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

Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds

Label-free quantitative proteomic (LFQ) and widely targeted metabolomic analyses were applied in the safety evaluation of three genetically modified (GM) maize varieties, BBL, BFL-1, and BFL-2, in addition to their corresponding non-GM parent maize. A total of 76, 40, and 25 differentially expressed proteins (DEPs) were screened out in BBL, BFL-1, and BFL-2, respectively, and their abundance compared was with that in their non-GM parents. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most of the DEPs participate in biosynthesis of secondary metabolites, biosynthesis of amino acids, and metabolic pathways. Metabolomic analyses revealed 145, 178, and 88 differentially accumulated metabolites (DAMs) in the BBL/ZH58, BFL-1/ZH58, and BFL-2/ZH58×CH72 comparisons, respectively. KEGG pathway enrichment analysis showed that most of the DAMs are involved in biosynthesis of amino acids, and in arginine and proline metabolism. Three co-DEPs and 11 co-DAMs were identified in the seeds of these GM maize lines. The proteomic profiling of seeds showed that the GM maize varieties were not dramatically different from their non-GM control. Similarly, the metabolomic profiling of seeds showed no dramatic changes in the GM/non-GM maize varieties compared with the GM/GM and non-GM/non-GM maize varieties. The genetic background of the transgenic maize was found to have some influence on its proteomic and metabolomic profiles.

Metabolomics based inferences to unravel phenolic compound diversity in cereals and its implications for human gut health

Background

Scope and approach

Key findings and conclusion

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Phenolic compounds are critical in avoiding metabolic disorders associated with oxidative stress.

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Breeding cereal crops to enrich phenolic compounds in grains contributes to personalized nutrition.

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A diet rich in cereal phenolics likely to increase human gut health, thereby lowering the risk of non-communicable illness.

Comparison of growth and aflatoxin B1 production profiles of Aspergillus flavus strains on conventional and isogenic GM-maize-based nutritional matrices

Maize grown in both North and South America are now predominantly genetically modified (GM) cultivars with some resistance to herbicide, pesticide, or both. There is little information on the relative colonisation and aflatoxin B₁ (AFB₁) production with maize meal-based nutritional matrices based on kernels of non-GM maize and isogenic GM-ones by strains of Aspergillus flavus. The objectives were to examine the effect of interacting conditions of temperature (25-35 °C) and water availability (0.99-0.90 water activity, a_w) on (a) mycelial growth, (b) AFB₁ production and (c) develop contour maps of optimum and marginal conditions of these parameters for four strains of A. flavus on three different non-GM and isogenic GM-maize based nutritional media. The growth of the four strains of A. flavus (three aflatoxigenic; one non-aflatoxigenic) was relatively similar in relation to the temperature × a_w conditions examined on both non-GM and GM-based matrices. Optimum growth overall was at 30-35 °C and 0.99 a_w for all four strains. Under water stress (0.90 a_w) growth was optimum at 35 °C. Statistically: non-GM, GM cultivars, temperature and a_w all significantly affected growth rates. For AFB₁ production, all single and interacting factors were statistically significant except for non-GM × GM cultivar. In conclusion, colonisation of GM- and non-GM nutritional sources was similar for the different A. flavus strains examined. The contour maps will be very useful for understanding the ecological niches for both toxigenic and non-toxigenic strains in the context of the competitive exclusion of those producing aflatoxins.

The utility of metabolomics as a tool to inform maize biology

With the rise of high-throughput omics tools and the importance of maize and its products as food and bioethanol, maize metabolism has been extensively explored. Modern maize is still rich in genetic and phenotypic variation, yielding a wide range of structurally and functionally diverse metabolites. The maize metabolome is also incredibly dynamic in terms of topology and subcellular compartmentalization. In this review, we examine a broad range of studies that cover recent developments in maize metabolism. Particular attention is given to current methodologies and to the use of metabolomics as a tool to define biosynthetic pathways and address biological questions. We also touch upon the use of metabolomics to understand maize natural variation and evolution, with a special focus on research that has used metabolite-based genome-wide association studies (mGWASs).

