Assessment of genetically modified soybean in relation to natural variation in the soybean seed metabolome

An Untargeted Metabolomics Approach to Study the Variation between Wild and Cultivated Soybeans

The differential metabolite profiles of four wild and ten cultivated soybeans genotypes were explored using an untargeted metabolomics approach. Ground soybean seed samples were extracted with methanol and water, and metabolic features were obtained using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) in both positive and negative ion modes. The UHPLC-HRMS analysis of the two different extracts resulted in the putative identification of 98 metabolites belonging to several classes of phytochemicals, including isoflavones, organic acids, lipids, sugars, amino acids, saponins, and other compounds. The metabolic profile was significantly impacted by the polarity of the extraction solvent. Multivariate analysis showed a clear difference between wild and cultivated soybean cultivars. Unsupervised and supervised learning algorithms were applied to mine the generated data and to pinpoint metabolites differentiating wild and cultivated soybeans. The key identified metabolites differentiating wild and cultivated soybeans were isoflavonoids, free amino acids, and fatty acids. Catechin analogs, cynaroside, hydroxylated unsaturated fatty acid derivatives, amino acid, and uridine diphosphate-N-acetylglucosamine were upregulated in the methanol extract of wild soybeans. In contrast, isoflavonoids and other minor compounds were downregulated in the same soybean extract. This metabolic information will benefit breeders and biotechnology professionals to develop value-added soybeans with improved quality traits.

Metabolome of flue-cured tobacco is significantly affected by the presence of leaf stem

BACKGROUND

Leaves of tobacco (Nicotiana tabacum L.) are flue-cured to use as a key industrial supply in various parts of the world. The quality of tobacco leaves is dependent on chemical components and their proportions. Generally, the stem attached to tobacco leaf is detached before curing. However, the leaf stem remains green for an extended period of time (as compared to leaf) during flue-curing. Hence, it is expected to affect the quality of tobacco's final product.

RESULTS

To understand the impact of the green stem of leaf on the metabolome of flue-cured tobacco, we employed a broad targeted metabolomics approach. We selected two tobacco cultivars (Yun87 and K326) and cultivated them in five geographic locations in China. For flue-curing, leaves were harvested without a stem (L) or with an attached stem (SPL). After metabolome analysis, a total of 1027 metabolites were annotated in these samples. A variable number of metabolites were differentially accumulated between both types of leaves (depending on geographic location or cultivar) representing an influence of environment or genotype. Interestingly, only 68 metabolites were differentially accumulated between L and SPL samples irrespective of the cultivar or geographic location. These differentially accumulated metabolites belonged to major groups of primary and secondary metabolites. We have discussed the importance of identified metabolites in terms of carbon, nitrogen, and polyphenolic metabolism.

CONCLUSION

The present research is the first comprehensive description of several metabolites in tobacco leaves related to the contribution of leaf stem. The current study opens novel prospects for investigating the potential of such metabolites in improving the quality of flue-cured tobacco.

Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement

Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.

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.

Quantitative Comparison and Chemical Profile of Different Botanical Parts of Panax notoginseng From Different Regions

The root of Panax notoginseng, a highly valued medicine and functional food, is the main part used for medicinal purposes. However, the stems and leaves are also used in practice. To provide a chemical basis for various uses, a quantitative comparison of 18 saponins using a non-targeted metabolomics approach was established, so as to investigate the chemical profiles of the different parts of P. notoginseng. The established strategy revealed that roots and stems, with their similar chemical characteristics, consisted mainly of protopanaxatriol-type saponins, whereas protopanaxadiol-type saponins were principally present in the leaves. Multivariate analysis further suggested that the quality of the stems and leaves of P. notoginseng was significantly affected by its geographical origin. Furthermore, 52 constituents (26 non-volatile and 26 volatile) were identified as potential markers for discriminating between different parts of the plant. Taken together, the study provides comprehensive chemical evidence for the rational application and exploitation of different parts of P. notoginseng.

