Phytic Acid Contents and Metabolite Profiles of Progenies from Crossing Low Phytic Acid OsMIK and OsMRP5 Rice (Oryza sativa L.) Mutants

The impact of cross-breeding two low phytic acid (lpa) rice mutants on the content of phytic acid and the metabolite profile of the resulting double mutant was investigated. Progenies resulting from the cross of Os-lpa-XS110-1, a rice mutant carrying the myo-inositol kinase (OsMIK) mutated gene, and Os-lpa-XS110-2, with the multidrug resistance-associated protein ABC transporter gene 5 (OsMRP5) as the mutation target, were subjected to high-pressure ion chromatography. The reduction of the phytic acid content in the double mutant (-63%) was much more pronounced than in the single mutants (-26 and -47%). Gas chromatography-based metabolite profiling revealed a superimposition of the metabolite profiles inherited from the lpa progenitors in the double mutant progenies; the resulting metabolite signature was predominated by the OsMIK mutation effect. The study demonstrated that cross-breeding of two single lpa mutants can be employed to generate double lpa rice mutants showing both a significant reduction in the content of phytic acid and the imprinting of a specific mutation-induced metabolite signature.

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.

Stability of the Metabolite Signature Resulting from the OsSULTR3;3 Mutation in Low Phytic Acid Rice ( Oryza sativa L.) Seeds upon Cross-breeding

The low phytic acid ( lpa) rice ( Oryza sativa L.) mutant Os-lpa-MH86-1, resulting from the mutation of the putative sulfate transporter gene OsSULTR3;3, was crossed with a commercial rice cultivar. The obtained progenies of generations F₄ to F₇ were subjected to a nontargeted metabolite profiling approach allowing the analyses of a broad spectrum of lipophilic and hydrophilic low-molecular-weight constituents. The metabolite profiles of the homozygous lpa progenies were characterized not only by a decreased concentration of phytic acid but also by increased contents of constituents from various classes, such as sugars, sugar alcohols, amino acids, phytosterols, and biogenic amines. Statistical assessments of the data via multivariate and univariate approaches demonstrated that this mutation-induced metabolite signature was nearly unaffected by the cross-breeding step and consistently expressed over several generations. The data demonstrate that even for complex metabolic changes resulting from a mutation, cross-breeding can be employed as a tool to generate progeny rice seeds stably exhibiting the mutation induced traits.

Quantitative profiling of polar primary metabolites of two chickpea cultivars with contrasting responses to salinity

This study reports a GC-QqQ-MS method for the quantification of forty-eight primary metabolites from four major classes (sugars, sugar acids, sugar phosphates, and organic acids) which can be applied to a number of biological systems. The method was validated in terms of linearity, reproducibility and recovery, using both calibration standards and real samples. Additionally, twenty-eight biogenic amines and amino acids were quantified using an established LC-QqQ-MS method. Both GC-QqQ-MS and LC-QqQ-MS quantitative methods were applied to plant extracts from flower and pod tissue of two chickpea (Cicer arietinum L.) cultivars differing in their ability to tolerate salinity, which were grown under control and salt-treated conditions. Statistical analysis was applied to the data sets using the absolute concentrations of metabolites to investigate the differences in metabolite profiles between the different cultivars, plant tissues, and treatments. The method is a significant improvement of present methodology for quantitative GC-MS metabolite profiling of organic acids and sugars, and provides new insights of chickpea metabolic responses to salinity stress. It is applicable to the analysis of dynamic changes in endogenous concentrations of polar primary metabolites to study metabolic responses to environmental stresses in complex biological tissues.

Analysis of phenolic and cyclic compounds in plants using derivatization techniques in combination with GC-MS-based metabolite profiling

Metabolite profiling has been established as a modern technology platform for the description of complex chemical matrices and compound identification in biological samples. Gas chromatography coupled with mass spectrometry (GC-MS) in particular is a fast and accurate method widely applied in diagnostics, functional genomics and for screening purposes. Following solvent extraction and derivatization, hundreds of metabolites from different chemical groups can be characterized in one analytical run. Besides sugars, acids, and polyols, diverse phenolic and other cyclic metabolites can be efficiently detected by metabolite profiling. The review describes own results from plant research to exemplify the applicability of GC-MS profiling and concurrent detection and identification of phenolics and other cyclic structures.

