Showing papers in "Metabolomics in 2009"

Environmental metabolomics: a critical review and future perspectives

Abstract: Environmental metabolomics is the application of metabolomics to characterise the interactions of organisms with their environment. This approach has many advantages for studying organism–environment interactions and for assessing organism function and health at the molecular level. As such, metabolomics is finding an increasing number of applications in the environmental sciences, ranging from understanding organismal responses to abiotic pressures, to investigating the responses of organisms to other biota. These interactions can be studied from individuals to populations, which can be related to the traditional fields of ecophysiology and ecology, and from instantaneous effects to those over evolutionary time scales, the latter enabling studies of genetic adaptation. This review provides a comprehensive and current overview of environmental metabolomics research. We begin with an overview of metabolomic studies into the effects of abiotic pressures on organisms. In the field of ecophysiology, studies on the metabolic responses to temperature, water, food availability, light and circadian rhythms, atmospheric gases and season are reviewed. A section on ecotoxicogenomics discusses research in aquatic and terrestrial ecotoxicology, assessing organismal responses to anthropogenic pollutants in both the laboratory and field. We then discuss environmental metabolomic studies of diseases and biotic–biotic interactions, in particular herbivory. Finally, we critically evaluate the contribution that metabolomics has made to the environmental sciences, and highlight and discuss recommendations to advance our understanding of the environment, ecology and evolution using a metabolomics approach.

Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research

Abstract: Mass spectrometry (MS) techniques, because of their sensitivity and selectivity, have become methods of choice to characterize the human metabolome and MS-based metabolomics is increasingly used to characterize the complex metabolic effects of nutrients or foods. However progress is still hampered by many unsolved problems and most notably the lack of well established and standardized methods or procedures, and the difficulties still met in the identification of the metabolites influenced by a given nutritional intervention. The purpose of this paper is to review the main obstacles limiting progress and to make recommendations to overcome them. Propositions are made to improve the mode of collection and preparation of biological samples, the coverage and quality of mass spectrometry analyses, the extraction and exploitation of the raw data, the identification of the metabolites and the biological interpretation of the results.

A direct cell quenching method for cell-culture based metabolomics

Abstract: A crucial step in metabolomic analysis of cellular extracts is the cell quenching process. The conventional method first uses trypsin to detach cells from their growth surface. This inevitably changes the profile of cellular metabolites since the detachment of cells from the extracellular matrix alters their physiology. This conventional method also includes time consuming wash/centrifuge steps after trypsinization, but prior to quenching cell activity. During this time, a considerable portion of intracellular metabolites are lost, rendering the conventional method less than ideal for application to metabolomics. We report here a novel sample preparation method for metabolomics applications using adherent mammalian cells, which eliminates the time consumption and physiological stress of the trypsinization and wash/centrifuge steps. This new method was evaluated in the study of metabolic changes caused by 17α-ethynylestradiol (EE2) in estrogen receptor (ER)-positive MCF-7 and ER-negative MDA-MB-231 human breast cancer cell lines using NMR spectroscopy. The results demonstrated that our direct cell quenching method is rapid, effective, and exhibits greater metabolite retention, providing an increase of approximately a factor of 50 compared to the conventional method.

Metabolomic analysis of the interaction between plants and herbivores

Abstract: Insect herbivores by necessity have to deal with a large arsenal of plant defence metabolites. The levels of defence compounds may be increased by insect damage. These induced plant responses may also affect the metabolism and performance of successive insect herbivores. As the chemical nature of induced responses is largely unknown, global metabolomic analyses are a valuable tool to gain more insight into the metabolites possibly involved in such interactions. This study analyzed the interaction between feral cabbage (Brassica oleracea) and small cabbage white caterpillars (Pieris rapae) and how previous attacks to the plant affect the caterpillar metabolism. Because plants may be induced by shoot and root herbivory, we compared shoot and root induction by treating the plants on either plant part with jasmonic acid. Extracts of the plants and the caterpillars were chemically analysed using Ultra Performance Liquid Chromatography/Time of Flight Mass Spectrometry (UPLCT/MS). The study revealed that the levels of three structurally related coumaroylquinic acids were elevated in plants treated on the shoot. The levels of these compounds in plants and caterpillars were highly correlated: these compounds were defined as the ‘metabolic interface’. The role of these metabolites could only be discovered using simultaneous analysis of the plant and caterpillar metabolomes. We conclude that a metabolomics approach is useful in discovering unexpected bioactive compounds involved in ecological interactions between plants and their herbivores and higher trophic levels.