Widely Targeted Metabolomics Analysis Reveals Key Quality-Related Metabolites in Kernels of Sweet Corn

Sweet corn (Zea mays convar. saccharata var. rugosa) is a major economic vegetable crop. Different sweet corn cultivars vary largely in flavor, texture, and nutrition. The present study performed widely targeted metabolomics analysis based on the HPLC-MS/MS technology to analyze the metabolic profiles in three sweet corn cultivars widely grown in China. A total of 568 metabolites in the three sweet corn cultivars were detected, of which 262 differential metabolites significantly changed among cultivars. Carbohydrates, organic acids, and amino acids were the majority detected primary metabolites. Organic acids were mainly concentrated on shikimate, benzoic acids, and quinic acid with aromatic groups. And the essential amino acids for the human body, methionine and threonine, were highly accumulated in the high-quality cultivar. In addition, phenylpropanoids and alkaloids were the most enriched secondary metabolites while terpenes were low-detected in sweet corn kernels. We found that the flavonoids exist in both free form and glycosylated form in sweet corn kernels. PCA and HCA revealed clear separations among the three sweet corn cultivars, suggesting distinctive metabolome profiles among three cultivars. The differential metabolites were mapped into flavonoid biosynthesis, phenylpropanoid biosynthesis, biosynthesis of amino acids, and other pathways according to the KEGG classification. Furthermore, we identified skimmin, N',N^″-diferuloylspermidine, and 3-hydroxyanthranilic acid as the key quality-related metabolites related to grain quality traits in sweet corn. The results suggested variations of metabolic composition among the three cultivars, providing the reference quality-related metabolites for sweet corn breeding.

Integrated proteomics and metabolomics analysis of transgenic and gene-stacked maize line seeds

Unintended effects of genetically modified (GM) crops may pose safety issues. Omics techniques provide researchers with useful tools to assess such unintended effects. Proteomics and metabolomics analyses were performed for three GM maize varieties, 2A-7, CC-2, and 2A-7×CC-2 stacked transgenic maize, and the corresponding non-GM parent Zheng58.Proteomics revealed 120, 271 and 135 maize differentially expressed proteins (DEPs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most DEPs participated in metabolic pathways and the biosynthesis of secondary metabolite. Metabolomics revealed 179, 135 and 131 differentially accumulated metabolites (DAMs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Based on KEGG enrichment analysis, most DAMs are involved in the biosynthesis of secondary metabolite and metabolic pathways. According to integrated proteomics and metabolomics analysis, the introduction of exogenous EPSPS did not affect the expression levels of six other enzymes or the abundance of seven metabolites involved in the shikimic acid pathway in CC-2 and 2A-7×CC-2 seeds. Six co-DEPs annotated by integrated proteomics and metabolomics pathway analysis were further analyzed by qRT-PCR.This study successfully employed integrated proteomic and metabolomic technology to assess unintended changes in maize varieties. The results suggest that GM and gene stacking do not cause significantly unintended effects.

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.

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.

Comparative Proteomics of Phytase-transgenic Maize Seeds Indicates Environmental Influence is More Important than that of Gene Insertion

Proteomic differences were compared between phytase-transgenic (PT) maize seeds and nontransgenic (NT) maize seeds through two-dimensional electrophoresis (2-DE) with mass spectrometry (MS). When maize was grown under field conditions, 30 differentially accumulated proteins (DAPs) were successfully identified in PT seeds (PT/NT). Clusters of Orthologous Groups (COG) functional classification of these proteins showed that the largest group was associated with posttranslational modifications. To investigate the effects of environmental factors, we further compared the seed protein profiles of the same maize planted in a greenhouse or under field conditions. There were 76 DAPs between the greenhouse- and field-grown NT maize seeds and 77 DAPs between the greenhouse- and field-grown PT maize seeds However, under the same planting conditions, there were only 43 DAPs (planted in the greenhouse) or 37 DAPs (planted in the field) between PT and NT maize seeds. The results revealed that DAPs caused by environmental factors were more common than those caused by the insertion of exogenous genes, indicating that the environment has much more important effects on the seed protein profiles. Our maize seed proteomics results also indicated that the occurrence of unintended effects is not specific to genetically modified crops (GMCs); instead, such effects often occur in traditionally bred plants. Our data may be beneficial for biosafety assessments of GMCs at the protein profile level in the future.

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.

