Biosynthetic Function of Genes in Plants and Their Consequences in Insects – a Metabolite Profiling Approach Driven by Automatic Compound Identification
May 17, 2016
11:00am EDT, 8:00am PDT, 16:00 BST, 17:00 CEST
Exploring the diversity of natural products in plants requires efficient methods to gain sufficient structural information to rapidly discriminate known compounds from novel or closely related ones. This process can be extremely challenging when analyzing profiles of transgenic/mutant plants in which natural product biosynthetic pathways are manipulated. The task is even more difficult when the objective is to follow plant metabolites as they move through trophic cascades, as plants are eaten by herbivores, and herbivores by predators. Workflows that combine statistical data mining and automatic compound identification routines are therefore needed.
Here, we present a software solution for the rapid and efficient screening of metabolites from wild tobacco plants transformed to alter the expression of several glycosyltransferase genes. These genes are part of the biosynthetic pathway leading to defensive 17-hydroxygeranyllinallool diterpene glycosides (HGL-DTGs). Furthermore we analyze post-ingestive modifications of these metabolites within the tobacco hornworm Manduca sexta. Our results illustrate the power of this software-based workflow for gene discovery in the HGL-DTG pathway in tobacco and for analyzing the consequences, in both the plant and insect, of manipulating this pathway.
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Metabolomics Workflow that combines:
• statistical data mining
• automatic compound identification routines
• pathway mapping functionalities for linking MS data to biology in discovery metabolomics
• Researchers/ R&D Mangagers
• Laboratory Managers/ Directors / Supervisors
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Sven Heiling, Ph. D.,
Department of Molecular Ecology,
Max Planck Institute for Chemical Ecology