A modified data normalization method for GC-MS-based metabolomics to minimize batch variation

The goal of metabolomics data pre-processing is to eliminate systematic variation, such that biologically-related metabolite signatures are detected by statistical pattern recognition. Although several methods have been developed to tackle the issue of batch-to-batch variation, each method has its advantages and disadvantages. In this study, we used a reference sample as a normalization standard for test samples within the same batch, and each metabolite value is expressed as a ratio relative to its counterpart in the reference sample. We then applied this approach to a large multi-batch data set to facilitate intra- and inter-batch data integration. Our results demonstrate that normalization to a single reference standard has the potential to minimize batch-to-batch data variation across a large, multi-batch data set.

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.

Metabolic engineering and profiling of rice with increased lysine

Lysine (Lys) is the first limiting essential amino acid in rice, a stable food for half of the world population. Efforts, including genetic engineering, have not achieved a desirable level of Lys in rice. Here, we genetically engineered rice to increase Lys levels by expressing bacterial lysine feedback-insensitive aspartate kinase (AK) and dihydrodipicolinate synthase (DHPS) to enhance Lys biosynthesis; through RNA interference of rice lysine ketoglutaric acid reductase/saccharopine dehydropine dehydrogenase (LKR/SDH) to down-regulate its catabolism; and by combined expression of AK and DHPS and interference of LKR/SDH to achieve both metabolic effects. In these transgenic plants, free Lys levels increased up to ~12-fold in leaves and ~60-fold in seeds, substantially greater than the 2.5-fold increase in transgenic rice seeds reported by the only previous related study. To better understand the metabolic regulation of Lys accumulation in rice, metabolomic methods were employed to analyse the changes in metabolites of the Lys biosynthesis and catabolism pathways in leaves and seeds at different stages. Free Lys accumulation was mainly regulated by its biosynthesis in leaves and to a greater extent by catabolism in seeds. The transgenic plants did not show observable changes in plant growth and seed germination nor large changes in levels of asparagine (Asn) and glutamine (Gln) in leaves, which are the major amino acids transported into seeds. Although Lys was highly accumulated in leaves of certain transgenic lines, a corresponding higher Lys accumulation was not observed in seeds, suggesting that free Lys transport from leaves into seeds did not occur.

Distribution and function of allantoin (5-ureidohydantoin) in rice grains

Despite increasing knowledge of allantoin as a phytochemical involved in rice, relatively little is known about its distribution and function in rice grains. In this study, allantoin was quantified in 15 Chinese rice grains, and its contents varied with grain fraction, cultivar, and genotype. Bran always had the highest allantoin level, followed by brown rice and milled rice. Hull contained the lowest allantoin content. Allantoin in japonica bran ranged from 70 to 171 μg/g but rarely exceeded 100 μg/g in indica bran. There was a positive relationship between allantoin level in grains and seedling survival in seedbeds under low temperature or water deficit. Exogenous allantoin stimulated plant growth, increased soluble sugar and free proline contents, and decreased malondialdehyde content in rice seedlings. However, allantoin did not show any antioxidant activity through free radical-scavenging capacity, reducing power, linoleic acid peroxidation inhibition, and chelating activity. The results suggest that allantoin in rice grains may play some roles in providing plant stress protection but not serving as a beneficial health antioxidant.

Application of GC-MS for the detection of lipophilic compounds in diverse plant tissues

BACKGROUND

The concept of metabolite profiling has been around for decades and technical innovations are now enabling it to be carried out on a large scale with respect to the number of both metabolites measured and experiments carried out. However, studies are generally confined to polar compounds alone. Here we describe a simple method for lipophilic compounds analysis in various plant tissues.

RESULTS

We choose the same preparative and instrumental platform for lipophilic profiling as that we routinely use for polar metabolites measurements. The method was validated in terms of linearity, carryover, reproducibility and recovery rates, as well as using various plant tissues.As a first case study we present metabolic profiling of Arabidopsis root and shoot tissue of wild type (C24) and mutant (rsr4-1) plants deficient on vitamin B6. We found significant alterations in lipid constituent contents, especially in the roots, which were characterised by dramatic increases in several fatty acids, thus providing further hint for the role of pyridoxine in oxidative stress and lipid peroxidation.The second example is the lipophilic profiling of red and green tomato fruit cuticles of wild type (Alisa Craig) and the DFD (delayed fruit deterioration) mutant, which we compared and contrasted with the more focused wax analysis of these plants reported before.

