The genetics of plant metabolism.

Variation for metabolite composition and content is often observed in plants. However, it is poorly understood to what extent this variation has a genetic basis. Here, we describe the genetic analysis of natural variation in the metabolite composition in Arabidopsis thaliana. Instead of focusing on specific metabolites, we have applied empirical untargeted metabolomics using liquid chromatography-time of flight mass spectrometry (LC-QTOF MS). This uncovered many qualitative and quantitative differences in metabolite accumulation between A. thaliana accessions. Only 13.4% of the mass peaks were detected in all 14 accessions analyzed. Quantitative trait locus (QTL) analysis of more than 2,000 mass peaks, detected in a recombinant inbred line (RIL) population derived from the two most divergent accessions, enabled the identification of QTLs for about 75% of the mass signals. More than one-third of the signals were not detected in either parent, indicating the large potential for modification of metabolic composition through classical breeding.

In silico prediction and automatic LC-MS(n) annotation of green tea metabolites in urine.

The colonic breakdown and human biotransformation of small molecules present in food can give rise to a large variety of potentially bioactive metabolites in the human body. However, the absence of reference data for many of these components limits their identification in complex biological samples, such as plasma and urine. We present an in silico workflow for automatic chemical annotation of metabolite profiling data from liquid chromatography coupled with multistage accurate mass spectrometry (LC-MS(n)), which we used to systematically screen for the presence of tea-derived metabolites in human urine samples after green tea consumption. Reaction rules for intestinal degradation and human biotransformation were systematically applied to chemical structures of 75 green tea components, resulting in a virtual library of 27,245 potential metabolites. All matching precursor ions in the urine LC-MS(n) data sets, as well as the corresponding fragment ions, were automatically annotated by in silico generated (sub)structures. The results were evaluated based on 74 previously identified urinary metabolites and lead to the putative identification of 26 additional green tea-derived metabolites. A total of 77% of all annotated metabolites were not present in the Pubchem database, demonstrating the benefit of in silico metabolite prediction for the automatic annotation of yet unknown metabolites in LC-MS(n) data from nutritional metabolite profiling experiments.

Assessment of pleiotropic transcriptome perturbations in Arabidopsis engineered for indirect insect defence.

BACKGROUND: Molecular characterization is an essential step of risk/safety assessment of genetically modified (GM) crops. Holistic approaches for molecular characterization using omics platforms can be used to confirm the intended impact of the genetic engineering, but can also reveal the unintended changes at the omics level as a first assessment of potential risks. The potential of omics platforms for risk assessment of GM crops has rarely been used for this purpose because of the lack of a consensus reference and statistical methods to judge the significance or importance of the pleiotropic changes in GM plants. Here we propose a meta data analysis approach to the analysis of GM plants, by measuring the transcriptome distance to untransformed wild-types. RESULTS: In the statistical analysis of the transcriptome distance between GM and wild-type plants, values are compared with naturally occurring transcriptome distances in non-GM counterparts obtained from a database. Using this approach we show that the pleiotropic effect of genes involved in indirect insect defence traits is substantially equivalent to the variation in gene expression occurring naturally in Arabidopsis. CONCLUSION: Transcriptome distance is a useful screening method to obtain insight in the pleiotropic effects of genetic modification.

Automatic chemical structure annotation of an LC-MS(n) based metabolic profile from green tea.

