Biosynthetic investigation of γ-lactones in Sextonia rubra wood using in situ TOF-SIMS MS/MS imaging to localize and characterize biosynthetic intermediates View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-02-13

AUTHORS

Tingting Fu, Emeline Houël, Nadine Amusant, David Touboul, Grégory Genta-Jouve, Serge Della-Negra, Gregory L. Fisher, Alain Brunelle, Christophe Duplais

ABSTRACT

Molecular analysis by parallel tandem mass spectrometry (MS/MS) imaging contributes to the in situ characterization of biosynthetic intermediates which is crucial for deciphering the metabolic pathways in living organisms. We report the first use of TOF-SIMS MS/MS imaging for the cellular localization and characterization of biosynthetic intermediates of bioactive γ-lactones rubrynolide and rubrenolide in the Amazonian tree Sextonia rubra (Lauraceae). Five γ-lactones, including previously reported rubrynolide and rubrenolide, were isolated using a conventional approach and their structural characterization and localization at a lateral resolution of ~400 nm was later achieved using TOF-SIMS MS/MS imaging analysis. 2D/3D MS imaging at subcellular level reveals that putative biosynthetic γ-lactones intermediates are localized in the same cell types (ray parenchyma cells and oil cells) as rubrynolide and rubrenolide. Consequently, a revised metabolic pathway of rubrynolide was proposed, which involves the reaction between 2-hydroxysuccinic acid and 3-oxotetradecanoic acid, contrary to previous studies suggesting a single polyketide precursor. Our results provide insights into plant metabolite production in wood tissues and, overall, demonstrate that combining high spatial resolution TOF-SIMS imaging and MS/MS structural characterization offers new opportunities for studying molecular and cellular biochemistry in plants. More... »

PAGES

1928

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-018-37577-5

DOI

http://dx.doi.org/10.1038/s41598-018-37577-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112090809

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30760744


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