Impact of Crossing Parent and Environment on the Metabolite Profiles of Progenies Generated from a Low Phytic Acid Rice ( Oryza sativa L.) Mutant

The low phytic acid ( lpa) rice mutant Os-lpa-MH86-1, exhibiting a mutation-induced metabolite signature (i.e., increased levels of sugars, sugar alcohols, amino acids, phytosterols, and biogenic amines), was crossed with two commercial wild-type cultivars. The resulting progenies of generation F₈ harvested at three independent field trials were subjected to a GC/MS-based metabolite profiling approach. Statistical assessments via multivariate and univariate analyses demonstrated that the environment had a strong impact on the metabolite profiles of the resulting progenies. In addition, the metabolites of homozygous lpa progenies were significantly influenced by the lipid profiles of the wild-type cultivars employed as the crossing parents. However, for each individual field trial, both the lpa trait and the mutation-specific metabolite signature were consistently expressed in the homozygous lpa mutant progenies of the two crosses. The data underline that cross-breeding can be employed as a tool to generate lpa progeny rice seeds stably exhibiting the mutation-induced metabolic traits.

Detection and Identification of Genome Editing in Plants: Challenges and Opportunities

Conventional genetic engineering techniques generate modifications in the genome via stable integration of DNA elements which do not occur naturally in this combination. Therefore, the resulting organisms and (most) products thereof can unambiguously be identified with event-specific PCR-based methods targeting the insertion site. New breeding techniques such as genome editing diversify the toolbox to generate genetic variability in plants. Several of these techniques can introduce single nucleotide changes without integrating foreign DNA and thereby generate organisms with intended phenotypes. Consequently, such organisms and products thereof might be indistinguishable from naturally occurring or conventionally bred counterparts with established analytical tools. The modifications can entirely resemble random mutations regardless of being spontaneous or induced chemically or via irradiation. Therefore, if an identification of these organisms or products thereof is demanded, a new challenge will arise for (official) seed, food, and feed testing laboratories and enforcement institutions. For detailed consideration, we distinguish between the detection of sequence alterations - regardless of their origin - the identification of the process that generated a specific modification and the identification of a genotype, i.e., an organism produced by genome editing carrying a specific genetic alteration in a known background. This article briefly reviews the existing and upcoming detection and identification strategies (including the use of bioinformatics and statistical approaches) in particular for plants developed with genome editing techniques.

Statistical study on the environmental effects on the natural variation of nutritional components in rice varieties

This study was investigated to compare the natural variation of nutrients in rice variety by different environmental factors. Fifteen kinds of rices were used, which were cultivated in two locations for 2 years. All data were analyzed by the various statistical tools to identify the nutritional variations of nutrients. The results of variable importance in the prediction analysis were found to be consistent with the % variability. The nutrient compositions most affected by variety were fatty acids, and next were vitamins, proximate nutrients, minerals, and amino acids in order. The nutrient compositions most affected by location were proximate, followed by minerals, vitamins, fatty acids, and amino acids. For cultivation year, vitamins were most affected and then minerals, fatty acids, proximate nutrients, and amino acids in order. These findings could explain that each kind of nutrients can be naturally varied by different environmental factors.

Comments on two recent publications on GM maize and Roundup

Two -omics studies on genetically modified maize and Roundup-fed rats, recently published in the journal Scientific Reports, contain serious flaws in the experimental design, methodology and interpretation of results, which we point out here. The use of -omics technologies are of increasing importance in research, however we argue for a cautious approach to the potential application in food safety assessments as these exceptionally sensitive and complex methods require a thorough and detailed evaluation of the biological significance of obtained results. Arising from: Mesnage et al. Sci Rep 7:39328 (2017), Mesnage et al. Sci Rep 6:37855 (2016).

Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures

The objective of this study was to quantitatively assess potato omics profiles of new varieties for meaningful differences from analogous profiles of commercial varieties through the SIMCA one-class classification model. Analytical profiles of nine commercial potato varieties, eleven experimental potato varieties, one GM potato variety that had acquired Phytophtora resistance based on a single insert with potato-derived DNA sequences, and its non-GM commercial counterpart were generated. The ten conventional varieties were used to construct the one-class model. Omics profiles from experimental non-GM and GM varieties were assessed using the one-class SIMCA models. No potential unintended effects were identified in the case of the GM variety. The model showed that varieties that were genetically more distant from the commercial varieties were recognized as aberrant, highlighting its potential in determining whether additional evaluation is required for the risk assessment of materials produced from any breeding technique, including genetic modification.