Liquid chromatography coupled with multistage accurate mass spectrometry (LC-MS(n)) can generate comprehensive spectral information of metabolites in crude extracts. To support structural characterization of the many metabolites present in such complex samples, we present a novel method ( http://www.emetabolomics.org/magma ) to automatically process and annotate the LC-MS(n) data sets on the basis of candidate molecules from chemical databases, such as PubChem or the Human Metabolite Database. Multistage MS(n) spectral data is automatically annotated with hierarchical trees of in silico generated substructures of candidate molecules to explain the observed fragment ions and alternative candidates are ranked on the basis of the calculated matching score. We tested this method on an untargeted LC-MS(n) (n ≤ 3) data set of a green tea extract, generated on an LC-LTQ/Orbitrap hybrid MS system. For the 623 spectral trees obtained in a single LC-MS(n) run, a total of 116,240 candidate molecules with monoisotopic masses matching within 5 ppm mass accuracy were retrieved from the PubChem database, ranging from 4 to 1327 candidates per molecular ion. The matching scores were used to rank the candidate molecules for each LC-MS(n) component. The median and third quartile fractional ranks for 85 previously identified tea compounds were 3.5 and 7.5, respectively. The substructure annotations and rankings provided detailed structural information of the detected components, beyond annotation with elemental formula only. Twenty-four additional components were putatively identified by expert interpretation of the automatically annotated data set, illustrating the potential to support systematic and untargeted metabolite identification.

Secondary metabolites of Capsicum species and their importance in the human diet.

The genus Capsicum (pepper) comprises a large number of wild and cultivated species. The plants are grown all over the world, primarily in tropical and subtropical countries. The fruits are an excellent source of health-related compounds, such as ascorbic acid (vitamin C), carotenoids (provitamin A), tocopherols (vitamin E), flavonoids, and capsaicinoids. Pepper fruits have been used for fresh and cooked consumption, as well as for medicinal purposes, such as treatment of asthma, coughs, sore throats, and toothache. Depending on its uses, there are several main characters important for product quality; pungency, bright attractive colors, highly concentrated extracts, and a small number of seeds are the main characters on which quality is based and priced. Herein, a general overview of biochemical composition, medical properties of these compounds, and characteristics of quality attributes of pepper fruits is presented.

Structural elucidation and quantification of phenolic conjugates present in human urine after tea intake.

In dietary polyphenol exposure studies, annotation and identification of urinary metabolites present at low (micromolar) concentrations are major obstacles. To determine the biological activity of specific components, it is necessary to have the correct structures and the quantification of the polyphenol-derived conjugates present in the human body. We present a procedure for identification and quantification of metabolites and conjugates excreted in human urine after single bolus intake of black or green tea. A combination of a solid-phase extraction (SPE) preparation step and two high pressure liquid chromatography (HPLC)-based analytical platforms was used, namely, accurate mass fragmentation (HPLC-FTMS(n)) and mass-guided SPE-trapping of selected compounds for nuclear magnetic resonance spectroscopy (NMR) measurements (HPLC-TOFMS-SPE-NMR). HPLC-FTMS(n) analysis led to the annotation of 138 urinary metabolites, including 48 valerolactone and valeric acid conjugates. By combining the results from MS(n) fragmentation with the one-dimensional (1D)-(1)H NMR spectra of HPLC-TOFMS-SPE-trapped compounds, we elucidated the structures of 36 phenolic conjugates, including the glucuronides of 3',4'-di- and 3',4',5'-trihydroxyphenyl-γ-valerolactone, three urolithin glucuronides, and indole-3-acetic acid glucuronide. We also obtained 26 h-quantitative excretion profiles for specific valerolactone conjugates. The combination of the HPLC-FTMS(n) and HPLC-TOFMS-SPE-NMR platforms results in the efficient identification and quantification of less abundant phenolic conjugates down to nanomoles of trapped amounts of metabolite corresponding to micromolar metabolite concentrations in urine.

Polyphenol identification based on systematic and robust high-resolution accurate mass spectrometry fragmentation.

