CHARACTERIZING PLANT SPECIALIZED METABOLISM THROUGH COMPUTATIONAL TOOLS AND OMICS APPROACHES

202 pagesTwo of the major bottlenecks that currently hinder the study of plant specialized metabolism are the structural elucidation of metabolites and the functional characterization of their associated genes. Although modern analytical instruments (typically mass spectrometers (MS) coupled with liquid chromatography (LC), or LC-MS) are capable of detecting up to thousands of metabolites in plant extracts, no comparable methods exist for the high-throughput structural elucidation of these metabolites. Similarly, the functions of specialized metabolic genes can be difficult to elucidate as they often belong to large gene families that undergo frequent gene duplication. While the most common method of gene function prediction – the transfer of known gene functions through related species – is easily implementable, it may yield inaccurate conclusions for metabolic genes. The goal of this dissertation is to contribute to the alleviation of both bottlenecks. Chapter 1 reviews current methodologies and algorithms for the elucidation of metabolite structure and gene function – especially in relation to plant specialized metabolism. Chapter 2 describes the development of machine learning algorithms to structurally annotate metabolites based on LC-MS data, and the evaluation of their performance with plant metabolites. Chapters 3 and 4 detail the analysis of an integrative transcriptomics and metabolomics experiment undertaken in the model grass species Brachypodium distachyon, designed to both elucidate metabolic functions of genes and characterize stress-induced shifts in metabolism. Chapter 3 explores the utilization of emerging algorithms for i) partial elucidation of the structures of plant metabolites, ii) quantification of the impacts of different environmental conditions on the plant metabolome. Chapter 4 implements integrative-omics analyses to characterize B. distachyon genes involved in facilitating arbuscular mycorrhizal symbiosis, and investigates the activity of one functionally unknown gene. Collectively, these studies find that structural annotation of plant metabolites facilitates the understanding of i) how plants adapt to changing environments, and ii) metabolic activities of plant genes. Such knowledge is essential for alleviation of major bottlenecks in the study of plant specialized metabolism.2023-07-1