Supervised Statistical Learning Prediction of Soybean Varieties and Cultivation Sites Using Rapid UPLC-MS Separation, Method Validation, and Targeted Metabolomic Analysis of 31 Phenolic Compounds in the Leaves

Soybean (Glycine max; SB) leaf (SL) is an abundant non-conventional edible resource that possesses value-adding bioactive compounds. We predicted the attributes of SB based on the metabolomes of an SL using targeted metabolomics. The SB was planted in two cities, and SLs were regularly obtained from the SB plant. Nine flavonol glycosides were purified from SLs, and a validated simultaneous quantification method was used to establish rapid separation by ultrahigh-performance liquid chromatography-mass detection. Changes in 31 targeted compounds were monitored, and the compounds were discriminated by various supervised machine learning (ML) models. Isoflavones, quercetin derivatives, and flavonol derivatives were discriminators for cultivation days, varieties, and cultivation sites, respectively, using the combined criteria of supervised ML models. The neural model exhibited higher prediction power of the factors with high fitness and low misclassification rates while other models showed lower. We propose that a set of phytochemicals of SL is a useful predictor for discriminating characteristics of edible plants.

Metabolomics as a Tool to Study Underused Soy Parts: In Search of Bioactive Compounds

The valorization of agri-food by-products is essential from both economic and sustainability perspectives. The large quantity of such materials causes problems for the environment; however, they can also generate new valuable ingredients and products which promote beneficial effects on human health. It is estimated that soybean production, the major oilseed crop worldwide, will leave about 597 million metric tons of branches, leaves, pods, and roots on the ground post-harvesting in 2020/21. An alternative for the use of soy-related by-products arises from the several bioactive compounds found in this plant. Metabolomics studies have already identified isoflavonoids, saponins, and organic and fatty acids, among other metabolites, in all soy organs. The present review aims to show the application of metabolomics for identifying high-added-value compounds in underused parts of the soy plant, listing the main bioactive metabolites identified up to now, as well as the factors affecting their production.

Plant Resistance in Some Modern Soybean Varieties May Favor Population Growth and Modify the Stylet Penetration of Bemisia tabaci (Hemiptera: Aleyrodidae)

Complaints of severe damage by whiteflies in soybean fields containing genetically engineered (GE) varieties led us to investigate the role of transgenic soybean varieties expressing resistance to some insects (Cry1Ac Bt toxin) and to herbicide (glyphosate) on the population growth and feeding behavior of Bemisia tabaci (Gennadius) MEAM1 (Hemiptera: Aleyrodidae). In the laboratory, the whiteflies reared on the GE Bt soybeans had a net reproductive rate (R0) 100% higher and intrinsic rate of population increase (rm) 15% higher than those reared on non-GE soybeans. The increased demographic performance was associated with a higher lifetime fecundity. In electrical penetration graphs, the whiteflies reared on the GE soybeans had fewer probes and spent 50% less time before reaching the phloem phase from the beginning of the first successful probe, indicating a higher risk of transmission of whitefly-borne viruses. Data from Neotropical fields showed a higher population density of B. tabaci on two soybean varieties expressing glyphosate resistance and Cry1Ac Bt toxin. These results indicate that some GE soybean varieties expressing insect and herbicide resistances can be more susceptible to whiteflies than non-GE ones or those only expressing herbicide resistance. Most likely, these differences are related to varietal features that increase host-plant susceptibility to whiteflies. Appropriate pest management may be needed to deal with whiteflies in soybean fields, especially in warm regions, and breeders may want to consider the issue when developing new soybean varieties.

Metabolic Analysis Reveals Cry1C Gene Transformation Does Not Affect the Sensitivity of Rice to Rice Dwarf Virus

Metabolomics is beginning to be used for assessing unintended changes in genetically modified (GM) crops. To investigate whether Cry1C gene transformation would induce metabolic changes in rice plants, and whether the metabolic changes would pose potential risks when Cry1C rice plants are exposed to rice dwarf virus (RDV), the metabolic profiles of Cry1C rice T1C-19 and its non-Bt parental rice MH63 under RDV-free and RDV-infected status were analyzed using gas chromatography–mass spectrometry (GC-MS). Compared to MH63 rice, slice difference was detected in T1C-19 under RDV-free conditions (less than 3%), while much more metabolites showed significant response to RDV infection in T1C-19 (15.6%) and in MH63 (5.0%). Pathway analysis showed biosynthesis of lysine, valine, leucine, and isoleucine may be affected by RDV infection in T1C-19. No significant difference in the contents of free amino acids (AAs) was found between T1C-19 and MH63 rice, and the free AA contents of the two rice plants showed similar responses to RDV infection. Furthermore, no significant differences of the RDV infection rates between T1C-19 and MH63 were detected. Our results showed the Cry1C gene transformation did not affect the sensitivity of rice to RDV, indicating Cry1C rice would not aggravate the epidemic and dispersal of RDV.

