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Front Plant Sci. 2018 Aug 17;9:1155. doi: 10.3389/fpls.2018.01155. eCollection 2018.

Shedding Light on Chemically Mediated Tri-Trophic Interactions: A 1H-NMR Network Approach to Identify Compound Structural Features and Associated Biological Activity.

Author information

1
Department of Biology, University of Nevada, Reno, NV, United States.
2
Department of Chemistry, University of Nevada, Reno, NV, United States.
3
Department of Biochemistry and Molecular Biology, University of Nevada, Reno, NV, United States.

Abstract

Diverse mixtures of plant natural products play an important role in plant-herbivore-parasitoid interactions. In the pursuit of understanding these chemically-mediated interactions, we are often faced with the challenge of determining ecologically and biologically relevant compounds present in complex phytochemical mixtures. Using a network-based approach, we analyzed binned 1H-NMR data from 196 prepared mixtures of commonly studied secondary metabolites including alkaloids, amides, terpenes, iridoid glycosides, saponins, phenylpropanoids, flavonoids and phytosterols. The mixtures included multiple dimensions of chemical diversity, including molecular complexity, mixture complexity and differences in relative compound concentrations. This approach yielded modules of co-occurring chemical shifts that were correlated with specific compounds or common structural features shared across compounds. This approach was then applied to crude phytochemical extracts of 31 species in the phytochemically diverse tropical plant genus Piper (Piperaceae). Combining the activity of crude plant extracts in an array of bioassays with our 1H-NMR network approach, we identified a potential prenylated benzoic acid from these mixtures that exhibits antifungal properties and identified small structural differences that were potentially responsible for antifungal activity. In an intraspecific analysis of individual Piper kelleyi plants, we also found ontogenetic differences in chemistry that may affect natural plant enemies. In sum, this approach allowed us to characterize mixtures as useful network modules and to combine chemical and ecological datasets to identify biologically important compounds from crude extracts.

KEYWORDS:

NMR; Piper; chemical ecology; multi-tropic interactions; network analysis

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