Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment

Integrating physiological and multi-omics methods to elucidate heat stress tolerance for sustainable rice production

Heat stress presents unique challenges compared to other environmental stressors, as predicting crop responses and understanding the mechanisms for heat tolerance are complex tasks. The escalating impact of devastating climate changes heightens the frequency and intensity of heat stresses, posing a noteworthy threat to global agricultural productivity, especially in rice-dependent regions of the developing world. Humidity has been demonstrated to negatively affect rice yields worldwide. Plants have evolved intricate biochemical adaptations, involving intricate interactions among genes, proteins, and metabolites, to counter diverse external signals and ensure their survival. Modern-omics technologies, encompassing transcriptomics, metabolomics, and proteomics, have revolutionized our comprehension of the intricate biochemical and cellular shifts that occur in stressed agricultural plants. Integrating these multi-omics approaches offers a comprehensive view of cellular responses to heat stress and other challenges, surpassing the insights gained from multi-omics analyses. This integration becomes vital in developing heat-tolerant crop varieties, which is crucial in the face of increasingly unpredictable weather patterns. To expedite the development of heat-resistant rice varieties, aiming at sustainability in terms of food production and food security globally, this review consolidates the latest peer-reviewed research highlighting the application of multi-omics strategies.

Spatial Lipidomics of EPSPS and PAT Transgenic and Non-Transgenic Soybean Seeds Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging

Herbicide-resistant soybeans are among the most widely planted transgenic crops. The in situ evaluation of spatial lipidomics in transgenic and non-transgenic soybeans is important for directly assessing the unintended effects of exogenous gene introduction. In this study, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI)-based non-targeted analytical strategies were used for the first time for in situ detection and imaging of endogenous lipid distributions in transgenic (EPSPS and PAT genes) herbicide-resistant soybean (Glycine max Merrill) (S4003.14) and non-transgenic soybean (JACK) seeds. Statistical analysis revealed significant differences in lipids between S4003.14 and JACK seeds. The variable importance of projection analysis further revealed that 18 identified lipids, including six phosphatidylcholines (PCs), four phosphatidylethanolamines (PEs), five triacylglycerols (TAGs), and three cytidine diphosphate-diacylglycerols (CDP-DAGs), had the strongest differential expression between S4003.14 and JACK seeds. Among those, the upregulated expressions of PC(P-36:1), PC(36:2), PC(P-36:0), PC(37:5), PE(40:2), TAG(52:1), TAG(55:5), and CDP-DAG(37:2) and the downregulated expressions of PC (36:1), TAG(43:0), and three PEs (i.e., PE(P-38:1), PE(P-38:0), and PE(P-40:3)) were successfully found in the S4003.14 seeds, compared to these lipids detected in the JACK seeds. Meanwhile, the lipids of PC (44:8), CDP-DAG(38:0), and CDP-DAG(42:0) were uniquely detected in the S4003.14 soybean seeds, and TAG(45:2) and TAG(57:10) were detected as the unique lipids in the JACK seeds. The heterogeneous distribution of these lipids in the soybean seeds was also clearly visualized using MALDI-MSI. MSI results showed that lipid expression was significantly up/downregulated in S4003.14 seeds, compared to that in JACK seeds. This study improves our understanding of the unintended effects of herbicide-resistant EPSPS and PAT gene transfers on spatial lipidomes in soybean seeds and enables the continued progression of MALDI-MSI as an emerging, reliable, and rapid molecular imaging tool for evaluating unintended effects in transgenic plants.

Integrative strategy for quality control of Radix Bupleuri based on non-targeted metabolomic profiling and molecular networking

Quality control of Radix Bupleuri (RB) can be challenging due to the complexity of origin, the similar morphological characteristics, and the diversity of the multiple components. In this study, an integrated strategy for extensive identification of metabolites in plants based on multiple data processing methods was proposed to distinguish four commercially available RB species. First, the pre-processed mass spectrometry data was uploaded to Global Natural Products Social Molecular Networking (GNPS) for spectral library search and molecular network analysis, which can effectively differentiate isomers and reduce molecular redundancy. Second, the possible cleavage mode was summarized from the characteristic MS/MS fragment ions of saikoside standard, and then the possible structure of saikoside in the sample was deduced according to the cleavage patterns. Third, collected all kinds of RB components reported in the literature and matched the information in the samples to obtain more comprehensive information about metabolites. Finally, chemical markers were found employing chemometrics. This strategy not only increases the variety and number of identified components, but also improves the accuracy of the data. Based on this strategy, a total of 132 components were identified from different species of RB, and 14 chemical constituents were considered to be potential chemical markers to distinguish four kinds of RB. Among them, saikogenin a, hydroxy-saikosaponin a, hydroxy-saikosaponin d, and rutinum were of great significance for identification. The method proposed in this study not only successfully identified and distinguished four species of RB, but also laid a good theoretical foundation for regulating the RB market. This strategy provides promising perspectives in the accurate analysis of the ingredients of traditional Chinese medicine.

Advances in Metabolomics-Driven Diagnostic Breeding and Crop Improvement

Climate change continues to threaten global crop output by reducing annual productivity. As a result, global food security is now considered as one of the most important challenges facing humanity. To address this challenge, modern crop breeding approaches are required to create plants that can cope with increased abiotic/biotic stress. Metabolomics is rapidly gaining traction in plant breeding by predicting the metabolic marker for plant performance under a stressful environment and has emerged as a powerful tool for guiding crop improvement. The advent of more sensitive, automated, and high-throughput analytical tools combined with advanced bioinformatics and other omics techniques has laid the foundation to broadly characterize the genetic traits for crop improvement. Progress in metabolomics allows scientists to rapidly map specific metabolites to the genes that encode their metabolic pathways and offer plant scientists an excellent opportunity to fully explore and rationally harness the wealth of metabolites that plants biosynthesize. Here, we outline the current application of advanced metabolomics tools integrated with other OMICS techniques that can be used to: dissect the details of plant genotype–metabolite–phenotype interactions facilitating metabolomics-assisted plant breeding for probing the stress-responsive metabolic markers, explore the hidden metabolic networks associated with abiotic/biotic stress resistance, facilitate screening and selection of climate-smart crops at the metabolite level, and enable accurate risk-assessment and characterization of gene edited/transgenic plants to assist the regulatory process. The basic concept behind metabolic editing is to identify specific genes that govern the crucial metabolic pathways followed by the editing of one or more genes associated with those pathways. Thus, metabolomics provides a superb platform for not only rapid assessment and commercialization of future genome-edited crops, but also for accelerated metabolomics-assisted plant breeding. Furthermore, metabolomics can be a useful tool to expedite the crop research if integrated with speed breeding in future.