High-mass resolution multi-stage mass spectrometry (MS(n)) fragmentation was tested for differentiation and identification of metabolites, using a series of 121 polyphenolic molecules. The MS(n) fragmentation approach is based on the systematic breakdown of compounds, forming a so-called spectral tree. A chip-based nanoelectrospray ionization source was used combined with an ion-trap, providing reproducible fragmentation, and accurate mass read-out in an Orbitrap Fourier transform (FT) MS enabling rapid assignment of elemental formulas to the molecular ions and all fragment ions derived thereof. The used protocol resulted in reproducible MS(n) fragmentation trees up to MS(5). Obtained results were stable over a 5 month time period, a concentration change of 100-fold, and small changes in normalized collision energy, which is key to metabolite annotation and helpful in structure and substructure elucidation. Differences in the hydroxylation and methoxylation patterns of polyphenolic core structures were found to be reflected by the differential fragmentation of the entire molecule, while variation in a glycosylation site displayed reproducible differences in the relative intensities of fragments originating from the same aglycone fragment ion. Accurate MS(n)-based spectral tree data are therefore a powerful tool to distinguish metabolites with similar elemental formula, thereby assisting compound identification in complex biological samples such as crude plant extracts.

A strategy for fast structural elucidation of metabolites in small volume plant extracts using automated MS-guided LC-MS-SPE-NMR.

In many metabolomics studies, metabolite identification by mass spectrometry (MS) often is hampered by the lack of good reference compounds, and hence, NMR information is essential for structural elucidation, especially for the very large group of secondary metabolites. The classical approach for compound identification is to perform time-consuming and laborious HPLC fractionations and purifications, before (re)dissolving the molecules in deuterated solvents for NMR measurements. Hence, a more direct and easy purification protocol would save time and efforts. Here, we propose an automated MS-guided HPLC-MS-solid phase extraction-NMR approach, which was used to fully characterize flavonoid structures present in crude tomato plant extracts. NMR spectra of plant metabolites, automatically trapped and purified from LC-MS traces, were successfully obtained, leading to the structural elucidation of the metabolites. The MS-based trapping enabled a direct link between the mass signals and NMR peaks derived from the selected LC-MS peaks, thereby decreasing the time needed for elucidation of the metabolite structures. In addition, automated 1H NMR spectrum fitting further speeded up the candidate rejection process. Our approach facilitates the more rapid unraveling of yet unknown metabolite structures and can therefore make untargeted metabolomics approaches more powerful.

Carotenoid and fatty acid metabolism in light-stressed Dunaliella salina.

beta-Carotene is overproduced in the alga Dunaliella salina in response to high light intensities. We have studied the effects of a sudden light increase on carotenoid and fatty acid metabolism using a flat panel photobioreactor that was run in turbidostat mode to ensure a constant light regime throughout the experiments. Upon the shift to an increased light intensity, beta-carotene production commenced immediately. The first 4 h after induction were marked by constant intracellular levels of beta-carotene (2.2 g LCV(-1)), which resulted from identical increases in the production rates of cell volume and beta-carotene. Following this initial phase, beta-carotene productivity continued to increase while the cell volume productivity dropped. As a result, the intracellular beta-carotene concentration increased reaching a maximum of 17 g LCV(-1) after 2 days of light stress. Approximately 1 day before that, the maximum beta-carotene productivity of 30 pg cell(-1) day(-1) (equivalent to 37 mg LRV(-1) day(-1)) was obtained, which was about one order of magnitude larger than the average productivity reported for a commercial beta-carotene production facility, indicating a vast potential for improvement. Furthermore, by studying the light-induced changes in both beta-carotene and fatty acid metabolism, it appeared that carotenoid overproduction was associated with oil globule formation and a decrease in the degree of fatty acid unsaturation. Our results indicate that cellular beta-carotene accumulation in D. salina correlates with accumulation of specific fatty acid species (C16:0 and C18:1) rather than with total fatty acid content.

Exploring and exploiting carotenoid accumulation in Dunaliella salina for cell-factory applications.

The unicellular alga Dunaliella salina is the most interesting cell factory for the commercial production of beta-carotene because this species accumulates carotenoids to high concentrations. Nevertheless, little is known about the underlying mechanisms of carotenoid accumulation. Here, we review the regulatory mechanisms involved in beta-carotene overproduction in D. salina. The potential roles of reactive oxygen species and the plastoquinone redox state in signal sensing are discussed, together with available evidence on transcriptional and (post)translational regulation. Moreover, future directions that might further our knowledge in this area are given. Ultimately, a better understanding of the regulatory mechanisms involved in beta-carotene overproduction will facilitate innovative production of specific carotenoids and other products in D. salina and in related organisms.

