Journal of the Korean Magnetic Resonance Society (한국자기공명학회논문지)

Korean Magnetic Resonance Society (한국자기공명학회)
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Metabolite analysis in the type 1 diabetic mouse model

  • Park, Sung Jean (College of Pharmacy and Gachon Institute of Pharmaceutical Sciences, Gachon University)
  • Received : 2021.09.02
  • Accepted : 2021.09.14
  • Published : 2021.09.20
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Abstract

Type 1 diabetes mellitus (T1DM) is caused by insufficient production of insulin, which is involved in carbohydrate metabolism. Type 2 diabetes mellitus (T2DM) has insulin resistance in which cells do not respond adequately to insulin. The purpose of this study was to estimate the characteristics of type 1 diabetes using streptozotocin-treated mice (STZ-mouse). The sera samples were collected from the models of hyperglycemic mouse and healthy mouse. Based on the pair-wise comparison, five metabolites were found to be noticeable: glucose, malonic acid, 3-hyroxybutyrate, methanol, and tryptophan. It was very natural glucose was upregulated in STZ-mouse. 3-hyroxybutyrate was also increased in the model. However, malonic acid, tryptophan, and methanol was downregulated in STZ-mouse. Several metabolites acetoacetate, acetone, alanine, arginine, asparagine, histidine, lysine, malate, methionine, ornithine, proline, propylene glycol, threonine, tyrosine, and urea tended to be varied in STZ-mouse while the statistical significance was not stratified for the variation. The multivariate model of PCA clearly showed the group separation between healthy control and STZ-mouse. The most significant metabolites that contributed the group separation included glucose, citrate, ascorbate, and lactate. Lactate did not show the statistical significance of change in t-test while it tends to down-regulated both in DNP and Diabetes.

Keywords

Acknowledgement

This work was supported by the Gachon University research fund of 2019 (GCU-2019-0707). This research was also supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (2018R1D1A1B07050426).

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