Characterization of GMO or glyphosate effects on the composition of maize grain and maize-based diet for rat feeding

INTRODUCTION

In addition to classical targeted biochemical analyses, metabolomic analyses seem pertinent to reveal expected as well as unexpected compositional differences between plant genetically modified organisms (GMO) and non-GMO samples. Data previously published in the existing literature led to divergent conclusions on the effect of maize transgenes on grain compositional changes and feeding effects. Therefore, a new study examining field-grown harvested products and feeds derived from them remains useful.

OBJECTIVES

Our aim was to use a metabolomics approach to characterize grain and grain-based diet compositional changes for two GMO events, one involving Bacillus thuringiensis toxin to provide insect resistance and the other one conferring herbicide tolerance by detoxification of glyphosate. We also investigated the potential compositional modifications induced by the use of a glyphosate-based herbicide on the transgenic line conferring glyphosate tolerance.

RESULTS

The majority of statistically significant differences in grain composition, evidenced by the use of 1H-NMR profiling of polar extracts and LC-ESI-QTOF-MS profiling of semi-polar extracts, could be attributed to the combined effect of genotype and environment. In comparison, transgene and glyphosate effects remained limited in grain for the compound families studied. Some but not all compositional changes observed in grain were also detected in grain-based diets formulated for rats.

CONCLUSION

Only part of the data previously published in the existing literature on maize grains of plants with the same GMO events could be reproduced in our experiment. All spectra have been deposited in a repository freely accessible to the public. Our grain and diet characterization opened the way for an in depth study of the effects of these diets on rat health.

Deciphering drought-induced metabolic responses and regulation in developing maize kernels

Drought stress conditions decrease maize growth and yield, and aggravate preharvest aflatoxin contamination. While several studies have been performed on mature kernels responding to drought stress, the metabolic profiles of developing kernels are not as well characterized, particularly in germplasm with contrasting resistance to both drought and mycotoxin contamination. Here, following screening for drought tolerance, a drought-sensitive line, B73, and a drought-tolerant line, Lo964, were selected and stressed beginning at 14 days after pollination. Developing kernels were sampled 7 and 14 days after drought induction (DAI) from both stressed and irrigated plants. Comparative biochemical and metabolomic analyses profiled 409 differentially accumulated metabolites. Multivariate statistics and pathway analyses showed that drought stress induced an accumulation of simple sugars and polyunsaturated fatty acids and a decrease in amines, polyamines and dipeptides in B73. Conversely, sphingolipid, sterol, phenylpropanoid and dipeptide metabolites accumulated in Lo964 under drought stress. Drought stress also resulted in the greater accumulation of reactive oxygen species (ROS) and aflatoxin in kernels of B73 in comparison with Lo964 implying a correlation in their production. Overall, field drought treatments disordered a cascade of normal metabolic programming during development of maize kernels and subsequently caused oxidative stress. The glutathione and urea cycles along with the metabolism of carbohydrates and lipids for osmoprotection, membrane maintenance and antioxidant protection were central among the drought stress responses observed in developing kernels. These results also provide novel targets to enhance host drought tolerance and disease resistance through the use of biotechnologies such as transgenics and genome editing.

UPLC-QTOF-MS metabolomics analysis revealed the contributions of metabolites to the pathogenesis of Rhizoctonia solani strain AG-1-IA

To explore the pathogenesis of Rhizoctonia solani and its phytotoxin phenylacetic acid (PAA) on maize leaves and sheaths, treated leaf and sheath tissues were analyzed and interpreted by ultra-performance liquid chromatography-mass spectrometry combined with chemometrics. The PAA treatment had similar effects to those of R. solani on maize leaves regarding the metabolism of traumatin, phytosphingosine, vitexin 2'' O-beta-D-glucoside, rutin and DIBOA-glucoside, which were up-regulated, while the synthesis of OPC-8:0 and 12-OPDA, precursors for the synthesis of jasmonic acid, a plant defense signaling molecule, was down-regulated under both treatments. However, there were also discrepancies in the influences exhibited by R. solani and PAA as the metabolic concentration of zeaxanthin diglucoside in the R. solani infected leaf group decreased. Conversely, in the PAA-treated leaf group, the synthesis of zeaxanthin diglucoside was enhanced. Moreover, although the synthesis of 12 metabolites were suppressed in both the R. solani- and PAA-treated leaf tissues, the inhibitory effect of R. solani was stronger than that of PAA. An increased expression of quercitrin and quercetin 3-O-glucoside was observed in maize sheaths treated by R. solani, while their concentrations were not changed significantly in the PAA-treated sheaths. Furthermore, a significant decrease in the concentration of L-Glutamate, which plays important roles in plant resistance to necrotrophic pathogens, only occurred in the R. solani-treated sheath tissues. The differentiated metabolite levels may be the partial reason of why maize sheaths were more susceptible to R. solani than leaves and may explain the underlying mechanisms of R. solani pathogenesis.

