Characterization of potato plants with reduced StSYR1 expression

Vesicle fusion processes in plants are important for both development and stress responses. Transgenic potato plants with reduced expression of SYNTAXIN-RELATED1 (StSYR1), a gene encoding the potato homolog of Arabidopsis PENETRATION1 (AtPEN1), display spontaneous necrosis and chlorosis at later stages of development. In accordance with this developmental defect, tuber number, weight and overall yield are significantly reduced in StSYR1-RNAi lines. Enhanced resistance of StSYR1-RNAi plants to Phytophthora infestans, the causal agent of late blight disease of potato, correlates with enhanced levels of salicylic acid, whereas levels of 12-oxophytodienoic acid and jasmonic acid are unaltered. Cultured cells of StSYR1-RNAi lines secrete at least two compounds which are not detectable in the supernatant of control cells, suggesting an involvement of StSYR1 in secretion processes to the apoplast.

Lipid metabolite profiling identifies desmosterol metabolism as a new antiviral target for hepatitis C virus

Hepatitis C virus (HCV) infection has been clinically associated with serum lipid abnormalities, yet our understanding of the effects of HCV on host lipid metabolism and conversely the function of individual lipids in HCV replication remains incomplete. Using liquid chromatography-mass spectrometry metabolite profiling of the HCV JFH1 cell culture infection model, we identified a significant steady-state accumulation of desmosterol, an immediate precursor to cholesterol. Pharmacological inhibition or RNAi-mediated depletion of DHCR7 significantly reduced steady-state HCV protein expression and viral genomic RNA. Moreover, this effect was reversed when cultures were supplemented with exogenous desmosterol. Together, these observations suggest an intimate connection between HCV replication and desmosterol homeostasis and that the enzymes responsible for synthesis of desmosterol may be novel targets for antiviral design.

Metabolic recovery of Arabidopsis thaliana roots following cessation of oxidative stress

To cope with the various environmental stresses resulting in reactive oxygen species (ROS) production plant metabolism is known to be altered specifically under different stresses. After overcoming the stress the metabolism should be reconfigured to recover basal operation however knowledge concerning how this is achieved is cursory. To investigate the metabolic recovery of roots following oxidative stress, changes in metabolite abundance and carbon flow were analysed. Arabidopsis roots were treated by menadione to elicit oxidative stress. Roots were fed with (13)C labelled glucose and the redistribution of isotope was determined in order to study carbon flow. The label redistribution through many pathways such as glycolysis, the tricarboxylic acid (TCA) cycle and amino acid metabolism were reduced under oxidative stress. After menadione removal many of the stress-related changes reverted back to basal levels. Decreases in amounts of hexose phosphates, malate, 2-oxoglutarate, glutamate and aspartate were fully recovered or even increased to above the control level. However, some metabolites such as pentose phosphates and citrate did not recover but maintained their levels or even increased further. The alteration in label redistribution largely correlated with that in metabolite abundance. Glycolytic carbon flow reverted to the control level only 18 h after menadione removal although the TCA cycle and some amino acids such as aspartate and glutamate took longer to recover. Taken together, plant root metabolism was demonstrated to be able to overcome menadione-induced oxidative stress with the differential time period required by independent pathways suggestive of the involvement of pathway specific regulatory processes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0296-1) contains supplementary material, which is available to authorized users.

"Add to subtract": a simple method to remove complex background signals from the 1H nuclear magnetic resonance spectra of mixtures

Because of its highly reproducible and quantitative nature and minimal requirements for sample preparation or separation, (1)H nuclear magnetic resonance (NMR) spectroscopy is widely used for profiling small-molecule metabolites in biofluids. However (1)H NMR spectra contain many overlapped peaks. In particular, blood serum/plasma and diabetic urine samples contain high concentrations of glucose, which produce strong peaks between 3.2 ppm and 4.0 ppm. Signals from most metabolites in this region are overwhelmed by the glucose background signals and become invisible. We propose a simple "Add to Subtract" background subtraction method and show that it can reduce the glucose signals by 98% to allow retrieval of the hidden information. This procedure includes adding a small drop of concentrated glucose solution to the sample in the NMR tube, mixing, waiting for an equilibration time, and acquisition of a second spectrum. The glucose-free spectra are then generated by spectral subtraction using Bruker Topspin software. Subsequent multivariate statistical analysis can then be used to identify biomarker candidate signals for distinguishing different types of biological samples. The principle of this approach is generally applicable for all quantitative spectral data and should find utility in a variety of NMR-based mixture analyses as well as in metabolite profiling.

