The Metabolism of Gibberellin A20 to Gibberellin A1 by Tall and Dwarf Mutants of Oryza sativa and Arabidopsis thaliana

The purpose of this study was to demonstrate the metabolism of gibberellin A20 (GA20) to gibberellin A1 (GA1) by tall and mutant shoots of rice (Oryza sativa L.) and Arabidopsis thaliana (L.) Heynh. The data show that the tall and dx mutant of rice and the tall and ga5 mutant of Arabidopsis metabolize GA20 to GA1. The data also show that the dy mutant of rice and the ga4 mutant of Arabidopsis block the metabolism of GA20 to GA1. [17-13C,3H]GA20 was fed to tall and the dwarf mutants, dx and dy, of rice and tall and the dwarf mutants, ga5 and ga4, of Arabidopsis. The metabolites were analyzed by high-performance liquid chromatography and full-scan gas chromatography-mass spectrometry together with Kovats retention index data. For rice, the metabolite [13C]GA, was identified from tall and dx seedlings; [13C]GA1 was not identified from the dy seedlings. [13C]GA29 was identified from tall, dx, and dy seedlings. For Arabidopsis, the metabolite [13C]GA1 was identified from tall, ga5, and ga4 plants. The amount of [13C]GA1 from ga4 plants was less than 15% of that obtained from tall and ga5 plants. [13C]GA29 was identified from tall, ga5, and ga4 plants. [13C]GA5 and [13C]GA3 were not identified from any of the six types of plant material.     

Two Arabidopsis threonine aldolases are nonredundant and compete with threonine deaminase for a common substrate pool

Amino acids are not only fundamental protein constituents but also serve as precursors for many essential plant metabolites. Although amino acid biosynthetic pathways in plants have been identified, pathway regulation, catabolism, and downstream metabolite partitioning remain relatively uninvestigated. Conversion of Thr to Gly and acetaldehyde by Thr aldolase (EC 4.1.2.5) was only recently shown to play a role in plant amino acid metabolism. Whereas one Arabidopsis thaliana Thr aldolase (THA1) is expressed primarily in seeds and seedlings, the other (THA2) is expressed in vascular tissue throughout the plant. Metabolite profiling of tha1 mutants identified a >50-fold increase in the seed Thr content, a 50% decrease in seedling Gly content, and few other significant metabolic changes. By contrast, homozygous tha2 mutations cause a lethal albino phenotype. Rescue of tha2 mutants and tha1 tha2 double mutants by overproduction of feedback-insensitive Thr deaminase (OMR1) shows that Gly formation by THA1 and THA2 is not essential in Arabidopsis. Seed-specific expression of feedback-insensitive Thr deaminase in both tha1 and tha2 Thr aldolase mutants greatly increases seed Ile content, suggesting that these two Thr catabolic enzymes compete for a common substrate pool.     

Broad connections in the Arabidopsis seed metabolic network revealed by metabolite profiling of an amino acid catabolism mutant

An Arabidopsis thaliana mutant was identified as having increases in 12 of 20 free proteogenic amino acids in seeds. Because these metabolites are produced from multiple, seemingly unrelated biosynthetic networks, it was not possible to use a candidate gene approach to discover the enzyme defect responsible for this complex syndrome. Complementary metabolite profiling analyses revealed increased seed homomethionine and isovaleroyloxypropyl‐glucosinolate, along with reduced 3‐benzoyloxypropyl‐glucosinolate. These data led to the discovery of impaired branched chain amino acid catabolic enzyme isovaleryl‐CoA dehydrogenase (encoded by gene At3g45300 or atIVD) as the cause of this metabolic syndrome. These results indicate that catabolism plays an important role in regulating levels of branched chain amino acids in seeds. The diverse set of metabolites affected in the ivd1 mutants suggests the existence of a more complex network regulating seed amino acid accumulation than previously observed. This combined targeted and non‐targeted metabolite profiling approach is broadly applicable to the characterization of metabolic mutants, human disease studies and crop germplasm.     