Differential regulation of volatile emission from Eucalyptus globulus leaves upon single and combined ozone and wounding treatments through recovery and relationships with ozone uptake

Both ozone and wounding constitute two key abiotic stress factors, but their interactive effects on plant constitutive and stress-elicited volatile (VOC) emissions are poorly understood. Furthermore, the information on time-dependent modifications in VOC release during recovery from a combined stress is very limited. We studied the modifications in photosynthetic characteristics and constitutive and stress-induced volatile emissions in response to single and combined applications of acute ozone (4, 5, and 6 ppm) and wounding treatments through recovery (0.5-75 h) in a constitutive isoprene and mono- and sesquiterpene emitter Eucalyptus globulus. Overall, the photosynthetic characteristics were surprisingly resistant to all ozone and wounding treatments. Constitutive isoprene emissions were strongly upregulated by ozone and combined ozone and wounding treatments and remained high through recovery phase, but wounding applied alone reduced isoprene emission. All stress treatments enhanced emissions of lipoxygenase pathway volatiles (LOX), mono- and sesquiterpenes, saturated aldehydes (C7-C10), benzenoids, and geranylgeranyl diphosphate (GGDP) pathway volatiles. Once elicited, GGDP volatile, saturated aldehyde and benzenoid emissions remained high through the recovery period. In contrast, LOX emissions, and total mono- and sesquiterpene emissions decreased through recovery period. However, secondary rises in total sesquiterpene emissions at 75 h and in total monoterpenes at 25-50 h were observed. Overall, acute ozone and wounding treatments synergistically altered gas exchange characteristics and stress volatile emissions. Through the treatments and recovery period, stomatal ozone uptake rate and volatile emission rates were poorly correlated, reflecting possible ozone-scavenging effect of volatiles and thus, reduction of effective ozone dose and elicitation of induced defense by the acute ozone concentrations applied. These results underscore the important role of interactive stresses on both constitutive and induced volatile emission responses.

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.

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.

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.

An integrated multi-omics analysis of the NK603 Roundup-tolerant GM maize reveals metabolism disturbances caused by the transformation process

Glyphosate tolerant genetically modified (GM) maize NK603 was assessed as 'substantially equivalent' to its isogenic counterpart by a nutrient composition analysis in order to be granted market approval. We have applied contemporary in depth molecular profiling methods of NK603 maize kernels (sprayed or unsprayed with Roundup) and the isogenic corn to reassess its substantial equivalence status. Proteome profiles of the maize kernels revealed alterations in the levels of enzymes of glycolysis and TCA cycle pathways, which were reflective of an imbalance in energy metabolism. Changes in proteins and metabolites of glutathione metabolism were indicative of increased oxidative stress. The most pronounced metabolome differences between NK603 and its isogenic counterpart consisted of an increase in polyamines including N-acetyl-cadaverine (2.9-fold), N-acetylputrescine (1.8-fold), putrescine (2.7-fold) and cadaverine (28-fold), which depending on context can be either protective or a cause of toxicity. Our molecular profiling results show that NK603 and its isogenic control are not substantially equivalent.

Changes of primary and secondary metabolites in barley plants exposed to CdO nanoparticles

The environmental fate of airborne nanoparticles and their toxicity to plants is not yet fully understood. Pot-grown barley plants with second leaves developed were therefore exposed to CdO nanoparticles (CdONPs) of ecologically relevant size (7-60 nm) and concentration (2.03 ± 0.45 × 10⁵ particles cm^-3) in air for 3 weeks. An experiment was designed to test the effects of different treatments when only leaves (T1); leaves and soil substrate (T2); and leaves, soil, and water supply were exposed to nanoparticles (T3). A fourth, control group of plants was left without treatment (T0). Although CdONPs were directly absorbed by leaves from the air, a part of leaf-allocated Cd was also transported from roots by transpiration flow. Chromatographic assays revealed that CdONPs had a significant effect on total content of primary metabolites (amino acids and saccharides) but no significant effect on total content of secondary metabolites (phenolic compounds, Krebs cycle acids, and fatty acids). In addition, the compositions of individual metabolite classes were affected by CdONP treatment. For example, tryptophan and phenylalanine were the most affected amino acids in both analysed organs, while ferulic acid and isovitexin constituted the polyphenols most affected in leaves. Even though CdONP treatment had no effect on total fatty acids content, there were significant changes in the composition of saturated and unsaturated fatty acids in both the roots and leaves of treated plants. Although the results indicate the most pronounced effect in T3 plants as compared to T1 and T2 plants, even just leaf exposure to CdONPs has the potential to induce changes in plant metabolism.