Tissue specialization at the metabolite level is perceived during the development of tomato fruit.

Fruit maturation and tissue differentiation are important topics in plant physiology. These biological phenomena are accompanied by specific alterations in the biological system, such as differences in the type and concentration of metabolites. The secondary metabolism of tomato (Solanum lycopersicum) fruit was monitored by using liquid chromatography (LC) coupled to photo-diode array (PDA) detection, fluorescence detection (FD), and mass spectrometry (MS). Through this integrated approach different classes of compounds were analysed: carotenoids, xanthophylls, chlorophylls, tocopherols, ascorbic acid, flavonoids, phenolic acids, glycoalkaloids, saponins, and other glycosylated derivatives. Related metabolite profiles of peel and flesh were found between several commercial tomato cultivars indicating similar metabolite trends despite the genetic background. For a single tomato cultivar, metabolite profiles of different fruit tissues (vascular attachment region, columella and placenta, epidermis, pericarp, and jelly parenchyma) were examined at the green, breaker, turning, pink, and red stages of fruit development. Unrelated to the chemical nature of the metabolites, behavioural patterns could be assigned to specific ripening stages or tissues. These findings suggest spatio-temporal specificity in the accumulation of endogenous metabolites from tomato fruit.

A proposed framework for the description of plant metabolomics experiments and their results.

The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.

A comparative study on the effect of algal and fish oil on viability and cell proliferation of Caco-2 cells.

Polyunsaturated fatty acid (PUFA) rich micro-algal oil was tested in vitro and compared with fish oil for antiproliferative properties on cancer cells in vitro. Oils derived from Crypthecodinium cohnii, Schizochytrium sp. and Nitzschia laevis, three commercial algal oil capsules, and menhaden fish oil were used in cell viability and proliferation tests with human colon adenocarcinoma Caco-2 cells. With these tests no difference was found between algal oil and fish oil. The nonhydrolysed algal oils and fish oil showed a much lower toxic effect on cell viability, and cell proliferation in Caco-2 cells than the hydrolysed oils and the free fatty acids (FFAs). Eicosapentaenoic acid (EPA; C20:5n-3) and docosahexaenoic acid (DHA; C22:6n-3) were used as samples for comparison with the tested hydrolysed and nonhydrolysed oils. The hydrolysed samples showed comparative toxicity as the free fatty acids and no difference between algal and fish oil. Oxidative stress was shown to play a role in the antiproliferative properties of EPA and DHA, as alpha-tocopherol could partially reverse the EPA/DHA-induced effects. The results of the present study support a similar mode of action of algal oil and fish oil on cancer cells in vitro, in spite of their different PUFA content.

Genetic mapping of semi-polar metabolites in pepper fruits (Capsicum sp.): towards unravelling the molecular regulation of flavonoid quantitative trait loci.

Untargeted LCMS profiling of semi-polar metabolites followed by metabolite quantitative trait locus (mQTL) analysis was performed in ripe pepper fruits of 113 F2 plants derived from a cross between Capsicum annuum AC1979 (no. 19) and Capsicum chinense No. 4661 Selection (no. 18). The parental accessions were selected based on their variation in fruit morphological characteristics and fruit content of some target phytonutrients. Clear segregation of fruit colour and fruit metabolite profiles was observed in the F2 population. The F2 plants formed three clusters based on their metabolite profiles. Of the total of 542 metabolites, 52 could be annotated, including a range of flavonoids, such as flavone C-glycosides, flavonol O-glycosides and naringenin chalcone, as well as several phenylpropanoids, a capsaicin analogue, fatty acid derivatives and amino acid derivatives. Interval mapping revealed 279 mQTLs in total. Two mQTL hotspots were found on chromosome 9. These two chromosomal regions regulated the relative levels of 35 and 103 metabolites, respectively. Analysis also revealed an mQTL for a capsaicin analogue, located on chromosome 7. Confirmation of flavonoid mQTLs using a set of six flavonoid candidate gene markers and their corresponding expression data (expression QTLs) indicated the Ca-MYB12 transcription factor gene on chromosome 1 and the gene encoding flavone synthase (FS-2) on chromosome 6 as likely causative genes determining the variation in naringenin chalcone and flavone C-glycosides, respectively, in this population. The combination of large-scale metabolite profiling and QTL analysis provided valuable insight into the genomic regions and genes important for the production of (secondary) metabolites in pepper fruit. This will impact breeding strategies aimed at optimising the content of specific metabolites in pepper fruit.

