Preliminary serum and fecal metabolomics study of spontaneously diabetic cynomolgus monkeys based on LC-MS/MS

J Med Primatol. 2022 Dec;51(6):355-366. doi: 10.1111/jmp.12610. Epub 2022 Aug 22.

Abstract

Background: Using untargeted metabolomics techniques, the goal of the study is to differentially screen serum and feces metabolite profiles of spontaneously diabetic and healthy cynomolgus monkeys, to explore potential serum and fecal biomarkers and analyze affected metabolic pathways.

Methods: We adopted the diagnostic criteria for T2DM recommended by ADA for humans: FSG ≥7.0 mmol/L (126 mg/dl) and HbA1c ≥ 6.5%. The serum and feces samples from three diagnosed spontaneously T2DM cynomolgus monkeys and 11 age-matched healthy controls were enrolled in the study. We employed LC-MS/MS-based untargeted metabolomic methods to reveal the differential metabolite profiles of serum and feces samples between the two groups and to analyze the affected metabolic pathways in MetaboAnalyst 5.0 based on KEGG library.

Results: Six and 44 differential metabolites were identified in serum and feces samples, respectively, and the corresponding affected commonly metabolic pathways involved several metabolic ways, such as arginine biosynthesis, pantothenate and CoA biosynthesis, alanine, aspartate and glutamate metabolism, valine, leucine and isoleucine biosynthesis, and histidine metabolism.

Conclusion: The differential potential serum and feces biomarkers obtained from the LC-MS/MS based untargeted metabolomic may help to explain the potential pathophysiological mechanisms of T2DM and offer pivotal information for the early diagnosis and treatment of DM.

Keywords: LC-MS/MS; T2DM; cynomolgus monkey; feces; metabolic pathway; serum; untargeted metabolomics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biomarkers
  • Chromatography, Liquid / methods
  • Diabetes Mellitus, Type 2*
  • Feces
  • Humans
  • Macaca fascicularis / metabolism
  • Metabolomics / methods
  • Tandem Mass Spectrometry*

Substances

  • Biomarkers