COMBINATORIAL ASSEMBLY OF MODULAR METABOLITES VIA CARBOXYLESTERASES IN NEMATODES
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The small molecule metabolites produced by living organisms play essential roles in nearly every aspect of their life history, including lifespan, development, and behavior. The identification of these small molecules and the discovery of their biosynthesis is key to understand the intra- and inter-organismal signaling pathways that exist within living systems and can offer insight into the function of related small molecules in orthologous organisms. In this dissertation, the author explores the combinatorial assembly of complex modular structures and how nematodes utilize building blocks derived from conserved catabolic, detoxification, and degradation pathways for the biosynthesis of modular metabolites. By utilizing comparative metabolomics of high-resolution mass spectrometry data, we were able to identify a novel class of modular metabolites, based on a glucoside core, that require a specific lysosome-related organelle and the activity of carboxylesterases for their biosynthesis. Caenorhabditis elegans are able to glucosylate endogenous and xenobiotic compounds forming glucosides. These glucosides are then further decorated by molecular moieties derived primarily from catabolic and detoxification pathways, such as amino acid degradation pathways, to form hundreds of different modular glucosides via carboxylesterases. We further demonstrate that these carboxylesterase-derived modular glucosides are involved in the starvation and stress response pathways in C. elegans. We show that this biosynthetic strategy to create chemical diversity from hijacking conserved detoxification mechanisms is shared with a related species of nematode, Caenorhabditis briggsae. While many aspects of modular metabolite biosynthesis and function remain to be elucidated, our results show that modular metabolites form an integral part of C. elegans metabolism and serve important biological roles. More generally, the work presented here demonstrates how untargeted comparative metabolomic analysis can be used to facilitate the annotation of the metabolic dark matter.
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Lin, Hening