Metabolomics and molecular marker analysis to explore pepper (Capsicum sp.) biodiversity.

An overview of the metabolic diversity in ripe fruits of a collection of 32 diverse pepper (Capsicum sp.) accessions was obtained by measuring the composition of both semi-polar and volatile metabolites in fruit pericarp, using untargeted LC-MS and headspace GC-MS platforms, respectively. Accessions represented C. annuum, C. chinense, C. frutescens and C. baccatum species, which were selected based on variation in morphological characters, pungency and geographic origin. Genotypic analysis using AFLP markers confirmed the phylogenetic clustering of accessions according to Capsicum species and separated C. baccatum from the C. annuum-C. chinense-C. frutescens complex. Species-specific clustering was also observed when accessions were grouped based on their semi-polar metabolite profiles. In total 88 semi-polar metabolites could be putatively identified. A large proportion of these metabolites represented conjugates of the main pepper flavonoids (quercetin, apigenin and luteolin) decorated with different sugar groups at different positions along the aglycone. In addition, a large group of acyclic diterpenoid glycosides, called capsianosides, was found to be highly abundant in all C. annuum genotypes. In contrast to the variation in semi-polar metabolites, the variation in volatiles corresponded well to the differences in pungency between the accessions. This was particularly true for branched fatty acid esters present in pungent accessions, which may reflect the activity through the acyl branch of the metabolic pathway leading to capsaicinoids. In addition, large genetic variation was observed for many well-established pepper aroma compounds. These profiling data can be used in breeding programs aimed at improving metabolite-based quality traits such as flavour and health-related metabolites in pepper fruits. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-012-0432-6) contains supplementary material, which is available to authorized users.

Carotenoid and fatty acid metabolism in nitrogen-starved Dunaliella salina, a unicellular green microalga.

Nitrogen availability and light intensity affect ß-carotene overproduction in the green alga Dunaliella salina. Following a previous study on high-light stress, we here report on the effect of nitrogen depletion on the growth characteristics and ß-carotene as well as fatty acid metabolism of D. salina under a constant light regime in a turbidostat. Upon nitrogen depletion, the biomass yield on absorbed light approximately doubled, due to a transient increase in cell division rate, swelling of the cells and a linear increase of the density of the cells. Simultaneously, ß-carotene started to accumulate up to a final intracellular concentration of 14 mg LCV⁻¹ (i.e. 2.7% of AFDW). This ß-carotene production accounted for 6% of the increased density of the cells, indicating that other biochemical constituents accumulated as well. Since D. salina accumulates ß-carotene in lipid globules, we also determined the fatty acid content and composition of D. salina. The intracellular concentration of the total fatty acid pool did not change significantly during nitrogen starvation, indicating that ß-carotene and total fatty acid accumulation were unrelated, similar to what was found previously for high-light treated cells. However, for both high-light and nitrogen stress, ß-carotene accumulation negatively correlated with the degree of unsaturation of the total fatty acid pool and, within the individual fatty acids, correlated positively with oleic acid biosynthesis, suggesting that oleic acid may be a key component of the lipid-globule-localized triacylglycerols and thereby in ß-carotene accumulation.