A new approach to toxicity testing in Daphnia magna: application of high throughput FT-ICR mass spectrometry metabolomics

Abstract: Currently there is a surge of interest in exploiting toxicogenomics to screen the toxicity of chemicals, enabling rapid and accurate categorisation into classes of defined mode-of-action (MOA), and prioritising chemicals for further testing. Direct infusion FT-ICR mass spectrometry-based metabolomics can provide a sensitive and unbiased analysis of metabolites in only 15 mins and therefore has considerable potential for chemical screening. The water flea, Daphnia magna, is an OECD test species and is utilised internationally for toxicity testing. However, no metabolomics studies of this species have been reported. Here we optimised and evaluated the effectiveness of FT-ICR mass spectrometry metabolomics for toxicity testing in D. magna. We confirmed that high-quality mass spectra can be recorded from as few as 30 neonates (<24 h old; 224 μg dry mass) or a single adult daphnid (301 μg dry mass). An OECD 24 h acute toxicity test was conducted with neonates at copper concentrations of 0, 5, 10, 25, 50 μg l−1. A total of 5447 unique peaks were detected reproducibly, of which 4768 were assigned at least one empirical formula and 1017 were putatively identified based upon accurate mass measurements. Significant copper-induced changes to the daphnid metabolome, consistent with the documented MOA of copper, were detected thereby validating the approach. In addition, N-acetylspermidine was putatively identified as a novel biomarker of copper toxicity. Collectively, our results highlight the excellent sensitivity, reproducibility and mass accuracy of FT-ICR mass spectrometry, and provide strong evidence for its applicability to high-throughput screening of chemical toxicity in D. magna.

Effects of Sample Handling and Storage on Quantitative Lipid Analysis in Human Serum

Abstract: There is sparse information about specific storage and handling protocols that minimize analytical error and variability in samples evaluated by targeted metabolomics. Variance components that affect quantitative lipid analysis in a set of human serum samples were determined. The effects of freeze-thaw, extraction state, storage temperature, and freeze-thaw prior to density-based lipoprotein fractionation were quantified. The quantification of high abundance metabolites, representing the biologically relevant lipid species in humans, was highly repeatable (with coefficients of variation as low as 0.01 and 0.02) and largely unaffected by 1–3 freeze-thaw cycles (with 0–8% of metabolites affected in each lipid class). Extraction state had effects on total lipid class amounts, including decreased diacylglycerol and increased phosphatidylethanolamine in thawed compared with frozen samples. The effects of storage temperature over 1 week were minimal, with 0–4% of metabolites affected by storage at 4°C, −20°C, or −80°C in most lipid classes, and 19% of metabolites in diacylglycerol affected by storage at −20°C. Freezing prior to lipoprotein fractionation by density ultracentrifugation decreased HDL free cholesterol by 37% and VLDL free fatty acid by 36%, and increased LDL cholesterol ester by 35% compared with fresh samples. These findings suggest that density-based fractionation should preferably be undertaken in fresh serum samples because up to 37% variability in HDL and LDL cholesterol could result from a single freeze-thaw cycle. Conversely, quantitative lipid analysis within unfractionated serum is minimally affected even with repeated freeze-thaw cycles.

An environmental 1H NMR metabolomic study of the exposure of the marine mussel Mytilus edulis to atrazine, lindane, hypoxia and starvation

Abstract: Marine mussels are useful, robust model organisms that have been widely used as biomonitors. In the natural environment they can be subjected simultaneously to a mixture of environmental stresses (hypoxia, starvation) and to pollutants. In this study Mytilus edulis was used to investigate the effects of two pesticides, atrazine and lindane, which have different modes of action but produce similar changes in behaviour (depression of ventilation and feeding) in the mussels, and can cause starvation and mild hypoxia. Acetonitrile/2H2O (60/40% v/v) extracts of foot muscle from animals subjected to hypoxia, or starvation, or low or high doses of pesticide were analysed using 1H NMR spectroscopy to produce metabolic fingerprints associated with these treatments. Discriminant analysis based on metabolites that showed significant differences between treated and control animals gave a clear separation between all treatment groups. The fingerprints of atrazine treated animals were clearly separated from those of animals that were starved or subjected to hypoxia. The high and low doses of atrazine were also well separated. Lindane treatment was separated from control animals in a dose dependent way, and was associated with an increase in the concentration of alanine, and a decrease in all of the other identified metabolites (including osmolytes). This is consistent with a general depression of activity. This limited study demonstrates the potential of the metabolomic approach to provide a separation of the effects of poisoning from those of environmental stress.

Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI-TOF/MS) based plant metabolomics

Abstract: The application of gas chromatography-mass spectrometry (GC-MS) to the 'global' analysis of metab- olites in complex samples (i.e. metabolomics) has now become routine. The generation of these data-rich profiles demands new strategies in data mining and standardisation of experimental and reporting aspects across laboratories. As part of the META-PHOR project's (METAbolomics for Plants Health and OutReach: http://www.meta-phor.eu/) priorities towards robust technology development, a GC- MS ring experiment based upon three complex matrices (melon, broccoli and rice) was launched. All sample preparation, data processing, multivariate analyses and comparisons of major metabolite features followed stand- ardised protocols, identical models of GC (Agilent 6890N) and TOF/MS (Leco Pegasus III) were also employed. In addition comprehensive GC9GC-TOF/MS was compared with 1 dimensional GC-TOF/MS. Comparisons of the paired data from the various laboratories were made with a single data processing and analysis method providing an unbiased assessment of analytical method variants and inter-laboratory reproducibility. A range of processing and statistical methods were also assessed with a single exemplary dataset revealing near equal performance between them. Further investigations of long-term repro- ducibility are required, though the future generation of global and valid metabolomics databases offers much promise.

1H NMR and GC/MS metabolomics of earthworm responses to sub-lethal DDT and endosulfan exposure

Abstract: The metabolic response of the earthworm Eisenia fetida to two pesticides, dichlorodiphenyltrichloroethane (DDT) and endosulfan, was characterized in contact tests using proton nuclear magnetic resonance (1H NMR) and principal component analysis (PCA). PCA loading plots suggested that maltose, leucine and alanine were important metabolites contributing to the differences in dosed and control earthworms for both compounds at doses of 0.5, 1.0 and 2.0 μg/cm2. Gas chromatography/mass spectrometry (GC/MS) was used to quantify the metabolites identified in E. fetida and determine if the changes in maltose, leucine and alanine following exposure to DDT and endosulfan (at 0.5 and 1.0 μg/cm2) were reproducible and greater than the natural variability. Quantification by GC/MS suggested that maltose was not a reliable biomarker since it both increased and decreased in earthworms exposed to DDT and increased by just 3% with exposure to endosulfan. Leucine was not stable with the GC/MS derivitization method used in this study and could not be confirmed as a reliable biomarker. However, alanine consistently increased for both DDT and endosulfan exposed E. fetida. Alanine showed considerable variability in control earthworms (±41.6%), yet the variability in alanine to glycine ratios was just ±10.5%. Increases in the alanine to glycine ratio were statistically significant at the P = 0.05 level for the 1.0 μg/cm2 DDT dose and both the 0.5 and 1.0 μg/cm2 endosulfan doses, suggesting that deviations from the normal homeostatic ratio of 1.5 for alanine to glycine is a potential biomarker of DDT and endosulfan exposure warranting further study.

Characterization of the biochemical variability of bovine milk using metabolomics

Abstract: Bovine milk contains a complex mixture of metabolites, which were identified by liquid and gas chromatography mass spectrometry methods. With the aid of new software methods, spectral assignment was carried out, enabling the identification of 223 metabolites. Those included amino acids, lipids, carbohydrates, nucleotides, energy metabolites, vitamins, cofactors and short peptides. Metabolite concentrations were compared between 10 bovine milk varieties, differing in brand, fat content, expiry date, package type and farming method. Principal components analysis showed a clear separation of the different milk varieties. Whole milk could be distinguished from reduced fat and fat free milk by higher lipid metabolites like free fatty acids, cholesterol and 1,2-dipalmitoylglycerol. But also, the reduced fat varieties had lower levels of vitamin E. In comparing organic to conventional milk, 14 named metabolites were statistically different between the two farming methods. This shows the potential of identifying farming-method-specific biomarkers upon analysis and validation of a larger sample size. Finally, high biochemical variability was shown in conventional whole milk derived from different producers. The distinct biochemical profiles of milk varieties shows the utility of metabolic profiling for authentication of milk varieties, and for deriving potential markers that can serve as signatures for a particular milk.

Metabolic characterization of primary human colorectal cancers using high resolution magic angle spinning 1H magnetic resonance spectroscopy

Abstract: Colorectal cancer is one of the most frequent and most lethal forms of cancer in the western world. The aim of this study is to characterize by 1H high resolution magic angle spinning NMR spectroscopy (HRMAS) the metabolic fingerprint of both tumoral and healthy tissue samples obtained from a cohort of patients affected by primary colorectal adenocarcinoma. By analyzing HRMAS data using multivariate statistical analysis (PLS-DA), the two types of tissues could be discriminated with a high level of confidence. The identification of the metabolites at the origin of this discrimination revealed that adenocarcinomas are richer in taurine, glutamate, aspartate, and lactate whereas healthy tissues contain a higher amount of myo-inositol and β-glucose. The statistical model resulting from the PLS-DA analysis was subsequently used to perform a blind test on tumoral and healthy colon biopsies. The results of the classification showed that the HRMAS analysis has very high sensitivity and specificity.

