209 research outputs found

    The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets

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    <p>Abstract</p> <p>Background</p> <p>Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis.</p> <p>Description</p> <p>Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline.</p> <p>Conclusions</p> <p>MetabolomeExpress <url>https://www.metabolome-express.org</url> provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published metabolomics datasets.</p

    A Statistically Rigorous Test for the Identification of Parent−Fragment Pairs in LC-MS Datasets

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    Untargeted global metabolic profiling by liquid chromato-graphy−mass spectrometry generates numerous signals that are due to unknown compounds and whose identification forms an important challenge. The analysis of metabolite fragmentation patterns, following collision-induced dissociation, provides a valuable tool for identification, but can be severely impeded by close chromatographic coelution of distinct metabolites. We propose a new algorithm for identifying related parent−fragment pairs and for distinguishing these from signals due to unrelated compounds. Unlike existing methods, our approach addresses the problem by means of a hypothesis test that is based on the distribution of the recorded ion counts, and thereby provides a statistically rigorous measure of the uncertainty involved in the classification problem. Because of technological constraints, the test is of primary use at low and intermediate ion counts, above which detector saturation causes substantial bias to the recorded ion count. The validity of the test is demonstrated through its application to pairs of coeluting isotopologues and to known parent−fragment pairs, which results in test statistics consistent with the null distribution. The performance of the test is compared with a commonly used Pearson correlation approach and found to be considerably better (e.g., false positive rate of 6.25%, compared with a value of 50% for the correlation for perfectly coeluting ions). Because the algorithm may be used for the analysis of high-mass compounds in addition to metabolic data, we expect it to facilitate the analysis of fragmentation patterns for a wide range of analytical problems

    Two alanine aminotranferases link mitochondrial glycolate oxidation to the major photorespiratory pathway in Arabidopsis and rice

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    The major photorespiratory pathway in higher plants is distributed over chloroplasts, mitochondria, and peroxisomes. In this pathway, glycolate oxidation takes place in peroxisomes. It was previously suggested that a mitochondrial glycolate dehydrogenase (GlcDH) that was conserved from green algae lacking leaf-type peroxisomes contributes to photorespiration in Arabidopsis thaliana. Here, the identification of two Arabidopsis mitochondrial alanine:glyoxylate aminotransferases (ALAATs) that link glycolate oxidation to glycine formation are described. By this reaction, the mitochondrial side pathway produces glycine from glyoxylate that can be used in the glycine decarboxylase (GCD) reaction of the major pathway. RNA interference (RNAi) suppression of mitochondrial ALAAT did not result in major changes in metabolite pools under standard conditions or enhanced photorespiratroy flux, respectively. However, RNAi lines showed reduced photorespiratory CO2 release and a lower CO2 compensation point. Mitochondria isolated from RNAi lines are incapable of converting glycolate to CO2, whereas simultaneous overexpression of GlcDH and ALAATs in transiently transformed tobacco leaves enhances glycolate conversion. Furthermore, analyses of rice mitochondria suggest that the side pathway for glycolate oxidation and glycine formation is conserved in monocotyledoneous plants. It is concluded that the photorespiratory pathway from green algae has been functionally conserved in higher plants

    Transcript and metabolite profiling of the adaptive response to mild decreases in oxygen concentration in the roots of arabidopsis plants

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    Oxygen can fall to low concentrations within plant tissues, either because of environmental factors that decrease the external oxygen concentration or because the movement of oxygen through the plant tissues cannot keep pace with the rate of oxygen consumption. Recent studies document that plants can decrease their oxygen consumption in response to relatively small changes in oxygen concentrations to avoid internal anoxia. The molecular mechanisms underlying this response have not been identified yet. The aim of this study was to use transcript and metabolite profiling to investigate the genomic response of arabidopsis roots to a mild decrease in oxygen concentrations. Arabidopsis seedlings were grown on vertical agar plates at 21, 8, 4 and 1 % (v/v) external oxygen for 0.5, 2 and 48 h. Roots were analysed for changes in transcript levels using Affymetrix whole genome DNA microarrays, and for changes in metabolite levels using routine GC-MS based metabolite profiling. Root extension rates were monitored in parallel to investigate adaptive changes in growth. The results show that root growth was inhibited and transcript and metabolite profiles were significantly altered in response to a moderate decrease in oxygen concentrations. Low oxygen leads to a preferential up-regulation of genes that might be important to trigger adaptive responses in the plant. A small but highly specific set of genes is induced very early in response to a moderate decrease in oxygen concentrations. Genes that were down-regulated mainly encoded proteins involved in energy-consuming processes. In line with this, root extension growth was significantly decreased which will ultimately save ATP and decrease oxygen consumption. This was accompanied by a differential regulation of metabolite levels at short- and long-term incubation at low oxygen. The results show that there are adaptive changes in root extension involving large-scale reprogramming of gene expression and metabolism when oxygen concentration is decreased in a very narrow range

