Metabolome variability in crop plant species--when, where, how much and so what?

Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

Multi-omic characterisation as a tool to improve knowledge, valorisation and conservation of wild fruit genetic resources: the case of Arbutus unedo L

The valorisation and conservation of plant genetic resources (PGRs) and wild fruit PGRs are critical to ensure the maintenance of genetic and cultural heritage and to promote new perspectives on resource use. New strategies to characterize PGRs are needed, and the omics approach can provide information that is still largely unknown. The Strawberry tree (Arbutus unedo L.) is an underutilized, drought and fire-resistant species distributed in the Mediterranean area and its berries have large ethnobotanical use. Although their phenolic profile and antioxidant capacity are known, they are not well characterised, particularly from a proteomic perspective. The aim of this work is the characterisation of two ecotypes of A. unedo (Campania and Sicily) from a molecular viewpoint to valorise and encourage the preservation of this wild fruit. Samples were collected from two different geographical areas to assess whether different geographical conditions could influence the characteristics of leaves and fruits at the three stages of ripening (green, veraison, red). Proteomic analysis identified 904 proteins, of which 122 showed significance along the ripening. Some of these differentially abundant proteins, such as chalcone synthase, show a marked increase during ripening. The protein functional classes with the highest representation are involved in protein and amino acid metabolism, glycolysis and in secondary metabolism. From a proteomic perspective, there are no differences between the fruits from the two regions compared by the ripening stage. However, the pedoclimatic metabolic imprinting allowed the observation of good diversity in the metabolomic profiles between the two ecotypes, especially for anthocyanins, 4 times more abundant in the Sicilian veraisoned fruit than in the Campania one, and catechins, with double the abundance in the Campania ecotype compared to the Sicilian ecotype in the green phase, but more abundant (3x) in the Sicilian veraisoned fruit. Phenolic compounds show a 20% greater abundance in the Campania green arbutus fruit than in the Sicilian one, values that then equalise as ripening progresses. Multi-omic characterisation enhanced the knowledge on a wild fruit plant species which shows specific adaptations and responses to the environment to be considered when addressing the issue of local agrobiodiversity.

Computational prediction of plant metabolic pathways

Uncovering genes encoding enzymes responsible for the biosynthesis of diverse plant metabolites is essential for metabolic engineering and production of plant metabolite-derived medicine. With the availability of multi-omics data for an ever-increasing number of plant species and the development of computational approaches, the metabolic pathways of many important plant compounds can be predicted, complementing a more traditional genetic and/or biochemical approach. Here, we summarize recent progress in predicting plant metabolic pathways using genome, transcriptome, proteome, interactome, and/or metabolome data, and the utility of integrating these data with machine learning to further improve metabolic pathway predictions.

Secondary Metabolic Profile as a Tool for Distinction and Characterization of Cultivars of Black Pepper (Piper nigrum L.) Cultivated in Pará State, Brazil

This study evaluated the chemical compositions of the leaves and fruits of eight black pepper cultivars cultivated in Pará State (Amazon, Brazil). Hydrodistillation and gas chromatography-mass spectrometry were employed to extract and analyze the volatile compounds, respectively. Sesquiterpene hydrocarbons were predominant (58.5-90.9%) in the cultivars "Cingapura", "Equador", "Guajarina", "Iaçará", and "Kottanadan", and "Bragantina", "Clonada", and "Uthirankota" displayed oxygenated sesquiterpenoids (50.6-75.0%). The multivariate statistical analysis applied using volatile composition grouped the samples into four groups: γ-Elemene, curzerene, and δ-elemene ("Equador"/"Guajarina", I); δ-elemene ("Iaçará"/"Kottanadan"/"Cingapura", II); elemol ("Clonada"/"Uthirankota", III) and α-muurolol, bicyclogermacrene, and cubebol ("Bragantina", IV). The major compounds in all fruit samples were monoterpene hydrocarbons such as α-pinene, β-pinene, and limonene. Among the cultivar leaves, phenolics content (44.75-140.53 mg GAE·g^-1 FW), the enzymatic activity of phenylalanine-ammonia lyase (20.19-57.22 µU·mL^-1), and carotenoids (0.21-2.31 µg·mL^-1) displayed significant variations. Due to black pepper's susceptibility to Fusarium infection, a molecular docking analysis was carried out on Fusarium protein targets using each cultivar's volatile components. F. oxysporum endoglucanase was identified as the preferential protein target of the compounds. These results can be used to identify chemical markers related to the susceptibility degree of black pepper cultivars to plant diseases prevalent in Pará State.