Systems toxicology study of doxorubicin on rats using ultra performance liquid chromatography coupled with mass spectrometry based metabolomics

Abstract: A metabolomics-based systems toxicology approach was used to profile the urinary metabolites for the toxicity related processes and pathogenesis induced by doxorubicin (DOX) to rats. Endogenous metabolite profiles were obtained with ultra performance liquid chromatography-mass spectrometry (UPLC-MS) for rats receiving different single dosages of DOX (5, 10 or 20 mg/kg) prior and at three time points after dosage. Principal components analysis (PCA) allowed detection of two major systemic metabolic changes with the time due to the induced toxicity. Furthermore, Analysis of variance (ANOVA) Simultaneous Component Analysis (ASCA) was applied to reveal the variation caused by time and dose, and their interaction in a multivariate way. Finally, various metabolites involved in the toxic processes could be identified using their accurate mass and MSn experiments, and possible mechanisms of the toxicity of DOX were postulated. In conclusion, metabolomics as a systems toxicology approach was able to provide comprehensive information on the dynamic process of drug induced toxicity. In addition, detection of the systemic toxic effects could be obtained with metabolomics at an earlier stage compared to the clinical chemistry and histopathological assessment.

Profiling lipid metabolites yields unique information on sex- and time-dependent responses of fathead minnows ( Pimephales promelas ) exposed to 17α-ethynylestradiol

Abstract: Alterations in hepatic lipid profiles of fathead minnows (FHM) exposed to the synthetic estrogen 17α-ethynylestradiol (EE2) were determined using 1H-NMR spectroscopy-based metabolite profiling. The exposures were conducted using either 10 ng/l or 100 ng/l EE2 via a continuous flow water delivery system. Livers were collected at 1, 4, and 8 days of the exposure and 8 days after the chemical was removed from the water (i.e. an 8 day depuration). The exposure resulted in a number of sex-specific changes in lipid profiles that were also highly time dependent. Those metabolites most affected by exposure included phosphatidylcholine, diglycerides, triglycerides and cholesterol. In addition, changes in the length and degree of unsaturation of hepatic fatty acids were observed. Lipid profiles in plasma for fish collected on the 4th day of exposure were also analyzed in order to provide further insights into changes observed in hepatic metabolite changes. Using validated partial least-squares discriminant analysis (PLS-DA), the response trajectories of the male liver lipid profiles at both exposure concentrations were compared. This analysis indicated that the males exposed to the low concentration of EE2 (10 ng/l) were largely able to recover from the exposure once the chemical was removed from the water. Conversely, the males exposed to the high concentration (100 ng/l) did not appear to recover from the exposure despite the 8 day depuration.

Terpenoid metabolic profiling analysis of transgenic Artemisia annua L. by comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry

Abstract: Amorpha-4,11-diene synthase (ADS) is a very important enzyme which catalyzes the committed step of artemisinin biosynthesis. In this work, two lines of transgenic Artemisia annua L. which ADS was over-expressed (line A9) and suppressed (line Amsi), respectively, were utilized. And the transgenic line GUS with β-Glucuronidase gene was regarded as the control. Their terpenoid metabolic profiling was investigated by using GC × GC–TOFMS. The metabolic profiling method established included simple extraction, two-dimension separation and multivariate analysis. Partial least squares discriminant analysis (PLS-DA) was used to classify two transgenic lines and the control line. Eleven important compounds in classification were identified. Most of them were sesquiterpenoids including monoterpenoid, diterpenoid and four bioprecursors of artemsisnin. Compared with the control, artemisinin and bioprecursors in the line A9 increased as a result of over-expressing ADS. Borneol and phytol also increased in the line A9, but (E)-β-farnesene and germacrene D were reversely altered. The result indicated that over-expression of the ADS affected not only artemisinin biosynthesis, but also the whole metabolic network of terpenoid. Compared with the line A9, no opposite change of artemisinin and related derivatives was observed in the line Amsi, the ADS inhibition had no significant effect on artemisinin biosynthesis in the line Amsi.

Metabolite profiling of maize grain: differentiation due to genetics and environment

Abstract: A comparative metabolite profiling approach based on gas chromatography-mass spectrometry (GC/MS) was applied to investigate the impact of genetic background, growing location and season on the chemical composition of maize grain. The metabolite profiling protocol involved sub-fractionation of the metabolites and allowed the assessment of about 300 distinct analytes from different chemical classes (polar to lipophilic), of which 167 could be identified. A comparison, over three consecutive growing seasons, of the metabolite profiles of four maize cultivars which differed in their maturity classification, was carried out using principal component analysis (PCA). This revealed a strong separation of one cultivar in the first growing season, which could be explained by the immaturity of the kernels of this cultivar compared with others in the field trial. Further evaluations by pair-wise comparison using Student’s t-test and analysis of variance (ANOVA) showed that the growing season was the most prominent impact factor driving variation of the metabolite pool. An increased understanding of metabolic variation was achieved by analysis of a second sample set comprising one cultivar grown for 3 years at four locations. The applied GC/MS-based metabolite profiling demonstrated the natural variation in maize grain metabolite pools resulting from the interplay of environment, season, and genotype.