New connections across pathways and cellular processes: industrialized mutant screening reveals novel associations between diverse phenotypes in Arabidopsis

In traditional mutant screening approaches, genetic variants are tested for one or a small number of phenotypes. Once bona fide variants are identified, they are typically subjected to a limited number of secondary phenotypic screens. Although this approach is excellent at finding genes involved in specific biological processes, the lack of wide and systematic interrogation of phenotype limits the ability to detect broader syndromes and connections between genes and phenotypes. It could also prevent detection of the primary phenotype of a mutant. As part of a systems biology approach to understand plastid function, large numbers of Arabidopsis thaliana homozygous T-DNA lines are being screened with parallel morphological, physiological, and chemical phenotypic assays (www.plastid.msu.edu). To refine our approaches and validate the use of this high-throughput screening approach for understanding gene function and functional networks, approximately 100 wild-type plants and 13 known mutants representing a variety of phenotypes were analyzed by a broad range of assays including metabolite profiling, morphological analysis, and chlorophyll fluorescence kinetics. Data analysis using a variety of statistical approaches showed that such industrial approaches can reliably identify plant mutant phenotypes. More significantly, the study uncovered previously unreported phenotypes for these well-characterized mutants and unexpected associations between different physiological processes, demonstrating that this approach has strong advantages over traditional mutant screening approaches. Analysis of wild-type plants revealed hundreds of statistically robust phenotypic correlations, including metabolites that are not known to share direct biosynthetic origins, raising the possibility that these metabolic pathways have closer relationships than is commonly suspected.     

Metabolic profiles of genetically modified potatoes using a combination of metabolite fingerprinting and multivariate analysis

Comprehensive metabolite fingerprinting of transgenic potatoes that constitutively express human beta amyloid, curdlan synthase (CRDS), and glycogen synthase (glgA); and of wild-type potatoes was carried out using FT-IR and ¹H NMR spectroscopy in combination with multivariate analyses. Comparison of metabolic patterns between transgenic and wild-type potatoes revealed that there were neither quantitative nor qualitative differences in metabolites between transgenic potatoes expressing human beta amyloid, CRDS or glgA, and non-transformed control potatoes. However, there were metabolic differences between two control potato lines — one that was fresh and the other stored. After 1 week of storage, comprehensive metabolite patterns were significantly modified. Although the differences between CRDS and glgA transgenic and control potato lines were small, PCA analysis of FT-IR and ¹H NMR spectral data identified two distinct control lines. These results suggest that the comprehensive metabolite changes in control potato lines, which occurred after 1 week of storage, were greater than the differences between CRDS and glgA transgenic and wild-type potato lines. Thus, the combination of FT-IR and ¹H NMR spectral data and multivariate analysis was valuable for the detection of comprehensive differences in metabolic profiles between transgenic and non-transformed control plants, even though peak-signal overlap prevented assignment of pure compounds. The combination of FT-IR and ¹H NMR spectral data and multivariate analysis is a simple and rapid method for evaluation of the metabolic equivalence of GM crops.     

Metabolite fingerprinting and profiling in plants using NMR

Although less sensitive than mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy provides a powerful complementary technique for the identification and quantitative analysis of plant metabolites either in vivo or in tissue extracts. In one approach, metabolite fingerprinting, multivariate analysis of unassigned 1H NMR spectra is used to compare the overall metabolic composition of wild-type, mutant, and transgenic plant material, and to assess the impact of stress conditions on the plant metabolome. Metabolite fingerprinting by NMR is a fast, convenient, and effective tool for discriminating between groups of related samples and it identifies the most important regions of the spectrum for further analysis. In a second approach, metabolite profiling, the 1H NMR spectra of tissue extracts are assigned, a process that typically identifies 20-40 metabolites in an unfractionated extract. These profiles may also be used to compare groups of samples, and significant differences in metabolite concentrations provide the basis for hypotheses on the underlying causes for the observed segregation of the groups. Both approaches generate a metabolic phenotype for a plant, based on a system-wide but incomplete analysis of the plant metabolome. However, a review of the literature suggests that the emphasis so far has been on the accumulation of analytical data and sample classification, and that the potential of 1H NMR spectroscopy as a tool for probing the operation of metabolic networks, or as a functional genomics tool for identifying gene function, is largely untapped.     

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.     

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.     

