Abstract
Diabetes results in hyperglycaemia, due to decreased/absent insulin production or decreased insulin sensitivity. The lack of cellular glucose absorption induces compensatory mechanisms involving carbohydrate and nitrogen metabolism and oxidative stress mechanisms. Metabolomics can provide comprehensive characterisation of molecular pathways and may contribute to understanding me tabolic changes in diabetes. The present study aims to combine experimental design optimisation with multivariate statistical analysis to validate a liver metabolite extraction protocol for the assessment of biomarkers of streptozotocin (STZ)-induced diabetes. Metabolic profiles of livers from STZ-induced diabetic rats and controls (n=8) were investigated with gas chromatography mass spectrometry (GC-MS). The data was further analysed by Principal Component Analysis to compare the metabolite profiles of diabetic and control rats. The analysis revealed an average of 143 ± 12.5 metabolites from the analysed livers. Of these 78 metabolites were positively identified. The two groups showed significant differences in metabolite profiles, including carbohydrates, amino acids, and organic acids. We have identified several relevant metabolites significantly altered in STZ-induced diabetes. These represent metabolites from key metabolic pathways, including gluconeogenesis and the tricarboxylic acid cycle. Metabolites that display significant and specific up or down regulation correspond well to existing data on diabetic metabolism. We have shown that GC-MS is a useful tool for characterising metabolic changes in diabetes. Understanding the biochemical changes occurring in diabetes will aid in the discovery and evaluation of possible treatments and provide a mechanism for further study of the disease itself.