A Carbonyl Capture Approach for Profiling Oxidized Metabolites in Cell Extracts

Fourier-transform ion-cyclotron resonance mass spectrometry (FT-ICR-MS) detection of oxidized cellular metabolites is described using isotopologic, carbonyl-selective derivatizing agents that integrate aminooxy functionality for carbonyl capture, quaternary nitrogen for electrospray enhancement, and a hydrophobic domain for sample cleanup. These modular structural features enable rapid, sensitive analysis of complex mixtures of metabolite-derivatives by FT-ICR-MS via continuous nanoelectrospray infusion. Specifically, this approach can be used to globally assess levels of low abundance and labile aldehyde and ketone metabolites quantitatively and in high throughput manner. These metabolites are often key and unique indicators of various biochemical pathways and their perturbations. Analysis of lung adenocarcinoma A549 cells established a profile of carbonyl metabolites spanning multiple structural classes. We also demonstrate a procedure for metabolite quantification using pyruvate as a model analyte.

Metabolite profiling of antidepressant drug action reveals novel drug targets beyond monoamine elevation

Currently used antidepressants elevate monoamine levels in the synaptic cleft. There is good reason to assume that this is not the only source for antidepressant therapeutic activities and that secondary downstream effects may be relevant for alleviating symptoms of depression. We attempted to elucidate affected biochemical pathways downstream of monoamine reuptake inhibition by interrogating metabolomic profiles in DBA/2Ola mice after chronic paroxetine treatment. Metabolomic changes were investigated using gas chromatography-mass spectrometry profiling and group differences were analyzed by univariate and multivariate statistics. Pathways affected by antidepressant treatment were related to energy metabolism, amino acid metabolism and hormone signaling. The identified pathways reveal further antidepressant therapeutic action and represent targets for drug development efforts. A comparison of the central nervous system with blood plasma metabolite alterations identified GABA, galactose-6-phosphate and leucine as biomarker candidates for assessment of antidepressant treatment effects in the periphery.

LC/MS profiling of flavonoid glycoconjugates isolated from hairy roots, suspension root cell cultures and seedling roots of Medicago truncatula

Hairy roots and suspension cell cultures are commonly used in deciphering different problems related to the biochemistry and physiology of plant secondary metabolites. Here, we address about the issue of possible differences in the profiles of flavonoid compounds and their glycoconjugates derived from various plant materials grown in a standard culture media. We compared profiles of flavonoids isolated from seedling roots, hairy roots, and suspension root cell cultures of a model legume plant, Medicago truncatula. The analyses were conducted with plant isolates as well as the media. The LC/MS profiles of target natural products obtained from M. truncatula seedling roots, hairy roots, and suspension root cell cultures differed substantially. The most abundant compounds in seedlings roots were mono- and diglucuronides of isoflavones and/or flavones. This type of glycosylation was not observed in hairy roots or suspension root cell cultures. The only recognized glycoconjugates in the latter samples were glucose derivatives of isoflavones. Application of a high-resolution mass spectrometer helped evaluate the elemental composition of protonated molecules, such as [M + H](+). Comparison of collision-induced dissociation MS/MS spectra registered with a quadrupole time-of-flight analyzer for tissue extracts and standards allowed us to estimate the aglycone structure on the basis of the pseudo-MS(3) experiment. Structures of these natural products were described according to the registered mass spectra and literature data. The analyses conducted represent an overview of flavonoids and their conjugates in different types of plant material representing the model legume, M. truncatula. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0287-2) contains supplementary material, which is available to authorized users.

Bioinformatics tools for cancer metabolomics

It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages.