CONCLUSION

We can rapidly and reliably detect and quantify over 40 lipophilic metabolites including fatty acids, fatty alcohols, alkanes, sterols and tocopherols. The method presented here affords a simple and rapid, yet robust complement to previously validated methods of polar metabolite profiling by gas-chromatography mass-spectrometry.

Not just a grain of rice: the quest for quality

A better understanding of the factors that contribute to the overall grain quality of rice (Oryza sativa) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. This is necessary to meet the growing global demand for high quality rice while offering producing countries additional opportunities for generating higher export revenues. Several recent developments in genetics, genomics, metabolomics and phenomics are enhancing our understanding of the pathways that determine several quality traits. New research strategies, as well as access to the draft of the rice genome, will not only advance our understanding of the molecular mechanisms that lead to quality rice but will also pave the way for efficient and targeted grain improvement.

Metabolite profiling of germinating rice seeds

A metabolite profiling approach based on gas chromatography-mass spectrometry (GC-MS) was used to investigate time-dependent metabolic changes in the course of the germination of rice. Brown rice kernels were soaked and incubated for a total of 96 h under ambient conditions. Samples taken during the germination process were subjected to an extraction and fractionation procedure covering a broad spectrum of lipophilic (e.g., fatty acid methyl esters, hydrocarbons, fatty alcohols, sterols) and hydrophilic (e.g., sugars, acids, amino acids, amines) low molecular weight rice constituents. Investigation of the obtained fractions by GC resulted in the detection of 615 distinct peaks, of which 174 were identified by means of MS. Statistical assessment of the data via principal component analysis demonstrated that the metabolic changes during the germination process are reflected by time-dependent shifts of the scores, which were similar for the three rice materials investigated. Analysis of the corresponding loadings showed that polar metabolites were major contributors to the separation along the first principal component. Relative quantifications based on standardized peak heights revealed dynamic changes of the metabolites in the course of the germination.

Comparative safety testing of genetically modified foods in a 90-day rat feeding study design allowing the distinction between primary and secondary effects of the new genetic event

This article discusses the wider experiences regarding the usefulness of the 90-day rat feeding study for the testing of whole foods from genetically modified (GM) plant based on data from a recent EU-project [Poulsen, M., Schrøder, M., Wilcks, A., Kroghsbo, S., Lindecrona, R.H., Miller, A., Frenzel, T., Danier, J., Rychlik, M., Shu, Q., Emami, K., Taylor, M., Gatehouse, A., Engel, K.-H., Knudsen, I., 2007a. Safety testing of GM-rice expressing PHA-E lectin using a new animal test design. Food Chem. Toxicol. 45, 364-377; Poulsen, M., Kroghsbo, S., Schrøder, M., Wilcks, A., Jacobsen, H., Miller, A., Frenzel, T., Danier, J., Rychlik, M., Shu, Q., Emami, K., Sudhakar, D., Gatehouse, A., Engel, K.-H., Knudsen, I., 2007b. A 90-day safety in Wistar rats fed genetically modified rice expressing snowdrop lectin Galanthus nivalis (GNA). Food Chem. Toxicol. 45, 350-363; Schrøder, M., Poulsen, M., Wilcks, A., Kroghsbo, S., Miller, A., Frenzel, T., Danier, J., Rychlik, M., Emami, K., Gatehouse, A., Shu, Q., Engel, K.-H., Knudsen, I., 2007. A 90-day safety study of genetically modified rice expressing Cry1Ab protein (Bacillus thuringiensis toxin) in Wistar rats. Food Chem. Toxicol. 45, 339-349]. The overall objective of the project has been to develop and validate the scientific methodology necessary for assessing the safety of foods from genetically modified plants in accordance with the present EU regulation. The safety assessment in the project is combining the results of the 90-day rat feeding study on the GM food with and without spiking with the pure novel gene product, with the knowledge about the identity of the genetic change, the compositional data of the GM food, the results from in-vitro/ex-vivo studies as well as the results from the preceding 28-day toxicity study with the novel gene product, before the hazard characterisation is concluded. The results demonstrated the ability of the 90-day rat feeding study to detect the biological/toxicological effects of the new gene product in the GM food. The authors consider on this basis that the 90-day, rodent feeding study with one high dose level and a dietary design based upon compositional data on the GM food and toxicity data on the gene product is sensitive and specific enough to verify the presence/absence of the biological/nutritional/toxicological effects of the novel gene insert and further by the use of spiking able to separate potentially unintended effects of the novel gene product from other unintended effects at the level of intake defined in the test and within the remit of the test. Recommendations for further work necessary in the field are given.

Metabolite profiling of two low phytic acid (lpa) rice mutants

Two low phytic acid (lpa) rice mutant lines, Os-lpa-XS110-1 and Os-lpa-XS110-2, were grown together with their parent wild-type variety Xiushui 110 in four field trials. HPLC analysis of inositol phosphates in the seeds produced demonstrated that compared to the wild-type, the reduction in phytic acid content in Os-lpa-XS110-1 (-46%) was more pronounced than that in Os-lpa-XS110-2 (-23%). Lower inositol phosphates (InsP 3, InsP 4, InsP 5) were not detected in the mutants. The lpa mutants and the wild-type rice were subjected to comparative metabolite profiling by capillary gas chromatography. On average, 34% (Os-lpa-XS110-1) and 42% (Os-lpa-XS110-2) of the detected peaks were statistically significantly different between wild-type and mutants. However, only a few of these differences could be consistently observed for all field trials. Identification and quantification of the consistently different metabolites revealed that contents of myo-inositol and raffinose were increased in Os-lpa-XS110-1 but decreased in Os-lpa-XS110-2 compared to the wild-type. In addition, Os-lpa-XS110-1 exhibited increased levels of galactose and galactinol. Consideration of these metabolic changes in light of the routes involved in the biosynthesis of phytic acid indicated a disturbance in the early biosynthetic pathway of phytic acid in Os-lpa-XS110-2 (similar to the lpa-1 type mutation in maize) and a mutation event affecting phosphorylation of myo-inositol in Os-lpa-XS110-1 (similar to the lpa-3-type mutation).

Unintended effects in genetically modified crops: revealed by metabolomics?

In Europe the commercialization of food derived from genetically modified plants has been slow because of the complex regulatory process and the concerns of consumers. Risk assessment is focused on potential adverse effects on humans and the environment, which could result from unintended effects of genetic modifications: unintended effects are connected to changes in metabolite levels in the plants. One of the major challenges is how to analyze the overall metabolite composition of GM plants in comparison to conventional cultivars, and one possible solution is offered by metabolomics. The ultimate aim of metabolomics is the identification and quantification of all small molecules in an organism; however, a single method enabling complete metabolome analysis does not exist. Given a comprehensive extraction method, a hierarchical strategy--starting with global fingerprinting and followed by complementary profiling attempts--is the most logical and economic approach to detect unintended effects in GM crops.

The potential of metabolite profiling as a selection tool for genotype discrimination in Populus

Differences between wild-type Populus tremulaxalba and two transgenic lines with modified lignin monomer composition, were interrogated using metabolic profiling. Analysis of metabolite abundance data by GC-MS, coupled with principal components analysis (PCA), successfully differentiated between lines that had distinct phenotypes, whether samples were taken from the cambial zone or non-lignifying suspension tissue cultures. Interestingly, the GC-MS analysis detected relatively few phenolic metabolites in cambial extracts, although a single metabolite associated with the differentiation between lines was directly related to the phenylpropanoid pathway or other down-stream aspects of lignin biosynthesis. In fact, carbohydrates, which have only an indirect relationship with the modified lignin monomer composition, featured strongly in the line-differentiating aspects of the statistical analysis. Traditional HPLC analysis was employed to verify the GC-MS data. These findings demonstrate that metabolic traits can be dissected reliably and accurately by metabolomic analyses, enabling the discrimination of individual genotypes of the same tree species that exhibit marked differences in industrially relevant wood traits. Furthermore, this validates the potential of using metabolite profiling techniques for marker generation in the context of plant/tree breeding for industrial applications.

