Identification of metabolites from 2D 1H-13C HSQC NMR using peak correlation plots

BMC Bioinformatics

Tommy Öman²  May-Britt Tessem¹  Tone F Bathen¹  Helena Bertilsson⁴  Anders Angelsen⁴  Mattias Hedenström²  Trygve Andreassen³ 

[1] St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway

[2] Department of Chemistry, Umeå University, Umeå, Sweden

[3] MR Core Facility, Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway

[4] Department of Cancer Research and Molecular Medicine, NTNU, Trondheim, Norway

关键词: Identification;    Biofluid;    Metabolite;    Correlation;    HSQC;   

Others  :  1084300
DOI  :  10.1186/s12859-014-0413-z

 received in 2014-04-11, accepted in 2014-12-08,  发布年份 2014

【 摘 要 】

Background

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 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).

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.

Conclusions

Correlation 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.

【 授权许可】

   
2014 Öman et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

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