The volatile metabolome of grapevine roots: first insights into the metabolic response upon phylloxera attack

Many plant species respond to herbivore attack by an increased formation of volatile organic compounds. In this preliminary study we analysed the volatile metabolome of grapevine roots [Teleki 5C (Vitis berlandieri Planch. × Vitis riparia Michx.)] with the aim to gain insight into the interaction between phylloxera (Daktulosphaira vitifoliae Fitch; Hemiptera: Phylloxeridae) and grapevine roots. In the first part of the study, headspace solid phase microextraction (HS-SPME) coupled to gas chromatography - mass spectrometry (GC-MS) was used to detect and identify volatile metabolites in uninfested and phylloxera-infested root tips of the grapevine rootstock Teleki 5C. Based on the comparison of deconvoluted mass spectra with spectra databases as well as experimentally derived retention indices with literature values, 38 metabolites were identified, which belong to the major classes of plant volatiles including C6-compounds, terpenes (including modified terpenes), aromatic compounds, alcohols and n-alkanes. Based on these identified metabolites, changes in root volatiles were investigated and resulted in metabolite profiles caused by phylloxera infestation. Our preliminary data indicate that defence related pathways such as the mevalonate and/or alternative isopentenyl pyrophosphate-, the lipoxygenase- (LOX) as well as the phenylpropanoid pathway are affected in root galls as a response to phylloxera attack.

Metabolite Signature during Short-Day Induced Growth Cessation in Populus

The photoperiod is an important environmental signal for plants, and influences a wide range of physiological processes. For woody species in northern latitudes, cessation of growth is induced by short photoperiods. In many plant species, short photoperiods stop elongational growth after a few weeks. It is known that plant daylength detection is mediated by Phytochrome A (PHYA) in the woody hybrid aspen species. However, the mechanism of dormancy involving primary metabolism remains unclear. We studied changes in metabolite profiles in hybrid aspen leaves (young, middle, and mature leaves) during short-day-induced growth cessation, using a combination of gas chromatography-time-of-flight mass spectrometry, and multivariate projection methods. Our results indicate that the metabolite profiles in mature source leaves rapidly change when the photoperiod changes. In contrast, the differences in young sink leaves grown under long and short-day conditions are less distinct. We found short daylength induced growth cessation in aspen was associated with rapid changes in the distribution and levels of diverse primary metabolites. In addition, we conducted metabolite profiling of leaves of PHYA overexpressor (PHYAOX) and those of the control to find the discriminative metabolites between PHYAOX and the control under the short-day conditions. The metabolite changes observed in PHYAOX leaves, together with those in the source leaves, identified possible candidates for the metabolite signature (e.g., 2-oxo-glutarate, spermidine, putrescine, 4-amino-butyrate, and tryptophan) during short-day-induced growth cessation in aspen leaves.

Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids

One dimensional selective TOCSY experiments have been shown to be advantageous in providing improved data inputs for principle component analysis (PCA) (Sandusky and Raftery 2005a, b). Better subpopulation cluster resolution in the observed scores plots results from the ability to isolate metabolite signals of interest via the TOCSY based filtering approach. This report reexamines the quantitative aspects of this approach, first by optimizing the 1D TOCSY experiment as it relates to the measurement of biofluid constituent concentrations, and second by comparing the integration of 1D TOCSY read peaks to the bucket integration of 1D proton NMR spectra in terms of precision and accuracy. This comparison indicates that, because of the extensive peak overlap that occurs in the 1D proton NMR spectra of biofluid samples, bucket integrals are often far less accurate as measures of individual constituent concentrations than 1D TOCSY read peaks. Even spectral fitting approaches have proven difficult in the analysis of significantly overlapped spectral regions. Measurements of endogenous taurine made over a sample population of human urine demonstrates that, due to background signals from other constituents, bucket integrals of 1D proton spectra routinely overestimate the taurine concentrations and distort its variation over the sample population. As a result, PCA calculations performed using data matrices incorporating 1D TOCSY determined taurine concentrations produce better scores plot subpopulation cluster resolution.

