SummaryThe integration of metabolomics and transcriptomics can provide precise information on gene-to-metabolite networks for identifying the function of unknown genes unless there has been a post-transcriptional modification. Here, we report a comprehensive analysis of the metabolome and transcriptome of Arabidopsis thaliana over-expressing the PAP1 gene encoding an MYB transcription factor, for the identification of novel gene functions involved in flavonoid biosynthesis. For metabolome analysis, we performed flavonoid-targeted analysis by high-performance liquid chromatography-mass spectrometry and non-targeted analysis by Fourier-transform ion-cyclotron mass spectrometry with an ultrahigh-resolution capacity. This combined analysis revealed the specific accumulation of cyanidin and quercetin derivatives, and identified eight novel anthocyanins from an array of putative 1800 metabolites in PAP1 over-expressing plants. The transcriptome analysis of 22 810 genes on a DNA microarray revealed the induction of 38 genes by ectopic PAP1 overexpression. In addition to well-known genes involved in anthocyanin production, several genes with unidentified functions or annotated with putative functions, encoding putative glycosyltransferase, acyltransferase, glutathione S-transferase, sugar transporters and transcription factors, were induced by PAP1. Two putative glycosyltransferase genes (At5g17050 and At4g14090) induced by PAP1 expression were confirmed to encode flavonoid 3-O-glucosyltransferase and anthocyanin 5-O-glucosyltransferase, respectively, from the enzymatic activity of their recombinant proteins in vitro and results of the analysis of anthocyanins in the respective T-DNA-inserted mutants. The functional genomics approach through the integration of metabolomics and transcriptomics presented here provides an innovative means of identifying novel gene functions involved in plant metabolism.

To determine the mechanism of inhibition of anthocyanin accumulation in the skin of grape berries due to high temperature, the effects of high temperature on anthocyanin composition and the responses in terms of gene transcript levels were examined using Vitis vinifera L. cv. Cabernet Sauvignon. High temperature (maximum 35 degrees C) reduced the total anthocyanin content to less than half of that in the control berries (maximum 25 degrees C). HPLC analysis showed that the concentrations of anthocyanins, with the exception of malvidin derivatives (3-glucoside, 3-acetylglucoside, and 3-p-coumaroylglucoside), decreased considerably in the berries grown under high temperature as compared with the control. However, Affymetrix Vitis GeneChip microarray analysis indicated that the anthocyanin biosynthetic genes were not strongly down-regulated at high temperature. A quantitative real time PCR analysis confirmed this finding. To demonstrate the possibility that high temperature increases anthocyanin degradation in grape skin, stable isotope-labelled tracer experiments were carried out. Softened green berries of Cabernet Sauvignon were cut and aseptically incubated on filter paper with 1 mM aqueous L-[1-(13)C]phenylalanine solution for 1 week. Thereafter, the changes in (13)C-labelled anthocyanins were examined under different temperatures (15, 25, and 35 degrees C). In the berries cultured at 35 degrees C, the content of total (13)C-labelled anthocyanins that were produced before exposure to high temperature was markedly reduced as compared with those cultured at 15 degrees C and 25 degrees C. These data suggest that the decrease in anthocyanin accumulation under high temperature results from factors such as anthocyanin degradation as well as the inhibition of mRNA transcription of the anthocyanin biosynthetic genes.

Since the completion of genome sequences of model organisms, functional identification of unknown genes has become a principal challenge in biology. Postgenomics sciences such as transcriptomics, proteomics, and metabolomics are expected to discover gene functions. This report outlines the elucidation of gene-togene and metabolite-to-gene networks via integration of metabolomics with transcriptomics and presents a strategy for the identification of novel gene functions. Metabolomics and transcriptomics data of Arabidopsis grown under sulfur deficiency were combined and analyzed by batch-learning self-organizing mapping. A group of metabolites/genes regulated by the same mechanism clustered together. The metabolism of glucosinolates was shown to be coordinately regulated. Three uncharacterized putative sulfotransferase genes clustering together with known glucosinolate biosynthesis genes were candidates for involvement in biosynthesis. In vitro enzymatic assays of the recombinant gene products confirmed their functions as desulfoglucosinolate sulfotransferases. Several genes involved in sulfur assimilation clustered with O-acetylserine, which is considered a positive regulator of these genes. The genes involved in anthocyanin biosynthesis clustered with the gene encoding a transcriptional factor that up-regulates specifically anthocyanin biosynthesis genes. These results suggested that regulatory metabolites and transcriptional factor genes can be identified by this approach, based on the assumption that they cluster with the downstream genes they regulate. This strategy is applicable not only to plant but also to other organisms for functional elucidation of unknown genes.In the era of post-genomics, a systematic and comprehensive understanding of the complex events of life is a great concern in biology. The first step in this process is to identify all gene functions and gene-to-gene networks as the components of the system, the whole events of life. The metabolome is the final product of a series of gene actions. Hence, metabolomics has a potential to elucidate gene functions and networks, especially when integrated with transcriptomics. A promising approach is pair-wise transcript-metabolite correlation analysis, which can reveal unexpected correlations and bring to light candidate genes for modifying the metabolite content (1). Gene functions involved in the specific pathway of interest have been identified by the integration of transcript and targeted metabolic profiling in experimental systems where the pathway was activated (2-6). However, up to now, no gene function has been identified by non-targeted analyses of the transcriptome and metabolome. In this report, we analyzed the non-targeted metabolome and transcriptome of a model plant Arabidopsis under sulfur (S) 1 deficiency whose genome sequencing has been completed. Our strategy for integrated analyses using batch-learning-selforganizing mapping (BL-SOM) (7-9) enabled the identification of gene-to-gene and metabolite-to-gene networks and new gene fun...

SummaryA large number of metabolites are found in each plant, most of which have not yet been identified. Development of a methodology is required to deal systematically with unknown metabolites, and to elucidate their biological roles in an integrated 'omics' framework. Here we report the development of a 'metabolite annotation' procedure. The metabolite annotation is a process by which structures and functions are inferred for metabolites. Tomato (Solanum lycopersicum cv. Micro-Tom) was used as a model for this study using LC-FTICR-MS. Collected mass spectral features, together with predicted molecular formulae and putative structures, were provided as metabolite annotations for 869 metabolites. Comparison with public databases suggests that 494 metabolites are novel. A grading system was introduced to describe the evidence supporting the annotations. Based on the comprehensive characterization of tomato fruit metabolites, we identified chemical building blocks that are frequently found in tomato fruit tissues, and predicted novel metabolic pathways for flavonoids and glycoalkaloids. These results demonstrate that metabolite annotation facilitates the systematic analysis of unknown metabolites and biological interpretation of their relationships, which provide a basis for integrating metabolite information into the system-level study of plant biology.

SummaryMembers of the BAHD family of plant acyl transferases are very versatile catalytically, and are thought to be able to evolve new substrate specificities rapidly. Acylation of anthocyanins occurs in many plant species and affects anthocyanin stability and light absorption in solution. The versatility of BAHD acyl transferases makes it difficult to identify genes encoding enzymes with defined substrate specificities on the basis of structural homology to genes of known catalytic function alone. Consequently, we have used a modification to standard functional genomics strategies, incorporating co-expression profiling with anthocyanin accumulation, to identify genes encoding three anthocyanin acyl transferases from Arabidopsis thaliana. We show that the activities of these enzymes influence the stability of anthocyanins at neutral pH, and some acylations also affect the anthocyanin absorption maxima. These properties make the BAHD acyl transferases suitable tools for engineering anthocyanins for an improved range of biotechnological applications.