Intraspecfic variation in cold-temperature metabolic phenotypes of Arabidopsis lyrata ssp. petraea

Abstract: Atmospheric temperature is a key factor in determining the distribution of a plant species. Alongside this, plant populations growing at the margin of their range may exhibit traits that indicate genetic differentiation and adaptation to their local abiotic environment. We investigated whether geographically separated marginal populations of Arabidopsis lyrata ssp. petraea have distinct metabolic phenotypes associated with exposure to cold temperatures. Seeds of A. petraea were obtained from populations along a latitudinal gradient, namely Wales, Sweden and Iceland and grown in a controlled cabinet environment. Mannose, glucose, fructose, sucrose and raffinose concentrations were different between cold treatments and populations, especially in the Welsh population, but polyhydric alcohol concentrations were not. The free amino acid compositions were population specific, with fold differences in most amino acids, especially in the Icelandic populations, with gross changes in amino acids, particularly those associated with glutamine metabolism. Metabolic fingerprints and profiles were obtained. Principal component analysis (PCA) of metabolite fingerprints revealed metabolic characteristic phenotypes for each population and temperature. It is suggested that amino acids and carbohydrates were responsible for discriminating populations within the PCA. Metabolite fingerprinting and profiling has proved to be sufficiently sensitive to identify metabolic differences between plant populations at different atmospheric temperatures. These findings show that there is significant natural variation in cold metabolism among populations of A. l. petraea which may signify plant adaptation to local climates.

Assessing individual metabolic responsiveness to a lipid challenge using a targeted metabolomic approach

Abstract: The development of assessment techniques with immediate clinical applicability is a priority for resolving the growing epidemic in metabolic disease. Many imbalances in diet-dependent metabolism are not detectable in the fasted state. Resolving the high inter-individual variability in response to diet requires the development of techniques that can detect metabolic dysfunction at the level of the individual. The intra- and inter-individual variation in lipid metabolism in response to a standardized test meal was determined. Following an overnight fast on three different days, three healthy subjects consumed a test meal containing 40% of their daily calories. Plasma samples were collected at fasting, and 1, 3, 6, and 8 h after the test meal. Plasma fatty acid (FA) concentrations within separated lipid classes and lipoprotein fractions were measured at each time point. The intra-individual variation within each subject across three days was lower than the inter-individual differences among the three subjects for over 50% of metabolites in the triacylglycerol (TG), FA, and phosphatidylcholine (PC) lipid classes at 6 h, and for 25–50% of metabolites across lipid classes at 0, 1, 3, and 8 h. The consistency of response within individuals was visualized by principal component analysis (PCA) and confirmed by ANOVA. Three representative metabolites that discriminated among the three individuals in the apolipoprotein B (ApoB) fraction, TG16:1n7, TG18:2n6, and PC18:3n3, are discussed in detail. The postprandial responses of individuals were unique within metabolites that were individual discriminators (ID) of metabolic phenotype. This study shows that the targeted metabolomic measurement of individual metabolic phenotype in response to a specially formulated lipid challenge is possible even without lead-in periods, dietary and lifestyle control, or intervention over a 3-month period in healthy free-living individuals.

Temporally resolved GC-MS-based metabolic profiling of herbicide treated plants treated reveals that changes in polar primary metabolites alone can distinguish herbicides of differing mode of action

Abstract: We conducted a comprehensive metabolic phenotyping of primary metabolism of photosynthetic tissue of Arabidopsis thaliana following spray treatment with a number of commercially used herbicides using a well established gas-chromatography mass-spectrometry profiling method. Applying this technique we were able to identify and quantify in excess of 80 polar metabolites and based on a combination of co-elution with standards and prediction from the mass spectra a similar number of lipophillic components within two chromatographic runs. The herbicides selected were glufosinate, sulcotrione, AE944 [N2-(1-ethyl-3-phenylpropyl)-6-(1-fluoro-1-methylethyl)-1,3,5-triazine-2,4-diamine], foramsulfuron, benfuresate and glyphosate. We determined causal changes in the metabolite profiles by following their time-dependent changes using a serial sampling strategy. The resultant profiles were compared both by looking at the largest changes in a metabolite by metabolite manner and by performance of statistical analyses. These data revealed that analysis of the polar metabolites allows clear separation of the compounds under test. This finding is discussed in the context of current strategies for agrochemical discovery.

