- Hasenour CM, Wall ML, Ridley DE, Hughey CC, James FD, Wasserman DH, Young JD. Mass spectrometry-based microassay of (2)H and (13)C plasma glucose labeling to quantify liver metabolic fluxes in vivo. American journal of physiology. Endocrinology and metabolism. 2015 Jul 15;309(2). E191-203. PMID: 25991647 [PubMed]. PMCID: PMC4504936.
Mouse models designed to examine hepatic metabolism are critical to diabetes and obesity research. Thus, a microscale method to quantitatively assess hepatic glucose and intermediary metabolism in conscious, unrestrained mice was developed. [(13)C3]propionate, [(2)H2]water, and [6,6-(2)H2]glucose isotopes were delivered intravenously in short- (9 h) and long-term-fasted (19 h) C57BL/6J mice. GC-MS and mass isotopomer distribution (MID) analysis were performed on three 40-μl arterial plasma glucose samples obtained during the euglycemic isotopic steady state. Model-based regression of hepatic glucose and citric acid cycle (CAC)-related fluxes was performed using a comprehensive isotopomer model to track carbon and hydrogen atom transitions through the network and thereby simulate the MIDs of measured fragment ions. Glucose-6-phosphate production from glycogen diminished, and endogenous glucose production was exclusively gluconeogenic with prolonged fasting. Gluconeogenic flux from phosphoenolpyruvate (PEP) remained stable, whereas that from glycerol modestly increased from short- to long-term fasting. CAC flux [i.e., citrate synthase (VCS)] was reduced with long-term fasting. Interestingly, anaplerosis and cataplerosis increased with fast duration; accordingly, pyruvate carboxylation and the conversion of oxaloacetate to PEP were severalfold higher than VCS in long-term fasted mice. This method utilizes state-of-the-art in vivo methodology and comprehensive isotopomer modeling to quantify hepatic glucose and intermediary fluxes during physiological stress in mice. The small plasma requirements permit serial sampling without stress and the affirmation of steady-state glucose kinetics. Furthermore, the approach can accommodate a broad range of modeling assumptions, isotope tracers, and measurement inputs without the need to introduce ad hoc mathematical approximations.