Metabonomic investigation of liver profiles of nonpolar metabolites obtained from alcohol-dosed rats and mice using high mass accuracy MSn analysis

Alcoholism is a complex disorder that, in man, appears to be genetically influenced, although the underlying genes and molecular pathways are not completely known. Here, the intragastric alcohol feeding model in rodents was used together with high mass accuracy LC-MS(n) analysis to assess the metabonomic changes in nonpolar metabolite profiles for livers from control and alcohol-treated rats and mice. Ion signals with a peak area variance of less than 30% (based on repeat analysis of a pooled quality control sample analyzed throughout the batch) were submitted to multivariate statistical analysis (using principal components analysis, PCA). PCA revealed robust differences between profiles from control and alcohol-treated animals from both species. The major metabolites seen to differ between control and alcohol-treated animals were identified using high accuracy MS(n) data and verified using external search engines ( http://www.lipidmaps.org ; http://www.hmdb.ca; http://www.genome.jp/kegg/ ) and authentic standards. The main metabolite classes to show major changes in the alcoholic liver-derived samples were fatty acyls, fatty acid ethyl esters, glycerolipids, and phosphatidylethanol homologues. Significant metabolites that were up-regulated by alcohol treatment in both rat and mouse livers included fatty acyls, metabolites such as octadecatrienoic acid and eicosapentaenoic acid, a number of fatty acid ethyl esters such as ethyl arachidonate, ethyl docosahexaenoic acid, ethyl linoleate, and ethyl oleate and phosphatidylethanol (PEth) homologues (predominantly PEth 18:0/18:2 and PEth 16:0/18:2; PEth homologues are currently considered as potential biomarkers for harmful and prolonged alcohol consumption in man). A number of glycerophospholipids resulted in both up-regulation (m/z 903.7436 [M + H](+) corresponding to a triglyceride) and down-regulation (m/z 667.5296 [M + H](+) corresponding to a diglyceride). Metabolite profiles were broadly similar in both mouse and rat models. However, there were a number of significant differences in the alcohol-treated group particularly in the marked down-regulation of retinol and free cholesterol in the mouse compared to the rat. Unique markers for alcohol treatment included ethyl docosahexaenoic acid. Metabolites were identified with high confidence using predominantly negative ion MS(n) data for the fatty acyl components to match to www.lipidmaps.org MS and MS/MS databases; interpreting positive ion data needed to take into account possible adduct ions which may confound the identification of other lipid classes. The observed changes in lipid profiles were consistent with alcohol-induced liver injury in humans.

Decision tree supported substructure prediction of metabolites from GC-MS profiles

Gas chromatography coupled to mass spectrometry (GC-MS) is one of the most widespread routine technologies applied to the large scale screening and discovery of novel metabolic biomarkers. However, currently the majority of mass spectral tags (MSTs) remains unidentified due to the lack of authenticated pure reference substances required for compound identification by GC-MS. Here, we accessed the information on reference compounds stored in the Golm Metabolome Database (GMD) to apply supervised machine learning approaches to the classification and identification of unidentified MSTs without relying on library searches. Non-annotated MSTs with mass spectral and retention index (RI) information together with data of already identified metabolites and reference substances have been archived in the GMD. Structural feature extraction was applied to sub-divide the metabolite space contained in the GMD and to define the prediction target classes. Decision tree (DT)-based prediction of the most frequent substructures based on mass spectral features and RI information is demonstrated to result in highly sensitive and specific detections of sub-structures contained in the compounds. The underlying set of DTs can be inspected by the user and are made available for batch processing via SOAP (Simple Object Access Protocol)-based web services. The GMD mass spectral library with the integrated DTs is freely accessible for non-commercial use at http://gmd.mpimp-golm.mpg.de/. All matching and structure search functionalities are available as SOAP-based web services. A XML + HTTP interface, which follows Representational State Transfer (REST) principles, facilitates read-only access to data base entities.

An inter-laboratory comparison demonstrates that [H]-NMR metabolite fingerprinting is a robust technique for collaborative plant metabolomic data collection

In any metabolomics experiment, robustness and reproducibility of data collection is of vital importance. These become more important in collaborative studies where data is to be collected on multiple instruments. With minimisation of variance in sample preparation and instrument performance it is possible to elucidate even subtle differences in metabolite fingerprints due to genotype or biological treatment. In this paper we report on an inter laboratory comparison of plant derived samples by [(1)H]-NMR spectroscopy across five different sites and within those sites utilising instruments with different probes and magnetic field strengths of 9.4 T (400 MHz), 11.7 T (500 MHz) and 14.1 T (600 MHz). Whilst the focus of the study is on consistent data collection across laboratories, aspects of sample stability and the requirement for sample rotation within the NMR magnet are also discussed. Comparability of the datasets from participating laboratories was exceptionally good and the data were amenable to comparative analysis by multivariate statistics. Field strength differences can be adjusted for in the data pre-processing and multivariate analysis demonstrating that [(1)H]-NMR fingerprinting is the ideal technique for large scale plant metabolomics data collection requiring the participation of multiple laboratories.