Evaluation of the use of untargeted metabolomics in the safety assessment of genetically modified crops

BACKGROUND

The safety assessment of foods and feeds from genetically modified (GM) crops includes the comparison of key characteristics, such as crop composition, agronomic phenotype and observations from animal feeding studies compared to conventional counterpart varieties that have a history of safe consumption, often including a near isogenic variety. The comparative compositional analysis of GM crops has been based on targeted, validated, quantitative analytical methods for the key food and feed nutrients and antinutrients for each crop, as identified by Organization of Economic Co-operation and Development (OCED). As technologies for untargeted metabolomic methods have evolved, proposals have emerged for their use to complement or replace targeted compositional analytical methods in regulatory risk assessments of GM crops to increase the number of analyzed metabolites.

AIM OF REVIEW

The technical opportunities, challenges and strategies of including untargeted metabolomics analysis in the comparative safety assessment of GM crops are reviewed. The results from metabolomics studies of GM and conventional crops published over the last eight years provide context to enable the discussion of whether metabolomics can materially improve the risk assessment of food and feed from GM crops beyond that possible by the Codex-defined practices used worldwide for more than 25 years.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Published studies to date show that environmental and genetic factors affect plant metabolomics profiles. In contrast, the plant biotechnology process used to make GM crops has little, if any consequence, unless the inserted GM trait is intended to alter food or feed composition. The nutritional value and safety of food and feed from GM crops is well informed by the quantitative, validated compositional methods for list of key analytes defined by crop-specific OECD consensus documents. Untargeted metabolic profiling has yet to provide data that better informs the safety assessment of GM crops than the already rigorous Codex-defined quantitative comparative assessment. Furthermore, technical challenges limit the implementation of untargeted metabolomics for regulatory purposes: no single extraction method or analytical technique captures the complete plant metabolome; a large percentage of metabolites features are unknown, requiring additional research to understand if differences for such unknowns affect food/feed safety; and standardized methods are needed to provide reproducible data over time and laboratories.

Applications of metabolomics in the research of soybean plant under abiotic stress

Qualitative and quantitative metabolomics analysis of all small-molecule metabolites in organisms is an emerging omics technology alongside genomics and proteomics. Plant metabolites are extremely diverse both within species and in terms of their physiological function. Plant metabolomics studies use mainly liquid/gas chromatography-mass spectrometry (LC/GC-MS) and nuclear magnetic resonance (NMR) techniques combined with chemometrics and multivariate statistical analysis to analyze plant metabolites, and metabolomics plays a key role in agricultural and food science research. In this review, we discuss the status of metabolomics in soybean in response to abiotic stresses such as drought, heat, salinity, flooding, chilling and heavy metal stresses and analyze the challenges and opportunities. Furthermore, the notable metabolites detected in response to different stresses are summarized to provide a reference for applications of metabolomics in soybean research.

Utilization of GC-MS untargeted metabolomics to assess the delayed response of glufosinate treatment of transgenic herbicide resistant (HR) buffalo grasses (Stenotaphrum secundatum L.)

INTRODUCTION

Herbicide resistant (HR) buffalo grasses were genetically engineered to resist the non-selective herbicide, glufosinate in order to facilitate a modern, 'weeding program' which is highly effective in terms of minimizing costs and labor. The resistant trait was conferred by an insertion of the pat gene to allow for the production of the enzyme phosphinothricin acetyltransferase (PAT) to detoxify the glufosinate inhibitive effect. To date, there are only a few reports using metabolomics as well as molecular characterizations published for glufosinate-resistant crops with no reports on HR turfgrass. Therefore, for the first time, this study examines the metabolome of glufosinate-resistant buffalo grasses which not only will be useful to future growers but also the scientific community.

OBJECTIVE

A major aim of this present work is to characterize and evaluate the metabolic alterations which may arise from a genetic transformation of HR buffalo grasses by comprehensively using gas chromatography-mass spectrometry (GC-MS) based untargeted metabolomics.