Integrative omics approaches revealed a crosstalk among phytohormones during tuberous root development in cassava

Integrative omics approaches revealed a crosstalk among phytohormones during tuberous root development in cassava. Tuberous root formation is a complex process consisting of phase changes as well as cell division and elongation for radial growth. We performed an integrated analysis to clarify the relationships among metabolites, phytohormones, and gene transcription during tuberous root formation in cassava (Manihot esculenta Crantz). We also confirmed the effects of the auxin (AUX), cytokinin (CK), abscisic acid (ABA), jasmonic acid (JA), gibberellin (GA), brassinosteroid (BR), salicylic acid, and indole-3-acetic acid conjugated with aspartic acid on tuberous root development. An integrated analysis of metabolites and gene expression indicated the expression levels of several genes encoding enzymes involved in starch biosynthesis and sucrose metabolism are up-regulated during tuberous root development, which is consistent with the accumulation of starch, sugar phosphates, and nucleotides. An integrated analysis of phytohormones and gene transcripts revealed a relationship among AUX signaling, CK signaling, and BR signaling, with AUX, CK, and BR inducing tuberous root development. In contrast, ABA and JA inhibited tuberous root development. These phenomena might represent the differences between stem tubers (e.g., potato) and root tubers (e.g., cassava). On the basis of these results, a phytohormonal regulatory model for tuberous root development was constructed. This model may be useful for future phytohormonal studies involving cassava.

Physiological and Multi-Omics Approaches for Explaining Drought Stress Tolerance and Supporting Sustainable Production of Rice

Drought differs from other natural disasters in several respects, largely because of the complexity of a crop's response to it and also because we have the least understanding of a crop's inductive mechanism for addressing drought tolerance among all abiotic stressors. Overall, the growth and productivity of crops at a global level is now thought to be an issue that is more severe and arises more frequently due to climatic change-induced drought stress. Among the major crops, rice is a frontline staple cereal crop of the developing world and is critical to sustaining populations on a daily basis. Worldwide, studies have reported a reduction in rice productivity over the years as a consequence of drought. Plants are evolutionarily primed to withstand a substantial number of environmental cues by undergoing a wide range of changes at the molecular level, involving gene, protein and metabolite interactions to protect the growing plant. Currently, an in-depth, precise and systemic understanding of fundamental biological and cellular mechanisms activated by crop plants during stress is accomplished by an umbrella of -omics technologies, such as transcriptomics, metabolomics and proteomics. This combination of multi-omics approaches provides a comprehensive understanding of cellular dynamics during drought or other stress conditions in comparison to a single -omics approach. Thus a greater need to utilize information (big-omics data) from various molecular pathways to develop drought-resilient crop varieties for cultivation in ever-changing climatic conditions. This review article is focused on assembling current peer-reviewed published knowledge on the use of multi-omics approaches toward expediting the development of drought-tolerant rice plants for sustainable rice production and realizing global food security.

Liver and urine metabolomics reveal the protective effect of Gandou decoction in copper-laden Hepatolenticular degeneration model rats

Hepatolenticular degeneration (HLD) is an inherited disorder associated with human copper metabolism. Gandou decoction (GDD), a traditional Chinese medicinal formula, has been used as a therapeutic agent for the treatment of HLD in China for decades. Recent pharmacological evaluation in our laboratory has demonstrated that GDD exerts positive and beneficial effects on HLD model rats. However, its underlying therapeutic mechanisms are not yet well understood. To explore the potential therapeutic effects of GDD against HLD, liver and urine metabolomics approach combined with histopathological examination were performed to reveal the underlying mechanisms. Changes in metabolic profiles were estimated by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) coupled with multivariate statistical analyses. The results indicated that GDD could significantly improve liver pathological variations. Moreover, 19 and 11 significantly altered metabolites were found in the liver and urine between the normal and model groups, respectively. After GDD treatment, the levels of all these disordered metabolites showed different degrees of improvement compared with the model group, including lysoPC(18:2), lysoPE(20:2/0:0), PC(18:1/14:1), alpha-linolenic acid, sphinganine, taurochenodesoxycholic acid, tetracosahexaenoic acid, 13-OxoODE, and 13-L-hydroperoxyl inoleic acid. Metabolic pathway enrichment suggested that lipid and oxidative stress metabolism were the two main pathways that participated in copper-laden rat models with GDD administration. This work indicates that GDD could achieve a therapeutic effect on HLD by ameliorating the associated metabolic disturbances.

Next-Generation Mass Spectrometry Metabolomics Revives the Functional Analysis of Plant Metabolic Diversity

The remarkable diversity of specialized metabolites produced by plants has inspired several decades of research and nucleated a long list of theories to guide empirical ecological studies. However, analytical constraints and the lack of untargeted processing workflows have long precluded comprehensive metabolite profiling and, consequently, the collection of the critical currencies to test theory predictions for the ecological functions of plant metabolic diversity. Developments in mass spectrometry (MS) metabolomics have revolutionized the large-scale inventory and annotation of chemicals from biospecimens. Hence, the next generation of MS metabolomics propelled by new bioinformatics developments provides a long-awaited framework to revisit metabolism-centered ecological questions, much like the advances in next-generation sequencing of the last two decades impacted all research horizons in genomics. Here, we review advances in plant (computational) metabolomics to foster hypothesis formulation from complex metabolome data. Additionally, we reflect on how next-generation metabolomics could reinvigorate the testing of long-standing theories on plant metabolic diversity.