Metabolomic Markers for the Early Selection of Coffea canephora Plants with Desirable Cup Quality Traits

Genetic improvement of coffee plants represents a great challenge for breeders. Conventional breeding takes a too long time for responding timely to market demands, climatic variations and new biological threads. The correlation of genetic markers with the plant phenotype and final product quality is usually poor. Additionally, the creation and use of genetically modified organisms (GMOs) are often legally restricted and rejected by customers that demand natural products. Therefore, we developed a non-targeted metabolomics approach to accelerate conventional breeding. Our main idea was to identify highly heritable metabolites in Coffea canephora seedlings, which are linked to coffee cup quality. We employed a maternal half-sibs approach to estimate the metabolites heritability in open-pollinated plants in both leaves and fruits at an early plant development stage. We evaluated the cup quality of roasted beans and correlated highly heritable metabolites with sensory quality traits of the coffee beverage. Our results provide new insights about the heritability of metabolites of C. canephora plants. Furthermore, we found strong correlations between highly heritable metabolites and sensory traits of coffee beverage. We revealed metabolites that serve as predictive metabolite markers at an early development stage of coffee plants. Informed decisions can be made on plants of six months old, compared to 3.5 to 5 years using conventional selection methods. The metabolome-wide association study (MWAS) drastically accelerates the selection of C. canephora plants with desirable characteristics and represents a novel approach for the focused breeding of crops.

Contribution of Untargeted Metabolomics for Future Assessment of Biotech Crops

The nutritional value and safety of food crops are ultimately determined by their chemical composition. Recent developments in the field of metabolomics have made it possible to characterize the metabolic profile of crops in a comprehensive and high-throughput manner. Here, we propose that state-of-the-art untargeted metabolomics technology should be leveraged for safety assessment of new crop products. We suggest generally applicable experimental design principles that facilitate the efficient and rigorous identification of both intended and unintended metabolic alterations associated with a newly engineered trait. Our proposition could contribute to increased transparency of the safety assessment process for new biotech crops.

Secondary Metabolic Profiles of Two Cultivars of Piper nigrum (Black Pepper) Resulting from Infection by Fusarium solani f. sp. piperis

Bragantina and Cingapura are the main black pepper (Piper nigrum L.) cultivars and the Pará state is the largest producer in Brazil with about 90% of national production, representing the third largest production in the world. The infection of Fusarium solani f. sp. piperis, the causal agent of Fusarium disease in black pepper, was monitored on the cultivars Bragantina (susceptible) and Cingapura (tolerant), during 45 days’ post infection (dpi). Gas Chromatography-Mass spectrometry (GC-MS) analysis of the volatile concentrates of both cultivars showed that the Bragantina responded with the production of higher contents of α-bisabolol at 21 dpi and a decrease of elemol, mostly at 30 dpi; while Cingapura displayed an decrease of δ-elemene production, except at 15 dpi. The phenolic content determined by the Folin Ciocalteu method showed an increase in the leaves of plants inoculated at 7 dpi (Bragantina) and 7–15 dpi (Cingapura); in the roots, the infection caused a phenolic content decrease in Bragantina cultivar at 45 dpi and an increase in the Cingapura cultivar at 15, 30 and 45 dpi. High Performance Liquid Chromatography-Mass spectrometry (HPLC-MS) analysis of the root extracts showed a qualitative variation of alkamides during infection. The results indicated that there is a possible relationship between secondary metabolites and tolerance against phytopathogens.

Comparative Proteomic and Nutritional Composition Analysis of Independent Transgenic Pigeon Pea Seeds Harboring cry1AcF and cry2Aa Genes and Their Nontransgenic Counterparts

Safety assessment of genetically modified plants is an important aspect prior to deregulation. Demonstration of substantial equivalence of the transgenics compared to their nontransgenic counterparts can be performed using different techniques at various molecular levels. The present study is a first-ever comprehensive evaluation of pigeon pea transgenics harboring two independent cry genes, cry2Aa and cry1AcF. The absence of unintended effects in the transgenic seed components was demonstrated by proteome and nutritional composition profiling. Analysis revealed that no significant differences were found in the various nutritional compositional analyses performed. Additionally, 2-DGE-based proteome analysis of the transgenic and nontransgenic seed protein revealed that there were no major changes in the protein profile, although a minor fold change in the expression of a few proteins was observed. Furthermore, the study also demonstrated that neither the integration of T-DNA nor the expression of the cry genes resulted in the production of unintended effects in the form of new toxins or allergens.

Accumulation of Carotenoids and Metabolic Profiling in Different Cultivars of Tagetes Flowers

Species of Tagetes, which belong to the family Asteraceae show different characteristics including, bloom size, shape, and color; plant size; and leaf shape. In this study, we determined the differences in primary metabolites and carotenoid yields among six cultivars from two Tagetes species, T. erecta and T. patula. In total, we detected seven carotenoids in the examined cultivars: violaxanthin, lutein, zeaxanthin, α-carotene, β-carotene, 9-cis-β-carotene, and 13-cis-β-carotene. In all the cultivars, lutein was the most abundant carotenoid. Furthermore, the contents of each carotenoid in flowers varied depending on the cultivar. Principal component analysis (PCA) facilitated metabolic discrimination between Tagetes cultivars, with the exception of Inca Yellow and Discovery Orange. Moreover, PCA and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) results provided a clear discrimination between T. erecta and T. patula. Primary metabolites, including xylose, citric acid, valine, glycine, and galactose were the main components facilitating separation of the species. Positive relationships were apparent between carbon-rich metabolites, including those of the TCA cycle and sugar metabolism, and carotenoids.

Comparative Metabolome Profile between Tobacco and Soybean Grown under Water-Stressed Conditions

Understanding how plants respond to water deficit is important in order to develop crops tolerant to drought. In this study, we compare two large metabolomics datasets where we employed a nontargeted metabolomics approach to elucidate metabolic pathways perturbed by progressive dehydration in tobacco and soybean plants. The two datasets were created using the same strategy to create water deficit conditions and an identical metabolomics pipeline. Comparisons between the two datasets therefore reveal common responses between the two species, responses specific to one of the species, responses that occur in both root and leaf tissues, and responses that are specific to one tissue. Stomatal closure is the immediate response of the plant and this did not coincide with accumulation of abscisic acid. A total of 116 and 140 metabolites were observed in tobacco leaves and roots, respectively, while 241 and 207 were observed in soybean leaves and roots, respectively. Accumulation of metabolites is significantly correlated with the extent of dehydration in both species. Among the metabolites that show increases that are restricted to just one plant, 4-hydroxy-2-oxoglutaric acid (KHG) in tobacco roots and coumestrol in soybean roots show the highest tissue-specific accumulation. The comparisons of these two large nontargeted metabolomics datasets provide novel information and suggest that KHG will be a useful marker for drought stress for some members of Solanaceae and coumestrol for some legume species.

