Systematic structural characterization of metabolites in arabidopsis via candidate substrate-product pair networks

dc.contributor.authorMorreel, Kris
dc.contributor.authorSaeys, Yvan
dc.contributor.authorDima, Oana
dc.contributor.authorLu, Fachuang
dc.contributor.authorVan de Peer, Yves
dc.contributor.authorVanholme, Ruben
dc.contributor.authorRalph, John
dc.contributor.authorVanholme, Bartel
dc.contributor.authorBoerjan, Wout
dc.date.accessioned2015-09-04T07:21:37Z
dc.date.available2015-09-04T07:21:37Z
dc.date.issued2014-03
dc.description.abstractPlant metabolomics is increasingly used for pathway discovery and to elucidate gene function. However, the main bottleneck is the identification of the detected compounds. This is more pronounced for secondary metabolites as many of their pathways are still underexplored. Here, an algorithm is presented in which liquid chromatography–mass spectrometry profiles are searched for pairs of peaks that have mass and retention time differences corresponding with those of substrates and products from well-known enzymatic reactions. Concatenating the latter peak pairs, called candidate substrate-product pairs (CSPP), into a network displays tentative (bio)synthetic routes. Starting from known peaks, propagating the network along these routes allows the characterization of adjacent peaks leading to their structure prediction. As a proof-of-principle, this high-throughput cheminformatics procedure was applied to the Arabidopsis thaliana leaf metabolome where it allowed the characterization of the structures of 60% of the profiled compounds. Moreover, based on searches in the Chemical Abstract Service database, the algorithm led to the characterization of 61 compounds that had never been described in plants before. The CSPP-based annotation was confirmed by independent MSn experiments. In addition to being high throughput, this method allows the annotation of low-abundance compounds that are otherwise not amenable to isolation and purification. This method will greatly advance the value of metabolomics in systems biology.en_ZA
dc.description.librarianhb2015en_ZA
dc.description.sponsorshipStanford University Global Climate and Energy Project (“Towards New Degradable Lignin Types,” “Efficient Biomass Conversion: Delineating the Best Lignin Monomer-Substitutes,” and “Lignin management: optimizing yield and composition in lignin-modified plants”) by the Multidisciplinary Research Project “Biotechnology for a sustainable economy” of Ghent University, by the European Community’s Seventh Framework Programme (FP7/2009) under grant agreement 251132 (SUNLIBB), and the “Bijzonder Onderzoeksfonds-ZwareApparatuur” of Ghent University for the FT-ICR-MS (Grant 174PZA05).Research Foundation-Flanders.en_ZA
dc.description.urihttp://www.plantcell.orgen_ZA
dc.identifier.citationMorreel, K, Saeys, Y, Dima, O, Lu, F, Van de Peer, Y, Vanholme, R, Ralph, J, Vanholme, B & Boerjan, W 2014, 'Systematic structural characterization of metabolites in arabidopsis via candidate substrate-product pair networks', Plant Cell, vol. 26, no. 3, pp. 929-945.en_ZA
dc.identifier.issn1040-4651 (print)
dc.identifier.issn1532-298X (online)
dc.identifier.other10.​1105/​tpc.​113.​122242
dc.identifier.urihttp://hdl.handle.net/2263/49708
dc.language.isoenen_ZA
dc.publisherAmerican Society of Plant Biologistsen_ZA
dc.rights© 2014 American Society of Plant Biologists. All rights reserved.en_ZA
dc.subjectStructural characterizationen_ZA
dc.subjectMetabolites in arabidopsisen_ZA
dc.subjectPlant metabolomicsen_ZA
dc.subjectPathway discoveryen_ZA
dc.subjectDetected compoundsen_ZA
dc.subjectCandidate substrate-product pairs (CSPP)en_ZA
dc.titleSystematic structural characterization of metabolites in arabidopsis via candidate substrate-product pair networksen_ZA
dc.typePostprint Articleen_ZA

Files

Original bundle

Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
Morreel_Systematic_2014.pdf
Size:
1.38 MB
Format:
Adobe Portable Document Format
Description:
Postprint Article
Loading...
Thumbnail Image
Name:
Morreel_SystematicSuppl_2014.pdf
Size:
3.41 MB
Format:
Adobe Portable Document Format
Description:
Supplement

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: