Metabolite profiling of Douglas-fir (Pseudotsuga menziesii) field trials reveals strong environmental and weak genetic variation

The primary objective of this study was to assess metabolomics for its capacity to discern biological variation among 10 full-sib families of a Douglas-fir tree breeding population, replicated on two sites. The differential accumulation of small metabolites in developing xylem was examined through metabolite profiles (139 metabolites common to 181 individual trees) generated by gas chromatography mass spectrometry and a series of statistical analyses that incorporated family, site, and tree growth and quantitative phenotypic wood traits (wood density, microfibril angle, wood chemistry and fiber morphology). Multivariate discriminant, canonical discriminant and factor analyses and broad-sense heritabilities revealed that metabolic and phenotypic traits alike were strongly related to site, while similar associations relating to genetic (family) structure were weak in comparison. Canonical correlation analysis subsequently identified correlations between specific phenotypic traits (i.e. tree growth, fibre morphology and wood chemistry) and metabolic traits (i.e. carbohydrate and lignin biosynthetic metabolites), demonstrating a coherent relationship between genetics, metabolism, environmental and phenotypic expression in wood-forming tissue. The association between cambial metabolites and tree phenotype, as revealed by metabolite profiling, demonstrates the value of metabolomics for systems biology approaches to understanding tree growth and secondary cell wall biosynthesis in plants.     

Differences in the metabolite profiles of spinach (Spinacia oleracea L.) leaf in different concentrations of nitrate in the culture solution

The nitrogen (N) status of a plant determines the composition of its major components (amino acids, proteins, carbohydrates and organic acids) and, directly or indirectly, affects the quality of agricultural products in terms of their calorific value and taste. Although these effects are guided by changes in metabolic pathways, no overall metabolic analysis has previously been conducted to demonstrate such effects. Here, metabolite profiling using gas chromatography-mass spectrometry (GC-MS) was used to evaluate the effect of N levels on spinach tissue, comparing two cultivars that differed in their ability to use N. Wide variation in N content was observed without any distinct inhibition of growth in either cultivar. Principal component analysis (PCA) and self-organizing mapping (SOM) were undertaken to describe changes in the metabolites of mature spinach leaves. In PCA, the first component accounted for 44.5% of the total variance, the scores of which was positively correlated with the plant's N content, and a close relationship between metabolite profiles and N status was observed. Both PCA and SOM revealed that metabolites could be broadly divided into two types, correlating either positively or negatively with plant N content. The simple and co-coordinated metabolic stream, containing both general and spinach-specific aspects of plant N content, will be useful in future research on such topics as the detection of environmental effects on spinach through comprehensive metabolic profiling.     

MSClust: a tool for unsupervised mass spectra extraction of chromatography-mass spectrometry ion-wise aligned data

Mass peak alignment (ion-wise alignment) has recently become a popular method for unsupervised data analysis in untargeted metabolic profiling. Here we present MSClust-a software tool for analysis GC-MS and LC-MS datasets derived from untargeted profiling. MSClust performs data reduction using unsupervised clustering and extraction of putative metabolite mass spectra from ion-wise chromatographic alignment data. The algorithm is based on the subtractive fuzzy clustering method that allows unsupervised determination of a number of metabolites in a data set and can deal with uncertain memberships of mass peaks in overlapping mass spectra. This approach is based purely on the actual information present in the data and does not require any prior metabolite knowledge. MSClust can be applied for both GC-MS and LC-MS alignment data sets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0368-2) contains supplementary material, which is available to authorized users.     

Metabolic profiling of a mapping population exposes new insights in the regulation of seed metabolism and seed, fruit, and plant relations

To investigate the regulation of seed metabolism and to estimate the degree of metabolic natural variability, metabolite profiling and network analysis were applied to a collection of 76 different homozygous tomato introgression lines (ILs) grown in the field in two consecutive harvest seasons. Factorial ANOVA confirmed the presence of 30 metabolite quantitative trait loci (mQTL). Amino acid contents displayed a high degree of variability across the population, with similar patterns across the two seasons, while sugars exhibited significant seasonal fluctuations. Upon integration of data for tomato pericarp metabolite profiling, factorial ANOVA identified the main factor for metabolic polymorphism to be the genotypic background rather than the environment or the tissue. Analysis of the coefficient of variance indicated greater phenotypic plasticity in the ILs than in the M82 tomato cultivar. Broad-sense estimate of heritability suggested that the mode of inheritance of metabolite traits in the seed differed from that in the fruit. Correlation-based metabolic network analysis comparing metabolite data for the seed with that for the pericarp showed that the seed network displayed tighter interdependence of metabolic processes than the fruit. Amino acids in the seed metabolic network were shown to play a central hub-like role in the topology of the network, maintaining high interactions with other metabolite categories, i.e., sugars and organic acids. Network analysis identified six exceptionally highly co-regulated amino acids, Gly, Ser, Thr, Ile, Val, and Pro. The strong interdependence of this group was confirmed by the mQTL mapping. Taken together these results (i) reflect the extensive redundancy of the regulation underlying seed metabolism, (ii) demonstrate the tight co-ordination of seed metabolism with respect to fruit metabolism, and (iii) emphasize the centrality of the amino acid module in the seed metabolic network. Finally, the study highlights the added value of integrating metabolic network analysis with mQTL mapping.     