Downregulation of pyrophosphate: D-fructose-6-phosphate 1-phosphotransferase activity in sugarcane culms enhances sucrose accumulation due to elevated hexose-phosphate levels

Analyses of transgenic sugarcane clones with 45-95% reduced cytosolic pyrophosphate: D-fructose-6-phosphate 1-phosphotransferase (PFP, EC 2.7.1.90) activity displayed no visual phenotypical change, but significant changes were evident in in vivo metabolite levels and fluxes during internode development. In three independent transgenic lines, sucrose concentrations increased between three- and sixfold in immature internodes, compared to the levels in the wildtype control. There was an eightfold increase in the hexose-phosphate:triose-phosphate ratio in immature internodes, a significant restriction in the triose phosphate to hexose phosphate cycle and significant increase in sucrose cycling as monitored by (13)C nuclear magnetic resonance. This suggests that an increase in the hexose-phosphate concentrations resulting from a restriction in the conversion of hexose phosphates to triose phosphates drive sucrose synthesis in the young internodes. These effects became less pronounced as the tissue matured. Decreased expression of PFP also resulted in an increase of the ATP/ADP and UTP/UDP ratios, and an increase of the total uridine nucleotide and, at a later stage, the total adenine nucleotide pool, revealing strong interactions between PPi metabolism and general energy metabolism. Finally, decreased PFP leads to a reduction of PPi levels in older internodes indicating that in these developmental stages PFP acts in the gluconeogenic direction. The lowered PPi levels might also contribute to the absence of increases in sucrose contents in the more mature tissues of transgenic sugarcane with reduced PFP activity.

Application of 31P NMR spectroscopy and chemical derivatization for metabolite profiling of lipophilic compounds in human serum

New methods for obtaining metabolic fingerprints of biological samples with improved resolution and sensitivity are highly sought for early disease detection, studies of human health and pathophysiology, and for better understanding systems biology. Considering the complexity of biological samples, interest in biochemical class selection through the use of chemoselective probes for improved resolution and quantitation is increasing. Considering the role of lipids in the pathogenesis of a number of diseases, in this study fingerprinting of lipid metabolites was achieved by (31)P labeling using the derivatizing agent 2-chloro-4,4,5,5-tetramethyldioxaphospholane. Lipids containing hydroxyl, aldehyde and carboxyl groups were selectively tagged with (31)P and then detected with good resolution using (31)P NMR by exploiting the 100% natural abundance and wide chemical shift range of (31)P. After standardizing the reaction conditions using representative compounds, the derivatization approach was used to profile lipids in human serum. The results show that the (31)P derivatization approach is simple, reproducible and highly quantitative, and has the potential to profile a number of important lipids in complex biological samples.

1H NMR metabolomics study of age profiling in children

Metabolic profiling of urine provides a fingerprint of personalized endogenous metabolite markers that correlate to a number of factors such as gender, disease, diet, toxicity, medication, and age. It is important to study these factors individually, if possible to unravel their unique contributions. In this study, age-related metabolic changes in children of age 12 years and below were analyzed by (1)H NMR spectroscopy of urine. The effect of age on the urinary metabolite profile was observed as a distinct age-dependent clustering even from the unsupervised principal component analysis. Further analysis, using partial least squares with orthogonal signal correction regression with respect to age, resulted in the identification of an age-related metabolic profile. Metabolites that correlated with age included creatinine, creatine, glycine, betaine/TMAO, citrate, succinate, and acetone. Although creatinine increased with age, all the other metabolites decreased. These results may be potentially useful in assessing the biological age (as opposed to chronological) of young humans as well as in providing a deeper understanding of the confounding factors in the application of metabolomics.

