is available to authorized users.
Highlights
Identification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies
NMR spectroscopy is well suited for analysis of complex mixtures of organic compounds and has some distinct advantages compared to other analytical techniques such as GC-MS and LC-MS
The drawback of NMR spectroscopy is the inherent low sensitivity compared to MS-based methods, but it has become a cornerstone in metabolomic studies [1]
Summary
Identification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies. Results: From 50 1H-13C Heteronuclear Single Quantum Correlation spectra, 23 correlation plots resembling pure metabolites were constructed The identities of these metabolites were confirmed by comparing the correlation plots with reported NMR data, mostly from the Human Metabolome Database. Recent technical advances with higher magnetic fields and the introduction of cryogenic probes have drastically increased the sensitivity and thereby reduced experimental times for inverse detection experiments of other nuclei such as 13C and 31P. This allows analyses of large data sets of dilute samples, e.g. biofluids, within a reasonable timeframe
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