Impact of genetics and environment on nutritional and metabolite components of maize grain.

The Organization for Economic Co-operation and Development (OECD) recommends the measurement of specific plant components for compositional assessments of new biotechnology-derived crops. These components include proximates, nutrients, antinutrients, and certain crop-specific secondary metabolites. A considerable literature on the natural variability of these components in conventional and biotechnology-derived crops now exists. Yet the OECD consensus also suggests measurements of any metabolites that may be directly associated with a newly introduced trait. Therefore, steps have been initiated to assess natural variation in metabolites not typically included in the OECD consensus but which might reasonably be expected to be affected by new traits addressing, for example, nutritional enhancement or improved stress tolerance. The compositional study reported here extended across a diverse genetic range of maize hybrids derived from 48 inbreds crossed against two different testers. These were grown at three different, but geographically similar, locations in the United States. In addition to OECD analytes such as proximates, total amino acids and free fatty acids, the levels of free amino acids, sugars, organic acids, and selected stress metabolites in harvested grain were assessed. The major free amino acids identified were asparagine, aspartate, glutamate, and proline. The major sugars were sucrose, glucose, and fructose. The most predominant organic acid was citric acid, with only minor amounts of other organic acids detected. The impact of genetic background and location was assessed for all components. Overall, natural variation in free amino acids, sugars, and organic acids appeared to be markedly higher than that observed for the OECD analytes.

Application of two-dimensional gel electrophoresis to interrogate alterations in the proteome of genetically modified crops. 2. Assessing natural variability.

Proteomics is currently tested as a complementary tool for the safety assessment of genetically modified (GM) crops. Understanding the natural variability of the proteome is crucial for the interpretation of biological differences between transgenic and nontransgenic parental lines. The natural variation of seed protein profiles among a set of 12 Arabidopsis thaliana ecotypes was determined by utilizing two-dimensional electrophoresis (2DE). The total number of different resolved protein spots found among the 12 ecotypes was 931 with a range of 573 (Mt-0) to 653 (Condara) in any one ecotype. Although the ecotypes were grown side-by-side in an environmentally controlled growth chamber, almost half of the resolved spots varied with respect to their presence/absence, and 95% of the spots present in all ecotypes varied in spot quantity (2-53-fold). In the evaluation of unintended effects of genetic modification, it is concluded that the experimental design must account for existing natural variability, which, in the case of the expressed proteome, can be substantial.

Application of two-dimensional gel electrophoresis to interrogate alterations in the proteome of genetically modified crops. 1. Assessing analytical validation.

Current tools used to assess the safety of food and feed derived from modern biotechnology emphasize the investigation of possible unintended effects caused directly by the expression of transgenes or indirectly by pleiotropy. These tools include extensive multisite and multiyear agronomic evaluations, compositional analyses, animal nutrition, and classical toxicology evaluations. Because analytical technologies are rapidly developing, proteome analysis based on two-dimensional gel electrophoresis (2DE) was investigated as a complementary tool to the existing technologies. A 2DE method was established for the qualitative and quantitative analysis of the seed proteome of Arabidopsis thaliana with the following validation parameters examined: (1) source and scope of variation; (2) repeatability; (3) sensitivity; and (4) linearity of the method. The 2DE method resolves proteins with isoelectric points between 4 and 9 and molecular masses (MM) of 6-120 kDa and is sensitive enough to detect protein levels in the low nanogram range. The separation of the proteins was demonstrated to be very reliable with relative position variations of 1.7 and 1.1% for the pI and MM directions, respectively. The mean coefficient of variation of 254 matched spot qualities was found to be 24.8% for the gel-to-gel and 26% for the overall variability. A linear relationship (R2 > 0.9) between protein amount and spot volume was demonstrated over a 100-fold range for the majority of selected proteins. Therefore, this method could be used to interrogate proteome alterations such as a novel protein, fusion protein, or any other change that affects molecular mass, isoelectric point, and/or quantity of a protein.