Plant Volatiles of Lettuce and Chicory Cultivated in Aquaponics Are Associated to Their Microbial Community

In this work, an aquaponic cultivation system for Lactuca sativa (L.) and Chicorium intybus (L.) was compared to a hydroponic one, focusing on the main microbial populations related to food safety and their volatile compounds (VOCs), concluding with Spearman correlations among the microbes and VOCs. Different sections of both systems were sampled at the end of the commercial development of the plants. Plants cultivated in aquaponics were in general more contaminated than those from hydroponics, while for the cultivation waters a higher contamination of the hydroponics than aquaponics system was unexpectedly observed. Furthermore, the chicory exhibited higher levels of all microbial groups compared to lettuce grown under the same cultivation system. The results obtained also showed correlations between the distribution of some VOCs and microbial groups in the phyllosphere, while some examples of positive correlations between 2-nonanone (a positive phytostimulant compound) and anaerobic bacilli of the rhizosphere in lettuce were reported. So far, multivariate analysis of VOCs was able to discriminate on the basis of varieties but not on the cultivation systems. In conclusion, the microbial characteristics of the two ecosystems depended both on plant variety and cultivation method but further studies will need to deeply investigate the variables influencing the microbial quality of vegetable foods obtained by aquaponics. On the other hand, the analysis of the VOCs was more related to the microbial community of each plant variety considered, whatever the cultivation system. In precision agriculture, metabolomics may represent an opportunity to study the holobiome and through it the interactions between plants and their microbial populations, to possibly provide for a tool to assess the microbiological quality of vegetable foods obtained by aquaponic systems.

Promoting Human Nutrition and Health through Plant Metabolomics: Current Status and Challenges

Simple Summary

This review summarizes the status, applications, and challenges of plant metabolomics in the context of crop breeding, food quality and safety, and human nutrition and health. It also highlights the importance of plant metabolomics in elucidating biochemical and genetic bases of traits associated with nutritive and healthy beneficial foods and other plant products to secure food supply, to ensure food quality, to protect humans from malnutrition and other diseases. Meanwhile, this review calls for comprehensive collaborations to accelerate relevant researches and applications in the context of human nutrition and health.

Abstract

Plant metabolomics plays important roles in both basic and applied studies regarding all aspects of plant development and stress responses. With the improvement of living standards, people need high quality and safe food supplies. Thus, understanding the pathways involved in the biosynthesis of nutritionally and healthily associated metabolites in plants and the responses to plant-derived biohazards in humans is of equal importance to meet people’s needs. For each, metabolomics has a vital role to play, which is discussed in detail in this review. In addition, the core elements of plant metabolomics are highlighted, researches on metabolomics-based crop improvement for nutrition and safety are summarized, metabolomics studies on plant natural products including traditional Chinese medicine (TCM) for health promotion are briefly presented. Challenges are discussed and future perspectives of metabolomics as one of the most important tools to promote human nutrition and health are proposed.

Metabolite and Phytohormone Profiling Illustrates Metabolic Reprogramming as an Escape Strategy of Deepwater Rice during Partially Submerged Stress

Rice varieties that can survive under submergence conditions respond to flooding either by enhancing internode elongation or by quiescence of shoot elongation. Despite extensive efforts to identify key metabolites triggered by complete submergence of rice possessing SUBMERGENCE 1 (SUB1) locus, metabolic responses of internode elongation of deepwater rice governed by the SNORKEL 1 and 2 genes remain elusive. This study investigated specific metabolomic responses under partial submergence (PS) to deepwater- (C9285) and non-deepwater rice cultivars (Taichung 65 (T65)). In addition, we examined the response in a near-isogenic line (NIL-12) that has a C9285 genomic fragment on chromosome 12 introgressed into the genetic background of T65. Under short-term submergence (0-24 h), metabolite profiles of C9285, NIL-12, and T65 were compared to extract significantly changed metabolites in deepwater rice under PS conditions. Comprehensive metabolite and phytohormone profiling revealed increases in metabolite levels in the glycolysis pathway in NIL-12 plants. Under long-term submergence (0-288 h), we found decreased amino acid levels. These metabolomic changes were opposite when compared to those in flood-tolerant rice with SUB1 locus. Auxin conjugate levels related to stress response decreased in NIL-12 lines relative to T65. Our analysis helped clarify the complex metabolic reprogramming in deepwater rice as an escape strategy.

A Systems Analysis With "Simplified Source-Sink Model" Reveals Metabolic Reprogramming in a Pair of Source-to-Sink Organs During Early Fruit Development in Tomato by LED Light Treatments

Tomato (Solanum lycopersicum) is a model crop for studying development regulation and ripening in flesh fruits and vegetables. Supplementary light to maintain the optimal light environment can lead to the stable growth of tomatoes in greenhouses and areas without sufficient daily light integral. Technological advances in genome-wide molecular phenotyping have dramatically enhanced our understanding of metabolic shifts in the plant metabolism across tomato fruit development. However, comprehensive metabolic and transcriptional behaviors along the developmental process under supplementary light provided by light-emitting diodes (LEDs) remain to be fully elucidated. We present integrative omic approaches to identify the impact on the metabolism of a single tomato plant leaf exposed to monochromatic red LEDs of different intensities during the fruit development stage. Our special light delivery system, the "simplified source-sink model," involves the exposure of a single leaf below the second truss to red LED light of different intensities. We evaluated fruit-size- and fruit-shape variations elicited by different light intensities. Our findings suggest that more than high-light treatment (500 μmol m-2 s-1) with the red LED light is required to accelerate fruit growth for 2 weeks after anthesis. To investigate transcriptomic and metabolomic changes in leaf- and fruit samples we used microarray-, RNA sequencing-, and gas chromatography-mass spectrometry techniques. We found that metabolic shifts in the carbohydrate metabolism and in several key pathways contributed to fruit development, including ripening and cell-wall modification. Our findings suggest that the proposed workflow aids in the identification of key metabolites in the central metabolism that respond to monochromatic red-LED treatment and contribute to increase the fruit size of tomato plants. This study expands our understanding of systems-level responses mediated by low-, appropriate-, and high levels of red light irradiation in the fruit growth of tomato plants.

