Development, Optimization and Validation of Targeted and Global Metabolite Profiling Strategies for Probing Plant Metabolism
Cuthbertson, Daniel James
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Metabolomics is the attempt to comprehensibly identify and quantify all metabolites in a cell, tissue or organism, which is a tremendous challengedue to the enormous chemical diversity found in living systems, particularly in plants. To meet these challenges sensitive and selective technologies for chromatography and mass spectrometry have been developed. In this dissertation I am presenting applications of two major strategies for interrogating the metabolome: (1) targeted metabolic profiling which focuses in the analysis of metabolites of similar chemical properties and (2) non-targeted metabolomic analyses which seek to achieve more comprehensive metabolite coverage. In these studies I used both gas chromatography and liquid chromatography coupled to mass spectrometry. The first study integrated metabolic profiling with microarray analysis to examine the effects of experimental sink limitation treatments in soybean and found an up-regulation of stress response genes and the accumulation of stress metabolites like γ-aminobutyric acid and isoflavones. Our results demonstrated that experiments using sink removal have unintended consequences, in addition to the induced accumulation of putative storage proteins, indicating that the roles of these proteins in source-sink relationships need to be reinvestigated. I the second study I developed a platform for acquiring non-targeted metabolomics datawith tree fruit, which was used successfully to differentiate several commercially grown cultivars of apple. This study has implications for the use of metabolomics to assist breeding program and to screen for metabolic quality traits. Taken together these studies highlight the utility of probing the metabolome using different analytical techniques and strategies. This dissertation refers to supplementary material files. Supplementary Material 1 includes the processed microarray data set used in Chapter 2. Supplementary Material 2 provides meta data regarding the experimental design of the microarray experiment. Supplementary Material 3 includes processed metabolomics data, including statistical analyses, for the study to differentiate fruit from various apple cultivars as described in Chapter 3.