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|Title:||Integration of metabolomics and fluxomics via nonequilibrium thermodynamics|
|Authors:||Park, Junyoung O.|
|Advisors:||Rabinowitz, Joshua D|
|Contributors:||Chemical and Biological Engineering Department|
Metabolic flux analysis
|Publisher:||Princeton, NJ : Princeton University|
|Abstract:||Metabolism is the process of converting nutrients into usable energy (e.g., ATP) and biomass building blocks (e.g., amino acids, nucleotides, and lipids). The biochemistry of metabolic reactions and the structure of metabolic networks bear impressive resemblance across widely divergent organisms. Like all chemical networks, metabolism must obey the second law of thermodynamics: each pathway step must generate entropy and cost free energy (ΔG). As available free energy is limited, a fundamental challenge is partitioning the requisite free energy loss across pathway steps. For each reaction, ΔG is log-proportional both to a concentration ratio (reaction quotient-to-equilibrium constant) and to a flux ratio (backward-to-forward flux). With 13C isotope labeling, absolute metabolite concentrations and fluxes can be measured in various cell types and organisms including E. coli, yeast, and mammalian cells. Then, the concentration and flux ratios can be integrated via ΔG using the non-equilibrium thermodynamic principle. The integrative analysis yields internally consistent and comprehensive sets of metabolite concentrations and ΔG in each organism. In glycolysis, free energy is partitioned so as to mitigate unproductive backwards fluxes associated with ΔG near zero. Across metabolism, absolute metabolite concentrations and ΔG are substantially conserved such that most substrate (but not inhibitor) concentrations exceed the associated enzyme binding site affinity. The observed conservation of metabolite concentrations may reflect an evolutionary drive to simultaneously satisfy thermodynamic constraints and efficiently utilize enzyme active sites. Modulation of metabolic fluxes allows cells to meet their energetic and material demand in various conditions. In pathway upregulation, cells must coordinate the pathway steps as any one reaction may become limiting. A combination of 2H and 13C labeling reveals the extent of reversibility of glycolytic reactions. In E. coli, glycolysis under nitrogen limitation is substantially closer to equilibrium than in nutrient rich condition. Upon N-upshift, glycolysis immediately restores sufficient driving force to increase glucose consumption and growth rate. In mammalian cells cultured in a rich-nutrient condition, upregulation of glycolysis by Ras or Akt oncogene activation is achieved without substantial alteration of reversibility. These observations suggest that, under nutrient limitation, cells sacrifice enzyme efficiency for fast adaptation.|
|Alternate format:||The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: http://catalog.princeton.edu/|
|Type of Material:||Academic dissertations (Ph.D.)|
|Appears in Collections:||Chemical and Biological Engineering|
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