Relative Mass Defect Filtering of Mass Spectra: A Path to Discovery of Plant Specialized Metabolites

Abstract

The rapid identification of novel plant metabolites and assignments of newly discovered substances to natural product classes present the main bottlenecks to defining plant specialized phenotypes. Although mass spectrometry provides powerful support for metabolite discovery by measuring molecular masses, ambiguities in elemental formulas often fail to reveal the biosynthetic origins of specialized metabolites detected using liquid chromatography-mass spectrometry. A promising approach for mining liquid chromatography-mass spectrometry metabolite profiling data for specific metabolite classes is achieved by calculating relative mass defects (RMDs) from molecular and fragment ions. This strategy enabled the rapid recognition of an extensive range of terpenoid metabolites in complex plant tissue extracts and is independent of retention time, abundance, and elemental formula. Using RMD filtering and tandem mass spectrometry data analysis, 24 novel elemental formulas corresponding to glycosylated sesquiterpenoid metabolites were identified in extracts of the wild tomato Solanum habrochaites LA1777 trichomes. Extensive isomerism was revealed by ultra-high-performance liquid chromatography, leading to evidence of more than 200 distinct sesquiterpenoid metabolites. RMD filtering led to the recognition of the presence of glycosides of two unusual sesquiterpenoid cores that bear limited similarity to known sesquiterpenes in the genus Solanum. In addition, RMD filtering is readily applied to existing metabolomics databases and correctly classified the annotated terpenoid metabolites in the public metabolome database for Catharanthus roseus.Plant metabolic networks generate amazing chemical diversity, but our understanding of the genetic factors responsible for plant chemistry remains primitive. The discovery and identification of metabolites has posed the greatest bottleneck in recent efforts to exploit metabolomics to address questions about the basis for biosynthetic diversity in the plant kingdom (Ji et al., 2009;Zhou et al., 2012). Since the specialized metabolism of nonmodel plants is taxonomically restricted, metabolite databases offer a poor representation of plant chemical diversity, and de novo recognition and discovery of metabolite chemistry is necessary. A common strategy for metabolite discovery has often started with the generation of tandem mass spectrometry (MS/MS) spectra, usually beginning with the most abundant metabolites, and uses characteristic fragment ions to assign metabolites to a particular class of compounds. Flavonoid identification from MS/MS spectra is often successful because most flavonoids yield MS/MS fragment ions characteristic of their flavonoid cores (Ma et al., 1997;Li et al., 2013). However, when MS/MS spectra fail to display classcharacteristic fragment ions, the recognition of a metabolite's structural class is less obvious.Specialized plant metabolites are often grouped as polyphenolic, terpenoid, alkaloid, polyketide, or fatty acid metabolites based upon the biosynthesis of their...

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