Metabolite-Content-Guided Prediction of Medicinal/Edible Properties in Plants for Bioprospecting
2018
Abstract Metabolite-content
(MC) refers to all small molecules which are the products or intermediates of
metabolism within an organism. The metabolite-contents of plants which involve
numerous secondary metabolites are highly related to their nutritional and
medicinal features. Previous researches have confirmed that phylogeny-guided
approaches have been seen as one of the time-efficient and informative
approaches to plant-based drug discovery. However, the phylogenetic
reconstruction of plants is not determined conclusively from genomic sequence
data. Here, we investigate the systematic value of metabolite-contents of
plants, especially the predictive power of metabolite-content data in
exploration of edible and medicinal properties for bioprospecting . In this study, we reconstructed the phylogenetic
tree for a set of plants which are distributed in different genera and families
by their metabolite-content data obtained from KNApSAcK Core DB. We used a
network based approach to abstract structurally similar metabolites as
features, and measure the phylogenetic distance by a binary method. We also reconstructed
phylogenetic trees based on plastid markers rbcL, matK and ITS2 for the same set of
plants, to investigate the predictive power of these two approaches, sequence-
and MC-based approaches, in guiding the prediction of medicinal/edible
properties. Our
results reveal that besides the genomic sequence data, metabolite-content data
is also closely associated with medicinal and edible bioactivity of plants and
can be used to explore the medicinal/edible properties in a different
perspective from sequence-based approach. Our study therefore provides a new
approach for plant bioprospecting, and the predictive power of
metabolite-content data for medicinal/edible plants will also be improved with
the improvement and completeness of the metabolite-content database. Keywords: Chemosystematics;
Metabolite-content; Phylogeny; Prediction; Secondary Metabolite
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