Comparative metabolomic analysis on industrial continuous and batch ethanol fermentation processes by GC-TOF-MS

Abstract: The intracellular metabolic profile characterization of Saccharomyces cerevisiae throughout industrial ethanol fermentation was investigated using gas chromatography coupled to time-of-flight mass spectrometry. A total of 143 and 128 intracellular metabolites in S. cerevisiae were detected and quantified in continuous and batch fermentations, respectively. The two fermentation processes were both clearly distinguished into three main phases by principal components analysis. Furthermore, the levels of some metabolites involved in central carbon metabolism varied significantly throughout both processes. Glycerol and phosphoric acid were principally responsible for discriminating seed, main and final phases of continuous fermentation, while lactic acid and glycerol contributed mostly to telling different phases of batch fermentation. In addition, the levels of some amino acids such as glycine varied significantly during both processes. These findings provide new insights into the metabolomic characteristics during industrial ethanol fermentation processes.

Metabolic network discovery through reverse engineering of metabolome data

Abstract: Reverse engineering of high-throughput omics data to infer underlying biological networks is one of the challenges in systems biology. However, applications in the field of metabolomics are rather limited. We have focused on a systematic analysis of metabolic network inference from in silico metabolome data based on statistical similarity measures. Three different data types based on biological/environmental variability around steady state were analyzed to compare the relative information content of the data types for inferring the network. Comparing the inference power of different similarity scores indicated the clear superiority of conditioning or pruning based scores as they have the ability to eliminate indirect interactions. We also show that a mathematical measure based on the Fisher information matrix gives clues on the information quality of different data types to better represent the underlying metabolic network topology. Results on several datasets of increasing complexity consistently show that metabolic variations observed at steady state, the simplest experimental analysis, are already informative to reveal the connectivity of the underlying metabolic network with a low false-positive rate when proper similarity-score approaches are employed. For experimental situations this implies that a single organism under slightly varying conditions may already generate more than enough information to rightly infer networks. Detailed examination of the strengths of interactions of the underlying metabolic networks demonstrates that the edges that cannot be captured by similarity scores mainly belong to metabolites connected with weak interaction strength.

NMR-based metabolomics using earthworms as potential indicators for soil health

Abstract: Soil health is key for sustainable productivity and adaptation to climate change. Agricultural practice can significantly impact on soil health. The aim of this study was to examine the effect of two land management regimes on organisms (earthworms) that may be used as indicators for soil health via NMR metabolomics. Earthworms are important in the soil decomposition process and viewed as a sentinel species in soil. The presence/absence of earthworm species and their relative abundances provide a gross indication of the health of the soil and it is expected that land use would affect earthworm metabolism as the populations rose or declined in response to changing soil health parameters. In order to test this hypothesis metabolomics approaches were employed to determine if biological indicators of soil change can be detected. Two species of earthworms, an unidentified native species and the European species Aporrectodea caliginosa, were collected from properties in Victoria, Australia where the land was treated with either biological (organic) or conventional (chemical) treatment regimes. Both lipid and aqueous NMR metabolomics for earthworms was employed, demonstrating that class classifications can be achieved with both datasets and provide orthogonal, complementary, chemical information. The study indicates that land-use has a measurable effect on the biochemistry of worm populations. Potential biomarkers of land use and worm stress were found, including elevated levels of glucose, maltose, alanine and triacylglycerides. This study demonstrates the utility of NMR metabolomics approaches in detecting biomarkers related to land treatment regimes and potentially soil health attributes.

Proton NMR quantitative profiling for quality assessment of greenhouse-grown tomato fruit

Abstract: Tomato is an essential crop in terms of economic importance and nutritional quality. In France, the third most important region for tomato (Solanum lycopersicum L.) production is Aquitaine where the major part of production is now grown soilless under greenhouse conditions with harvest from March to November. Tomato fruit quality at harvest is a direct function of its metabolite content at that time. The aim of this work was to use a global approach to characterize changes in the fruit organoleptic quality at harvest under commercial culture conditions during an entire season for two varieties and two different fertilization practices (with or without recycling of the nutrient solution) for one variety. Absolute quantification data of 32 major compounds in fruit without seeds were obtained through untargeted (proton nuclear magnetic resonance, 1H-NMR) quantitative profiling. These data were complemented by colorimetric analysis of ascorbate and total phenolics. They were analyzed with chemometric approaches. Principal component analysis (PCA) or partial least square analyses (PLS) revealed more discriminant metabolites for season than for variety and showed that nutrient solution recycling had very little effect on fruit composition. These tendencies were confirmed with univariate analyses. 1H-NMR profiling complemented with colorimetric analyses therefore provided a diagnostic tool to follow the changes in organoleptic and nutritional quality of tomato. In addition the quantitative information generated will help to increase our knowledge on the mechanisms of plant response to environmental modifications.