Interdependence of signal processing and analysis of urine 1H NMR spectra for metabolic profiling

Metabolic profiling of urine presents challenges because of the extensive random variation of metabolite concentrations and the dilution resulting from changes in the overall urine volume. Thus statistical analysis methods play a particularly important role; however, appropriate choices of these methods are not straightforward. Here we investigate constant and variance-stabilization normalization of raw and peak picked spectra, for use with exploratory analysis (principal component analysis) and confirmatory analysis (ordinary and Empirical Bayes t-test) in (1)H NMR-based metabolic profiling of urine. We compare the performance of these methods using urine samples spiked with known metabolites according to a Latin square design. We find that analysis of peak picked and logarithm-transformed spectra is preferred, and that signal processing and statistical analysis steps are interdependent. While variance-stabilizing transformation is preferred in conjunction with principal component analysis, constant normalization is more appropriate for use with a t-test. Empirical Bayes t-test provides more reliable conclusions when the number of samples in each group is relatively small. Performance of these methods is illustrated using a clinical metabolomics experiment on patients with type 1 diabetes to evaluate the effect of insulin deprivation.

Stilbene synthase gene transfer caused alterations in the phenylpropanoid metabolism of transgenic strawberry (Fragaria x ananassa)

The gene encoding stilbene synthase is frequently used to modify plant secondary metabolism with the aim of producing the self-defence phytoalexin resveratrol. In this study, strawberry (Fragaria x ananassa) was transformed with the NS-Vitis3 gene encoding stilbene synthase from frost grape (Vitis riparia) under the control of the cauliflower mosaic virus 35S and the floral filament-specific fil1 promoters. Changes in leaf metabolites were investigated with UPLC-qTOF-MS (ultra performance liquid chromatography-quadrupole time of flight mass spectrometry) profiling, and increased accumulation of cinnamate, coumarate, and ferulate derivatives concomitantly with a decrease in the levels of flavonols was observed, while the anticipated resveratrol or its derivatives were not detected. The changed metabolite profile suggested that chalcone synthase was down-regulated by the genetic modification; this was verified by decreased chalcone synthase transcript levels. Changes in the levels of phenolic compounds led to increased susceptibility of the transgenic strawberry to grey mould fungus.

Metabolic characterization of loci affecting sensory attributes in tomato allows an assessment of the influence of the levels of primary metabolites and volatile organic contents

Numerous studies have revealed the extent of genetic and phenotypic variation between both species and cultivars of tomato. Using a series of tomato lines resulting from crosses between a cherry tomato and three independent large fruit cultivar (Levovil, VilB, and VilD), extensive profiling of both central primary metabolism and volatile organic components of the fruit was performed. In this study, it was possible to define a number of quantitative trait loci (QTLs) which determined the levels of primary metabolites and/or volatile organic components and to evaluate their co-location with previously defined organoleptic QTLs. Correlation analyses between either the primary metabolites or the volatile organic compounds and organoleptic properties revealed a number of interesting associations, including pharmaceutical aroma-guaiacol and sourness-alanine, across the data set. Considerable correlation within the levels of primary metabolites or volatile organic compounds, respectively, were also observed. However, there was relatively little association between the levels of primary metabolites and volatile organic compounds, implying that they are not tightly linked to one another. A notable exception to this was the strong association between the levels of sucrose and those of a number of volatile organic compounds. The combined data presented here are thus discussed both with respect to those obtained recently from wide interspecific crosses of tomato and within the framework of current understanding of the chemical basis of fruit taste.

Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry

Gas chromatography coupled to mass spectrometry (GC-MS) is one of the most frequently used tools for profiling primary metabolites. Instruments are mature enough to run large sequences of samples; novel advancements increase the breadth of compounds that can be analyzed, and improved algorithms and databases are employed to capture and utilize biologically relevant information. Around half the published reports on metabolite profiling by GC-MS focus on biological problems rather than on methodological advances. Applications span from comprehensive analysis of volatiles to assessment of metabolic fluxes for bioengineering. Method improvements emphasize extraction procedures, evaluations of quality control of GC-MS in comparison to other techniques and approaches to data processing. Two major challenges remain: rapid annotation of unknown peaks; and, integration of biological background knowledge aiding data interpretation.