Unintended effects and their detection in genetically modified crops

The commercialisation of GM crops in Europe is practically non-existent at the present time. The European Commission has instigated changes to the regulatory process to address the concerns of consumers and member states and to pave the way for removing the current moratorium. With regard to the safety of GM crops and products, the current risk assessment process pays particular attention to potential adverse effects on human and animal health and the environment. This document deals with the concept of unintended effects in GM crops and products, i.e. effects that go beyond that of the original modification and that might impact primarily on health. The document first deals with the potential for unintended effects caused by the processes of transgene insertion (DNA rearrangements) and makes comparisons with genetic recombination events and DNA rearrangements in traditional breeding. The document then focuses on the potential value of evolving "profiling" or "omics" technologies as non-targeted, unbiased approaches, to detect unintended effects. These technologies include metabolomics (parallel analysis of a range of primary and secondary metabolites), proteomics (analysis of polypeptide complement) and transcriptomics (parallel analysis of gene expression). The technologies are described, together with their current limitations. Importantly, the significance of unintended effects on consumer health are discussed and conclusions and recommendations presented on the various approaches outlined.

Metabolite profiling as an aid to metabolic engineering in plants

The past decade has seen some impressive successes in the metabolic engineering of biotechnologically important plant pathways. However, plant metabolic engineering currently proceeds more by trial and error than by intelligent system design. A change in philosophy away from studying pathways in isolation and towards studying metabolism as a network is necessary. To support this development, improvements in technologies for metabolic analysis, a wider adoption of metabolite-profiling approaches and significant innovations in data analysis methodologies are required.

Exploitation of molecular profiling techniques for GM food safety assessment

Several strategies have been developed to identify unintended alterations in the composition of genetically modified (GM) food crops that may occur as a result of the genetic modification process. These include comparative chemical analysis of single compounds in GM food crops and their conventional non-GM counterparts, and profiling methods such as DNA/RNA microarray technologies, proteomics and metabolite profiling. The potential of profiling methods is obvious, but further exploration of specificity, sensitivity and validation is needed. Moreover, the successful application of profiling techniques to the safety evaluation of GM foods will require linked databases to be built that contain information on variations in profiles associated with differences in developmental stages and environmental conditions.

Construction and application of a mass spectral and retention time index database generated from plant GC/EI-TOF-MS metabolite profiles

The non-supervised construction of a mass spectral and retention time index data base (MS/RI library) from a set of plant metabolic profiles covering major organs of potato (Solanum tuberosum), tobacco (Nicotiana tabaccum), and Arabidopsis thaliana, was demonstrated. Typically 300-500 mass spectral components with a signal to noise ratio > or =75 were obtained from GC/EI-time-of-flight (TOF)-MS metabolite profiles of methoxyaminated and trimethylsilylated extracts. Profiles from non-sample controls contained approximately 100 mass spectral components. A MS/RI library of 6205 mass spectral components was accumulated and applied to automated identification of the model compounds galactonic acid, a primary metabolite, and 3-caffeoylquinic acid, a secondary metabolite. Neither MS nor RI alone were sufficient for unequivocal identification of unknown mass spectral components. However library searches with single bait mass spectra of the respective reference substance allowed clear identification by mass spectral match and RI window. Moreover, the hit lists of mass spectral searches were demonstrated to comprise candidate components of highly similar chemical nature. The search for the model compound galactonic acid allowed identification of gluconic and gulonic acid among the top scoring mass spectral components. Equally successful was the exemplary search for 3-caffeoylquinic acid, which led to the identification of quinic acid and of the positional isomers, 4-caffeoylquinic acid, 5-caffeoylquinic acid among other still non-identified conjugates of caffeic and quinic acid. All identifications were verified by co-analysis of reference substances. Finally we applied hierarchical clustering to a complete set of pair-wise mass spectral comparisons of unknown components and reference substances with known chemical structure. We demonstrated that the resulting clustering tree depicted the chemical nature of the reference substances and that most of the nearest neighbours represented either identical components, as judged by co-elution, or conformational isomers exhibiting differential retention behaviour. Unknown components could be classified automatically by grouping with the respective branches and sub-branches of the clustering tree.

Deciphering metabolic networks

All higher organisms divide major biochemical steps into different cellular compartments and often use tissue-specific division of metabolism for the same purpose. Such spatial resolution is accompanied with temporal changes of metabolite synthesis in response to environmental stimuli or developmental needs. Although analyses of primary and secondary gene products, i.e. transcripts, proteins, and metabolites, regularly do not cope with this spatial and temporal resolution, these gene products are often observed to be highly coregulated forming complex networks. Methods to study such networks are reviewed with respect to data acquisition, network statistics, and biochemical interpretation.