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.</p

Tracing Phenolic Metabolism in Vitis vinifera Berries with ¹³C₆‑Phenylalanine: Implication of an Unidentified Intermediate Reservoir

Understanding the regulation of phenolic compounds in agricultural products has been a topic of great interest. In V. vinifera berries, phenolics are responsible for important sensory and functional characteristics. To elucidate the ripening profile of phenolic compounds in Cabernet Sauvignon berries, the stable-isotope tracer l-phenyl-¹³C₆-alanine (Phe¹³) was incorporated in situ, and the development of labeled and unlabeled phenolics was tracked in the vineyard at different stages of maturity over two vintages. Phenolic profiles during ripening were consistent with previous research. However, individual anthocyanins accumulated with different profiles during ripening; malvidin species continually climbed in concentration, whereas other anthocyanins tended to plateau or drop near the end of the growing season. The isotopic label was predominantly incorporated into anthocyanins, presumably because of their dominant accumulation during ripening. Notably, the incorporation of label continued long after levels of Phe¹³ had dropped to below 1 nmol/berry, preventing an accurate assessment of the hypothesized turnover of anthocyanins. Although our tracer did not perform exactly as we had expected, the results of this study suggest the presence of a previously unreported pool of substrate in the phenolic pathway

Tracing Phenolic Metabolism in Vitis vinifera Berries with ¹³C₆‑Phenylalanine: Implication of an Unidentified Intermediate Reservoir

Understanding the regulation of phenolic compounds in agricultural products has been a topic of great interest. In V. vinifera berries, phenolics are responsible for important sensory and functional characteristics. To elucidate the ripening profile of phenolic compounds in Cabernet Sauvignon berries, the stable-isotope tracer l-phenyl-¹³C₆-alanine (Phe¹³) was incorporated in situ, and the development of labeled and unlabeled phenolics was tracked in the vineyard at different stages of maturity over two vintages. Phenolic profiles during ripening were consistent with previous research. However, individual anthocyanins accumulated with different profiles during ripening; malvidin species continually climbed in concentration, whereas other anthocyanins tended to plateau or drop near the end of the growing season. The isotopic label was predominantly incorporated into anthocyanins, presumably because of their dominant accumulation during ripening. Notably, the incorporation of label continued long after levels of Phe¹³ had dropped to below 1 nmol/berry, preventing an accurate assessment of the hypothesized turnover of anthocyanins. Although our tracer did not perform exactly as we had expected, the results of this study suggest the presence of a previously unreported pool of substrate in the phenolic pathway

Tracing Phenolic Metabolism in Vitis vinifera Berries with ¹³C₆‑Phenylalanine: Implication of an Unidentified Intermediate Reservoir

Understanding the regulation of phenolic compounds in agricultural products has been a topic of great interest. In V. vinifera berries, phenolics are responsible for important sensory and functional characteristics. To elucidate the ripening profile of phenolic compounds in Cabernet Sauvignon berries, the stable-isotope tracer l-phenyl-¹³C₆-alanine (Phe¹³) was incorporated in situ, and the development of labeled and unlabeled phenolics was tracked in the vineyard at different stages of maturity over two vintages. Phenolic profiles during ripening were consistent with previous research. However, individual anthocyanins accumulated with different profiles during ripening; malvidin species continually climbed in concentration, whereas other anthocyanins tended to plateau or drop near the end of the growing season. The isotopic label was predominantly incorporated into anthocyanins, presumably because of their dominant accumulation during ripening. Notably, the incorporation of label continued long after levels of Phe¹³ had dropped to below 1 nmol/berry, preventing an accurate assessment of the hypothesized turnover of anthocyanins. Although our tracer did not perform exactly as we had expected, the results of this study suggest the presence of a previously unreported pool of substrate in the phenolic pathway

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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-016-1017-6) contains supplementary material, which is available to authorized users

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

IntroductionPast 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).ObjectivesHere 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.MethodsFour 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&nbsp;=&nbsp;0.05), effect size evaluation (assessing magnitudes of differences), and variance component analysis.ResultsResults 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.ConclusionThe 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

Associations of Trimethylamine N-Oxide With Nutritional and Inflammatory Biomarkers and Cardiovascular Outcomes in Patients New to Dialysis.