The light-hyperresponsive high pigment-2dg mutation of tomato: alterations in the fruit metabolome

Overall metabolic modifications between fruit of light-hyperresponsive high-pigment (hp) tomato (Lycopersicon esculentum) mutant plants and isogenic nonmutant (wt) control plants were compared. Targeted metabolite analyses, as well as large-scale nontargeted mass spectrometry (MS)-based metabolite profiling, were used to phenotype the differences in fruit metabolite composition. Targeted high-performance liquid chromatography with photodiode array detection (HPLC-PDA) metabolite analyses showed higher levels of isoprenoids and phenolic compounds in hp-2dg fruit. Nontargeted GC-MS profiling of red fruits produced 25 volatile compounds that showed a 1.5-fold difference between the genotypes. Analyses of red fruits using HPLC coupled to high-resolution quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) in both ESI-positive and ESI-negative mode generated, respectively, 6168 and 5401 mass signals, of which 142 and 303 showed a twofold difference between the genotypes. hp-2dg fruits are characterized by overproduction of many metabolites, several of which are known for their antioxidant or photoprotective activities. These metabolites may now be more closely implicated as resources recruited by plants to respond to and manage light stress. The similarity in metabolic alterations in fruits of hp-1 and hp-2 mutant plants helps us to understand how hp mutations affect cellular processes.     

Modified lignin in tobacco and poplar plants over-expressing the Arabidopsis gene encoding ferulate 5-hydroxylase

Ferulate 5-hydroxylase (F5H) is a cytochrome P450-dependent monooxygenase that catalyses the hydroxylation of ferulic acid, coniferaldehyde and coniferyl alcohol in the pathways leading to sinapic acid and syringyl lignin biosynthesis. Earlier studies in Arabidopsis have demonstrated that F5H over-expression increases lignin syringyl monomer content and abolishes the tissue-specificity of its deposition. To determine whether this enzyme has a similar regulatory role in plants that undergo secondary growth, we over-expressed the F5H gene in tobacco and poplar. In tobacco, over-expression of F5H under the control of the cauliflower mosaic virus 35S promoter increased lignin syringyl monomer content in petioles, but had no detectable effect on lignification in stems. By contrast, when the cinnamate 4-hydroxylase (C4H) promoter was used to drive F5H expression, there was a significant increase in stem lignin syringyl monomer content. Yields of thioglycolic acid and Klason lignin in C4H-F5H lines were lower than in the wild-type, suggesting that F5H over-expression leads to a reduced deposition or an altered extractability of lignin in the transgenic plants. Histochemical analysis suggested that the novel lignin in C4H-F5H transgenic lines was altered in its content of hydroxycinnamyl aldehydes. Transgenic poplar trees carrying the C4H-F5H transgene also displayed enhanced lignin syringyl monomer content. Taken together, these data show that hydroxylation of guaiacyl-substituted lignin precursors controls lignin monomer composition in woody plants, and that F5H over-expression is a viable metabolic engineering strategy for modifying lignin biosynthesis in forest species.     

Metabolic profiling of transgenic tomato plants overexpressing hexokinase reveals that the influence of hexose phosphorylation diminishes during fruit development

We have conducted a comprehensive metabolic profiling on tomato (Lycopersicon esculentum) leaf and developing fruit tissue using a recently established gas chromatography-mass spectrometry profiling protocol alongside conventional spectrophotometric and liquid chromatographic methodologies. Applying a combination of these techniques, we were able to identify in excess of 70 small-M(r) metabolites and to catalogue the metabolite composition of developing tomato fruit. In addition to comparing differences in metabolite content between source and sink tissues of the tomato plant and after the change in metabolite pool sizes through fruit development, we have assessed the influence of hexose phosphorylation through fruit development by analyzing transgenic plants constitutively overexpressing Arabidopsis hexokinase AtHXK1. Analysis of the total hexokinase activity in developing fruits revealed that both wild-type and transgenic fruits exhibit decreasing hexokinase activity with development but that the relative activity of the transgenic lines with respect to wild type increases with development. Conversely, both point-by-point and principal component analyses suggest that the metabolic phenotype of these lines becomes less distinct from wild type during development. In summary, the data presented in this paper demonstrate that the influence of hexose phosphorylation diminishes during fruit development and highlights the importance of greater temporal resolution of metabolism.     