Analysis of plant leaf metabolites reveals no common response to insect herbivory by Pieris rapae in three related host-plant species

Studying the biochemical responses of different plant species to insect herbivory may help improve our understanding of the evolution of defensive metabolites found in host plants and their role in plant-herbivore interactions. Untargeted metabolic fingerprints measured as individual mass features were used to compare metabolite reactions in three Brassicales host-plant species (Cleome spinosa, Brassica oleracea, and Lunaria annua) to larval herbivore attack (Pieris rapae; Lepidoptera). Principal component analyses of metabolic fingerprints were able to distinguish among the three plant species and between uneaten control plants and plants that had been eaten. A large number of mass features (1186, 13% of mass features measured in control plants) were common to the three plant species. However, there were few similarities in the mass features that were induced (i.e. changed in abundance) following herbivory. Of the 87 and 68 induced mass features in B. oleracea and C. spinosa, respectively, there were only three that were induced in both plant species. By contrast, L. annua only had one mass feature induced by herbivory, and this was not induced in the other two plant species. The growth of the P. rapae larvae was poorer on the host plant L. annua than on B. oleracea and C. spinosa. The absence of common metabolites among the plants meant these induced responses could not be related to the performance of the herbivore. Thus, the response to herbivory by the same herbivore in these three host plants has evolved to be idiosyncratic in terms of the specific metabolites induced.

Measurement of endogenous allergens in genetically modified soybeans--short communication

The measurement of endogenous allergens is required by the European Commission (EC) as part of the compositional analysis for GM products from host plants that are common causes of food allergy, such as soybean (EC Implementing Regulation No. 503/2013). In each case, the EC Implementing Regulation indicates that analysis be conducted on identified allergens as specified in the Organization of Economic Cooperation and Development (OECD) consensus documents on compositional considerations for new plant varieties. This communication discusses the methods available to measure endogenous allergens as well as the endogenous soybean allergens that should be analyzed. It is suggested herein that in conjunction with the 2012 OECD consensus document on soybean, any list of soybean allergens should be based on clinically relevant data among publicly available allergen databases and peer-reviewed scientific publications, and the ability to measure the identified allergen. Based on a detailed analysis of the scientific literature, the following key points are recommended: (1) the acceptance of serum-free, quantitative analytical method data as an alternative to traditional IgE reactivity qualitative or semi-quantitative data for evaluation of endogenous soybean allergen content; (2) eight of the 15 potential allergens listed in the OECD soybean consensus document (Gly m 3, Gly m 4, Gly m Bd28K, Gly m Bd30K, Gly m 5, Gly m 6, Gly m 8, and Kunitz trypsin inhibitor) have both appropriate supporting clinical data and sufficient sequence information to be evaluated in comparative endogenous soybean allergen studies; and (3) the remaining seven proteins (Gly m 1, Gly m 2, unknown 50kDa protein, unknown 39kDa protein, P-22-25, lipoxygenase and lectin) lack sufficient data for clear classification as confirmed allergens and/or available sequence information and should not be currently included in the measurement of endogenous soybean allergens in the compositional analysis for the EU.

Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems

BACKGROUND

Identification of biomarkers capable of distinguishing organic and conventional products would be highly welcome to improve the strength of food quality assurance. Metabolite profiling was used for biomarker search in organic and conventional wheat grain (Triticum aestivum L.) of 11 different old and new bread wheat cultivars grown in the DOK system comparison trial. Metabolites were extracted using methanol and analysed by gas chromatography-mass spectrometry.

RESULTS

Altogether 48 metabolites and 245 non-identified metabolites (TAGs) were detected in the cultivar Runal. Principal component analysis showed a sample clustering according to farming systems and significant differences in peak areas between the farming systems for 10 Runal metabolites. Results obtained from all 11 cultivars indicated a greater influence of the cultivar than the farming system on metabolite concentrations. Nevertheless, a t-test on data of all cultivars still detected 5 metabolites and 11 TAGs with significant differences between the farming systems.

CONCLUSION

Based on individual cultivars, metabolite profiling showed promising results for the categorization of organic and conventional wheat. Further investigations are necessary with wheat from more growing seasons and locations before definite conclusions can be drawn concerning the feasibility to evolve a combined set of biomarkers for organically grown wheat using metabolite profiles.

