Systematic assessment of streptozotocin-induced diabetic metabolic alterations in rats using metabolomics

Abstract

Purpose: Type 1 diabetes is characterized by elevated blood glucose levels, which negatively impacts multiple organs and tissues throughout the body, and its prevalence is on the rise. Prior reports primarily investigated the serum and urine specimen from diabetic patients. However, only a few studies examined the overall metabolic profile of diabetic animals or patients. The current systemic investigation will benefit the knowledge of STZ-based type 1 diabetes pathogenesis.

Methods: Male SD rats were arbitrarily separated into control and streptozotocin (STZ)-treated diabetic rats (n = 7). The experimental rats received 50mg/kg STZ intraperitoneal injection daily for 2 consecutive days. Following 6 weeks, metabolites were assessed via gas chromatography-mass spectrometry (GC-MS), and multivariate analysis was employed to screen for differentially expressed (DE) metabolites between the induced diabetic and normal rats.

Results: We identified 18, 30, 6, 24, 34, 27, 27 and 12 DE metabolites in the serum, heart, liver, kidney, cortex, renal lipid, hippocampus, and brown fat tissues of STZ-treated diabetic rats, compared to control rats. Based on our analysis, the largest differences were observed in the amino acids (AAs), B-group vitamin, and purine profiles. Using the metabolic pathway analysis, we screened 13 metabolic pathways related to the STZ-exposed diabetes pathogenesis. These pathways were primarily AA metabolism, followed by organic acids, sugars, and lipid metabolism.

Conclusion: Based on our GC-MS analysis, we identified potential metabolic alterations within the STZ-exposed diabetic rats, which may aid in the understanding of diabetes pathogenesis.

Keywords: diabetes; gas chromatography mass spectrometry (GC-MS); metabolites; metabolomics; streptozotocin (STZ).

Figure 1

Typical gas chromatography–mass spectrometry (GC–MS) total ion chromatograms (TIC) of the quality control (QC) from serum (A), heart (B), liver (C), kidney (D), cortex (E), renal lipid (F), hippocampus (G), and brown fat (H).

Figure 2

Orthogonal projections to the latent structural (OPLS) scores and 200 permutation tests for the OPLS-discriminant analysis (OPLS-DA) models: serum (A), heart (B), liver (C), kidney (D), cortex (E), renal lipid (F), hippocampus (G), and brown fat (H).

Figure 3

significance (red, elevated; blue, diminished). Rows denote samples, columns denote metabolites.The heatmap of differentially regulated metabolites from the serum (A), heart (B), liver (C), kidney (D), cortex (E), renal lipid (F), hippocampus (G), and brown fat (H) of STZ and control rats. The color of each section signifies its alteration.

Figure 4

 A network analysis summary, as evidenced by MetaboAnalyst 5.0. Serum (A), Heart (B), kidney (C), cortex (D), renal lipid (E), hippocampus (F), and brown fat (G). Metabolisms or biosynthesis of (a) Phenylalanine, tyrosine, and tryptophan, (b) Phenylalanine, (c) Glycine, serine, and threonine, (d) Glyoxylate and dicarboxylate, (e) Glutathione (f) Nicotinate and nicotinamide, (g) Glycerolipid, (h) Pentose phosphate, (i) Alanine, aspartate, and glutamate, (j) D-Glutamine and D-glutamate, (k) Arginine, (l) Arginine and proline, (m) Butanoate.

Figure 5

 A flow chart of the metabolites and their associated networks in the target tissues of STZ-treated diabetic rats versus controls. Red arrows: phenylalanine, tyrosine and tryptophan biosynthesis; light blue arrows: pentose phosphate pathway; yellow arrows: glycine,serine, and threonine metabolism; green arrows: glyoxylate and dicarboxylate metabolism; blue arrows: alanine, aspartate, and glutamate metabolism; pink arrows: glutathione metabolism; purple arrows: D-glutamine and D-glutamate metabolism; orange arrows: glycerolipid metabolism; brown arrows: arginine and proline metabolism.