Abstract
Metabolism serves as the engine of cellular physiology, driving energy production, redox homeostasis and the biosynthesis of macromolecules essential for cell growth and repair. Dysregulated metabolism is increasingly recognized as a hallmark of disease, contributing to the initiation and progression of conditions such as cancer, steatotic liver disease, neurodegeneration and cancer-associated muscle wasting. In this dissertation, I utilize LC-MS-based metabolomics and stable isotope tracing to explore how genetic and environmental perturbations reshape metabolism. In chapter 2, I present a novel, calibration-factor-based LC-MS method for direct and accurate quantification of NAD(P)H/NAD(P)+ ratios, overcoming the limitations of traditional colorimetric assays and eliminating the need for standard curves. In chapter 3, I explore tumor-induced muscle wasting characterized by enhanced BCAA catabolism in a melanoma-bearing zebrafish model and identified ALT as a potential therapeutic target. In chapter 4, I establish NRASQ61R-driven melanoma zebrafish lines to investigate oncogene-specific metabolic alterations and uncover a tumor-liver alanine cycle that helps maintain circulating glucose levels. In chapter 5, I study zinc-dependent metabolic crosstalk between CAFs and PC3 cells, identifying aspartate and asparagine as key metabolites secreted by CAFs that support PC3 proliferation. Together, these studies showcase LC-MS-based metabolomics as a powerful discovery tool to understand how both genetic drivers and environmental factors alter metabolism. The findings in this dissertation provide insights into redox regulation, tumor-host metabolic interactions, and nutrient exchange, offering new avenues for treatments. In addition, this dissertation reinforces the utility of zebrafish as a robust animal model for investigating disease mechanisms, understanding systemic metabolism and identifying potential therapeutic targets.
Committee Chair
Gary Patti
Committee Members
Kevin Moeller; Meredith Jackrel; Michael Gross; Richard Harbison
Degree
Doctor of Philosophy (PhD)
Author's Department
Chemistry
Document Type
Dissertation
Date of Award
8-11-2025
Language
English (en)
DOI
https://doi.org/10.7936/m4d4-2590
Recommended Citation
Guo, Qiuyuan, "Improving metabolomics methods to measure redox balance and understand disease mechanisms" (2025). Arts & Sciences Theses and Dissertations. 3589.
The definitive version is available at https://doi.org/10.7936/m4d4-2590