Deciphering Chronometabolic Dynamics Through Metabolomics, Stable Isotope Tracers, And Genome-Scale Reaction Modeling

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Doctor of Philosophy (PhD)
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Pharmacology
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Bioinformatics
Biology
Chemistry
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2018-02-23T20:17:00-08:00
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Abstract

Synchrony across environmental cues, endogenous genetic clocks, sleep/wake cycles, and metabolism evoke physiological harmony for organismal health. Perturbation of this synchrony has been recently correlated with a growing list of pathologies, which is alarming given the ubiquity of sleep deprivation, mistimed light exposure, and altered eating schedules in modern society. Deeper insights into clocks, sleep, and metabolism are necessary to understand these outcomes. In this work, extensive metabolic profiles of circadian systems were obtained from the development of new liquid chromatography mass spectrometry (LC-MS) metabolomics methods. These methods were applied to Drosophila melanogaster to discern relative influences of environmental and genetic drivers of metabolic cycles. Unique sets of metabolites oscillated with 24-hour circadian periods under light:dark (LD) and constant darkness (DD) conditions, and ultradian rhythms were noted for clock mutant flies under LD, suggesting clock-independent metabolic cycles driven by environmental inputs. However, this metabolomic analysis does not fully capture the inherently dynamic nature of circadian metabolism. These LC-MS methods were adapted to analyze isotope enrichments from a novel 13C6 glucose injection platform in Drosophila. Metabolic flux cycles were noted from glucose carbons into serine, glutamine and reduced glutathione biosynthesis, and altered under sleep deprivation, demonstrating unique energy and redox demands in perturbed sleep/wake cycles. Global isotopolome shifts were most notable in WT flies after lights-on, suggesting a catabolic rush from glucose oxidation early in the active phase. As the scope of these isotope tracer-based metabolomic analyses expand, attributing labeling patterns to specific reactions requires consideration of genome-scale metabolic networks. A new computational approach was developed, called the IsoPathFinder, which uncovered biosynthetic paths from glucose to serine, and extends to glycine and glutathione production. Carbon flux into glutamine was predicted to occur through the TCA cycle, supported by enzyme thermodynamics and circadian expression datasets. This tool is presented as a new mechanism to simulate additional isotope tracer experiments, with broad applicability beyond circadian research. Collectively, a new set of analytical and computational tools are developed to both produce dynamic metabolomic data and improve data interpretability, with applications to uncover new chronometabolic connections.

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Aalim M. Weljie
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2017-01-01
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