METHODS

Eight-week old plants of 4 HR buffalo grasses, (93-1A, 93-2B, 93-3C and 93-5A) and 3 wild type varieties (WT 8-4A, WT 9-1B and WT 9-1B) were selected for physiological, molecular and metabolomics experiments. Plants were either sprayed with 1, 5, 10 and 15% v/v of glufosinate to evaluate the visual injuries or submerged in 5% v/v of glufosinate 3 days prior to a GC-MS based untargeted metabolomics analysis. In contrast, the control group was treated with distilled water. Leaves were extracted in 1:1 methanol:water and then analysed, using an in-house GC-MS untargeted workflow.

RESULTS

Results identified 199 metabolites with only 6 of them (cis-aconitic acid, allantoin, cellobiose, glyceric acid, maltose and octadecanoic acid) found to be statistically significant (p < 0.05) between the HR and wild type buffalo grass varieties compared to the control experiment. Among these metabolites, unusual accumulation of allantoin was prominent and was an unanticipated effect of the pat gene insertion. As expected, glufosinate treatment caused significant metabolic alterations in the sensitive wild type, with the up-regulation of several amino acids (e.g. phenylalanine and isoleucine) which was likely due to glufosinate-induced senescence. The aminoacyl-tRNA biosynthetic pathway was identified as the most significant enriched pathway as a result of glufosinate effects because a number of its intermediates were amino acids.

CONCLUSION

HR buffalo grasses were very similar to its wild type comparator based on a comprehensive GC-MS based untargeted metabolomics and therefore, should guarantee the safe use of these HR buffalo grasses. The current metabolomics analyses not only confirmed the effects of glufosinate to up-regulate free amino acid pools in the sensitive wild type but also several alterations in sugar, sugar phosphate and organic acid metabolism have been reported.

Recent developments in metabolomics-based research in understanding transgenic grass metabolism

BACKGROUND

Transgenic herbicide-resistant (HR) turfgrass together with its associated, broad spectrum herbicides promise cheap, selective and efficient weed control by excluding infested weeds resulting in turf lawn with high uniformity and aesthetic value. The concept of this "weeding program" initiated from modern biotechnology has been widely implemented in several principal crops including maize, soybean, canola and cotton as early as the 1990s. Transgenic HR turfgrass classified as a genetically modified organism (GMO) has undoubtedly caused public concern with respect to its biosafety and legalities similar to well-established HR crops. Nevertheless, applying metabolomics-based approaches which focuses on the identification of the global metabolic state of a biological system in response to either internal or external stimuli can also provide a comprehensive characterization of transgenic grass metabolism and its involvement in biosecurity and public perception.

AIM OF REVIEW

This review summaries the recent applications of metabolomics applied to HR crops to predict the molecular and physiological phenotypes of HR turfgrass species, glyphosate-resistant Kentucky bluegrass (Poa pratensis L.) and glufosinate-resistant creeping bentgrass (Agrotis stonifera L.). Additionally, this review also presents background knowledge with respect to the application of metabolomics, transformation of HR crops and its biosafety concerns, turfgrass botanical knowledge and its economic and aesthetic value.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is to demonstrate the molecular and physiological phenotypes of HR turfgrass based on several lines of evidence primarily derived from metabolomics data applied to HR crops to identify alterations on HR turfgrass metabolism as a result of genetic modification that confers resistant traits.

Mechanism study of cyfluthrin biodegradation by Photobacterium ganghwense with comparative metabolomics

A high-efficiency pyrethroid-degrading bacterium, Photobacterium ganghwense strain 6046 (PGS6046), was first isolated from an offshore seawater environment. Metabolomics method was used to investigate the biotransformation pathway of PGS6046 to cyfluthrin wherein 156 metabolites were identified. The growth rates of the PGS6046 cultivated in nourishing media were much higher than those cultivated in seawater, regardless of the presence of cyfluthrin. Statistical analyses revealed that the metabolic profile of PGS6046 was associated with the culture medium, the presence of cyfluthrin, and culture time. The PGS6046 cultivated in a nourishing medium was characterized by higher levels of amino acids, a lower abundance of intermediates in the tricarboxylic acid cycle, and the presence of some fatty acids than those cultivated in seawater. The effects of cyfluthrin on PGS6046 metabolism varied based on the culture medium, whereas the cyanoalanine levels increased under both culture conditions. Culture time significantly affected the metabolism of amino acids and carbohydrates in PGS6046. The present study revealed the metabolic characteristics of PGS6046 under different culture conditions and will further facilitate the exploration of the fundamental questions regarding PGS6046 and its potential applications in environmental bioremediation.