Metabolomics-guided investigations of unintended effects of the expression of the hydroxycinnamoyl quinate hydroxycinnamoyltransferase (hqt1) gene from Cynara cardunculus var. scolymus in Nicotiana tabacum cell cultures

Chlorogenic acids (CGAs) are phenolic compounds biosynthesized in the phenylpropanoid pathway, with hydroxycinnamoyl quinate hydroxycinnamoyltransferase (HQT) as the key enzyme. Variation of CGAs has been noted in different plants, with globe artichoke (Cynara cardunculus var. scolymus L.) producing high amounts and a diverse spectrum of CGAs in its leaves. In the current study, the effect of overexpression of the hqt1 transgene from globe artichoke in tobacco was evaluated at the metabolome level. Here, metabolomic approaches based on ultra-high performance liquid chromatography coupled to mass spectrometry, together with chemometric models such as principal component analysis and orthogonal partial least square discriminant analysis, were employed to evaluate altered metabolic changes due to hqt1 overexpression. CGA profiles (caffeoylquinic acids: 3-CQA, 4-CQA and 5-CQA; p-coumaroylquinic acids: 4-pCoQA and 5-pCoQA; and 4,5-di-caffeoylquinic acid) of transgenic tobacco cell cultures were detected at lower concentrations than in the wild type. Interestingly, the cells were found to rather accumulate, as an unintended effect, abscisic acid - and benzoic acid derivatives. The results suggest that insertion of hqt1 in tobacco, and overexpression in undifferentiated cells, led to rechannelling of the phenylpropanoid pathway to accumulate benzoic acids. These findings proved to be contrary to the results shown elsewhere in leaf tissues, thus indicating differential metabolic control and regulation in the undifferentiated cell culture system.

Metabolic Reprogramming in Leaf Lettuce Grown Under Different Light Quality and Intensity Conditions Using Narrow-Band LEDs

Light-emitting diodes (LEDs) are an artificial light source used in closed-type plant factories and provide a promising solution for a year-round supply of green leafy vegetables, such as lettuce (Lactuca sativa L.). Obtaining high-quality seedlings using controlled irradiation from LEDs is critical, as the seedling health affects the growth and yield of leaf lettuce after transplantation. Because key molecular pathways underlying plant responses to a specific light quality and intensity remain poorly characterised, we used a multi-omics-based approach to evaluate the metabolic and transcriptional reprogramming of leaf lettuce seedlings grown under narrow-band LED lighting. Four types of monochromatic LEDs (one blue, two green and one red) and white fluorescent light (control) were used at low and high intensities (100 and 300 μmol·m-2·s-1, respectively). Multi-platform mass spectrometry-based metabolomics and RNA-Seq were used to determine changes in the metabolome and transcriptome of lettuce plants in response to different light qualities and intensities. Metabolic pathway analysis revealed distinct regulatory mechanisms involved in flavonoid and phenylpropanoid biosynthetic pathways under blue and green wavelengths. Taken together, these data suggest that the energy transmitted by green light is effective in creating a balance between biomass production and the production of secondary metabolites involved in plant defence.

Metabolomics analysis of 'Housui' Japanese pear flower buds during endodormancy reveals metabolic suppression by thermal fluctuation

Dormancy is a complex phenomenon that allows plants to survive the winter season. Studies of dormancy have recently attracted more attention due to the expansion of temperate fruit production in areas under mild winters and due to climate changes. This study aimed to identify and characterize the metabolic changes induced by chilling temperatures, as well as during thermal fluctuation conditions that simulate mild winter and/or climate change scenarios. To do this, we compared the metabolic profile of Japanese pear flower buds exposed to constant chilling at 6 °C and thermal fluctuations of 6 °C/18 °C (150 h/150 h) during endodormancy. We detected 91 metabolites by gas chromatography paired with time-of-flight mass spectrometry (GC-TOF-MS) that could be classified into eight groups: amino acids, amino acid derivatives, organic acids, sugars and polyols, fatty acids and sterols, phenol lipids, phenylpropanoids, and other compounds. Metabolomics analysis revealed that the level of several amino acids decreased during endodormancy. Sugar and polyol levels increased during endodormancy during constant chilling and might be associated with chilling stress tolerance and providing an energy supply for resuming growth. In contrast, thermal fluctuations produced low levels of metabolites related to the pentose phosphate pathway, energy production, and tricarboxylic acid (TCA) cycle in flower buds, which may be associated with failed endodormancy release. This metabolic profile contributes to our understanding of the biological mechanism of dormancy during chilling accumulation and clarifies the metabolic changes during mild winters and future climate change scenarios.

[Development of Plant Metabolomics and Medicinal Plant Genomics]

 A variety of chemicals produced by plants, often referred to as 'phytochemicals', have been used as medicines, food, fuels and industrial raw materials. Recent advances in the study of genomics and metabolomics in plant science have accelerated our understanding of the mechanisms, regulation and evolution of the biosynthesis of specialized plant products. We can now address such questions as how the metabolomic diversity of plants is originated at the levels of genome, and how we should apply this knowledge to drug discovery, industry and agriculture. Our research group has focused on metabolomics-based functional genomics over the last 15 years and we have developed a new research area called 'Phytochemical Genomics'. In this review, the development of a research platform for plant metabolomics is discussed first, to provide a better understanding of the chemical diversity of plants. Then, representative applications of metabolomics to functional genomics in a model plant, Arabidopsis thaliana, are described. The extension of integrated multi-omics analyses to non-model specialized plants, e.g., medicinal plants, is presented, including the identification of novel genes, metabolites and networks for the biosynthesis of flavonoids, alkaloids, sulfur-containing metabolites and terpenoids. Further, functional genomics studies on a variety of medicinal plants is presented. I also discuss future trends in pharmacognosy and related sciences.