Validation of metabolomics for toxic mechanism of action screening with the earthworm Lumbricus rubellus

Abstract: One of the promises of environmental metabolomics, together with other ecotoxicogenomic approaches, is that it can give information on toxic compound mechanism of action (MOA), by providing a specific response profile or fingerprint. This could then be used either for screening in the context of chemical risk assessment, or potentially in contaminated site assessment for determining what compound classes were causing a toxic effect. However for either of these two ends to be achievable, it is first necessary to know if different compounds do indeed elicit specific and distinct metabolic profile responses. Such a comparative study has not yet been carried out for the earthworm Lumbricus rubellus. We exposed L. rubellus to sub-lethal concentrations of three very different toxicants (CdCl2, atrazine, and fluoranthene, representing three compound classes with different expected MOA), by semi-chronic exposures in a laboratory test, and used NMR spectroscopy to obtain metabolic profiles. We were able to use simple multivariate pattern-recognition analyses to distinguish different compounds to some degree. In addition, following the ranking of individual spectral bins according to their mutual information with compound concentrations, it was possible to identify both general and specific metabolite responses to different toxic compounds, and to relate these to concentration levels causing reproductive effects in the worms.

1H-NMR and mass spectrometric characterization of the metabolic response of juvenile Atlantic salmon (Salmo salar) to long-term handling stress

Abstract: Stressors of various kinds constantly affect fish both in the wild and in culture, examples being acute water temperature and quality changes, predation, handling, and confinement. Known physiological responses of fish to stress such as increases in plasma cortisol and glucose levels, are considered to be adaptive, allowing the animal to cope in the short term. Prolonged exposure to stressors however, has the potential to affect growth, immune function, and survival. Nonetheless, little is known about the mechanisms underlying the long-term stress response. We have investigated the metabolic response of juvenile Atlantic salmon (Salmo salar) to long-term handling stress by analyzing fish plasma via 1H nuclear magnetic resonance spectroscopy and ultra high performance liquid chromatography–mass spectrometry (UPLC–MS), and comparing results with controls. Analysis of NMR data indicated a difference in the metabolic profiles of control and stressed fish after 1 week of stress with a maximum difference observed after 2 weeks. These differences were associated with stress-induced increases in phosphatidyl choline, lactate, carbohydrates, alanine, valine and trimethylamine-N-oxide, and decreases in low density lipoprotein, very low density lipoprotein, and lipid. UPLC-MS data showed differences at week 2, associated with another set of compounds, tentatively identified on the basis of their mass/charge. Overall the results provided a multi-faceted view of the response of fish to long-term handling stress, indicating that the metabolic disparity between the control and stress groups increased to week 2, but declined by weeks 3 and 4, and revealed several new molecular indicators of long-term stress.

Metabolite profiling identifies the mycotoxin alternariol in the pathogen Stagonospora nodorum

Abstract: A recent comparative proteomics study identified the short-chain dehydrogenase (Sch1) as being required for asexual sporulation (Tan et al. Eukaryotic Cell 7:1916–1929, 2008). Metabolite profiling was undertaken on the mutant strains of Stagonospora nodorum lacking the Sch1 gene to help elucidate its role. Gas chromatography-mass spectrometry of the polar metabolites in the Sch1 mutants identified a secondary metabolite at a 200-fold greater concentration than observed in the wild-type strains. Comparative analysis of the secondary metabolite and the mycotoxin alternariol using ESI-MS/MS confirmed the identity of the compound as alternariol. This is the first report to confirm the presence of a mycotoxin in S. nodorum and compelling the field to consider the health implication of this disease.

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

Abstract: 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.

A metabolomics approach to assessing phytotoxic effects on the green alga Scenedesmus vacuolatus

Abstract: The potential of metabolomics for toxicity analysis with synchronized algal populations during growth was explored in a proof of principle study. Low molecular weight compounds from hydrophilic and lipophilic extracts of algal populations of the unicellular green alga Scenedesmus vacuolatus were analyzed using gas chromatography-mass spectrometry (GC-MS) and subsequent multivariate analysis to identify time-related patterns. Algal metabolite responses were studied under control and exposure conditions for the photosystem II-inhibiting herbicide prometryn. To define the typical metabolic profile of control S. vacuolatus cultures seven time points over a growth period of 14 h were evaluated. The results show a clear time-related trend in metabolite levels and a distinct separation of exposed and reference algal populations. The results suggest an impairment of the energy metabolism associated with an activation of catabolic processes and a retardation of carbohydrate biosynthesis in treated algae. Metabolite results were compared to observation parameters, currently used in phytotoxicity assessment, showing that metabolites respond faster to exposure than algal growth. The potential of metabolomics for toxicity evaluation, especially to identify physiological markers and to detect effects at an early state of exposure, are discussed. Therefore, we suggest a metabolomics approach utilizing synchronous algal cultures to be a suitable future tool in ecotoxicology.

