Frontiers in Molecular Neuroscience (Sep 2022)

13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell

  • Birui Tian,
  • Meifeng Chen,
  • Lunxian Liu,
  • Bin Rui,
  • Zhouhui Deng,
  • Zhengdong Zhang,
  • Tie Shen,
  • Tie Shen

DOI
https://doi.org/10.3389/fnmol.2022.883466
Journal volume & issue
Vol. 15

Abstract

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13C metabolic flux analysis (13C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of 13C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of 13C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.

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