GC-EI-TOF-MS analysis of in vivo carbon-partitioning into soluble metabolite pools of higher plants by monitoring isotope dilution after 13CO2 labelling

The established GC-EI-TOF-MS method for the profiling of soluble polar metabolites from plant tissue was employed for the kinetic metabolic phenotyping of higher plants. Approximately 100 typical GC-EI-MS mass fragments of trimethylsilylated and methoxyaminated metabolite derivatives were structurally interpreted for mass isotopomer analysis, thus enabling the kinetic study of identified metabolites as well as the so-called functional group monitoring of yet non-identified metabolites. The monitoring of isotope dilution after (13)CO(2) labelling was optimized using Arabidopsis thaliana Col-0 or Oryza sativa IR57111 plants, which were maximally labelled with (13)C. Carbon isotope dilution was evaluated for short (2h) and long-term (3 days) kinetic measurements of metabolite pools in root and shoots. Both approaches were shown to enable the characterization of metabolite specific partitioning processes and kinetics. Simplifying data reduction schemes comprising calculation of (13)C-enrichment from mass isotopomer distributions and of initial (13)C-dilution rates were employed. Metabolites exhibited a highly diverse range of metabolite and organ specific half-life of (13)C-label in their respective pools ((13)C-half-life). This observation implied the setting of metabolite specific periods for optimal kinetic monitoring. A current experimental design for the kinetic metabolic phenotyping of higher plants is proposed.     

Quantitative analysis of metabolite concentrations in human urine samples using 13C{1H} NMR spectroscopy

Targeted profiling is a library-based method of using mathematically modeled reference spectra for quantification of metabolite concentrations in NMR mixture analysis. Metabolomics studies of biofluids, such as urine, represent a highly complex problem in this area, and for this reason targeted profiling of ¹H NMR spectra can be hampered. A number of the issues relating to ¹H NMR spectroscopy can be overcome using ¹³C{¹H} NMR spectroscopy. In this work, a ¹³C{¹H} NMR database was created using Chenomx NMR Suite, incorporating 120 metabolites. The ¹³C{¹H} NMR database was standardized through the analysis of a series of metabolite solutions containing varying concentrations of 19 distinct metabolites, where the metabolite concentrations were varied across a range of values including biological ranges. Subsequently, the NMR spectra of urine samples were collected using ¹³C{¹H} NMR spectroscopy and profiled using the ¹³C{¹H} NMR library. In total, about 30 metabolites were conclusively identified and quantified in the urine samples using ¹³C{¹H} NMR targeted profiling. The proton decoupling and larger spectral window provided easier identification and more accurate quantification for specific classes of metabolites, such as sugars and amino acids with overlap in the aliphatic region of the ¹H NMR spectrum. We discuss potential application areas in which ¹³C{¹H} NMR targeted profiling may be superior to ¹H NMR targeted profiling.     

Toward Arabidopsis thaliana hydrophilic metabolome: assessment of extraction methods and quantitative 1H NMR

Our goal was to establish the hydrophilic metabolome of heterotrophic Arabidopsis thaliana cells grown in suspension, a cellular model of plant sink tissues. Water‐soluble metabolites were extracted using four protocols: perchloric acid, boiling ethanol, methanol and methanol/chloroform (M/Chl). They were detected and quantified using ¹H nuclear magnetic resonance (NMR) spectroscopy at 400 MHz. Extraction yields and reproducibility of the extraction methods were investigated. The effects of cell harvest protocol, cell grinding and lyophilization and storage conditions on the measured metabolic profiles were also studied. These quantitative studies demonstrated for the first time that the four extraction protocols commonly used do lead to quite similar molecular compositions as analyzed by ¹H NMR. The M/Chl method proved effective and reliable to prepare series of physiologically significant extracts from plant cells for ¹H NMR analysis. Reproducibility of the detected metabolome was assessed over long periods of time by analyzing a large number of separate extracts prepared from independent cultures. Larger variations in the NMR metabolite profiles could be correlated to changes in physiological parameters of the culture medium. Quantitative resolved ¹H NMR of cell extracts proved to be robust and reliable for routine metabolite profiling of plant cell cultures.     

