Metabolomic studies of experimental diabetic urine samples by 1H NMR spectroscopy and LC/MS method

Metabolomic strategies based on nuclear magnetic resonance (NMR) and liquid chromatography coupled with mass spectrometry (LC/MS) have been developed to obtain metabolite profiles for urine samples excreted by male Goto–Kakizaki (G–K) and Wistar rats from 12–20 weeks of age. Multivariate statistical analysis was applied to the generated data sets. The efficiencies of two software packages for LC/MS data processing, MZmine and XCMS, were compared and gave similar results. The extracted data from both analytical methods were subjected to statistical analysis by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The performance of PLS-DA modeling was compared for both analytical methods and after different data normalization methods were used. The changes in metabolite profile included increased creatinine, glucose, and dimethylamine and decreased creatine, hippurate, formate, phenylalanine, allantoin, fumarate, citrate, acetate, amino acids, and some unidentified metabolites in the urine of G–K rats compared to Wistar rats. The obtained results gave evidence that 1H NMR procedures produce more information about the identity of metabolites. The multivariate analysis allowed the differentiation of the metabolic profiles related to animal age. In conclusion, the metabolomic studies of G–K rat urine samples provided further insights concerning experimental methodologies for data generation and processing, as well as possible markers for diabetes research.