Metabolic dynamics during autumn cold acclimation within and among populations of Sitka spruce (Picea sitchensis)

? Autumnal cold acclimation in conifers is a complex process, the timing and extent of which vary widely along latitudinal gradients for many tree species and reflect local adaptation to climate. Although previous studies have detailed some aspects of the metabolic remodelling that accompanies cold acclimation in conifers, little is known about global metabolic dynamics, or how these changes vary among phenotypically divergent populations. ? Using untargeted GC-MS metabolite profiling, we monitored metabolic dynamics during autumnal cold acclimation in three populations of Sitka spruce from the southern, central, and northern portions of the species range, which differ in both the timing and extent of cold acclimation. ? Latitudinal variation was evident in the nature, intensity, and timing of metabolic events. Early development of strong freezing tolerance in the northern population was associated with a transient accumulation of amino acids. By late autumn, metabolic profiles were highly similar between the northern and central populations, whereas profiles for the southern population were relatively distinct. ? Our results provide insight into the metabolic architecture of latitudinal adaptive variation in autumn acclimation and show that different mechanisms are the basis of early October cold hardiness and autumn-acclimated cold hardiness.     

Plant metabolomics reveals conserved and divergent metabolic responses to salinity

New metabolic profiling technologies provide data on a wider range of metabolites than traditional targeted approaches. Metabolomic technologies currently facilitate acquisition of multivariate metabolic data using diverse, mostly hyphenated, chromatographic detection systems, such as GC-MS or liquid chromatography coupled to mass spectrometry, Fourier-transformed infrared spectroscopy or NMR-based methods. Analysis of the resulting data can be performed through a combination of non-supervised and supervised statistical methods, such as independent component analysis and analysis of variance, respectively. These methods reduce the complex data sets to information, which is relevant for the discovery of metabolic markers or for hypothesis-driven, pathway-based analysis. Plant responses to salinity involve changes in the activity of genes and proteins, which invariably lead to changes in plant metabolism. Here, we highlight a selection of recent publications in the salt stress field, and use gas chromatography time-of-flight mass spectrometry profiles of polar fractions from the plant models, Arabidopsis thaliana, Lotus japonicus and Oryza sativa to demonstrate the power of metabolite profiling. We present evidence for conserved and divergent metabolic responses among these three species and conclude that a change in the balance between amino acids and organic acids may be a conserved metabolic response of plants to salt stress.     

Profiling phenolic metabolites in transgenic alfalfa modified in lignin biosynthesis

Soluble phenolics, wall-bound phenolics and soluble and core lignin were analyzed in transgenic alfalfa with genetically down-regulated O-methyltransferase genes involved in lignin biosynthesis. High performance liquid chromatography and principal component analysis were used to distinguish metabolic phenotypes of different transgenic alfalfa genotypes growing under standard greenhouse conditions. Principal component analysis of HPLC chromatograms did not resolve differences in leaf metabolite profiles between wild-type and transgenic plants of the same genetic background, although stem phenolic profiles were clearly different between wild-type and transgenic plants. However, the analytical methods clearly differentiated two non-transgenic alfalfa cultivars based on either leaf or stem profiles. Metabolic profiling provides a useful approach to monitoring the broader biochemical phenotypes of transgenic plants with altered expression of lignin pathway enzymes.     

基于气相色谱-质谱联用技术的代谢组学方法在转植酸酶基因玉米代谢物指纹图谱分析中的应用

目的:建立气相色谱-质谱联用技术(GC-MS)的代谢组学方法,初步研究转基因株系与对照株系之间代谢物指纹图谱的差异性,为转基因作物安全的评价提供参考。方法:优化提取条件,考察色谱条件,并采用主成分分析(PCA)数据处理方法对转基因株系及对照进行模式识别。结果:优化了提取条件及色谱条件,建立了GC-MS的代谢组学方法,获得了小分子的代谢产物的表达谱,发现转基因与其对照之间呈现出显著性差异。结论:优化的GC-MS的代谢组学方法可以从代谢水平检测转基因作物,找出差异性,为转基因作物的检测与评价提供技术支持。     

Application of metabolite profiling to the identification of traits in a population of tomato introgression lines