Cyclic changes in metabolic state during the life of a yeast cell

Budding yeast undergo robust oscillations in oxygen consumption during continuous growth in a nutrient-limited environment. Using liquid chromatography-mass spectrometry and comprehensive 2D gas chromatography-mass spectrometry-based metabolite profiling methods, we have determined that the intracellular concentrations of many metabolites change periodically as a function of these metabolic cycles. These results reveal the logic of cellular metabolism during different phases of the life of a yeast cell. They may further indicate that oscillation in the abundance of key metabolites might help control the temporal regulation of cellular processes and the establishment of a cycle. Such oscillations in metabolic state might occur during the course of other biological cycles.

Metabolic processes sustaining the reviviscence of lichen Xanthoria elegans (Link) in high mountain environments

To survive in high mountain environments lichens must adapt themselves to alternating periods of desiccation and hydration. Respiration and photosynthesis of the foliaceous lichen, Xanthoria elegans, in the dehydrated state were below the threshold of CO2-detection by infrared gas analysis. Following hydration, respiration totally recovered within seconds and photosynthesis within minutes. In order to identify metabolic processes that may contribute to the quick and efficient reactivation of lichen physiological processes, we analysed the metabolite profile of lichen thalli step by step during hydration/dehydration cycles, using 31P- and 13C-NMR. It appeared that the recovery of respiration was prepared during dehydration by the accumulation of a reserve of gluconate 6-P (glcn-6-P) and by the preservation of nucleotide pools, whereas glycolytic and photosynthetic intermediates like glucose 6-P and ribulose 1,5-diphosphate were absent. The large pools of polyols present in both X. elegans photo- and mycobiont are likely to contribute to the protection of cell constituents like nucleotides, proteins, and membrane lipids, and to preserve the integrity of intracellular structures during desiccation. Our data indicate that glcn-6-P accumulated due to activation of the oxidative pentose phosphate pathway, in response to a need for reducing power (NADPH) during the dehydration-triggered down-regulation of cell metabolism. On the contrary, glcn-6-P was metabolised immediately after hydration, supplying respiration with substrates during the replenishment of pools of glycolytic and photosynthetic intermediates. Finally, the high net photosynthetic activity of wet X. elegans thalli at low temperature may help this alpine lichen to take advantage of brief hydration opportunities such as ice melting, thus favouring its growth in harsh high mountain climates.

Metabolic engineering of dhurrin in transgenic Arabidopsis plants with marginal inadvertent effects on the metabolome and transcriptome

Focused and nontargeted approaches were used to assess the impact associated with introduction of new high-flux pathways in Arabidopsis thaliana by genetic engineering. Transgenic A. thaliana plants expressing the entire biosynthetic pathway for the tyrosine-derived cyanogenic glucoside dhurrin as accomplished by insertion of CYP79A1, CYP71E1, and UGT85B1 from Sorghum bicolor were shown to accumulate 4% dry-weight dhurrin with marginal inadvertent effects on plant morphology, free amino acid pools, transcriptome, and metabolome. In a similar manner, plants expressing only CYP79A1 accumulated 3% dry weight of the tyrosine-derived glucosinolate, p-hydroxybenzylglucosinolate with no morphological pleitropic effects. In contrast, insertion of CYP79A1 plus CYP71E1 resulted in stunted plants, transcriptome alterations, accumulation of numerous glucosides derived from detoxification of intermediates in the dhurrin pathway, and in loss of the brassicaceae-specific UV protectants sinapoyl glucose and sinapoyl malate and kaempferol glucosides. The accumulation of glucosides in the plants expressing CYP79A1 and CYP71E1 was not accompanied by induction of glycosyltransferases, demonstrating that plants are constantly prepared to detoxify xenobiotics. The pleiotrophic effects observed in plants expressing sorghum CYP79A1 and CYP71E1 were complemented by retransformation with S. bicolor UGT85B. These results demonstrate that insertion of high-flux pathways directing synthesis and intracellular storage of high amounts of a cyanogenic glucoside or a glucosinolate is achievable in transgenic A. thaliana plants with marginal inadvertent effects on the transcriptome and metabolome.