| dc.description.abstract | Biochemical methods to quantify gene transcript, enzyme, and metabolite levels are widely used to assess metabolic pathway regulation. Though informative and even vital in some contexts, static measurements of biomolecule abundance may not be reliable indicators of the movement of substrates through a metabolic pathway (i.e., metabolic flux). A combination of advances in mass spectroscopy (MS) and nuclear magnetic resonance (NMR) coupled with the use of isotope-labeled tracers have enabled the quantification of dynamic pathway operation inside living cells and tissues using metabolic flux analysis (MFA). This dissertation describes the development of in vitro and in vivo metabolic models and complementary experimental workflows to investigate regulation of mammalian metabolism using stable isotope-based MFA. First, CRISPR-Cas9 gene editing of an in vitro β-cell line was used to assess the metabolic effects of G6pc2 loss on glucose oxidation and insulin secretion. Next, a previously published hepatic model was expanded to better understand the impacts of Cori cycling and secondary tracer effects on estimates of in vivo liver fluxes. Then, by combining the hepatic model with a renal compartment, liver and kidney fluxes were simultaneously assessed under conditions of impaired liver gluconeogenesis. This multi-tissue MFA approach was further leveraged to concurrently quantify metabolic fluxes in the liver, heart, and skeletal muscle of individual mice that varied in severity of metabolic disease due to increasing adiposity. Lastly, the INCA software package was upgraded with the capability to model steady-state and dynamic NMR measurements, and these new features were validated using both synthetic and experimental datasets to precisely determine cardiac and hepatic fluxes. The major contribution of this dissertation is to provide novel multi-tissue MFA models, analytical methods, and software tools with a broad range of potential applications in metabolism research. | |