Naturally occurring variation in wild species can be used to increase the genetic diversity of cultivated crops and improve agronomic value. Populations of introgression lines carrying wild species alleles afford an opportunity to identify traits associated with the introgressed regions, and facilitate characterization of the biochemistry and genetics underlying these phenotypes. Understanding plant metabolic pathways and the interactions between genes, phenotype, and environment is fundamental to functional genomics. Successful analysis of the complex network of plant metabolism requires analytical methods able to record information on as many metabolites as possible. Metabolite profiling is used to provide a snapshot of the metabolome in samples which differ in a known factor such as genetic background. Differences between the metabolite profiles can identify those metabolites/metabolic pathways affected by the introgression and allow genetic maps for metabolic alterations to be established. A Time-of-Flight Mass Spectrometry method is presented, with associated data reduction, used for profiling aqueous metabolites fom tomato. Analysis of ripe fruits of two tomato species, Lycopersicon esculentum and L. pennellii, showed differences in the amounts of many metabolites, including organic acids and sugars. Six introgression lines, L. pennellii introgressions within L. esculentum, were also examined and showed that Principal Component Analysis can reveal subtle differences in metabolism of the introgressed lines when compared to their parents.     

Application of nontargeted metabolite profiling to discover novel markers of quality traits in an advanced population of malting barley

The process of breeding superior varieties for the agricultural industry is lengthy and expensive. Plant metabolites may act as markers of quality traits, potentially expediting the appraisal of experimental lines during breeding. Here, we evaluated the utility of metabolites as markers by assessing metabolic variation influenced by genetic and environmental factors in an advanced breeding setting and in relation to the phenotypic distribution of 20 quality traits. Nontargeted liquid chromatography–mass spectrometry metabolite profiling was performed on barley (Hordeum vulgare L.) grain and malt from 72 advanced malting barley lines grown at two distinct but climatically similar locations, with 2‐row and 6‐row barley as the main genetic factors. 27 420 molecular features were detected, and the metabolite and quality trait profiles were similarly influenced by genotype and environment; however, malt was more influenced by genotype compared with barley. An O2PLS model characterized molecular features and quality traits that covaried, and 1319 features associated with at least one of 20 quality traits. An indiscriminant MS/MS acquisition and novel data analysis method facilitated the identification of metabolites. The analysis described 216 primary and secondary metabolites that correlated with multiple quality traits and included amines, amino acids, alkaloids, polyphenolics and lipids. The mechanisms governing quality trait–metabolite associations were interpreted based on colocalization to genetic markers and their gene annotations. The results of this study support the hypothesis that metabolism and quality traits are co‐influenced by relatively narrow genetic and environmental factors and illustrate the utility of grain metabolites as functional markers of quality traits.     

Metabolomic Profiles of Body Mass Index in the Framingham Heart Study Reveal Distinct Cardiometabolic Phenotypes

Background

Although obesity and cardiometabolic traits commonly overlap, underlying pathways remain incompletely defined. The association of metabolite profiles across multiple cardiometabolic traits may lend insights into the interaction of obesity and metabolic health. We sought to investigate metabolic signatures of obesity and related cardiometabolic traits in the community using broad-based metabolomic profiling.

Methods and Results

We evaluated the association of 217 assayed metabolites and cross-sectional as well as longitudinal changes in cardiometabolic traits among 2,383 Framingham Offspring cohort participants. Body mass index (BMI) was associated with 69 of 217 metabolites (P<0.00023 for all), including aromatic (tyrosine, phenylalanine) and branched chain amino acids (valine, isoleucine, leucine). Additional metabolic pathways associated with BMI included the citric acid cycle (isocitrate, alpha-ketoglutarate, aconitate), the tryptophan pathway (kynurenine, kynurenic acid), and the urea cycle. There was considerable overlap in metabolite profiles between BMI, abdominal adiposity, insulin resistance [IR] and dyslipidemia, modest overlap of metabolite profiles between BMI and hyperglycemia, and little overlap with fasting glucose or elevated blood pressure. Metabolite profiles were associated with longitudinal changes in fasting glucose, but the involved metabolites (ornithine, 5-HIAA, aminoadipic acid, isoleucine, cotinine) were distinct from those associated with baseline glucose or other traits. Obesity status appeared to “modify” the association of 9 metabolites with IR. For example, bile acid metabolites were strongly associated with IR among obese but not lean individuals, whereas isoleucine had a stronger association with IR in lean individuals.

Conclusions

In this large-scale metabolite profiling study, body mass index was associated with a broad range of metabolic alterations. Metabolite profiling highlighted considerable overlap with abdominal adiposity, insulin resistance, and dyslipidemia, but not with fasting glucose or blood pressure traits.