Metabolomic Evaluation of the Quality of Leaf Lettuce Grown in Practical Plant Factory to Capture Metabolite Signature

Vegetables produce metabolites that affect their taste and nutritional value and compounds that contribute to human health. The quality of vegetables grown in plant factories under hydroponic cultivation, e.g., their sweetness and softness, can be improved by controlling growth factors including the temperature, humidity, light source, and fertilizer. However, soil is cheaper than hydroponic cultivation and the visual phenotype of vegetables grown under the two conditions is different. As it is not clear whether their metabolite composition is also different, we studied leaf lettuce raised under the hydroponic condition in practical plant factory and strictly controlled soil condition. We chose two representative cultivars, "black rose" (BR) and "red fire" (RF) because they are of high economic value. Metabolite profiling by comprehensive gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) resulted in the annotation of 101 metabolites from 223 peaks detected by GC-MS; LC-MS yielded 95 peaks. The principal component analysis (PCA) scatter plot showed that the most distinct separation patterns on the first principal component (PC1) coincided with differences in the cultivation methods. There were no clear separations related to cultivar differences in the plot. PC1 loading revealed the discriminant metabolites for each cultivation method. The level of amino acids such as lysine, phenylalanine, tryptophan, and valine was significantly increased in hydroponically grown leaf lettuce, while soil-cultivation derived leaf lettuce samples contained significantly higher levels of fatty-acid derived alcohols (tetracosanol and hexacosanol) and lettuce-specific sesquiterpene lactones (lactucopicrin-15-oxalate and 15-deoxylactucin-8-sulfate). These findings suggest that the metabolite composition of leaf lettuce is primarily affected by its cultivation condition. As the discriminant metabolites reveal important factors that contribute to the nutritional value and taste characteristics of leaf lettuce, we performed comprehensive metabolite profiling to identify metabolite compositions, i.e., metabolite signature, that directly improve its quality and value.

Metabolic changes in primary, secondary, and lipid metabolism in tobacco leaf in response to topping

As an important cultivation practice used for flue-cured tobacco, topping affects diverse biological processes in the later stages of development and growth. Some studies have focused on using tobacco genes to reflect the physiological changes caused by topping. However, the complex metabolic shifts in the leaf resulting from topping have not yet been investigated in detail. In this study, a comprehensive metabolic profile of primary, secondary, and lipid metabolism in flue-cured tobacco leaf was generated with use of a multiple platform consisting of gas chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and liquid chromatography-mass spectrometry/ultraviolet spectroscopy. A total of 367 metabolites were identified and determined. Both principal component analysis and the number of significantly different metabolites indicated that topping had the greatest influence on the upper leaves. During the early stage of topping, great lipid level variations in the upper leaves were observed, and antioxidant defense metabolites were accumulated. This indicated that the topping activated lipid turnover and the antioxidant defense system. At the mature stage, lower levels of senescence-related metabolites and higher levels of secondary metabolites were found in the topped mature leaves. This implied that topping delayed leaf senescence and promoted secondary metabolite accumulation. This study provides a global view of the metabolic perturbation in response to topping. Graphical abstract Metabolic alterations in tobacco leaf in response to topping using a multiplatform metabolomics.

Metabolomics-assisted biotechnological interventions for developing plant-based functional foods and nutraceuticals

Today, the dramatic changes in types of food consumed have led to an increased burden of chronic diseases. Therefore, the emphasis of food research is not only to ensure quality food that can supply adequate nutrients to prevent nutrition related diseases, but also to ensure overall physical and mental-health. This has led to the concept of functional foods and nutraceuticals (FFNs), which can be ideally produced and delivered through plants. Metabolomics can help in getting the most relevant functional information, and thus has been considered the greatest -OMICS technology to date. However, metabolomics has not been exploited to the best potential in plant sciences. The technology can be leveraged to identify the health promoting compounds and metabolites that can be used for the development of FFNs. This article reviews (i) plant-based FFNs-related metabolites and their health benefits; (ii) use of different analytic platforms for targeted and non-targeted metabolite profiling along with experimental considerations; (iii) exploitation of metabolomics to develop FFNs in plants using various biotechnological tools; and (iv) potential use of metabolomics in plant breeding. We have also provided some insights into integration of metabolomics with latest genome editing tools for metabolic pathway regulation in plants.

Seed Metabolome Analysis of a Transgenic Rice Line Expressing Cholera Toxin B-subunit

Plant-based human vaccines have been actively developed in recent years, and rice (Oryza sativa L.) is one of the best candidate crops for their production and delivery. By expressing a modified cholera toxin B (CTB) subunit, we previously developed MucoRice-CTB, a rice-based vaccine against cholera, which is caused by infection of the intestine with the bacteria Vibrio cholerae. MucoRice-CTB lines have been extensively characterized by whole-genome sequencing and proteome analyses to evaluate the mutation profiles and proteome status, respectively. Here, we report non-targeted metabolomic profiling of the MucoRice-CTB transgenic rice line 51A (MR-CTB51A), MucoRice-RNAi (MR-RNAi), and their non-transgenic parent line by using gas chromatography-time-of-flight mass spectrometry. The levels of several amino acids, organic acids, carbohydrates, lipids, and secondary metabolites were significantly increased in MR-CTB51A compared with the non-transgenic parent line. These metabolomics results complement essential information obtained by genome sequencing and proteomics approaches, thereby contributing to comprehensive understanding of the properties of MucoRice-CTB as a plant-based vaccine.

Effect of Genetics, Environment, and Phenotype on the Metabolome of Maize Hybrids Using GC/MS and LC/MS

We evaluated the variability of metabolites in various maize hybrids due to the effect of environment, genotype, phenotype as well as the interaction of the first two factors. We analyzed 480 forage and the same number of grain samples from 21 genetically diverse non-GM Pioneer brand maize hybrids, including some with drought tolerance and viral resistance phenotypes, grown at eight North American locations. As complementary platforms, both GC/MS and LC/MS were utilized to detect a wide diversity of metabolites. GC/MS revealed 166 and 137 metabolites in forage and grain samples, respectively, while LC/MS captured 1341 and 635 metabolites in forage and grain samples, respectively. Univariate and multivariate analyses were utilized to investigate the response of the maize metabolome to the environment, genotype, phenotype, and their interaction. Based on combined percentages from GC/MS and LC/MS datasets, the environment affected 36% to 84% of forage metabolites, while less than 7% were affected by genotype. The environment affected 12% to 90% of grain metabolites, whereas less than 27% were affected by genotype. Less than 10% and 11% of the metabolites were affected by phenotype in forage and grain, respectively. Unsupervised PCA and HCA analyses revealed similar trends, i.e., environmental effect was much stronger than genotype or phenotype effects. On the basis of comparisons of disease tolerant and disease susceptible hybrids, neither forage nor grain samples originating from different locations showed obvious phenotype effects. Our findings demonstrate that the combination of GC/MS and LC/MS based metabolite profiling followed by broad statistical analysis is an effective approach to identify the relative impact of environmental, genetic and phenotypic effects on the forage and grain composition of maize hybrids.

