Ryo Nakabayashi

Comprehensive Flavonol Profiling and Transcriptome Coexpression Analysis Leading to Decoding Gene–Metabolite Correlations in Arabidopsis

To complete the metabolic map for an entire class of compounds, it is essential to identify gene–metabolite correlations of a metabolic pathway. We used liquid chromatography–mass spectrometry (LC-MS) to identify the flavonoids produced by Arabidopsis thaliana wild-type and flavonoid biosynthetic mutant lines. The structures of 15 newly identified and eight known flavonols were deduced by LC-MS profiling of these mutants. Candidate genes presumably involved in the flavonoid pathway were delimited by transcriptome coexpression network analysis using public databases, leading to the detailed analysis of two flavonoid pathway genes, UGT78D3 (At5g17030) and RHM1 (At1g78570). The levels of flavonol 3-O-arabinosides were reduced in ugt78d3 knockdown mutants, suggesting that UGT78D3 is a flavonol arabinosyltransferase. Recombinant UGT78D3 protein could convert quercetin to quercetin 3-O-arabinoside. The strict substrate specificity of UGT78D3 for flavonol aglycones and UDP-arabinose indicate that UGT78D3 is a flavonol arabinosyltransferase. A comparison of flavonol profile in RHM knockout mutants indicated that RHM1 plays a major role in supplying UDP-rhamnose for flavonol modification. The rate of flavonol 3-O-glycosylation is more affected than those of 7-O-glycosylation by the supply of UDP-rhamnose. The precise identification of flavonoids in conjunction with transcriptomics thus led to the identification of a gene function and a more complete understanding of a plant metabolic network.

Enhancement of oxidative and drought tolerance in Arabidopsis by overaccumulation of antioxidant flavonoids

The notion that plants use specialized metabolism to protect against environmental stresses needs to be experimentally proven by addressing the question of whether stress tolerance by specialized metabolism is directly due to metabolites such as flavonoids. We report that flavonoids with radical scavenging activity mitigate against oxidative and drought stress in Arabidopsis thaliana. Metabolome and transcriptome profiling and experiments with oxidative and drought stress in wild-type, single overexpressors of MYB12/PFG1 (PRODUCTION OF FLAVONOL GLYCOSIDES1) or MYB75/PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT1), double overexpressors of MYB12 and PAP1, transparent testa4 (tt4) as a flavonoid-deficient mutant, and flavonoid-deficient MYB12 or PAP1 overexpressing lines (obtained by crossing tt4 and the individual MYB overexpressor) demonstrated that flavonoid overaccumulation was key to enhanced tolerance to such stresses. Antioxidative activity assays using 2,2-diphenyl-1-picrylhydrazyl, methyl viologen, and 3,3′-diaminobenzidine clearly showed that anthocyanin overaccumulation with strong in vitro antioxidative activity mitigated the accumulation of reactive oxygen species in vivo under oxidative and drought stress. These data confirm the usefulness of flavonoids for enhancing both biotic and abiotic stress tolerance in crops.

The flavonoid biosynthetic pathway in Arabidopsis: Structural and genetic diversity

Flavonoids are representative plant secondary products. In the model plant Arabidopsis thaliana, at least 54 flavonoid molecules (35 flavonols, 11 anthocyanins and 8 proanthocyanidins) are found. Scaffold structures of flavonoids in Arabidopsis are relatively simple. These include kaempferol, quercetin and isorhamnetin for flavonols, cyanidin for anthocyanins and epicatechin for proanthocyanidins. The chemical diversity of flavonoids increases enormously by tailoring reactions which modify these scaffolds, including glycosylation, methylation and acylation. Genes responsible for the formation of flavonoid aglycone structures and their subsequent modification reactions have been extensively characterized by functional genomic efforts - mostly the integration of transcriptomics and metabolic profiling followed by reverse genetic experimentation. This review describes the state-of-art of flavonoid biosynthetic pathway in Arabidopsis regarding both structural and genetic diversity, focusing on the genes encoding enzymes for the biosynthetic reactions and vacuole translocation.

RIKEN tandem mass spectral database (ReSpect) for phytochemicals: a plant-specific MS/MS-based data resource and database.