Application of two-dimensional gel electrophoresis to interrogate alterations in the proteome of gentically modified crops. 3. Assessing unintended effects.

The current procedures to assess the safety of food and feed derived from modern biotechnology include the investigation of possible unintended effects. To improve the probability of detecting unintended effects, profiling techniques such as proteomics are currently tested as complementary analytical tools to the existing safety assessment. An optimized two-dimensional gel electrophoresis (2DE) method was used as a proteomics approach to investigate insertional and pleiotropic effects on the proteome due to genetic engineering. Twelve transgenic Arabidopsis thaliana lines were analyzed by 2DE, and their seed proteomes were compared to that of their parental line as well as to 12 Arabidopsis ecotype lines. The genetic modification of the Arabidopsis lines, using three different genes and three different promoters, did not cause unintended changes to the analyzed seed proteome. Differences in spot quantity between transgenic and nontransgenic lines fell in the range of values found in the 12 Arabidopsis ecotype lines or were related to the introduced gene.

Applications of metabolomics in agriculture.

Biological systems are exceedingly complex. The unraveling of the genome in plants and humans revealed fewer than the anticipated number of genes. Therefore, other processes such as the regulation of gene expression, the action of gene products, and the metabolic networks resulting from catalytic proteins must make fundamental contributions to the remarkable diversity inherent in living systems. Metabolomics is a relatively new approach aimed at improved understanding of these metabolic networks and the subsequent biochemical composition of plants and other biological organisms. Analytical tools within metabolomics including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy can profile the impact of time, stress, nutritional status, and environmental perturbation on hundreds of metabolites simultaneously resulting in massive, complex data sets. This information, in combination with transcriptomics and proteomics, has the potential to generate a more complete picture of the composition of food and feed products, to optimize crop trait development, and to enhance diet and health. Selected presentations from an American Chemical Society symposium held in March 2005 have been assembled to highlight the emerging application of metabolomics in agriculture.

Natural variability of metabolites in maize grain: differences due to genetic background.

Understanding the impact of genetic diversity on crop biochemical composition is a prerequisite to the interpretation and potential relevance of biochemical differences experimentally observed between genotypes. This is particularly important in the context of comparative safety assessments for crops developed by new technologies such as genetic engineering. To interrogate the natural variability of biochemical composition, grain from seven maize hybrids grown at four geographically distinct sites in Europe was analyzed for levels of proximates (fat, protein, moisture, ash, and carbohydrates), fiber, amino acids, fatty acids, four vitamins, nine minerals, and secondary metabolites. Statistical evaluation of the compositional data at the p < 0.05 level compared each hybrid against every other hybrid (head-to-head) for all analytes at each site and then across all sites to understand the factors contributing to variability. Of the 4935 statistical comparisons made in this study, 40% (1986) were found to be significant. The magnitude of differences observed, as a percent, ranged between 0.84 and 149% when all individual sites and the combined sites were considered. The large number of statistically significant differences in the levels of these analytes between seven commercial hybrids emphasizes the importance of genetic background and environment as determinants of the biochemical composition of maize grain, reflects the inherent natural variability in those analytes across a representative sampling of maize hybrids, and provides a baseline of the natural range of these nutritional and antinutritional components in maize for comparative compositional assessments.

Impact of genetics and environment on the metabolite composition of maize grain.