Characterization of the natural variation in Arabidopsis thaliana metabolome by the analysis of metabolic distance.

Metabolite fingerprinting is widely used to unravel the chemical characteristics of biological samples. Multivariate data analysis and other statistical tools are subsequently used to analyze and visualize the plasticity of the metabolome and/or the relationship between those samples. However, there are limitations to these approaches for example because of the multi-dimensionality of the data that makes interpretation of the data obtained from untargeted analysis almost impossible for an average human being. These limitations make the biological information that is of prime importance in untargeted studies be partially exploited. Even in the case of full exploitation, current methods for relationship elucidation focus mainly on between groups variation and differences. Therefore, a measure that is capable of exploiting both between- and within-group biological variation would be of great value. Here, we examined the natural variation in the metabolome of nine Arabidopsis thaliana accessions grown under various environmental conditions and established a measure for the metabolic distance between accessions and across environments. This data analysis approach shows that there is just a minor correlation between genetic and metabolic diversity of the nine accessions. On the other hand, it delivers so far in Arabidopsis unexplored chemical information and is shown to be biologically relevant for resistance studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0375-3) contains supplementary material, which is available to authorized users.

Structural annotation and elucidation of conjugated phenolic compounds in black, green, and white tea extracts.

Advanced analytical approaches consisting of both LC-LTQ-Orbitrap Fourier transformed (FT)-MS and LC-time-of-flight-(TOF)-MS coupled to solid-phase extraction (SPE) NMR were used to obtain more insight into the complex phenolic composition of tea. On the basis of the combined structural information from (i) accurate mass fragmentation spectra, derived by using LC-Orbitrap FTMS(n), and (ii) proton NMR spectra, derived after LC-TOFMS triggered SPE trapping of selected compounds, 177 phenolic compounds were annotated. Most of these phenolics were glycosylated and acetylated derivatives of flavan-3-ols and flavonols. Principal component analysis based on the relative abundance of the annotated phenolic compounds in 17 commercially available black, green, and white tea products separated the black teas from the green and white teas, with epicatechin-3,5-di-O-gallate and prodelphinidin-O-gallate being among the main discriminators. The results indicate that the combined use of LC-LTQ-Orbitrap FTMS and LC-TOFMS-SPE-NMR leads to a more comprehensive metabolite description and comparison of tea and other plant samples.

Metabolite biodiversity in pepper (Capsicum) fruits of thirty-two diverse accessions: variation in health-related compounds and implications for breeding.

A comprehensive study on morphology and biochemical compounds of 32 Capsicum spp. accessions has been performed. Accessions represented four pepper species, Capsicum annuum, Capsicum frutescens, Capsicum chinense and Capsicum baccatum which were selected by their variation in morphological characters such as fruit color, pungency and origin. Major metabolites in fruits of pepper, carotenoids, capsaicinoids (pungency), flavonoid glycosides, and vitamins C and E were analyzed and quantified by high performance liquid chromatography. The results showed that composition and level of metabolites in fruits varied greatly between accessions and was independent of species and geographical location. Fruit color was determined by the accumulation of specific carotenoids leading to salmon, yellow, orange, red and brown colored fruits. Levels of both O- and C-glycosides of quercetin, luteolin and apigenin varied strongly between accessions. All non-pungent accessions were devoid of capsaicins, whereas capsaicinoid levels ranged from 0.07 up to 80 mg/100g fr. wt. in fruit pericarp. In general, pungent accessions accumulated the highest capsaicinoid levels in placenta plus seed tissue compared to pericarp. The non-pungent capsaicinoid analogs, capsiates, could be detected at low levels in some pungent accessions. All accessions accumulated high levels of vitamin C, up to 200 mg/100g fr. wt. The highest vitamin E concentration found was 16 mg/100g fr. wt. Based on these metabolic data, five accessions were selected for further metabolic and molecular analysis, in order to isolate key genes involved in the production of these compounds and to assist future breeding programs aimed at optimizing the levels of health-related compounds in pepper fruit.