In vitro analysis of metabolites from the untreated tissue of Torpedo californica electric organ by mid-infrared laser ablation electrospray ionization mass spectrometry

Abstract: The neuromuscular junction (NMJ), where a motor neuron intercepts and activates a muscle fiber, is a highly versatile and complex subcellular region. Genomic and proteomic approaches using the large (>1 kg) electric organ of Torpedo californica have helped advancing our understanding of this minute (30–50 μm) electric synapse. However, the majority of these studies have focused on mRNA and proteins, therefore neglecting small signaling molecules involved in muscle-nerve ‘dialogue’. We developed a novel technique, mid-infrared laser ablation electrospray ionization (LAESI) mass spectrometry (MS), with the potential of detecting a diversity of small signaling molecules in vitro. LAESI uses the native water in the tissue as the matrix to couple the laser pulse energy into the target for the ablation process and enables its direct analysis essentially without sample preparation. Here, we report the detection of metabolites from the untreated frozen tissue of the Torpedo electric organ with LAESI MS at atmospheric pressure. A total of 24 metabolites were identified by accurate mass measurements, natural isotope patterns, and tandem mass spectrometry. Most of the identified metabolites were related to the cholinergic function of the electric synapse (acetylcholine and choline), fatty acid metabolism and acetyl transfer (carnitine and acetylcarnitine), the mitigation of osmotic stress (betaine and trimethylamine N-oxide), and energy production (creatine and creatinine). The biosynthetic precursors of these metabolites and their expected degradation products were also detected indicating that LAESI MS is well suited for tissue metabolomics with the ultimate goal of imaging and in vivo studies.

ω-3 oil intake during weight loss in obese women results in remodelling of plasma triglyceride and fatty acids

Abstract: Previous studies have shown that a combination of weight loss and fish oil supplementation reduce cardiovascular disease and diabetes risks by increasing adiponectin and reducing triacylglyceride concentrations, while weight loss alone significantly improves insulin sensitivity and reduces inflammation Here, a metabolomic approach, using a combination of 1H-Nuclear Magnetic Resonance spectroscopy, and gas and liquid chromatography and mass spectrometry, was employed to elucidate the metabolic changes in blood plasma following weight loss and fish oil supplementation The intervention study was conducted over 24 weeks, with 93 female subjects randomised to one of three groups Two groups followed a 12-week weight loss program, followed by a 12-week weight maintenance period and were randomised to fish or placebo oil capsules; a control group did not follow the weight loss program and were given placebo oil capsules Lipid profiles changed dramatically upon fish oil intake and subtly across the two weight loss groups While the fish oil supplementation increased the proportion of various phospholipid species, previously reported reductions in total triacylglycerides (TAGs) upon fish oil intake were shown to be driven by a reduction in a specific subset of the measured TAGs This remodelling of triglycerides may represent further beneficial effects of fish oil supplementation Electronic supplementary material The online version of this article (doi:101007/s11306-009-0161-7) contains supplementary material, which is available to authorized users

Metabolic profiling of transgenic wheat over-expressing the high-molecular-weight Dx5 glutenin subunit

Abstract: The primary aim of this work was to evaluate potential changes in the metabolic network of transgenic wheat grain over-expressing the high-molecular-weight (HMW) glutenin Dx5-subunit gene. GC-MS and multivariate analyses were used to compare the metabolite profiles of developing caryopses of two independently transformed lines over-expressing Dx5 and another two independently transformed lines expressing only the selectable-marker gene (controls). Developing grain at 7, 14 and 21 Days Post-Anthesis (DPA) was studied to observe differences in metabolically active tissues. There was no distinction between the Dx5 transformants and the controls by principal component analysis (PCA) suggesting that their metabolite compositions were similar. Most changes in metabolite levels and starch occurred at 14 DPA but tapered off by 21 DPA. Only 3 metabolites, guanine, 4-hydroxycinnamic acid and Unknown 071306a, were altered due to Dx5 expression after correction for false discovery rates (P < 0.0005). However, discriminant function analysis (DFA) and correlative analyses of the metabolites showed that Dx5-J, which had the highest level of Dx5 protein in ripe caryopses, could be distinguished from the other genotypes. The second aim of this work was to determine the influence of gene transformation on the metabolome. Cross-comparison of the transformed controls to each other, and to the Dx5 genotypes showed that approximately 50% of the metabolic changes in the Dx5 genotypes were potentially due to variations arising from gene transformation and not from the expression of the Dx5-gene per se. This study therefore suggests the extent to which plant transformation by biolistics can potentially influence phenotype.