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 profiles of Cuibi-1 and Zhongyan-100 flue-cured tobacco leaves in different growing regions by gas chromatography/mass spectrometry

The metabolic profiles of tobacco leaves of two differential Chinese cultivars from different growing regions were analysed using gas chromatography-mass spectrometry (GC-MS). The results of principal component analysis, partial least-squares discriminant analysis and hierarchical cluster analysis showed significant differences in metabolome among three groups, identified 24 differential metabolites, and analysed the metabolic pathway in which the metabolites were involved. Among them, 13 metabolites were associated with geographical regions, including seven organic and fatty acids, four carbohydrates and two secondary metabolites. Four amino acids and two monosaccharides were associated with cultivars and the remaining five metabolites were associated with both. The relationships among the differential metabolites and the distinct characteristics of environment and cultivar were further discussed. In addition, correlation analysis indicated that most of the differential carbohydrates were negatively correlated with the differential amino acids and organic acids. Taken together, this study demonstrates the metabolite differences between two cultivars in different regions, and highlights the effect of environment and cultivar on tobacco leaf metabolism.

Metabolic dynamics and physiological adaptation of Panax ginseng during development

The dynamics of metabolites from leaves to roots of Panax ginseng during development has revealed the tissue-specific and year-specific metabolic networks. Being an essential Oriental medicinal plant, ginseng (Panax ginseng Meyer) is a slow-growing perennial herb-accumulating pharmaceutically active metabolites such as ginsenosides in roots during growth. However, little is known about how ginseng plants survive in the harsh environments such as winter cold and summer heat for a longer period and accumulates those active metabolites as the plant grows. To understand the metabolic kinetics in both source and sink organs such as leaves and roots of ginseng plant, respectively, and to assess the changes in ginsenosides biosynthesis during ginseng growth, we investigated the metabolic profiles from leaves and roots of 1-, 4-, and 6-year-old field-grown ginseng plants. Using an integrated non-targeted metabolomic approach, we identified in total 348 primary and secondary metabolites, which provided us for the first time a global metabolomic assessment of ginseng during growth, and morphogenesis. Strikingly, the osmoprotectants and oxidized chemicals were highly accumulated in 4- and 6-year-old ginseng leaves suggested that ginseng develop a wide range of metabolic strategies to adapt unfavorable conditions as they mature. In 6-year-old plants, ginsenosides were decreased in leaves but increased in roots up to 1.2- to sixfold, supporting the view that there is a long-distance transport of ginsenosides from leaves to roots as ginseng plants mature. Our findings provide insights into the metabolic kinetics during the development of ginseng plant and this could complement the pharmacological importance of ginseng and its compounds according to their age.

Comparative Metabolomic Analysis of the Cambium Tissue of Non-transgenic and Multi-Gene Transgenic Poplar (Populus × euramericana 'Guariento')

Poplar, a model for woody plant research, is the most widely distributed tree species in the world. Metabolites are the basis of phenotypes, allowing an intuitive and effective understanding of biological processes and their mechanisms. However, metabolites in non-transgenic and multi-gene transgenic poplar remains poorly characterized, especially in regards of the influences on quantity and in the analysis of the relative abundance of metabolites after the introduction of multi stress-related genes. In this study, we investigated the cambium metabolomes of one non-transgenic (D5-0) and two multi-gene (vgb, SacB, ERF36, BtCry3A, and OC-I) transgenic lines (D5-20 and D5-21) of hybrid poplar (Populus × euramericana 'Guariento') using both gas chromatography-mass spectrometry (GC-MS) and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). We aimed to explore the effects of the exogenous genes on metabolite composition and to screen out metabolites with important biological functions. Finally, we identified 239 named metabolites and determined their relative abundance. Among these, 197 metabolites had a different abundance across the three lines. These methabolites spanned nine primary and 44 secondary metabolism pathways. Arginine and glutamate, as substrates and intermediates in nitrogen metabolism, and important in growth and stress-related processes, as well as sucrose, uridine diphosphate glucose, and their derivatives, precursors in cell wall pathways, and catechol, relevant to insect resistance, differed greatly between the genetically modified and non-transgenic poplar. These findings may provide a basis for further study of cambium metabolism, and fully understand metabolites associated with stress response.

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.