Effect of the environment on the secondary metabolic profile of Tithonia diversifolia: a model for environmental metabolomics of plants

Tithonia diversifolia is an invasive weed commonly found in tropical ecosystems. In this work, we investigate the influence of different abiotic environmental factors on the plant's metabolite profile by multivariate statistical analyses of spectral data deduced by UHPLC-DAD-ESI-HRMS and NMR methods. Different plant part samples of T. diversifolia which included leaves, stems, roots, and inflorescences were collected from two Brazilian states throughout a 24-month period, along with the corresponding monthly environmental data. A metabolomic approach employing concatenated LC-MS and NMR data was utilised for the first time to study the relationships between environment and plant metabolism. A seasonal pattern was observed for the occurrence of metabolites that included sugars, sesquiterpenes lactones and phenolics in the leaf and stem parts, which can be correlated to the amount of rainfall and changes in temperature. The distribution of the metabolites in the inflorescence and root parts were mainly affected by variation of some soil nutrients such as Ca, Mg, P, K and Cu. We highlight the environment-metabolism relationship for T. diversifolia and the combined analytical approach to obtain reliable data that contributed to a holistic understanding of the influence of abiotic environmental factors on the production of metabolites in various plant parts.

Metabolomic Assessment of Key Maize Resources: GC-MS and NMR Profiling of Grain from B73 Hybrids of the Nested Association Mapping (NAM) Founders and of Geographically Diverse Landraces

The present study expands metabolomic assessments of maize beyond commercial lines to include two sets of hybrids used extensively in the scientific community. One set included hybrids derived from the nested association mapping (NAM) founder lines, a collection of 25 inbreds selected on the basis of genetic diversity and used to investigate the genetic basis of complex plant traits. A second set included 24 hybrids derived from a collection of landraces representative of native diversity from North and South America that may serve as a source of new alleles for improving modern maize hybrids. Metabolomic analysis of grain harvested from these hybrids utilized gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) and (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) techniques. Results highlighted extensive metabolomic variation in grain from both hybrid sets, but also demonstrated that, within each hybrid set, subpopulations could be differentiated in a pattern consistent with the known genetic and compositional variation of these lines. Correlation analysis did not indicate a strong association of the metabolomic data with grain nutrient composition, although some metabolites did show moderately strong correlations with agronomic features such as plant and ear height. Overall, this study provides insights into the extensive metabolomic diversity associated with conventional maize germplasm.

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.

Evaluation of metabolomics profiles of grain from maize hybrids derived from near-isogenic GM positive and negative segregant inbreds demonstrates that observed differences cannot be attributed unequivocally to the GM trait

INTRODUCTION

Past studies on plant metabolomes have highlighted the influence of growing environments and varietal differences in variation of levels of metabolites yet there remains continued interest in evaluating the effect of genetic modification (GM).

OBJECTIVES

Here we test the hypothesis that metabolomics differences in grain from maize hybrids derived from a series of GM (NK603, herbicide tolerance) inbreds and corresponding negative segregants can arise from residual genetic variation associated with backcrossing and that the effect of insertion of the GM trait is negligible.

METHODS

Four NK603-positive and negative segregant inbred males were crossed with two different females (testers). The resultant hybrids, as well as conventional comparator hybrids, were then grown at three replicated field sites in Illinois, Minnesota, and Nebraska during the 2013 season. Metabolomics data acquisition using gas chromatography-time of flight-mass spectrometry (GC-TOF-MS) allowed the measurement of 367 unique metabolite features in harvested grain, of which 153 were identified with small molecule standards. Multivariate analyses of these data included multi-block principal component analysis and ANOVA-simultaneous component analysis. Univariate analyses of all 153 identified metabolites was conducted based on significance testing (α = 0.05), effect size evaluation (assessing magnitudes of differences), and variance component analysis.