Discrimination of Basal Cell Carcinoma from Normal Skin Tissue Using High-Resolution Magic Angle Spinning 1H NMR Spectroscopy

High-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy is a useful tool for investigating the metabolism of various cancers. Basal cell carcinoma (BCC) is the most common skin cancer. However, to our knowledge, data on metabolic profiling of BCC have not been reported in the literature. The objective of the present study was to investigate the metabolic profiling of cutaneous BCC using HR-MAS ¹H NMR spectroscopy. HR-MAS ¹H NMR spectroscopy was used to analyze the metabolite profile and metabolite intensity of histopathologically confirmed BCC tissues and normal skin tissue (NST) samples. The metabolic intensity normalized to the total spectral intensities in BCC and NST was compared, and multivariate analysis was performed with orthogonal partial least-squares discriminant analysis (OPLS-DA). P values < 0.05 were considered statistically significant. Univariate analysis revealed 9 metabolites that showed statistically significant difference between BCC and NST. In multivariate analysis, the OPLS-DA models built with the HR-MAS NMR metabolic profiles revealed a clear separation of BCC from NST. The receiver operating characteristic curve generated from the results revealed an excellent discrimination of BCC from NST with an area under the curve (AUC) value of 0.961. The present study demonstrated that the metabolite profile and metabolite intensity differ between BCC and NST, and that HR-MAS ¹H NMR spectroscopy can be a valuable tool in the diagnosis of BCC.     

Distinguishing transgenic from non-transgenic Arabidopsis plants by 1H NMR-based metabolic fingerprinting

We have recently reported the construction of an nuclear magnetic resonance （NMR）-based metabonomics study platform, Automics. To examine the application of Automics in transgenic plants, we performed metabolic fingerprinting analysis, i.e., 1H NMR spectroscopy and multivariate analysis, on wild-type and transgenic Arabidopsis. We found that it was possible to distinguish wild-type from four transgenic plants by PLS-DA following application of orthogonal signal correction （OSC）. Scores plot following OSC clearly demonstrates significant variation between the transgenic and non-transgenic groups, suggesting that the metabolic changes among wild-type and transgenic lines are possibly associated with transgenic event, We also found that the major contributing metabolites were some specific amino acids （i.e., threonine and alanine）, which could correspond to the insertion of the selective marker BAR gene in the transgenic plants. Our data suggests that NMR-based metabonomics is an efficient method to distinguish fingerprinting difference between wild-type and transgenic plants, and can potentially be applied in the bio-safety assessment of transgenic plants.     

Distinguishing transgenic from non-transgenic Arabidopsis plants by 1H NMR-based metabolic fingerprinting

We have recently reported the construction of an nuclear magnetic resonance (NMR)-based metabonomics study platform, Automics.To examine the application of Automics in transgenic plants, we performed metabolic fingerprinting analysis, i.e., 1H NMR spectroscopy and multivariate analysis, on wild-type and transgenic Arabidopsis. We found that it was possible to distinguish wild-type from four transgenic plants by PLS-DA following application of orthogonal signal correction (OSC). Scores plot following OSC clearly demonstrates significant variation between the transgenic and non-transgenic groups, suggesting that the metabolic changes among wild-type and transgenic lines are possibly associated with transgenic event. We also found that the major contributing metabolites were some specific amino acids (i.e., threonine and alanine), which could correspond to the insertion of the selective marker BAR gene in the transgenic plants. Our data suggests that NMR-based metabonomics is an efficient method to distinguish fingerprinting difference between wild-type and transgenic plants, and can potentially be applied in the bio-safety assessment of transgenic plants.     

Dynamic imaging of glucose flux impedance using FRET sensors in wild-type Arabidopsis plants

Quantitative and dynamic analysis of metabolites and signalling molecules is limited by technical challenges in obtaining temporally resolved information at the cellular and compartmental level. Real-time information on signalling and metabolite levels with subcellular granularity can be obtained with the help of genetically encoded FRET (F?rster resonance energy transfer) nanosensors. FRET nanosensors represent powerful tools for gene discovery, and analysis of regulatory networks, for example by screening mutants. However, RNA silencing has impaired our ability to express FRET nanosensors functionally in Arabidopsis plants. This drawback was overcome here by expressing the nanosensors in RNA silencing mutants. However, the use of silencing mutants requires the generation of homozygous lines deficient in RNA silencing as well as the mutation of interest and co-expression of the nanosensor. Here it is shown that dynamic changes in cytosolic glucose levels can readily be quantified in wild-type Arabidopsis plants at early stages of development (7-15 d) before silencing had a major effect on fluorescence intensity. A detailed protocol for screening 10-20 mutant seedlings per day is provided. The detailed imaging protocol provided here is suitable for analysing sugar flux in young wild-type plants as well as mutants affected in sugar signalling, metabolism, or transport using a wide spectrum of FRET nanosensors.     