Metabolomic Profiling of Soybeans (Glycine max L.) Reveals the Importance of Sugar and Nitrogen Metabolism under Drought and Heat Stress

Soybean is an important crop that is continually threatened by abiotic stresses, especially drought and heat stress. At molecular levels, reduced yields due to drought and heat stress can be seen as a result of alterations in metabolic homeostasis of vegetative tissues. At present an incomplete understanding of abiotic stress-associated metabolism and identification of associated metabolites remains a major gap in soybean stress research. A study with a goal to profile leaf metabolites under control conditions (28/24 °C), drought [28/24 °C, 10% volumetric water content (VWC)], and heat stress (43/35 °C) was conducted in a controlled environment. Analyses of non-targeted metabolomic data showed that in response to drought and heat stress, key metabolites (carbohydrates, amino acids, lipids, cofactors, nucleotides, peptides and secondary metabolites) were differentially accumulated in soybean leaves. The metabolites for various cellular processes, such as glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway, and starch biosynthesis, that regulate carbohydrate metabolism, amino acid metabolism, peptide metabolism, and purine and pyrimidine biosynthesis, were found to be affected by drought as well as heat stress. Computationally based regulatory networks predicted additional compounds that address the possibility of other metabolites and metabolic pathways that could also be important for soybean under drought and heat stress conditions. Metabolomic profiling demonstrated that in soybeans, keeping up with sugar and nitrogen metabolism is of prime significance, along with phytochemical metabolism under drought and heat stress conditions.

Integration of omics approaches to understand oil/protein content during seed development in oilseed crops

Oilseed crops, especially soybean (Glycine max) and canola/rapeseed (Brassica napus), produce seeds that are rich in both proteins and oils and that are major sources of energy and nutrition worldwide. Most of the nutritional content in the seed is accumulated in the embryo during the seed filling stages of seed development. Understanding the metabolic pathways that are active during seed filling and how they are regulated are essential prerequisites to crop improvement. In this review, we summarize various omics studies of soybean and canola/rapeseed during seed filling, with emphasis on oil and protein traits, to gain a systems-level understanding of seed development. Currently, most (80-85%) of the soybean and rapeseed reference genomes have been sequenced (950 and 850 megabases, respectively). Parallel to these efforts, extensive omics datasets from different seed filling stages have become available. Transcriptome and proteome studies have detected preponderance of starch metabolism and glycolysis enzymes to be the possible cause of higher oil in B. napus compared to other crops. Small RNAome studies performed during the seed filling stages have revealed miRNA-mediated regulation of transcription factors, with the suggestion that this interaction could be responsible for transitioning the seeds from embryogenesis to maturation. In addition, progress made in dissecting the regulation of de novo fatty acid synthesis and protein storage pathways is described. Advances in high-throughput omics and comprehensive tissue-specific analyses make this an exciting time to attempt knowledge-driven investigation of complex regulatory pathways.

Characterization of factors underlying the metabolic shifts in developing kernels of colored maize

Elucidation of the metabolic pathways determining pigmentation and their underlying regulatory mechanisms in maize kernels is of high importance in attempts to improve the nutritional composition of our food. In this study, we compared dynamics in the transcriptome and metabolome between colored SW93 and white SW48 by integrating RNA-Seq and non-targeted metabolomics. Our data revealed that expression of enzyme coding genes and levels of primary metabolites decreased gradually from 11 to 21 DAP, corresponding well with the physiological change of developing maize kernels from differentiation through reserve accumulation to maturation, which was cultivar independent. A remarkable up-regulation of anthocyanin and phlobaphene pathway distinguished SW93 from SW48, in which anthocyanin regulating transcriptional factors (R1 and C1), enzyme encoding genes involved in both pathways and corresponding metabolic intermediates were up-regulated concurrently in SW93 but not in SW48. The shift from the shikimate pathway of primary metabolism to the flavonoid pathway of secondary metabolism, however, appears to be under posttranscriptional regulation. This study revealed the link between primary metabolism and kernel coloration, which facilitate further study to explore fundamental questions regarding the evolution of seed metabolic capabilities as well as their potential applications in maize improvement regarding both staple and functional foods.

