A MYB Triad Controls Primary and Phenylpropanoid Metabolites for Pollen Coat Patterning.

The pollen wall is a complex, durable structure essential for plant reproduction. A substantial portion of phenylpropanoids (e.g. flavonols) produced by pollen grain tapetal cells are deposited in the pollen wall. Transcriptional regulation of pollen wall formation has been studied extensively, and a specific regulatory mechanism for Arabidopsis (Arabidopsis thaliana) pollen flavonol biosynthesis has been postulated. Here, metabolome and transcriptome analyses of anthers from mutant and overexpression genotypes revealed that Arabidopsis MYB99, a putative ortholog of the petunia (Petunia hybrida) floral scent regulator ODORANT1 (ODO1), controls the exclusive production of tapetum diglycosylated flavonols and hydroxycinnamic acid amides. We discovered that MYB99 acts in a regulatory triad with MYB21 and MYB24, orthologs of emission of benzenoids I and II, which together with ODO1 coregulate petunia scent biosynthesis genes. Furthermore, promoter-activation assays showed that MYB99 directs precursor supply from the Calvin cycle and oxidative pentose-phosphate pathway in primary metabolism to phenylpropanoid biosynthesis by controlling TRANSKETOLASE2 expression. We provide a model depicting the relationship between the Arabidopsis MYB triad and structural genes from primary and phenylpropanoid metabolism and compare this mechanism with petunia scent control. The discovery of orthologous protein triads producing related secondary metabolites suggests that analogous regulatory modules exist in other plants and act to regulate various branches of the intricate phenylpropanoid pathway.

Transcriptome and Metabolic Profiling Provides Insights into Betalain Biosynthesis and Evolution in Mirabilis jalapa.

Betalains are tyrosine-derived pigments that occur solely in one plant order, the Caryophyllales, where they largely replace the anthocyanins in a mutually exclusive manner. In this study, we conducted multi-species transcriptome and metabolic profiling in Mirabilis jalapa and additional betalain-producing species to identify candidate genes possibly involved in betalain biosynthesis. Among the candidates identified, betalain-related cytochrome P450 and glucosyltransferase-type genes, which catalyze tyrosine hydroxylation or (hydroxy)cinnamoyl-glucose formation, respectively, were further functionally characterized. We detected the expression of genes in the flavonoid/anthocyanin biosynthetic pathways as well as their metabolite intermediates in betalain-accumulating M. jalapa flowers, and found that the anthocyanin-related gene ANTHOCYANIDIN SYNTHASE (MjANS) is highly expressed in the betalain-accumulating petals. However, it appears that MjANS contains a significant deletion in a region spanning the corresponding enzyme active site. These findings provide novel insights into betalain biosynthesis and a possible explanation for how anthocyanins have been lost in this plant species. Our study also implies a complex, non-uniform history for the loss of anthocyanin production across betalain producers, previously assumed to be strictly due to diminished expression of anthocyanin-related genes.

The WEIZMASS spectral library for high-confidence metabolite identification.

Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.