The fragment pattern analysis of tandem mass spectrometry (MS/MS) has long been used for the structural characterization of metabolites. The construction of a plant-specific MS/MS data resource and database will enable complex phytochemical structures to be narrowed down to candidate structures. Therefore, a web-based database of MS/MS data pertaining to phytochemicals was developed and named ReSpect (RIKEN tandem mass spectral database). Of the 3595 metabolites in ReSpect, 76% were derived from 163 literature reports, whereas the rest was obtained from authentic standards. As a main web application of ReSpect, a fragment search was established based on only the m/z values of query data and records. The confidence levels of the annotations were managed using the MS/MS fragmentation association rule, which is an algorithm for discovering common fragmentations in MS/MS data. Using this data resource and database, a case study was conducted for the annotation of untargeted MS/MS data that were selected after quantitative trait locus analysis of the accessions (Gifu and Miyakojima) of a model legume Lotus japonicus. In the case study, unknown metabolites were successfully narrowed down to putative structures in the website.

Dissection of genotype–phenotype associations in rice grains using metabolome quantitative trait loci analysis

A comprehensive and large-scale metabolome quantitative trait loci (mQTL) analysis was performed to investigate the genetic backgrounds associated with metabolic phenotypes in rice grains. The metabolome dataset consisted of 759 metabolite signals obtained from the grains of 85 lines of rice (Oryza sativa, Sasanishiki × Habataki back-crossed inbred lines). Metabolome analysis was performed using four mass spectrometry pipelines to enhance detection of different classes of metabolites. This mQTL analysis of a wide range of metabolites highlighted an uneven distribution of 802 mQTLs on the rice genome, as well as different modes of metabolic trait (m-trait) control among various types of metabolites. The levels of most metabolites within rice grains were highly sensitive to environmental factors, but only weakly associated with mQTLs. Coordinated control was observed for several groups of metabolites, such as amino acids linked to the mQTL hotspot on chromosome 3. For flavonoids, m-trait variation among the experimental lines was tightly governed by genetic factors that alter the glycosylation of flavones. Many loci affecting levels of metabolites were detected by QTL analysis, and plausible gene candidates were evaluated by in silico analysis. Several mQTLs profoundly influenced metabolite levels, providing insight into the control of rice metabolism. The genomic region and genes potentially responsible for the biosynthesis of apigenin-6,8-di-C-α-l-arabinoside are presented as an example of a critical mQTL identified by the analysis.

Metabolomics-oriented isolation and structure elucidation of 37 compounds including two anthocyanins from Arabidopsis thaliana.

In order to conduct metabolomic studies in a model plant for genome research, such as Arabidopsis thaliana (Arabidopsis), it is a prerequisite to obtain structural information for the isolated metabolites from the plant of interest. In this study, we isolated metabolites of Arabidopsis in a relatively non-targeted way, aiming at the construction of metabolite standards and chemotaxonomic comparison. Anthocyanins (5 and 7) called A8 and A10 were isolated and their structures were elucidated as cyanidin 3-O-[2-O-(beta-D-xylopyranosyl)-6-O-(4-O-(beta-D-glucopyranosyl)-E-p-coumaroyl)-beta-D-glucopyranoside]-5-O-[6-O-(malonyl)-beta-D-glucopyranoside] and cyanidin 3-O-[2-O-(2-O-(E-sinapoyl)-beta-D-xylopyranosyl)-6-O-(4-O-(beta-D-glucopyranosyl)-E-p-coumaroyl)-beta-D-glucopyranoside]-5-O-[beta-D-glucopyranoside] from analyses of 1D NMR, 2D NMR ((1)H NMR, NOE, (13)C NMR, HMBC and HMQC), HRFABMS, FT-ESI-MS and GC-TOF-MS data. In addition, 35 known compounds, including six anthocyanins, eight flavonols, one nucleoside, one indole glucosinolate, four phenylpropanoids and a derivative, together with three indoles, one carotenoid, one apocarotenoid, three galactolipids, two chlorophyll derivatives, one steroid, one hydrocarbon, and two dicarboxylic acids, were also isolated and identified from their spectroscopic data.

