Abstract
BackgroundOne-dimensional (1D) 1H nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomic studies involving biofluids and tissue extracts. There are several software packages that support compound identification and quantification via 1D 1H NMR by spectral fitting techniques. Because 1D 1H NMR spectra are characterized by extensive peak overlap or spectral congestion, two-dimensional (2D) NMR, with its increased spectral resolution, could potentially improve and even automate compound identification or quantification. However, the lack of dedicated software for this purpose significantly restricts the application of 2D NMR methods to most metabolomic studies.ResultsWe describe a standalone graphics software tool, called MetaboMiner, which can be used to automatically or semi-automatically identify metabolites in complex biofluids from 2D NMR spectra. MetaboMiner is able to handle both 1H-1H total correlation spectroscopy (TOCSY) and 1H-13C heteronuclear single quantum correlation (HSQC) data. It identifies compounds by comparing 2D spectral patterns in the NMR spectrum of the biofluid mixture with specially constructed libraries containing reference spectra of ~500 pure compounds. Tests using a variety of synthetic and real spectra of compound mixtures showed that MetaboMiner is able to identify >80% of detectable metabolites from good quality NMR spectra.ConclusionMetaboMiner is a freely available, easy-to-use, NMR-based metabolomics tool that facilitates automatic peak processing, rapid compound identification, and facile spectrum annotation from either 2D TOCSY or HSQC spectra. Using comprehensive reference libraries coupled with robust algorithms for peak matching and compound identification, the program greatly simplifies the process of metabolite identification in complex 2D NMR spectra.
Highlights
One-dimensional (1D) 1H nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomic studies involving biofluids and tissue extracts
Since the presence of these biofluid-specific metabolites was determined by a variety of technologies not limited to NMR, we further investigated the appearance of these metabolites in a large number of 1D 1H spectra collected from cerebrospinal fluid (CSF), plasma and urine
The utility of different NMR data types were investigated for our approach of compound identification
Summary
One-dimensional (1D) 1H nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomic studies involving biofluids and tissue extracts. Metabolomics only became possible as a result of recent technology breakthroughs in small molecule separation, identification and quantification. While other techniques may be more sensitive or less expensive, NMR has emerged as an ideal platform for studying metabolites in biofluids. It is a rapid, highly precise, non-destructive, and quantitative technique that allows one to compare, identify and quantify a wide range of compounds without the need for prior compound separation or derivatization [3,4,5,6]. A key disadvantage of NMR is that it is a relatively insensitive technique, with a lower limit of detection of 1~5 μM and a requirement of relatively large sample sizes (~500 μL)
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