Systematic Structural Characterization of Metabolites in Arabidopsis via Candidate Substrate-Product Pair Networks

Plant metabolomics is increasingly used as a tool for pathway discovery and to elucidate the function of genes. The main bottleneck in metabolomics 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 (bio)synthetic routes. Starting from known peaks, propagating the network along these routes allows the characterization of adjacent peaks leading to the structure prediction. As a proof-of-principle, this high-throughput cheminformatics procedure was applied to the Arabidopsis thaliana leaf metabolome where it allowed characterizing the structures of 60% of the profiled compounds. Moreover, the algorithm leads 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.

Morreel, K., Saeys, Y., Dima, O., Lu, F., Van de Peer, Y., Vanholme, R., Ralph, S., Vanholme, B., Boerjan, W. (2014) Systematic Structural Characterization of Metabolites in Arabidopsis via Candidate Substrate-Product Pair Networks. The Plant Cell 26(3):929-945.









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