Raoul J. Bino

Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry

Untargeted metabolomics aims to gather information on as many metabolites as possible in biological systems by taking into account all information present in the data sets. Here we describe a detailed protocol for large-scale untargeted metabolomics of plant tissues, based on reversed phase liquid chromatography coupled to high-resolution mass spectrometry (LC-QTOF MS) of aqueous methanol extracts. Dedicated software, MetAlign, is used for automated baseline correction and alignment of all extracted mass peaks across all samples, producing detailed information on the relative abundance of thousands of mass signals representing hundreds of metabolites. Subsequent statistics and bioinformatics tools can be used to provide a detailed view on the differences and similarities between (groups of) samples or to link metabolomics data to other systems biology information, genetic markers and/or specific quality parameters. The complete procedure from metabolite extraction to assembly of a data matrix with aligned mass signal intensities takes about 6 days for 50 samples.

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.

A liquid chromatography-mass spectrometry-based metabolome database for tomato.

For the description of the metabolome of an organism, the development of common metabolite databases is of utmost importance. Here we present the Metabolome Tomato Database (MoTo DB), a metabolite database dedicated to liquid chromatography-mass spectrometry (LC-MS)- based metabolomics of tomato fruit (Solanum lycopersicum). A reproducible analytical approach consisting of reversed-phase LC coupled to quadrupole time-of-flight MS and photodiode array detection (PDA) was developed for large-scale detection and identification of mainly semipolar metabolites in plants and for the incorporation of the tomato fruit metabolite data into the MoTo DB. Chromatograms were processed using software tools for mass signal extraction and alignment, and intensity-dependent accurate mass calculation. The detected masses were assigned by matching their accurate mass signals with tomato compounds reported in literature and complemented, as much as possible, by PDA and MS/MS information, as well as by using reference compounds. Several novel compounds not previously reported for tomato fruit were identified in this manner and added to the database. The MoTo DB is available at http://appliedbioinformatics.wur.nl and contains all information so far assembled using this LC-PDA-quadrupole time-of-flight MS platform, including retention times, calculated accurate masses, PDA spectra, MS/MS fragments, and literature references. Unbiased metabolic profiling and comparison of peel and flesh tissues from tomato fruits validated the applicability of the MoTo DB, revealing that all flavonoids and α-tomatine were specifically present in the peel, while several other alkaloids and some particular phenylpropanoids were mainly present in the flesh tissue.

A Novel Approach for Nontargeted Data Analysis for Metabolomics. Large-Scale Profiling of Tomato Fruit Volatiles

To take full advantage of the power of functional genomics technologies and in particular those for metabolomics, both the analytical approach and the strategy chosen for data analysis need to be as unbiased and comprehensive as possible. Existing approaches to analyze metabolomic data still do not allow a fast and unbiased comparative analysis of the metabolic composition of the hundreds of genotypes that are often the target of modern investigations. We have now developed a novel strategy to analyze such metabolomic data. This approach consists of (1) full mass spectral alignment of gas chromatography (GC)-mass spectrometry (MS) metabolic profiles using the MetAlign software package, (2) followed by multivariate comparative analysis of metabolic phenotypes at the level of individual molecular fragments, and (3) multivariate mass spectral reconstruction, a method allowing metabolite discrimination, recognition, and identification. This approach has allowed a fast and unbiased comparative multivariate analysis of the volatile metabolite composition of ripe fruits of 94 tomato (Lycopersicon esculentum Mill.) genotypes, based on intensity patterns of >20,000 individual molecular fragments throughout 198 GC-MS datasets. Variation in metabolite composition, both between- and within-fruit types, was found and the discriminative metabolites were revealed. In the entire genotype set, a total of 322 different compounds could be distinguished using multivariate mass spectral reconstruction. A hierarchical cluster analysis of these metabolites resulted in clustering of structurally related metabolites derived from the same biochemical precursors. The approach chosen will further enhance the comprehensiveness of GC-MS-based metabolomics approaches and will therefore prove a useful addition to nontargeted functional genomics research.

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.

Plant Metabolomics: The Missing Link in Functional Genomics Strategies

After the establishment of technologies for high-throughput DNA sequencing (genomics), gene expression analysis (transcriptomics), and protein analysis (proteomics), the remaining functional genomics challenge is that of metabolomics . Metabolomics is the term coined for essentially comprehensive,

Gene Expression Programs during Brassica oleracea Seed Maturation, Osmopriming, and Germination Are Indicators of Progression of the Germination Process and the Stress Tolerance Level

During seed maturation and germination, major changes in physiological status, gene expression, and metabolic events take place. Using chlorophyll sorting, osmopriming, and different drying regimes, Brassica oleracea seed lots of different maturity, stress tolerance, and germination behavior were created. Through careful physiological analysis of these seed lots combined with gene expression analysis using a dedicated cDNA microarray, gene expression could be correlated to physiological processes that occurred within the seeds. In addition, gene expression was studied during early stages of seed germination, prior to radicle emergence, since very little detailed information of gene expression during this process is available. During seed maturation expression of many known seed maturation genes, such as late-embryogenesis abundant or storage-compound genes, was high. Notably, a small but distinct subgroup of the maturation genes was found to correlate to seed stress tolerance in osmoprimed and dried seeds. Expression of these genes rapidly declined during priming and/or germination in water. The majority of the genes on the microarray were up-regulated during osmopriming and during germination on water, confirming the hypothesis that during osmopriming, germination-related processes are initiated. Finally, a large group of genes was up-regulated during germination on water, but not during osmopriming. These represent genes that are specific to germination in water. Germination-related gene expression was found to be partially reversible by physiological treatments such as slow drying of osmoprimed seeds. This correlated to the ability of seeds to withstand stress.

Carotenoid and Fatty Acid Metabolism in Light-Stressed Dunaliella salina

β‐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, β‐carotene production commenced immediately. The first 4 h after induction were marked by constant intracellular levels of β‐carotene (2.2 g LCV−1), which resulted from identical increases in the production rates of cell volume and β‐carotene. Following this initial phase, β‐carotene productivity continued to increase while the cell volume productivity dropped. As a result, the intracellular β‐carotene concentration increased reaching a maximum of 17 g LCV−1 after 2 days of light stress. Approximately 1 day before that, the maximum β‐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 β‐carotene production facility, indicating a vast potential for improvement. Furthermore, by studying the light‐induced changes in both β‐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 β‐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. Biotechnol. Bioeng. 2010;106: 638–648.

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.

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.