Combined mass spectrometry-based metabolite profiling of different pigmented rice (Oryza sativa L.) seeds and correlation with antioxidant activities

Nine varieties of pigmented rice (Oryza sativa L.) seeds that were black, red, or white were used to perform metabolite profiling by using ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and gas chromatography (GC) TOF-MS, to measure antioxidant activities. Clear grouping patterns determined by the color of the rice seeds were identified in principle component analysis (PCA) derived from UPLC-Q-TOF-MS. Cyanidin-3-glucoside, peonidin-3-glucoside, proanthocyanidin dimer, proanthocyanidin trimer, apigenin-6-C-glugosyl-8-C-arabiboside, tricin-O-rhamnoside-O-hexoside, and lipids were identified as significantly different secondary metabolites. In PCA score plots derived from GC-TOF-MS, Jakwangdo (JKD) and Ilpoom (IP) species were discriminated from the other rice seeds by PC1 and PC2. Valine, phenylalanine, adenosine, pyruvate, nicotinic acid, succinic acid, maleic acid, malonic acid, gluconic acid, xylose, fructose, glucose, maltose, and myo-inositol were significantly different primary metabolites in JKD species, while GABA, asparagine, xylitol, and sucrose were significantly distributed in IP species. Analysis of antioxidant activities revealed that black and red rice seeds had higher activity than white rice seeds. Cyanidin-3-glucoside, peonidin-3-glucoside, proanthocyanidin dimers, proanthocyanidin trimers, and catechin were highly correlated with antioxidant activities, and were more plentiful in black and red rice seeds. These results are expected to provide valuable information that could help improve and develop rice-breeding techniques.

Recent Advances in the Application of Metabolomics to Studies of Biogenic Volatile Organic Compounds (BVOC) Produced by Plant

In many plants, biogenic volatile organic compounds (BVOCs) are produced as specialized metabolites that contribute to the characteristics of each plant. The varieties and composition of BVOCs are chemically diverse by plant species and the circumstances in which the plants grow, and also influenced by herbivory damage and pathogen infection. Plant-produced BVOCs are receptive to many organisms, from microorganisms to human, as both airborne attractants and repellants. In addition, it is known that some BVOCs act as signals to prime a plant for the defense response in plant-to-plant communications. The compositional profiles of BVOCs can, thus, have profound influences in the physiological and ecological aspects of living organisms. Apart from that, some of them are commercially valuable as aroma/flavor compounds for human. Metabolomic technologies have recently revealed new insights in biological systems through metabolic dynamics. Here, the recent advances in metabolomics technologies focusing on plant-produced BVOC analyses are overviewed. Their application markedly improves our knowledge of the role of BVOCs in chemosystematics, ecological influences, and aroma research, as well as being useful to prove the biosynthetic mechanisms of BVOCs.

Analytical method evaluation and discovery of variation within maize varieties in the context of food safety: transcript profiling and metabolomics

Profiling techniques such as microarrays, proteomics, and metabolomics are used widely to assess the overall effects of genetic background, environmental stimuli, growth stage, or transgene expression in plants. To assess the potential regulatory use of these techniques in agricultural biotechnology, we carried out microarray and metabolomic studies of 3 different tissues from 11 conventional maize varieties. We measured technical variations for both microarrays and metabolomics, compared results from individual plants and corresponding pooled samples, and documented variations detected among different varieties with individual plants or pooled samples. Both microarray and metabolomic technologies are reproducible and can be used to detect plant-to-plant and variety-to-variety differences. A pooling strategy lowered sample variations for both microarray and metabolomics while capturing variety-to-variety variation. However, unknown genomic sequences differing between maize varieties might hinder the application of microarrays. High-throughput metabolomics could be useful as a tool for the characterization of transgenic crops. However, researchers will have to take into consideration the impact on the detection and quantitation of a wide range of metabolites on experimental design as well as validation and interpretation of results.