Two glycosyltransferases involved in anthocyanin modification delineated by transcriptome independent component analysis in Arabidopsis thaliana

To identify candidate genes involved in Arabidopsis flavonoid biosynthesis, we applied transcriptome coexpression analysis and independent component analyses with 1388 microarray data from publicly available databases. Two glycosyltransferases, UGT79B1 and UGT84A2 were found to cluster with anthocyanin biosynthetic genes. Anthocyanin was drastically reduced in ugt79b1 knockout mutants. Recombinant UGT79B1 protein converted cyanidin 3-O-glucoside to cyanidin 3-O-xylosyl(1→2)glucoside. UGT79B1 recognized 3-O-glucosylated anthocyanidins/flavonols and uridine diphosphate (UDP)-xylose, but not 3,5-O-diglucosylated anthocyanidins, indicating that UGT79B1 encodes anthocyanin 3-O-glucoside: 2′′-O-xylosyltransferase. UGT84A2 is known to encode sinapic acid: UDP-glucosyltransferase. In ugt84a2 knockout mutants, a major sinapoylated anthocyanin was drastically reduced. A comparison of anthocyanin profiles in ugt84a knockout mutants indicated that UGT84A2 plays a major role in sinapoylation of anthocyanin, and that other UGT84As contribute the production of 1-O-sinapoylglucose to a lesser extent. These data suggest major routes from cyanidin 3-O-glucoside to the most highly modified cyanidin in the potential intricate anthocyanin modification pathways in Arabidopsis.

Metabolome‐genome‐wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism

Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications.

Metabolomics for unknown plant metabolites

In this article we discuss current trends in the techniques available for plant metabolomics. Chemical assignment of unknown metabolites leads to understanding of biosynthetic mechanisms at the gene level for genome-sequenced plants. Metabolomics using mass spectrometry has achieved innovative results in phytochemical genomics for primary and secondary metabolism in the model plant Arabidopsis thaliana by using publicly and commercially available information and standard compounds. However, finding a consolidated analytical technique for elucidation of structural information (e.g., elemental composition and structure) remains challenging. Recently, hyphenated analytical techniques and computer-assisted structural analysis with high-throughput and high-accuracy have been developing. Metabolite-driven approaches using such technology will be of central importance in phytochemical genomics.

Combination of Liquid Chromatography–Fourier Transform Ion Cyclotron Resonance-Mass Spectrometry with 13C-Labeling for Chemical Assignment of Sulfur-Containing Metabolites in Onion Bulbs

Phytochemicals containing heteroatoms (N, O, S, and halogens) often have biological activities that are beneficial to humans. Although targeted profiling methods for such phytochemicals are expected to contribute to rapid chemical assignments, thus making phytochemical genomics and crop breeding much more efficient, there are few profiling methods for the metabolites. Here, as an ultrahigh performance approach, we propose a practical profiling method for S-containing metabolites (S-omics) using onions (Allium cepa) as a representative species and (12)C- and (13)C-based mass spectrometry (MS) and tandem mass spectrometry (MS/MS) analyses by liquid chromatography-Fourier transform ion cyclotron resonance-mass spectrometry (LC-FTICR-MS). Use of the ultrahigh quality data from FTICR-MS enabled simplifying the previous methods to determine specific elemental compositions. MS analysis with a resolution of >250,000 full width at half-maximum and a mass accuracy of <1 ppm can distinguish S-containing monoisotopic ions from other ions on the basis of the natural abundance of (32)S and (34)S and the mass differences among the S isotopes. Comprehensive peak picking using the theoretical mass difference (1.99579 Da) between (32)S-containing monoisotopic ions and their (34)S-substituted counterparts led to the assignment of 67 S-containing monoisotopic ions from the (12)C-based MS spectra, which contained 4693 chromatographic ions. The unambiguous elemental composition of 22 ions was identified through comparative analysis of the (12)C- and (13)C-based MS spectra. Finally, of these, six ions were found to be derived from S-alk(en)ylcysteine sulfoxides and glutathione derivatives. This S-atom-driven approach afforded an efficient chemical assignment of S-containing metabolites, suggesting its potential application for screening not only S but also other heteroatom-containing metabolites in MS-based metabolomics.