    Metabolomics Unravel Contrasting Effects of Biodiversity on the Performance of Individual Plant Species

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    In spite of evidence for positive diversity-productivity relationships increasing plant diversity has highly variable effects on the performance of individual plant species, but the mechanisms behind these differential responses are far from being understood. To gain deeper insights into the physiological responses of individual plant species to increasing plant diversity we performed systematic untargeted metabolite profiling on a number of herbs derived from a grassland biodiversity experiment (Jena Experiment). The Jena Experiment comprises plots of varying species number (1, 2, 4, 8, 16 and 60) and number and composition of functional groups (1 to 4; grasses, legumes, tall herbs, small herbs). In this study the metabolomes of two tall-growing herbs (legume: Medicago x varia; non-legume: Knautia arvensis) and three small-growing herbs (legume: Lotus corniculatus; non-legumes: Bellis perennis, Leontodon autumnalis) in plant communities of increasing diversity were analyzed. For metabolite profiling we combined gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) and UPLC coupled to FT-ICR-MS (LC-FT-MS) analyses from the same sample. This resulted in several thousands of detected m/z-features. ANOVA and multivariate statistical analysis revealed 139 significantly changed metabolites (30 by GC-TOF-MS and 109 by LC-FT-MS). The small-statured plants L. autumnalis, B. perennis and L. corniculatus showed metabolic response signatures to increasing plant diversity and species richness in contrast to tall-statured plants. Key-metabolites indicated C- and N-limitation for the non-leguminous small-statured species B. perennis and L. autumnalis, while the metabolic signature of the small-statured legume L. corniculatus indicated facilitation by other legumes. Thus, metabolomic analysis provided evidence for negative effects of resource competition on the investigated small-statured herbs that might mechanistically explain their decreasing performance with increasing plant diversity. In contrast, taller species often becoming dominant in mixed plant communities did not show modified metabolite profiles in response to altered resource availability with increasing plant diversity. Taken together, our study demonstrates that metabolite profiling is a strong diagnostic tool to assess individual metabolic phenotypes in response to plant diversity and ecophysiological adjustment

    Comparative Functional Genomics of Salt Stress in Related Model and Cultivated Plants Identifies and Overcomes Limitations to Translational Genomics

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    One of the objectives of plant translational genomics is to use knowledge and genes discovered in model species to improve crops. However, the value of translational genomics to plant breeding, especially for complex traits like abiotic stress tolerance, remains uncertain. Using comparative genomics (ionomics, transcriptomics and metabolomics) we analyzed the responses to salinity of three model and three cultivated species of the legume genus Lotus. At physiological and ionomic levels, models responded to salinity in a similar way to crop species, and changes in the concentration of shoot Cl− correlated well with tolerance. Metabolic changes were partially conserved, but divergence was observed amongst the genotypes. Transcriptome analysis showed that about 60% of expressed genes were responsive to salt treatment in one or more species, but less than 1% was responsive in all. Therefore, genotype-specific transcriptional and metabolic changes overshadowed conserved responses to salinity and represent an impediment to simple translational genomics. However, ‘triangulation’ from multiple genotypes enabled the identification of conserved and tolerant-specific responses that may provide durable tolerance across species

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

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    The application of gas chromatography–mass spectrometry (GC–MS) to the ‘global’ analysis of metabolites 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 standardised protocols, identical models of GC (Agilent 6890N) and TOF/MS (Leco Pegasus III) were also employed. In addition comprehensive GC×GC–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 reproducibility are required, though the future generation of global and valid metabolomics databases offers much promise

    Enhancement of Transport Selectivity through Nano-Channels by Non-Specific Competition

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    The functioning of living cells requires efficient and selective transport of materials into and out of the cell, and between different cellular compartments. Much of this transport occurs through nano-scale channels that do not require large scale molecular re-arrangements (such as transition from a ‘closed’ to an ‘open’ state) and do not require a direct input of metabolic energy during transport. Nevertheless, these ‘always open’ channels are highly selective and pass only their cognate molecules, while efficiently excluding all others; indeed, these channels can efficiently transport specific molecules even in the presence of a vast excess of non-specific molecules. Such biological transporters have inspired the creation of artificial nano-channels. These channels can be used as nano-molecular sorters, and can also serve as testbeds for examining modes of biological transport. In this paper, we propose a simple kinetic mechanism that explains how the selectivity of such ‘always open’ channels can be based on the exclusion of non-specific molecules by specific ones, due to the competition for limited space inside the channel. The predictions of the theory account for the behavior of the nuclear pore complex and of artificial nanopores that mimic its function. This theory provides the basis for future work aimed at understanding the selectivity of various biological transport phenomena
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