This study sought to assess genetic and environmental impacts on the metabolite composition of maize grain. Gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) measured 119 identified metabolites including free amino acids, free fatty acids, sugars, organic acids, and other small molecules in a range of hybrids derived from 48 inbred lines crossed against two different tester lines (from the C103 and Iodent heterotic groups) and grown at three locations in Iowa. It was reasoned that expanded metabolite coverage would contribute to a comprehensive evaluation of the grain metabolome, its degree of variability, and, in principle, its relationship to other compositional and agronomic features. The metabolic profiling results established that the small molecule metabolite pool is highly dependent on genotypic variation and that levels of certain metabolite classes may have an inverse genotypic relationship to each other. Different metabolic phenotypes were clearly associated with the two distinct tester populations. Overall, grain from the C103 lines contained higher levels of free fatty acids and organic acids, whereas grain from the Iodent lines were associated with higher levels of amino acids and carbohydrates. In addition, the fold-range of genotype mean values [composed of six samples each (two tester crosses per inbred x three field sites)] for identified metabolites ranged from approximately 1.5- to 93-fold. Interestingly, some grain metabolites showed a non-normal distribution over the entire corn population, which could, at least in part, be attributed to large differences in metabolite values within specific inbred crosses relative to other inbred sets. This study suggests a potential role for metabolic profiling in assisting the process of selecting elite germplasm in biotechnology development, or marker-assisted breeding.

Endogenous small RNAs in grain: semi-quantification and sequence homology to human and animal genes.

Small interfering RNAs (siRNAs) and microRNAs (miRNAs) are effector molecules of RNA interference (RNAi), a highly conserved RNA-based gene suppression mechanism in plants, mammals and other eukaryotes. Endogenous RNAi-based gene suppression has been harnessed naturally and through conventional breeding to achieve desired plant phenotypes. The present study demonstrates that endogenous small RNAs, such as siRNAs and miRNAs, are abundant in soybean seeds, corn kernels, and rice grain, plant tissues that are traditionally used for food and feed. Numerous endogenous plant small RNAs were found to have perfect complementarity to human genes as well as those of other mammals. The abundance of endogenous small RNA molecules in grain from safely consumed food and feed crops such as soybean, corn, and rice and the homology of a number of these dietary small RNAs to human and animal genomes and transcriptomes establishes a history of safe consumption for dietary small RNAs.

Characterization of unique small RNA populations from rice grain.

Small RNAs (approximately 20 to 24 nucleotides) function as naturally occurring molecules critical in developmental pathways in plants and animals. Here we analyze small RNA populations from mature rice grain and seedlings by pyrosequencing. Using a clustering algorithm to locate regions producing small RNAs, we classified hotspots of small RNA generation within the genome. Hotspots here are defined as 1 kb regions within which small RNAs are significantly overproduced relative to the rest of the genome. Hotspots were identified to facilitate characterization of different categories of small RNA regulatory elements. Included in the hotspots, we found known members of 23 miRNA families representing 92 genes, one trans acting siRNA (ta-siRNA) gene, novel siRNA-generating coding genes and phased siRNA generating genes. Interestingly, over 20% of the small RNA population in grain came from a single foldback structure, which generated eight phased 21-nt siRNAs. This is reminiscent of a newly arising miRNA derived from duplication of progenitor genes. Our results provide data identifying distinct populations of small RNAs, including phased small RNAs, in mature grain to facilitate characterization of small regulatory RNA expression in monocot species.

Composition of forage and grain from second-generation insect-protected corn MON 89034 is equivalent to that of conventional corn (Zea mays L.).

Insect-protected corn hybrids containing Cry insecticidal proteins derived from Bacillus thuringiensis have protection from target pests and provide effective management of insect resistance. MON 89034 hybrids have been developed that produce both the Cry1A.105 and Cry2Ab2 proteins, which provide two independent modes of insecticidal action against the European corn borer ( Ostrinia nubilalis ) and other lepidopteran insect pests of corn. The composition of MON 89034 corn was compared to conventional corn by measuring proximates, fiber, and minerals in forage and by measuring proximates, fiber, amino acids, fatty acids, vitamins, minerals, antinutrients, and secondary metabolites in grain collected from 10 replicated field sites across the United States and Argentina during the 2004-2005 growing seasons. Analyses established that the forage and grain from MON 89034 are compositionally comparable to the control corn hybrid and conventional corn reference hybrids. These findings support the conclusion that MON 89034 is compositionally equivalent to conventional corn hybrids.