Use of Foodomics for Control of Food Processing and Assessing of Food Safety

Food chain, food safety, and food-processing sectors face new challenges due to globalization of food chain and changes in the modern consumer preferences. In addition, gradually increasing microbial resistance, changes in climate, and human errors in food handling remain a pending barrier for the efficient global food safety management. Consequently, a need for development, validation, and implementation of rapid, sensitive, and accurate methods for assessment of food safety often termed as foodomics methods is required. Even though, the growing role of these high-throughput foodomic methods based on genomic, transcriptomic, proteomic, and metabolomic techniques has yet to be completely acknowledged by the regulatory agencies and bodies. The sensitivity and accuracy of these methods are superior to previously used standard analytical procedures and new methods are suitable to address a number of novel requirements posed by the food production sector and global food market.

Spatially resolved metabolic distribution for unraveling the physiological change and responses in tomato fruit using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI)

Information on spatiotemporal metabolic behavior is indispensable for a precise understanding of physiological changes and responses, including those of ripening processes and wounding stress, in fruit, but such information is still limited. Here, we visualized the spatial distribution of metabolites within tissue sections of tomato (Solanum lycopersicum L.) fruit using a matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) technique combined with a matrix sublimation/recrystallization method. This technique elucidated the unique distribution patterns of more than 30 metabolite-derived ions, including primary and secondary metabolites, simultaneously. To investigate spatiotemporal metabolic alterations during physiological changes at the whole-tissue level, MALDI-MSI was performed using the different ripening phenotypes of mature green and mature red tomato fruits. Although apparent alterations in the localization and intensity of many detected metabolites were not observed between the two tomatoes, the amounts of glutamate and adenosine monophosphate, umami compounds, increased in both mesocarp and locule regions during the ripening process. In contrast, malate, a sour compound, decreased in both regions. MALDI-MSI was also applied to evaluate more local metabolic responses to wounding stress. Accumulations of a glycoalkaloid, tomatine, and a low level of its glycosylated metabolite, esculeoside A, were found in the wound region where cell death had been induced. Their inverse levels were observed in non-wounded regions. Furthermore, the amounts of both compounds differed in the developmental stages. Thus, our MALDI-MSI technique increased the understanding of the physiological changes and responses of tomato fruit through the determination of spatiotemporally resolved metabolic alterations. Graphical abstract ᅟ.

Technical Challenges in Mass Spectrometry-Based Metabolomics

Metabolomics is a strategy for analysis, and quantification of the complete collection of metabolites present in biological samples. Metabolomics is an emerging area of scientific research because there are many application areas including clinical, agricultural, and medical researches for the biomarker discovery and the metabolic system analysis by employing widely targeted analysis of a few hundred preselected metabolites from 10-100 biological samples. Further improvement in technologies of mass spectrometry in terms of experimental design for larger scale analysis, computational methods for tandem mass spectrometry-based elucidation of metabolites, and specific instrumentation for advanced bioanalysis will enable more comprehensive metabolome analysis for exploring the hidden secrets of metabolism.

Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

Metabolic Profiling with Gas Chromatography-Mass Spectrometry and Capillary Electrophoresis-Mass Spectrometry Reveals the Carbon-Nitrogen Status of Tobacco Leaves Across Different Planting Areas

The interaction between carbon (C) and nitrogen (N) metabolism can reflect plant growth status and environmental factors. Little is known regarding the connections between C-N metabolism and growing regions under field conditions. To comprehensively investigate the relationship in mature tobacco leaves, we established metabolomics approaches based on gas chromatography-mass spectrometry (GC-MS) and capillary electrophoresis-time-of-flight-mass spectrometry (CE-TOF-MS). Approximately 240 polar metabolites were determined. Multivariate statistical analysis revealed that the growing region greatly influenced the metabolic profiles of tobacco leaves. A metabolic correlation network and related pathway maps were used to reveal the global overview of the alteration of C-N metabolism across three typical regions. In Yunnan, sugars and tricarboxylic acid (TCA) cycle intermediates were closely correlated with amino acid pools. Henan tobacco leaves showed positive correlation between the pentose phosphate pathway (PPP) intermediates and C-rich secondary metabolism. In Guizhou, the proline and asparagine had significant links with TCA cycle intermediates and urea cycle, and antioxidant accumulation was observed in response to drought. These results demonstrate that combined analytical approaches have great potential to detect polar metabolites and provide information on C-N metabolism related to planting regional characteristics.

Metabolic changes in transgenic maize mature seeds over-expressing the Aspergillus niger phyA2

Non-targeted metabolomics analysis revealed only intended metabolic changes in transgenic maize over-expressing the Aspergillus niger phyA2. Genetically modified (GM) crops account for a large proportion of modern agriculture worldwide, raising increasingly the public concerns of safety. Generally, according to substantial equivalence principle, if a GM crop is demonstrated to be equivalently safe to its conventional species, it is supposed to be safe. In this study, taking the advantage of an established non-target metabolomic profiling platform based on the combination of UPLC-MS/MS with GC-MS, we compared the mature seed metabolic changes in transgenic maize over-expressing the Aspergillus niger phyA2 with its non-transgenic counterpart and other 14 conventional maize lines. In total, levels of nine out of identified 210 metabolites were significantly changed in transgenic maize as compared with its non-transgenic counterpart, and the number of significantly altered metabolites was reduced to only four when the natural variations were taken into consideration. Notably, those four metabolites were all associated with targeted engineering pathway. Our results indicated that although both intended and non-intended metabolic changes occurred in the mature seeds of this GM maize event, only intended metabolic pathway was found to be out of the range of the natural metabolic variation in the metabolome of the transgenic maize. Therefore, only when natural metabolic variation was taken into account, could non-targeted metabolomics provide reliable objective compositional substantial equivalence analysis on GM crops.

