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Open Access Publications from the University of California

Scholarly Works (3 results)

  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2016)

Simulation of metabolic systems with kinetic models requires a large number of parameter values, which are either difficult or impossible to obtain experimentally. Network information, such as stoichiometry, reversibility and steady state flux, can be used to determine mechanistically realistic rate laws, and these can be used to constrain the parameter space to only those values which satisfy the constraints. Until now, stability has been overlooked when considering kinetic metabolic models. However, dynamical stability and robustness to perturbation are important qualities for living organisms, since they may encounter changing environments or stochastic variation across time or within populations. Considering stability can both provide constraints on the parameter space and be used to interpret the response of the model to queries about the performance of the metabolic system under various perturbations. I have used stability analysis to predict the performance of many metabolic systems, with an emphasis on providing guidance for experimental efforts and uncovering biological significance.

The uses of stability analysis have encompassed several projects. Optimization of a novel methanol condensation cycle (MCC) was accomplished by tuning the amount of an irreversible phosphoketolase enzyme to a local productivity and stability maximum, as predicted by stability analysis and confirmed by in vitro experimentation. Several other in vitro enzymatic were subjected to stability analysis, and predictions matched previously published experimental results.

Stability analysis was also applied to several microbial systems to maximize production of a desired compound: n-butanol in Escherichia coli, isobutanol in Clostridium thermocellum and lipids in Yarrowia lipolytica. In these systems, production simulations matched the observations and predictions for further production improvements were made.

Stability analysis was also applied to gain biological understanding of the significance of structural features of the Calvin-Bassham-Benson (CBB) pathway in plants. The phosphate/glyceraldehyde-3-phosphate translocator was identified as more important for stability than a proposed glucose-6-phosphate shunt. Further, productivity was increased after overexpression of sedoheptulose-1,7-biosphosphatase, but not RuBiSCO, in agreement with previous experimental reports.

The importance of stability in analysis of metabolic systems is affirmed by this work, and the techniques demonstrated here pave the way for even further explorations.

    Cover page: Stability as a Criterion for Metabolic Systems
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2014)
    Methanol is an important intermediate in the utilization of natural gas for synthesizing other feedstock chemicals. Typically, chemical approaches for building C-C bonds from methanol require high temperature and pressure. Biological conversion of methanol to longer carbon chain compounds is feasible; however, the natural biological pathways for methanol utilization involve carbon dioxide loss or ATP expenditure. Here we demonstrated a biocatalytic pathway, termed the methanol condensation cycle (MCC), by combining the nonoxidative glycolysis with the ribulose monophosphate pathway to convert methanol to higher-chain alcohols or other acetyl-CoA derivatives using enzymatic reactions in a carbon-conserved and ATP-independent system. We investigated the robustness of MCC and identified operational regions. We confirmed that the pathway forms a catalytic cycle through (13)C-carbon labeling. With a cell-free system, we demonstrated the conversion of methanol to ethanol or n-butanol. The high carbon efficiency and low operating temperature are attractive for transforming natural gas-derived methanol to longer-chain liquid fuels and other chemical derivatives.
      Cover page: Building carbon–carbon bonds using a biocatalytic methanol condensation cycle
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2014)
      Glioblastoma (GBM) harbors subpopulations of therapy-resistant tumor-initiating cells (TICs) that are self-renewing and multipotent. To understand the regulation of the TIC state, we performed an image-based screen for genes regulating GBM TIC maintenance and identified ZFHX4, a 397 kDa transcription factor. ZFHX4 is required to maintain TIC-associated and normal human neural precursor cell phenotypes in vitro, suggesting that ZFHX4 regulates differentiation, and its suppression increases glioma-free survival in intracranial xenografts. ZFHX4 interacts with CHD4, a core member of the nucleosome remodeling and deacetylase (NuRD) complex. ZFHX4 and CHD4 bind to overlapping sets of genomic loci and control similar gene expression programs. Using expression data derived from GBM patients, we found that ZFHX4 significantly affects CHD4-mediated gene expression perturbations, which defines ZFHX4 as a master regulator of CHD4. These observations define ZFHX4 as a regulatory factor that links the chromatin-remodeling NuRD complex and the GBM TIC state.
        Cover page: ZFHX4 Interacts with the NuRD Core Member CHD4 and Regulates the Glioblastoma Tumor-Initiating Cell State
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