A metabolic fingerprinting technique for functional genomics in Fusarium verticillioides

The maize pathogen, Fusarium verticillioides, infects roots, stalks, ears, and kernels. In addition, the fungus produces fumonisin mycotoxins during kernel colonization. Although the regulation of fumonisin biosynthesis is increasingly well understood, little is known about broad changes in the metabolome underlying pathogenesis. The objective of this study was to develop a metabolic fingerprinting technique to simultaneously detect and quantify structurally diverse metabolites produced by F. verticillioides . To create a metabolic fingerprint of the fungus, a workflow based on gas chromatography-mass spectrometry (GC-MS) was developed that could reliably detect 46 metabolites, 16 of which were putatively identified based on matches with characterized compounds in structural databases. Then, metabolic fingerprints obtained from a genetically defined mutant of the fungus lacking PAC1, a pH-dependant transcriptional regulator, were compared to the fingerprint of the wild type. Statistically significant differences in the production of characterized and uncharacterized metabolites were reliably detected in the mutant. Additionally, changes in the metabolome of both strains in response to environmental conditions such as pH were consistently detected. This metabolic fingerprinting technique provides a novel tool for functional genomics and reverse genetics in F. verticillioides, in that a wide range of "silent" metabolic phenotypes can be identified rapidly.