Signal pattern plot: a simple tool for time-dependent metabolomics studies by 1H NMR spectroscopy
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We show an alternative way to visualize time course NMR data without the application of multivariate data analysis, based on the temporal change of the metabolome of hazelnuts after mold infestation. Fresh hazelnuts were inoculated with eight different natural mold species and the growth was studied over a period of 14 days. The data were plotted in a color-coded scheme showing metabolic changes as a function of chemical shift, which we named signal pattern plot. This plot graphically displays alteration (trend) of a respected signal over time and allows visual interpretation in a simple manner. Changes are compared with a reference sample stored under identical conditions as the infected nuts. The plot allows, at a glance, the recognition of individual landmarks specific to a sample group as well as common features of the spectra. Each sample reveals an individual signal pattern. The plot facilitates the recognition of signals that belong to biological relevant metabolites. Betaine and five signals were identified that specifically changed upon mold infestation.
KeywordsMetabolomics Chemometrics 1H NMR spectroscopy Time course data
The authors thank Vera Priegnitz and Claudia Wontorra for their support in sample measurement.
This study was performed within the project “Food Profiling – Development of analytical tools for the authentication of food”. This project (Support Code 2816500914) is supported by means of the Federal Ministry of Food and Agriculture (BMEL) by a decision of the German Bundestag (parliament). Project support is provided by the Federal Institute for Agriculture and Food (BLE) within the scope of the program for promoting innovation.
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Conflict of interest
The authors declare that they have no conflict of interest.
- 3.Solanky KS, Bailey NJC, Beckwith-Hall BM, Davis A, Bingham S, Holmes E, et al. Application of biofluid 1H nuclear magnetic resonance-based metabonomic techniques for the analysis of the biochemical effects of dietary isoflavones on human plasma profile. Anal Biochem. 2003;323:197–204.CrossRefGoogle Scholar
- 18.Chen T, Cao Y, Zhang Y, Liu J, Bao Y, Wang C, et al. Random forest in clinical metabolomics for phenotypic discrimination and biomarker selection. Evid Based Complement Alternat Med. 2013;2013:298183.Google Scholar