Analysis of metabolite profiles obtained by mass spectrometry using graphs

Abstract

The natural product bioprospection is a complex and laborious process, with a high average cost and intensive manual inspection to isolate and identify active compounds from a natural product source. Brazilian endemic species of Lychnophora (Asteraceae) figure as a rich plant genus that have been used as the source for natural products exploration. Public compendia of molecular information with biological hierarchical organization of catalytic and regulatory genome potential, metabolic pathways and compounds potentially produced by a given organism, are incipient, often lacking for Lychnophora species. Recent studies of genome scale metabolism reconstruction perform exhaustive searches of genetic and biochemical information about a particular organism, reconstructing the known metabolism for the same. This approach allows a better inference of an organism chemical potential, enhancing its biotechnological exploitation. Besides the absence of molecular information compendia for Lychnophora metabolism inference, with conventional methods to analise plant extracts, the spatial information of metabolites in tissue, cells and organelles is lost. The IMS technique (Imaging Mass Spectrometry) allows the mass spectra collection for hundreds to thousands of points at predefined coordinates of a tissue area. With this spectras a map of the tissue distribution of the target substance can be built. The use of a compendium of biologically hierarchical known compounds for Lychnophora, and its compartmentalization in reactions and metabolic pathways, allows the natural product search in spatially defined regions of plant tissue and can be very useful for understanding their biological function as well as to guide its isolation improvement. Given the great complexity of the datasets produced in MALDI-imaging experiments and the lack of databases for metabolite comparison and inference of biochemical processes, this project aims to build a database with hierarchical genetic and biochemical information of Lychnophora phylogenetically related species and perform the inference by graphs of spatially specific metabolic pathways, using data obtained from IMS . (AU)