Terpene metabolic engineering via nuclear or chloroplast genomes profoundly and globally impacts off-target pathways through metabolite signalling

The impact of metabolic engineering on nontarget pathways and outcomes of metabolic engineering from different genomes are poorly understood questions. Therefore, squalene biosynthesis genes FARNESYL DIPHOSPHATE SYNTHASE (FPS) and SQUALENE SYNTHASE (SQS) were engineered via the Nicotiana tabacum chloroplast (C), nuclear (N) or both (CN) genomes to promote squalene biosynthesis. SQS levels were ~4300-fold higher in C and CN lines than in N, but all accumulated ~150-fold higher squalene due to substrate or storage limitations. Abnormal leaf and flower phenotypes, including lower pollen production and reduced fertility, were observed regardless of the compartment or level of transgene expression. Substantial changes in metabolomes of all lines were observed: levels of 65-120 unrelated metabolites, including the toxic alkaloid nicotine, changed by as much as 32-fold. Profound effects of transgenesis on nontarget gene expression included changes in the abundance of 19 076 transcripts by up to 2000-fold in CN; 7784 transcripts by up to 1400-fold in N; and 5224 transcripts by as much as 2200-fold in C. Transporter-related transcripts were induced, and cell cycle-associated transcripts were disproportionally repressed in all three lines. Transcriptome changes were validated by qRT-PCR. The mechanism underlying these large changes likely involves metabolite-mediated anterograde and/or retrograde signalling irrespective of the level of transgene expression or end product, due to imbalance of metabolic pools, offering new insight into both anticipated and unanticipated consequences of metabolic engineering.

Proteomics and metabolomics analyses reveal the cucurbit sieve tube system as a complex metabolic space

The plant vascular system, and specifically the phloem, plays a pivotal role in allocation of fixed carbon to developing sink organs. Although the processes involved in loading and unloading of sugars and amino acids are well characterized, little information is available regarding the nature of other metabolites in the sieve tube system (STS) at specific sites along the pathway. Here, we elucidate spatial features of metabolite composition mapped with phloem enzymes along the cucurbit STS. Phloem sap (PS) was collected from the loading (source), unloading (apical sink region) and shoot-root junction regions of cucumber, watermelon and pumpkin. Our PS analyses revealed significant differences in the metabolic and proteomic profiles both along the source-sink pathway and between the STSs of these three cucurbits. In addition, metabolite profiles established for PS and vascular tissue indicated the presence of distinct compositions, consistent with the operation of the STS as a unique symplasmic domain. In this regard, at various locations along the STS we could map metabolites and their related enzymes to specific metabolic pathways. These findings are discussed with regard to the function of the STS as a unique and highly complex metabolic space within the plant vascular system.

Development of interspecies hybrids to increase ginseng biomass and ginsenoside yield

Interspecific hybrids between Panax ginseng and P. quinquefolius results in hybrid vigor and higher ginsenoside contents. Ginseng is one of the most important herbs with valued pharmaceutical effects contributing mainly by the presence of bioactive ginsenosides in the roots. However, ginseng industry is impeded largely by its biological properties, because ginseng plants are slow-growing perennial herbs with lower yield. To increase the ginseng yield and amounts of ginsenosides, we developed an effective ginseng production system using the F(1) progenies obtained from the interspecific reciprocal cross between two Panax species: P. ginseng and P. quinquefolius. Although hybrid plants show reduced male fertility, F(1) hybrids with the maternal origin either from P. ginseng or P. quinquefolius displayed heterosis; they had larger roots and higher contents of ginsenosides as compared with non-hybrid parental lines. Remarkably, the F(1) hybrids with the maternal origin of P. quinquefolius had much higher ginsenoside contents, especially ginsenoside Re and Rb1, than those with the maternal origin of P. ginseng. Additionally, non-targeted metabolomic profiling revealed a clear increase of a large number of primary and secondary metabolites including fatty acids, amino acids and ginsenosides in hybrid plants. To effectively identify the F(1) hybrids for the large-scale cultivation, we successfully developed a molecular marker detection system for discriminating F(1) reciprocal hybrids. In summary, this work provided a practical system for reciprocal hybrid ginseng production, which would facilitate the ginseng production in the future.

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.

RNA Interference for Functional Genomics and Improvement of Cotton (Gossypium sp.)

RNA interference (RNAi), is a powerful new technology in the discovery of genetic sequence functions, and has become a valuable tool for functional genomics of cotton (Gossypium sp.). The rapid adoption of RNAi has replaced previous antisense technology. RNAi has aided in the discovery of function and biological roles of many key cotton genes involved in fiber development, fertility and somatic embryogenesis, resistance to important biotic and abiotic stresses, and oil and seed quality improvements as well as the key agronomic traits including yield and maturity. Here, we have comparatively reviewed seminal research efforts in previously used antisense approaches and currently applied breakthrough RNAi studies in cotton, analyzing developed RNAi methodologies, achievements, limitations, and future needs in functional characterizations of cotton genes. We also highlighted needed efforts in the development of RNAi-based cotton cultivars, and their safety and risk assessment, small and large-scale field trials, and commercialization.

