Literature DB >> 28994599

Metabolomics and Lipidomics Study of Mouse Models of Type 1 Diabetes Highlights Divergent Metabolism in Purine and Tryptophan Metabolism Prior to Disease Onset.

Steven A Murfitt1, Paola Zaccone2, Xinzhu Wang1, Animesh Acharjee3, Yvonne Sawyer2, Albert Koulman3, Lee D Roberts3, Anne Cooke2, Julian Leether Griffin1,3.   

Abstract

With the increase in incidence of type 1 diabetes (T1DM), there is an urgent need to understand the early molecular and metabolic alterations that accompany the autoimmune disease. This is not least because in murine models early intervention can prevent the development of disease. We have applied a liquid chromatography (LC-) and gas chromatography (GC-) mass spectrometry (MS) metabolomics and lipidomics analysis of blood plasma and pancreas tissue to follow the progression of disease in three models related to autoimmune diabetes: the nonobese diabetic (NOD) mouse, susceptible to the development of autoimmune diabetes, and the NOD-E (transgenic NOD mice that express the I-E heterodimer of the major histocompatibility complex II) and NOD-severe combined immunodeficiency (SCID) mouse strains, two models protected from the development of diabetes. All three analyses highlighted the metabolic differences between the NOD-SCID mouse and the other two strains, regardless of diabetic status indicating that NOD-SCID mice are poor controls for metabolic changes in NOD mice. By comparing NOD and NOD-E mice, we show the development of T1DM in NOD mice is associated with changes in lipid, purine, and tryptophan metabolism, including an increase in kynurenic acid and a decrease in lysophospholipids, metabolites previously associated with inflammation.

Entities:  

Keywords:  NOD-severe combined immunodeficiency (SCID) mouse; kynurenic acid; mass spectrometry; nonobese diabetic (NOD) mouse; xanthinine

Mesh:

Substances:

Year:  2018        PMID: 28994599     DOI: 10.1021/acs.jproteome.7b00489

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  8 in total

Review 1.  A Contemporary Insight of Metabolomics Approach for Type 1 Diabetes: Potential for Novel Diagnostic Targets.

Authors:  Jiatong Chai; Zeyu Sun; Jiancheng Xu
Journal:  Diabetes Metab Syndr Obes       Date:  2022-05-25       Impact factor: 3.249

2.  NMR-based metabolomics characterizes metabolic changes in different brain regions of streptozotocin-induced diabetic mice with cognitive decline.

Authors:  Tingting Zhang; Hong Zheng; Kai Fan; Nengzhi Xia; Jiance Li; Changwei Yang; Hongchang Gao; Yunjun Yang
Journal:  Metab Brain Dis       Date:  2020-07-08       Impact factor: 3.584

Review 3.  Obesity and Cancer: Existing and New Hypotheses for a Causal Connection.

Authors:  Trevor W Stone; Megan McPherson; L Gail Darlington
Journal:  EBioMedicine       Date:  2018-02-27       Impact factor: 8.143

Review 4.  Functional Lipids in Autoimmune Inflammatory Diseases.

Authors:  Michele Dei Cas; Gabriella Roda; Feng Li; Francesco Secundo
Journal:  Int J Mol Sci       Date:  2020-04-27       Impact factor: 5.923

5.  Short Term Intrarectal Administration of Sodium Propionate Induces Antidepressant-Like Effects in Rats Exposed to Chronic Unpredictable Mild Stress.

Authors:  Jianguo Li; Luwen Hou; Cui Wang; Xueyang Jia; Xuemei Qin; Changxin Wu
Journal:  Front Psychiatry       Date:  2018-09-27       Impact factor: 4.157

6.  Feasibility of Localized Metabolomics in the Study of Pancreatic Islets and Diabetes.

Authors:  Oscar Alcazar; Luis F Hernandez; Ashley Tschiggfrie; Michael J Muehlbauer; James R Bain; Peter Buchwald; Midhat H Abdulreda
Journal:  Metabolites       Date:  2019-09-29

7.  Fenofibrate increases very-long-chain sphingolipids and improves blood glucose homeostasis in NOD mice.

Authors:  Laurits J Holm; Martin Haupt-Jorgensen; Jano D Giacobini; Jane P Hasselby; Mesut Bilgin; Karsten Buschard
Journal:  Diabetologia       Date:  2019-08-13       Impact factor: 10.122

8.  Evaluation of the antitumor effects of PP242 in a colon cancer xenograft mouse model using comprehensive metabolomics and lipidomics.

Authors:  Md Mamunur Rashid; Hyunbeom Lee; Byung Hwa Jung
Journal:  Sci Rep       Date:  2020-10-16       Impact factor: 4.379

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.