RESULTS

Results demonstrated that the largest effects on metabolomic variation were associated with different growing locations and the female tester. They further demonstrated that differences observed between GM and non-GM comparators, even in stringent tests utilizing near-isogenic positive and negative segregants, can simply reflect minor genomic differences associated with conventional back-crossing practices.

CONCLUSION

The effect of GM on metabolomics variation was determined to be negligible and supports that there is no scientific rationale for prioritizing GM as a source of variation.

Effect of genetic and climatic variability on the metabolic profiles of black gram (Vigna mungo L.) seeds and sprouts

BACKGROUND

Black gram is becoming increasingly of interest for consumers worldwide. The metabolomics have been conducted to reflect the life history of each individual plant. The metabolic pattern of black gram seeds and sprouts was profiled to investigate genetic and climatic influences on a broad range of chemical constituents.

RESULTS

Distinct differences in metabolite profiles among three black gram varieties for both intact seeds and sprouts were observed. The differential impact of climate on metabolite profiles of the variety Chai Nat 80 during both dry and rainy seasons was investigated. Univariate statistical analysis demonstrated that greater maturity due to adequate moisture in the rainy season led to a higher content of nutritionally relevant polar metabolites, whereas the dry season resulted in a high relative amount of storage lipid because of immaturity due to insufficient rain and water supply.

CONCLUSION

The investigation confirmed the potential of metabolite profiling to assist in breeding and farming practices.

Insect-protected event DAS-81419-2 soybean (Glycine max L.) grown in the United States and Brazil is compositionally equivalent to nontransgenic soybean

The transgenic soybean event DAS-81419-2 contains genes that encode the Cry1F, Cry1Ac, and PAT proteins. Cry1F and Cry1Ac provide protection against key lepidopteran insect pests, while PAT confers tolerance to the herbicide glufosinate. To satisfy regulatory requirements for the safety evaluation of transgenic crops, studies were conducted in the United States and Brazil to evaluate the nutrient and antinutrient composition of event DAS-81419-2 soybean. On the basis of the results of these studies, event DAS-81419-2 soybean is compositionally equivalent to nontransgenic soybean. This conclusion concurs with numerous other published studies in soybean and other crops where compositional equivalence between the transgenic crop and its nontransgenic comparator has been demonstrated.

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.

Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat

Transferring the knowledge bases between related species may assist in enlarging the yield potential of crop plants. Being cereals, rice and wheat share a high level of gene conservation; however, they differ at metabolic levels as a part of the environmental adaptation resulting in different yield capacities. This review focuses on the current understanding of genetic and molecular regulation of yield-associated traits in both crop species, highlights the similarities and differences and presents the putative knowledge gaps. We focus on the traits associated with phenology, photosynthesis, and assimilate partitioning and lodging resistance; the most important drivers of yield potential. Currently, there are large knowledge gaps in the genetic and molecular control of such major biological processes that can be filled in a translational biology approach in transferring genomics and genetics informations between rice and wheat.

Tempest in a tea pot: How did the public conversation on genetically modified crops drift so far from the facts?

The debate over genetically modified (GM) crops has raged in Europe since 1996, but had barely risen above a whisper in the USA until recent labeling debates raised public attention. This article will explain GM crops and traits discuss safety assessment provide a view on safety from authoritative organizations discuss selected issues of current debate, and provide the author's perspective as to why the public debate has drifted so far from scientific reality. The economic and environmental benefits of GM crops are beyond scope, but references are provided. GM food and feed undergo comprehensive assessments using recognized approaches to assure they are as safe as the conventional congener. Issues of food safety and nutrition, unrelated to the GM process, may arise when GM foods display novel components or composition. Unanticipated genetic effects in GM crops appear to be limited in contrast to existing variations among conventional varieties resulting from breeding, mutation, and natural mobile genetic elements. Allergenic potential is assessed when selecting genes for introduction into GM crops and remains a theoretical risk to date. Emerging weed and insect resistance is not unique to GM technology and will require the use of integrated pest management/best practices for pest control. Gene flow from GM crops to wild relatives is limited by existing biological barriers but can at time be a relevant consideration in gene selection and planting practices. Insect-resistant GM crops have significantly reduced use of chemical insecticides and appear to have reduced the incidence of pesticide poisoning in areas where small scale farming and hand application are common. Changes in herbicide patterns are more complex and are evolving over time in response to weed resistance management needs. Recent public debate is driven by a combination of unfounded allegations about the technology and purveyors, pseudoscience, and attempts to apply a strict precautionary principle.