基于核磁共振波谱的盐芥盐胁迫代谢组学分析

以甲醇/水(1∶1)作为溶剂,利用高分辨核磁共振氢谱分析了盐生模式植物盐芥(Thellungiella salsuginea)代谢组对盐胁迫的响应。根据1H核磁共振(NMR)波谱,在盐芥莲座叶中准确鉴定出23种代谢产物,包括11种氨基酸、4种糖类、6种有机酸和2种其他代谢产物。主成分分析表明,150、300 mmol/L NaCl处理盐芥的代谢组与对照均有显著差异(P<0.05),两种浓度的NaCl处理对盐芥代谢组的影响也不相同。盐胁迫处理以后,盐芥23种代谢产物含量均发生显著变化,除天冬氨酸、延胡索酸受盐胁迫诱导含量下降以外,其余代谢物含量均不同程度升高。这些代谢物主要参与了糖类代谢途径、氨基酸合成途径、三羧酸循环和甜菜碱合成途径,这些代谢途径在盐芥响应盐胁迫过程中有重要作用。     

Intra- and inter-metabolite correlation spectroscopy of tomato metabolomics data obtained by liquid chromatography-mass spectrometry and nuclear magnetic resonance

Nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LCMS) are frequently used as technological platforms for metabolomics applications. In this study, the metabolic profiles of ripe fruits from 50 different tomato cultivars, including beef, cherry and round types, were recorded by both ¹H NMR and accurate mass LC-quadrupole time-of-flight (QTOF) MS. Different analytical selectivities were found for these both profiling techniques. In fact, NMR and LCMS provided complementary data, as the metabolites detected belong to essentially different metabolic pathways. Yet, upon unsupervised multivariate analysis, both NMR and LCMS datasets revealed a clear segregation of, on the one hand, the cherry tomatoes and, on the other hand, the beef and round tomatoes. Intra-method (NMR–NMR, LCMS–LCMS) and inter-method (NMR–LCMS) correlation analyses were performed enabling the annotation of metabolites from highly correlating metabolite signals. Signals belonging to the same metabolite or to chemically related metabolites are among the highest correlations found. Inter-method correlation analysis produced highly informative and complementary information for the identification of metabolites, even in de case of low abundant NMR signals. The applied approach appears to be a promising strategy in extending the analytical capacities of these metabolomics techniques with regard to the discovery and identification of biomarkers and yet unknown metabolites. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Subcellular reprogramming of metabolism during cold acclimation in Arabidopsis thaliana

Metabolite changes in plant leaves during exposure to low temperatures involve re‐allocation of a large number of metabolites between sub‐cellular compartments. Therefore, metabolite determination at the whole cell level may be insufficient for interpretation of the functional significance of cellular compounds. To investigate the cold‐induced metabolite dynamics at the level of individual sub‐cellular compartments, an integrative platform was developed that combines quantitative metabolite profiling by gas chromatography coupled to mass spectrometry (GC‐MS) with the non‐aqueous fractionation technique allowing separation of cytosol, vacuole and the plastidial compartment. Two mutants of Arabidopsis thaliana representing antipodes in the diversion of carbohydrate metabolism between sucrose and starch were compared to Col‐0 wildtype before and after cold acclimation to investigate interactions of cold acclimation with subcellular re‐programming of metabolism. A multivariate analysis of the data set revealed dominant effects of compartmentation on metabolite concentrations that were modulated by environmental condition and genetic determinants. While for both, the starchless mutant of plastidial phospho‐gluco mutase (pgm) and a mutant defective in sucrose‐phosphate synthase A1, metabolic constraints, especially at low temperature, could be uncovered based on subcellularly resolved metabolite profiles, only pgm had lowered freezing tolerance. Metabolic profiles of pgm point to redox imbalance as a possible reason for reduced cold acclimation capacity.