Metabolite analysis in the type 1 diabetic mouse model
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
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.
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.
참고문헌 (28)
- J. Rui, , Nat. Commun., 12, pp.5074~ (2021)
- L. Wigger, , Nat. Metab., 3, pp.1017~ (2021)
- L. Ikelle, , Adv. Exp. Med. Biol., 1185, pp.335~ (2019)
- N. C. Holoman, , J. Neurosci., 41, pp.3275~ (2021)
- J. H. Lee, , Int. J. Biol. Macromol., 187, pp.409~ (2021)
- J. Danielsson, , World J. Gastroenterol, 20, pp.11743~ (2014)
- J. Blahova, , Pharmaceuticals (Basel), 14, pp.806~ (2021)
- K. V. Gantenbein, , Nutrients, 13, pp.1951~ (2021)
- Y. Liu, , Am. J. Physiol. Heart Circ. Physiol., 320, pp.H549~ (2021)
- H. C. Park, , PLoS One, 14, pp.e0220506~ (2019)
- Ja-Shil Hyun, "1H NMR metabolomics study for diabetic neuropathy and diabetes", Journal of the Korean Magnetic Resonance Society, 22(4), pp.149~157 (2018), 한국자기공명학회[DOI]
- K. Sánchez-Alegría, , FASEB J., 35, pp.e21712~ (2021)
- X Pan, , Eur. J. Pharmacol., 893, pp.173816~ (2021)
- K. Abramov-Harpaz, , ACS Chem. Neurosci., 12, pp.3266~ (2021)
- Sung Jean Park, "Brain energy metabolism and multiple sclerosis: progress and prospects", Archives of Pharmacal Research, 43(10), pp.1017~1030 (2020), 대한약학회[DOI]
- C. A. Daykin, , Anal. Biochem., 304, pp.220~ (2002)
- A. Guleria, , Sci. Rep., 6, pp.35309~ (2016)
- M. Bylesjö, , J. Chemom., 20, pp.341~ (2006)
- A. Craig, , Anal. Chem., 78, pp.2262~ (2006)
- F. Dieterle, , Anal. Chem., 78, pp.4281~ (2006)
- J. Trygg, , J. Proteome Res., 6, pp.469~ (2007)
- S. Wiklund, , Anal. Chem., 80, pp.115~ (2008)
- F. Pesarin, "Multivariate permutation tests: with applications in biostatistics" (2001), Wiley Chichester
- B. Worley, , Analytical biochemistry, 433, pp.102~ (2013)
- J. D. Spurrier, , J. Nonparametric Stat., 15, pp.685~ (2003)
- 허수정, "Metabolic perturbation of an Hsp90 C-domain inhibitor in a lung cancer cell line, A549 studied by NMR-based chemometric analysis", Journal of the Korean Magnetic Resonance Society, 18(1), pp.10~14 (2014), 한국자기공명학회[DOI]
- M. S. Bjune, , Biochim. Biophys. Acta Mol. Cell. Biol. Lipids, 1866, pp.158887~ (2021)
- F. Zhang, , Ren. Fail., 43, pp.980~ (2021)