Effect of environment and genotype on commercial maize hybrids using LC/MS-based metabolomics

We recently applied gas chromatography coupled to time-of-flight mass spectrometry (GC/TOF-MS) and multivariate statistical analysis to measure biological variation of many metabolites due to environment and genotype in forage and grain samples collected from 50 genetically diverse nongenetically modified (non-GM) DuPont Pioneer commercial maize hybrids grown at six North American locations. In the present study, the metabolome coverage was extended using a core subset of these grain and forage samples employing ultra high pressure liquid chromatography (uHPLC) mass spectrometry (LC/MS). A total of 286 and 857 metabolites were detected in grain and forage samples, respectively, using LC/MS. Multivariate statistical analysis was utilized to compare and correlate the metabolite profiles. Environment had a greater effect on the metabolome than genetic background. The results of this study support and extend previously published insights into the environmental and genetic associated perturbations to the metabolome that are not associated with transgenic modification.

Field-omics-understanding large-scale molecular data from field crops

The recent advances in gene expression analysis as well as protein and metabolite quantification enable genome-scale capturing of complex biological processes at the molecular level in crop field trials. This opens up new possibilities for understanding the molecular and environmental complexity of field-based systems and thus shedding light on the black box between genotype and environment, which in agriculture always is influenced by a multi-stress environment and includes management interventions. Nevertheless, combining different types of data obtained from the field and making biological sense out of large datasets remain challenging. Here we highlight the need to create a cross-disciplinary platform for innovative experimental design, sampling and subsequent analysis of large-scale molecular data obtained in field trials. For these reasons we put forward the term field-omics: "Field-omics strives to couple information from genomes, transcriptomes, proteomes, metabolomes and metagenomes to the long-established practice in crop science of conducting field trials as well as to adapt current strategies for recording and analysing field data to facilitate integration with '-omics' data."

VitisCyc: a metabolic pathway knowledgebase for grapevine (Vitis vinifera)

We have developed VitisCyc, a grapevine-specific metabolic pathway database that allows researchers to (i) search and browse the database for its various components such as metabolic pathways, reactions, compounds, genes and proteins, (ii) compare grapevine metabolic networks with other publicly available plant metabolic networks, and (iii) upload, visualize and analyze high-throughput data such as transcriptomes, proteomes, metabolomes etc. using OMICs-Viewer tool. VitisCyc is based on the genome sequence of the nearly homozygous genotype PN40024 of Vitis vinifera "Pinot Noir" cultivar with 12X v1 annotations and was built on BioCyc platform using Pathway Tools software and MetaCyc reference database. Furthermore, VitisCyc was enriched for plant-specific pathways and grape-specific metabolites, reactions and pathways. Currently VitisCyc harbors 68 super pathways, 362 biosynthesis pathways, 118 catabolic pathways, 5 detoxification pathways, 36 energy related pathways and 6 transport pathways, 10,908 enzymes, 2912 enzymatic reactions, 31 transport reactions and 2024 compounds. VitisCyc, as a community resource, can aid in the discovery of candidate genes and pathways that are regulated during plant growth and development, and in response to biotic and abiotic stress signals generated from a plant's immediate environment. VitisCyc version 3.18 is available online at http://pathways.cgrb.oregonstate.edu.

New EU legislation for risk assessment of GM food: no scientific justification for mandatory animal feeding trials

This commentary focuses on the potential added value of and need for (sub)-chronic testing of whole genetically modified (GM) foods in rodents to assess their safety. Such routine testing should not be required since, due to apparent weaknesses in the approach, it does not add to current risk assessment of GM foods. Moreover, the demand for routine testing using animals is in conflict with the European Union (EU) Commission's efforts to reduce animal experimentation. Regulating agencies in the EU are invited to respect the sound scientific principles applied to the risk assessment of foods derived from GM plants and not to interfere in the risk assessment by introducing extra requirements based on pseudo-scientific or political considerations.