Capillary Electrophoresis in Food and Foodomics

Quality and safety assessment as well as the evaluation of other nutritional and functional properties of foods imply the use of robust, efficient, sensitive, and cost-effective analytical methodologies. Among analytical technologies used in the fields of food analysis and foodomics, capillary electrophoresis (CE) has generated great interest for the analyses of a large number of compounds due to its high separation efficiency, extremely small sample and reagent requirements, and rapid analysis. The introductory section of this chapter provides an overview of the recent applications of capillary electrophoresis (CE) in food analysis and foodomics. Relevant reviews and research articles on these topics are tabulated including papers published in the period 2011-2014. In addition, to illustrate the great capabilities of CE in foodomics the chapter describes the main experimental points to be taken into consideration for a metabolomic study of the antiproliferative effect of carnosic acid (a natural diterpene found in rosemary) against HT-29 human colon cancer cells.

Accumulation of Flavonols over Hydroxycinnamic Acids Favors Oxidative Damage Protection under Abiotic Stress

Efficient detoxification of reactive oxygen species (ROS) is thought to play a key role in enhancing the tolerance of plants to abiotic stresses. Although multiple pathways, enzymes, and antioxidants are present in plants, their exact roles during different stress responses remain unclear. Here, we report on the characterization of the different antioxidant mechanisms of tomato plants subjected to heat stress, salinity stress, or a combination of both stresses. All the treatments applied induced an increase of oxidative stress, with the salinity treatment being the most aggressive, resulting in plants with the lowest biomass, and the highest levels of H2O2 accumulation, lipid peroxidation, and protein oxidation. However, the results obtained from the transcript expression study and enzymatic activities related to the ascorbate-glutathione pathway did not fully explain the differences in the oxidative damage observed between salinity and the combination of salinity and heat. An exhaustive metabolomics study revealed the differential accumulation of phenolic compounds depending on the type of abiotic stress applied. An analysis at gene and enzyme levels of the phenylpropanoid metabolism concluded that under conditions where flavonols accumulated to a greater degree as compared to hydroxycinnamic acids, the oxidative damage was lower, highlighting the importance of flavonols as powerful antioxidants, and their role in abiotic stress tolerance.

A Comparison of transgenic and wild type soybean seeds: analysis of transcriptome profiles using RNA-Seq

BACKGROUND

Soybean (Glycine max) has been bred for thousands of years to produce seeds rich in protein for human and animal consumption, making them an appealing bioreactor for producing valuable recombinant proteins at high levels. However, the effects of expressing recombinant protein at high levels on bean physiology are not well understood. To address this, we investigated whether gene expression within transgenic soybean seed tissue is altered when large amounts of recombinant proteins are being produced and stored exclusively in the seeds. We used RNA-Seq to survey gene expression in three transgenic soybean lines expressing recombinant protein at levels representing up to 1.61 % of total protein in seed tissues. The three lines included: ST77, expressing human thyroglobulin protein (hTG), ST111, expressing human myelin basic protein (hMBP), and 764, expressing a mutant, nontoxic form of a staphylococcal subunit vaccine protein (mSEB). All lines selected for analysis were homozygous and contained a single copy of the transgene.

METHODS

Each transgenic soybean seed was screened for transgene presence and recombinant protein expression via PCR and western blotting.  Whole seed mRNA was extracted and cDNA libraries constructed for Illumina sequencing.  Following alignment to the soybean reference genome, differential gene expression analysis was conducted using edgeR and cufflinks.  Functional analysis of differentially expressed genes was carried out using the gene ontology analysis tool AgriGO.

RESULTS

The transcriptomes of nine seeds from each transgenic line were sequenced and compared with wild type seeds. Native soybean gene expression was significantly altered in line 764 (mSEB) with more than 3000 genes being upregulated or downregulated. ST77 (hTG) and ST111 (hMBP) had significantly less differences with 52 and 307 differentially expressed genes respectively. Gene ontology enrichment analysis found that the upregulated genes in the 764 line were annotated with functions related to endopeptidase inhibitors and protein synthesis, but suppressed expression of genes annotated to the nuclear pore and to protein transport. No significant gene ontology terms were detected in ST77, and only a few genes involved in photosynthesis and thylakoid functions were downregulated in ST111. Despite these differences, transgenic plants and seeds appeared phenotypically similar to non-transgenic controls. There was no correlation between recombinant protein expression level and the quantity of differentially expressed genes detected.

CONCLUSIONS

Measurable unscripted gene expression changes were detected in the seed transcriptomes of all three transgenic soybean lines analyzed, with line 764 being substantially altered. Differences detected at the transcript level may be due to T-DNA insert locations, random mutations following transformation or direct effects of the recombinant protein itself, or a combination of these. The physiological consequences of such changes remain unknown.

Metabolomics-Inspired Insight into Developmental, Environmental and Genetic Aspects of Tomato Fruit Chemical Composition and Quality

Tomato was one of the first plant species to be evaluated using metabolomics and remains one of the best characterized, with tomato fruit being both an important source of nutrition in the human diet and a valuable model system for the development of fleshy fruits. Additionally, given the broad habitat range of members of the tomato clade and the extensive use of exotic germplasm in tomato genetic research, it represents an excellent genetic model system for understanding both metabolism per se and the importance of various metabolites in conferring stress tolerance. This review summarizes technical approaches used to characterize the tomato metabolome to date and details insights into metabolic pathway structure and regulation that have been obtained via analysis of tissue samples taken under different developmental or environmental circumstance as well as following genetic perturbation. Particular attention is paid to compounds of importance for nutrition or the shelf-life of tomatoes. We propose furthermore how metabolomics information can be coupled to the burgeoning wealth of genome sequence data from the tomato clade to enhance further our understanding of (i) the shifts in metabolic regulation occurring during development and (ii) specialization of metabolism within the tomato clade as a consequence of either adaptive evolution or domestication.

Tomato Glutamate Decarboxylase Genes SlGAD2 and SlGAD3 Play Key Roles in Regulating γ-Aminobutyric Acid Levels in Tomato (Solanum lycopersicum)

Tomato (Solanum lycopersicum) can accumulate relatively high levels of γ-aminobutyric acid (GABA) during fruit development. However, the molecular mechanism underlying GABA accumulation and its physiological function in tomato fruits remain elusive. We previously identified three tomato genes (SlGAD1, SlGAD2 and SlGAD3) encoding glutamate decarboxylase (GAD), likely the key enzyme for GABA biosynthesis in tomato fruits. In this study, we generated transgenic tomato plants in which each SlGAD was suppressed and those in which all three SlGADs were simultaneously suppressed. A significant decrease in GABA levels, i.e. 50-81% compared with wild-type (WT) levels, was observed in mature green (MG) fruits of the SlGAD2-suppressed lines, while a more drastic reduction (up to <10% of WT levels) was observed in the SlGAD3- and triple SlGAD-suppressed lines. These findings suggest that both SlGAD2 and SlGAD3 expression are crucial for GABA biosynthesis in tomato fruits. The importance of SlGAD3 expression was also confirmed by generating transgenic tomato plants that over-expressed SlGAD3. The MG and red fruits of the over-expressing transgenic lines contained higher levels of GABA (2.7- to 5.2-fold) than those of the WT. We also determined that strong down-regulation of the SlGADs had little effect on overall plant growth, fruit development or primary fruit metabolism under normal growth conditions.

