UC Riverside

The goal of this dissertation was to advance plant metabolomics through optimization of biological experimental design, sampling and sample preparation, data acquisition and pre-processing, and multivariable data analysis. The analytical platform most employed for comparative metabonomics was nuclear magnetic resonance (NMR). Liquid-chromatography (LC) coupled to NMR and mass spectrometry (MS) extended metabolic profile coverage from primary into secondary metabolic pathways. Comparative profiling of tissue extracts by LC-MS and complementary analyses by NMR were performed to establish metabolite identity and quantify responses to low-oxygen stress using the model Angiosperm, Arabidopsis thaliana.

Angiosperms, or flowering plants, constitute the most diverse and numerous group of land plants, and the most commercially important, producing an estimated 200,000 small molecule metabolites through conserved primary metabolism and divergent secondary pathways. No single metabolic profiling experiment has been able to quantify metabolite abundance over the relevant dynamic range (spanning seven orders of magnitude) and across the necessary structural diversity (chemical space coverage exceeds all known synthetic molecules). Challenges in plant metabolic profiling also arise through inherent limitations in methods (availability of diverse solid-phases, solvents, pure standards), instrument performance (reproducibility, robustness, speed, sensitivity), and data management (pre-processing, modeling, data basing and sharing).

The field of plant metabolic profiling has grown steadily over the past two decades, although it is still considered an emerging technique. Comparison of methods for sample preparation provided a foundation for one-dimensional NMR-based comparative metabonomics. Signal overlap was alleviated by liquid-liquid extraction (LLE), solid-phase extraction (SPE), and liquid chromatography (LC). A combined approach involving ultraviolet-visible absorption spectroscopy (UV-Vis), NMR, exact mass MS, and tandem MS (MS/MS) was used for dereplication.

Results are presented illustrating the ability of one-dimensional NMR combined with multivariable data analysis (MVDA) to quantify responses of a model plant to a biological problem of fundamental and practical relevance: cellular respiration under oxygen-limited conditions. The suitability of LC-NMR and LC-MS for dereplication is highlighted. Profiling of secondary metabolites by UPLC-MS combined with MVDA was undertaken for comparison with NMR-based comparative metabonomics. Efforts toward quantitative targeted analyses, hurdles and solutions, are highlighted.