The use of metabolomics to dissect plant responses to abiotic stresses

Plant metabolism is perturbed by various abiotic stresses. As such the metabolic network of plants must be reconfigured under stress conditions in order to allow both the maintenance of metabolic homeostasis and the production of compounds that ameliorate the stress. The recent development and adoption of metabolomics and systems biology approaches enable us not only to gain a comprehensive overview, but also a detailed analysis of crucial components of the plant metabolic response to abiotic stresses. In this review we introduce the analytical methods used for plant metabolomics and describe their use in studies related to the metabolic response to water, temperature, light, nutrient limitation, ion and oxidative stresses. Both similarity and specificity of the metabolic responses against diverse abiotic stress are evaluated using data available in the literature. Classically discussed stress compounds such as proline, γ-amino butyrate and polyamines are reviewed, and the widespread importance of branched chain amino acid metabolism under stress condition is discussed. Finally, where possible, mechanistic insights into metabolic regulatory processes are discussed.

Leveraging metabolomics for functional investigations in sequenced marine diatoms

Recent years have witnessed the genomic decoding of a wide range of photosynthetic organisms from the model plant Arabidopsis thaliana and the complex genomes of important crop species to single-celled marine phytoplankton. The comparative sequencing of green, red and brown algae has provided considerable insight into a number of important questions concerning their evolution, physiology and metabolism. The combinatorial application of metabolomics has further deepened our understanding both of the function of individual genes and of metabolic processes. Here we discuss the power of utilising metabolomics in conjunction with sequencing data to gain greater insight into the metabolic hierarchies underpinning the function of individual organisms, using unicellular marine diatoms as a case study to exemplify the advantages of this approach.

Metabolite profiling of maize kernels--genetic modification versus environmental influence

A metabolite profiling approach based on gas chromatography-mass spectrometry (GC-MS) was applied to investigate the metabolite profiles of genetically modified (GM) Bt-maize (DKC78-15B, TXP 138F) and Roundup Ready-maize (DKC78-35R). For the comparative investigation of the impact of genetic modification versus environmental influence on the metabolite profiles, GM maize was grown together with the non-GM near-isogenic comparators under different environmental conditions, including several growing locations and seasons in Germany and South Africa. Analyses of variance (ANOVA) revealed significant differences between GM and non-GM maize grown in Germany and South Africa. For the factor genotype, 4 and 3%, respectively, of the total number of peaks detected by GC-MS showed statistically significant differences (p < 0.01) in peak heights as compared to the respective isogenic lines. However, ANOVA for the factor environment (growing location, season) revealed higher numbers of significant differences (p < 0.01) between the GM and the non-GM maize grown in Germany (42%) and South Africa (10%), respectively. This indicates that the majority of differences observed are related to natural variability rather than to the genetic modifications. In addition, multivariate data assessment by means of principal component analysis revealed that environmental factors, that is, growing locations and seasons, were dominant parameters driving the variability of the maize metabolite profiles.

Molecular profiling--a tool for addressing emerging gaps in the comparative risk assessment of GMOs

Assessing the risks of genetically modified organisms (GMOs) is required by both international agreement and domestic legislation. Many view the use of the "omics" tools for profiling classes of molecules as useful in risk assessment, but no consensus has formed on the need or value of these techniques for assessing the risks of all GMOs. In this and many other cases, experts support case-by-case use of molecular profiling techniques for risk assessment. We review the latest research on the applicability and usefulness of molecular profiling techniques for GMO risk assessment. As more and more kinds of GMOs and traits are developed, broader use of molecular profiling in a risk assessment may be required to supplement the comparative approach to risk assessment. The literature-based discussions on the use of profiling appear to have settled on two findings: 1. profiling techniques are reliable and relevant, at least no less so than other techniques used in risk assessment; and 2. although not required routinely, regulators should be aware of when they are needed. The dismissal of routine molecular profiling may be confusing to regulators who then lack guidance on when molecular profiling might be worthwhile. Molecular profiling is an important way to increase confidence in risk assessments if the profiles are properly designed to address relevant risks and are applied at the correct stage of the assessment.