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Revealing insect herbivory‐induced phenolamide metabolism: from single genes to metabolic network plasticity analysis
Author(s) -
Gaquerel Emmanuel,
Gulati Jyotasana,
Baldwin Ian T.
Publication year - 2014
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.12503
Subject(s) - phenylpropanoid , biology , metabolic pathway , metabolomics , metabolic network , gene , secondary metabolism , computational biology , metabolism , adaptation (eye) , microbiology and biotechnology , biochemistry , biosynthesis , bioinformatics , neuroscience
Summary The phenylpropanoid metabolic space comprises a network of interconnected metabolic branches that contribute to the biosynthesis of a large array of compounds with functions in plant development and stress adaptation. During biotic challenges, such as insect attack, a major rewiring of gene networks associated with phenylpropanoid metabolism is observed. This rapid reconfiguration of gene expression allows prioritized production of metabolites that help the plant solve ecological problems. Phenolamides are a group of phenolic derivatives that originate from diversion of hydroxycinnamoyl acids from the main phenylpropanoid pathway after N –acyltransferase‐dependent conjugation to polyamines or aryl monoamines. These structurally diverse metabolites are abundant in the reproductive organs of many plants, and have recently been shown to play roles as induced defenses in vegetative tissues. In the wild tobacco, Nicotiana attenuata , in which herbivory‐induced regulation of these metabolites has been studied, rapid elevations of the levels of phenolamides that function as induced defenses result from a multi‐hormonal signaling network that re‐shapes connected metabolic pathways. In this review, we summarize recent findings in the regulation of phenolamides obtained by mass spectrometry‐based metabolomics profiling, and outline a conceptual framework for gene discovery in this pathway. We also introduce a multifactorial approach that is useful in deciphering metabolic pathway reorganizations among tissues in response to stress.

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