Metabolite Profiling of Soybean Seed Extracts from Near-Isogenic Low and Normal Phytate Lines Using Orthogonal Separation Strategies

Untargeted metabolomic profiling using liquid chromatography-mass spectrometry (LC-MS) was applied to lipid-depleted methanolic extracts of soybean seeds utilizing orthogonal chromatographic separations (reversed-phase and hydrophilic interaction) in both positive and negative ionization modes. Four near-isogenic lines (NILs) differing in mutations for two genes encoding highly homologous multidrug resistant proteins (MRPs) were evaluated. The double mutant exhibited a low phytate phenotype, whereas the other three NILs, the two single mutants and the wild type, did not. Principal component analysis (PCA) of the four LC-MS data sets fully separated the low phytate line from the other three. While the levels of neutral oligosaccharides were the same for all lines, there were significant metabolite differences residing in the levels of malonyl isoflavones, soyasaponins, and arginine. Two methanol-soluble polypeptides were also found as differing in abundance levels, one of which was identified as the allergen Gly m 1.

Food metabolomics: from farm to human

Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans.

Expanding Omics Resources for Improvement of Soybean Seed Composition Traits

Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with "omics" technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of "omics tools" is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in "omics" approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs.

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.

Quantitative comparison and metabolite profiling of saponins in different parts of the root of Panax notoginseng

Although both rhizome and root of Panax notoginseng are officially utilized as notoginseng in "Chinese Pharmacopoeia", individual parts of the root were differently used in practice. To provide chemical evidence for the differentiated usage, quantitative comparison and metabolite profiling of different portions derived from the whole root, as well as commercial samples, were carried out, showing an overall higher content of saponins in rhizome, followed by main root, branch root, and fibrous root. Ginsenoside Rb2 was proposed as a potential marker with a content of 0.5 mg/g as a threshold value for differentiating rhizome from other parts. Multivariate analysis of the metabolite profile further suggested 32 saponins as potential markers for the discrimination of different parts of notoginseng. Collectively, the study provided comprehensive chemical evidence for the distinct usage of different parts of notoginseng and, hence, is of great importance for the rational application and exploitation of individual parts of notoginseng.

Seed metabolomic study reveals significant metabolite variations and correlations among different soybean cultivars

Soybean [Glycine max (L.) Merr.] is one of the world's major crops, and soybean seeds are a rich and important resource for proteins and oils. While "omics" studies, such as genomics, transcriptomics, and proteomics, have been widely applied in soybean molecular research, fewer metabolomic studies have been conducted for large-scale detection of low molecular weight metabolites, especially in soybean seeds. In this study, we investigated the seed metabolomes of 29 common soybean cultivars through combined gas chromatography-mass spectrometry and ultra-performance liquid chromatography-tandem mass spectrometry. One hundred sixty-nine named metabolites were identified and subsequently used to construct a metabolic network of mature soybean seed. Among the 169 detected metabolites, 104 were found to be significantly variable in their levels across tested cultivars. Metabolite markers that could be used to distinguish genetically related soybean cultivars were also identified, and metabolite-metabolite correlation analysis revealed some significant associations within the same or among different metabolite groups. Findings from this work may potentially provide the basis for further studies on both soybean seed metabolism and metabolic engineering to improve soybean seed quality and yield.

Metabolic variation between japonica and indica rice cultivars as revealed by non-targeted metabolomics

Seed metabolites are critically important both for plant development and human nutrition; however, the natural variation in their levels remains poorly characterized. Here we profiled 121 metabolites in mature seeds of a wide panel Oryza sativa japonica and indica cultivars, revealing correlations between the metabolic phenotype and geographic origin of the rice seeds. Moreover, japonica and indica subspecies differed significantly not only in the relative abundances of metabolites but also in their corresponding metabolic association networks. These findings provide important insights into metabolic adaptation in rice subgroups, bridging the gap between genome and phenome, and facilitating the identification of genetic control of metabolic properties that can serve as a basis for the future improvement of rice quality via metabolic engineering.