ObjectivesTrimethylamine N-oxide (TMAO) is a product of metabolism of phosphatidylcholine (lecithin) and carnitine by the intestinal microbiome. Elevated serum concentrations of TMAO have been linked to adverse cardiovascular outcomes in the general population. We examined correlates of serum TMAO and the relations among serum TMAO concentrations, all-cause mortality, and cardiovascular mortality and hospitalizations in a nationally derived cohort of patients new to hemodialysis (HD).MethodsWe quantified serum TMAO by liquid chromatography and online tandem mass spectrometry and assessed nutritional and cardiovascular risk factors in 235 patients receiving HD and measured TMAO in pooled serum from healthy controls. We analyzed time to death and time to cardiovascular death or hospitalization using Cox proportional hazards regression.ResultsSerum TMAO concentrations of patients undergoing HD (median, 43&nbsp;μM/L; 25th-75th percentile, 28-67&nbsp;μM/L) were elevated compared with those with normal or near-normal kidney function (1.41&nbsp;±&nbsp;0.49&nbsp;μM/L). TMAO was directly correlated with serum albumin (Spearman rank correlation, 0.24; 95% CI, 0.12-0.35; P &lt;.001), prealbumin (Spearman rank correlation, 0.19; 95% CI, 0.07-0.31; P&nbsp;=&nbsp;.003), and creatinine (Spearman rank correlation, 0.21; 95% CI, 0.08-0.33; P&nbsp;=&nbsp;.002) and inversely correlated with log C-reactive protein (Spearman rank correlation, -0.18; 95% CI, -0.30 to -0.06; P&nbsp;=&nbsp;.005). Higher serum concentrations of TMAO were not significantly associated with time to death (Spearman rank correlation, 0.84; CI, 0.65-1.09; P&nbsp;=&nbsp;.19) or time to cardiovascular hospitalization or cardiovascular death (Spearman rank correlation, 0.88; CI, 0.57-1.35; P&nbsp;=&nbsp;.55).ConclusionsSerum TMAO concentrations were markedly elevated and correlated directly with biochemical markers of nutritional status and inversely with markers of inflammation in patients receiving HD. There was no significant association between serum TMAO concentrations and all-cause mortality, cardiovascular death, or hospitalizations. In patients receiving dialysis-in contrast with the general population-adverse vascular effects of TMAO may be counterbalanced by associations with nutritional or inflammatory status

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 ¹H nuclear magnetic resonance spectroscopy (¹H 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

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 ¹H nuclear magnetic resonance spectroscopy (¹H 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

Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS

An untargeted metabolomics workflow for the detection of metabolites derived from endogenous or exogenous tracer substances is presented. To this end, a recently developed stable isotope-assisted LC–HRMS-based metabolomics workflow for the global annotation of biological samples has been further developed and extended. For untargeted detection of metabolites arising from labeled tracer substances, isotope pattern recognition has been adjusted to account for nonlabeled moieties conjugated to the native and labeled tracer molecules. Furthermore, the workflow has been extended by (i) an optional ion intensity ratio check, (ii) the automated combination of positive and negative ionization mode mass spectra derived from fast polarity switching, and (iii) metabolic feature annotation. These extensions enable the automated, unbiased, and global detection of tracer-derived metabolites in complex biological samples. The workflow is demonstrated with the metabolism of ¹³C₉-phenylalanine in wheat cell suspension cultures in the presence of the mycotoxin deoxynivalenol (DON). In total, 341 metabolic features (150 in positive and 191 in negative ionization mode) corresponding to 139 metabolites were detected. The benefit of fast polarity switching was evident, with 32 and 58 of these metabolites having exclusively been detected in the positive and negative modes, respectively. Moreover, for 19 of the remaining 49 phenylalanine-derived metabolites, the assignment of ion species and, thus, molecular weight was possible only by the use of complementary features of the two ion polarity modes. Statistical evaluation showed that treatment with DON increased or decreased the abundances of many detected metabolites