Using metabolomic approaches to explore chemical diversity in rice

Rice (Oryza sativa) is an excellent resource; it comprises 25% of the total caloric intake of the world's population, and rice plants yield many types of bioactive compounds. To determine the number of metabolites in rice and their chemical diversity, the metabolite composition of cultivated rice has been investigated with analytical techniques such as mass spectrometry (MS) and/or nuclear magnetic resonance spectroscopy and rice metabolite databases have been constructed. This review summarizes current knowledge on metabolites in rice including sugars, amino and organic acids, aromatic compounds, and phytohormones detected by gas chromatography-MS, liquid chromatography-MS, and capillary electrophoresis-MS. The biological properties and the activities of polar and nonpolar metabolites produced by rice plants are also presented. Challenges in the estimation of the structure(s) of unknown metabolites by metabolomic approaches are introduced and discussed. Lastly, examples are presented of the successful application of metabolite profiling of rice to characterize the gene(s) that are potentially critical for improving its quality by combining metabolite quantitative trait loci analysis and to identify potential metabolite biomarkers that play a critical role when rice is grown under abiotic stress conditions.

Metabolomics of genetically modified crops

Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

Metabolic differences in ripening of Solanum lycopersicum 'Ailsa Craig' and three monogenic mutants

Application of mass spectrometry enables the detection of metabolic differences between groups of related organisms. Differences in the metabolic fingerprints of wild-type Solanum lycopersicum and three monogenic mutants, ripening inhibitor (rin), non-ripening (nor) and Colourless non-ripening (Cnr), of tomato are captured with regard to ripening behaviour. A high-resolution tandem mass spectrometry system coupled to liquid chromatography produced a time series of the ripening behaviour at discrete intervals with a focus on changes post-anthesis. Internal standards and quality controls were used to ensure system stability. The raw data of the samples and reference compounds including study protocols have been deposited in the open metabolomics database MetaboLights via the metadata annotation tool Isatab to enable efficient re-use of the datasets, such as in metabolomics cross-study comparisons or data fusion exercises.

Evaluation of unintended effects in the composition of tomatoes expressing a human immunoglobulin A against rotavirus

The production of neutralizing immunoglobulin A (IgA) in edible fruits as a means of oral passive immunization is a promising strategy for the inexpensive treatment of mucosal diseases. This approach is based on the assumption that the edible status remains unaltered in the immunoglobulin-expressing fruit, and therefore extensive purification is not required for mucosal delivery. However, unintended effects associated with IgA expression such as toxic secondary metabolites and protein allergens cannot be dismissed a priori and need to be investigated. This paper describes a collection of independent transgenic tomato lines expressing a neutralizing human IgA against rotavirus, a mucosal pathogen producing severe diarrhea episodes. This collection was used to evaluate possible unintended effects associated with recombinant IgA expression. A comparative analysis of protein and secondary metabolite profiles using wild type lines and other commercial varieties failed to find unsafe features significantly associated with IgA expression. Preliminary, the data indicate that formulations derived from IgA tomatoes are as safe for consumption as equivalent formulations derived from wild type tomatoes.

Tools and databases of the KOMICS web portal for preprocessing, mining, and dissemination of metabolomics data

A metabolome—the collection of comprehensive quantitative data on metabolites in an organism—has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data.

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.

Conserved changes in the dynamics of metabolic processes during fruit development and ripening across species

Computational analyses of molecular phenotypes traditionally aim at identifying biochemical components that exhibit differential expression under various scenarios (e.g. environmental and internal perturbations) in a single species. High-throughput metabolomics technologies allow the quantification of (relative) metabolite levels across developmental stages in different tissues, organs, and species. Novel methods for analyzing the resulting multiple data tables could reveal preserved dynamics of metabolic processes across species. The problem we address in this study is 2-fold. (1) We derive a single data table, referred to as a compromise, which captures information common to the investigated set of multiple tables containing data on different fruit development and ripening stages in three climacteric (i.e. peach [Prunus persica] and two tomato [Solanum lycopersicum] cultivars, Ailsa Craig and M82) and two nonclimacteric (i.e. strawberry [Fragaria × ananassa] and pepper [Capsicum chilense]) fruits; in addition, we demonstrate the power of the method to discern similarities and differences between multiple tables by analyzing publicly available metabolomics data from three tomato ripening mutants together with two tomato cultivars. (2) We identify the conserved dynamics of metabolic processes, reflected in the data profiles of the corresponding metabolites that contribute most to the determined compromise. Our analysis is based on an extension to principal component analysis, called STATIS, in combination with pathway overenrichment analysis. Based on publicly available metabolic profiles for the investigated species, we demonstrate that STATIS can be used to identify the metabolic processes whose behavior is similarly affected during fruit development and ripening. These findings ultimately provide insights into the pathways that are essential during fruit development and ripening across species.

Network analysis for gene discovery in plant-specialized metabolism

Recent omics technologies provide information on multiple components of biological networks. Web-based data mining tools are continuously being developed. Because genes involved in specialized (secondary) metabolism are often co-ordinately regulated at the transcriptional level, a number of gene discovery studies have been successfully conducted using network analysis, especially by integrating gene co-expression network analysis and metabolomic investigation. In addition, next-generation sequencing technologies are currently utilized in functional genomics investigations of Arabidopsis and non-model plant species including medicinal plants. Systems-based approaches are expected to gain importance in medicinal plant research. This review discussed network analysis in Arabidopsis and gene discovery in plant-specialized metabolism in non-model plants.