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.

Unintended compositional changes in genetically modified (GM) crops: 20 years of research

The compositional equivalency between genetically modified (GM) crops and nontransgenic comparators has been a fundamental component of human health safety assessment for 20 years. During this time, a large amount of information has been amassed on the compositional changes that accompany both the transgenesis process and traditional breeding methods; additionally, the genetic mechanisms behind these changes have been elucidated. After two decades, scientists are encouraged to objectively assess this body of literature and determine if sufficient scientific uncertainty still exists to continue the general requirement for these studies to support the safety assessment of transgenic crops. It is concluded that suspect unintended compositional effects that could be caused by genetic modification have not materialized on the basis of this substantial literature. Hence, compositional equivalence studies uniquely required for GM crops may no longer be justified on the basis of scientific uncertainty.

Metabolomics in plant environmental physiology

Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants. When study is in reference to analysing samples that are relevant to environmental or ecologically based hypotheses, it is termed 'environmental metabolomics'. The emergence of environmental metabolomics as one of the latest of the omics technologies has been one of the most critically important recent developments in plant physiology. Its applications broach the entire landscape of plant ecology, from the understanding of plant plasticity and adaptation through to community composition and even genetic modification in crops. The multitude of novel studies published utilizing metabolomics methods employ a variety of techniques, from the initial stages of tissue sampling, through to sample preservation, transportation, and analysis. This review introduces the concept and applications of plant environmental metabolomics as an ecologically important investigative tool. It examines the main techniques used in situ within field sites, with particular reference to sampling and processing, and those more appropriate for use in laboratory-based settings with emphasis on secondary metabolite analysis.

Assessment of GE food safety using '-omics' techniques and long-term animal feeding studies

Despite the fact that a thorough, lengthy and costly evaluation of genetically engineered (GE) crop plants (including compositional analysis and toxicological tests) is imposed before marketing some European citizens remain sceptical of the safety of GE food and feed. In this context, are additional tests necessary? If so, what can we learn from them? To address these questions, we examined data from 60 recent high-throughput '-omics' comparisons between GE and non-GE crop lines and 17 recent long-term animal feeding studies (longer than the classical 90-day subchronic toxicological tests), as well as 16 multigenerational studies on animals. The '-omics' comparisons revealed that the genetic modification has less impact on plant gene expression and composition than that of conventional plant breeding. Moreover, environmental factors (such as field location, sampling time, or agricultural practices) have a greater impact than transgenesis. None of these '-omics' profiling studies has raised new safety concerns about GE varieties; neither did the long-term and multigenerational studies on animals. Therefore, there is no need to perform such long-term studies in a case-by-case approach, unless reasonable doubt still exists after conducting a 90-day feeding test. In addition, plant compositional analysis and '-omics' profiling do not indicate that toxicological tests should be mandatory. We discuss what complementary fundamental studies should be performed and how to choose the most efficient experimental design to assess risks associated with new GE traits. The possible need to update the current regulatory framework is discussed.

Effects of genetics and environment on the metabolome of commercial maize hybrids: a multisite study

This study was designed to elucidate the biological variation in expression of many metabolites due to environment, genotype, or both, and to investigate the potential utility of metabolomics to supplement compositional analysis for substantial equivalence assessments of genetically modified (GM) crops. A total of 654 grain and 695 forage samples from 50 genetically diverse non-GM DuPont Pioneer maize hybrids grown at six locations in the U.S. and Canada were analyzed by coupled gas chromatography time-of-flight-mass spectrometry (GC/TOF-MS). A total of 156 and 185 metabolites were measured in grain and forage samples, respectively. Univariate and multivariate statistical analyses were employed extensively to compare and correlate the metabolite profiles. We show that the environment had far more impact on the forage metabolome compared to the grain metabolome, and the environment affected up to 50% of the metabolites compared to less than 2% by the genetic background. The findings from this study demonstrate that the combination of GC/TOF-MS metabolomics and comprehensive multivariate statistical analysis is a powerful approach to identify the sources of natural variation contributed by the environment and genotype.

Metabolomics in food science

Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science.