Systemic and characteristic metabolites in the serum of streptozotocin-induced diabetic rats at different stages as revealed by a (1)H-NMR based metabonomic approach.

Diabetes mellitus is a typical heterogeneous metabolic disorder characterized by abnormal metabolism of carbohydrates, lipids, and proteins. Investigating the changes in metabolic pathways during the evolution of diabetes mellitus may contribute to the understanding of its metabolic features and pathogenesis. In this study, serum samples were collected from diabetic rats and age-matched controls at different time points: 1 and 9 weeks after streptozotocin (STZ) treatment. (1)H nuclear magnetic resonance ((1)H NMR)-based metabonomics with quantitative analysis was performed to study the metabolic changes. The serum samples were also subjected to clinical chemistry analysis to verify the metabolic changes observed by metabonomics. Partial least squares discriminant analysis (PLS-DA) demonstrated that the levels of serum metabolites in diabetic rats are different from those in control rats. These findings indicate that the metabolic characteristics of the two groups are markedly different at 1 and 9 weeks. Quantitative analysis showed that the levels of some metabolites, such as pyruvate, lactate, citrate, acetone, acetoacetate, acetate, glycerol, and valine, varied in a time-dependent manner in diabetic rats. These results suggest that serum metabolites related to glycolysis, the tricarboxylic acid cycle, gluconeogenesis, fatty acid ß-oxidation, branched-chain amino acid metabolism, and the tyrosine metabolic pathways are involved in the evolution of diabetes. The metabolic changes represent potential features and promote a better understanding of the mechanisms involved in the development of diabetes mellitus. This work further suggests that (1)H NMR metabonomics is a valuable approach for providing novel insights into the pathogenesis of diabetes mellitus and its complications.

Systemic perturbations of key metabolites in diabetic rats during the evolution of diabetes studied by urine metabonomics.

BACKGROUND: Elucidation of metabolic profiles during diabetes progression helps understand the pathogenesis of diabetes mellitus. In this study, urine metabonomics was used to identify time-related metabolic changes that occur during the development of diabetes mellitus and characterize the biochemical process of diabetes on a systemic, metabolic level. METHODOLOGY/PRINCIPAL FINDINGS: Urine samples were collected from diabetic rats and age-matched controls at different time points: 1, 5, 10, and 15 weeks after diabetes modeling. (1)H nuclear magnetic resonance ((1)H NMR) spectra of the urine samples were obtained and analyzed by multivariate data analysis and quantitative statistical analysis. The metabolic patterns of diabetic groups are separated from the controls at each time point, suggesting that the metabolic profiles of diabetic rats were markedly different from the controls. Moreover, the samples from the diabetic 1-wk group are closely associated, whereas those of the diabetic 15-wk group are scattered, suggesting that the presence of various of complications contributes significantly to the pathogenesis of diabetes. Quantitative analysis indicated that urinary metabolites related to energy metabolism, tricarboxylic acid (TCA) cycle, and methylamine metabolism are involved in the evolution of diabetes. CONCLUSIONS/SIGNIFICANCE: The results highlighted that the numbers of metabolic changes were related to diabetes progression, and the perturbed metabolites represent potential metabolic biomarkers and provide clues that can elucidate the mechanisms underlying the generation and development of diabetes as well as its complication.

Application of ex vivo (1)H NMR metabonomics to the characterization and possible detection of renal cell carcinoma metastases.

PURPOSE: Renal cell carcinoma (RCC) is the most prevalent malignancy of the kidney. Its survival rates are very low since most of patients develop metastases beyond the kidney at the time of diagnosis. Early detection is currently by far the most promising approach to reduce RCC mortality. Metabolic alterations have been suggested to have a crucial role in cancer development. Metabonomics can present a holistic picture of the metabolites alterations and provide biomarkers that could revolutionize disease characterization and detection. METHODS: Ex vivo (1)H NMR spectra of tumors and the paired adjacent tissues obtained from living patients with RCC were recorded and analyzed using multivariate statistical techniques combined with quantitative statistical analyses. RESULTS: In the present study, we showed that the metabonomes of RCC, either with or without metastases, differ markedly from those of their adjacent tissues. Besides, the RCC patients with metastases can be distinctly differentiated from those without metastases. Metabolic perturbations arising from malignant transformations were also systematically characterized. Compared to the adjacent tissues, RCC tumors had elevated levels of lactate, glutamate, pyruvate, glutamine, and creatine, but decreased levels of acetate, malate, and amino acids including valine, alanine, and aspartate. CONCLUSIONS: Systemic changes in metabolite concentrations are most likely the result of cells switching to glycolysis to maintain energy homeostasis. The results suggest that metabonomics may also facilitate the discovery of novel cancer biomarkers and allows the stratification of tumors under different pathophysiological conditions, which might be a valuable future tool for RCC detection and possibly other cancers.