Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 113, Issue 47, Pages E7610-E7618Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1610218113
Keywords
secondary metabolism; mass spectrometry; metabolomics; information theory; Nicotiana attenuata
Categories
Funding
- Max Planck Society
- European Research Council [293926]
- Collaborative Research Centre Chemical Mediators in Complex Biosystems [SFB 1127]
- Deutsche Forschungsgemeinschaft Excellence Initiative
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Secondary metabolite diversity is considered an important fitness determinant for plants' biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissue-metabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function.
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