Manipulation of ß-carotene levels in tomato fruits results in increased ABA content and extended shelf life.

Tomato fruit ripening is controlled by the hormone ethylene and by a group of transcription factors, acting upstream of ethylene. During ripening, the linear carotene lycopene accumulates at the expense of cyclic carotenoids. Fruit-specific overexpression of LYCOPENE ß-CYCLASE (LCYb) resulted in increased ß-carotene (provitamin A) content. Unexpectedly, LCYb-overexpressing fruits also exhibited a diverse array of ripening phenotypes, including delayed softening and extended shelf life. These phenotypes were accompanied, at the biochemical level, by an increase in abscisic acid (ABA) content, decreased ethylene production, increased density of cell wall material containing linear pectins with a low degree of methylation, and a thicker cuticle with a higher content of cutin monomers and triterpenoids. The levels of several primary metabolites and phenylpropanoid compounds were also altered in the transgenic fruits, which could be attributed to delayed fruit ripening and/or to ABA. Network correlation analysis and pharmacological experiments with the ABA biosynthesis inhibitor, abamine, indicated that altered ABA levels were a direct effect of the increased ß-carotene content and were in turn responsible for the extended shelf life phenotype. Thus, manipulation of ß-carotene levels results in an improvement not only of the nutritional value of tomato fruits, but also of their shelf life.

Metabolic profiling of wheat rachis node infection by Fusarium graminearum - decoding deoxynivalenol-dependent susceptibility.

Fusarium graminearum is a filamentous ascomycete and the causal agent of Fusarium head blight on wheat that threatens food and feed production worldwide as infection reduces crop yield both quantitatively by interfering with kernel development and qualitatively by poisoning any remaining kernels with mycotoxins. In wheat, F. graminearum infects spikelets and colonizes the entire head by growing through the rachis node at the bottom of each spikelet. Without the mycotoxin deoxynivalenol (DON), the pathogen cannot penetrate the rachis node and wheat is able to resist colonization. Using a global metabolite profiling approach we compared the metabolic profile of rachis nodes inoculated with either water, the Fusarium graminearum wild-type or the DON-deficient ∆tri5 mutant. Extensive metabolic rearrangements mainly affect metabolites for general stress perception and signaling, reactive oxygen species (ROS) metabolism, cell wall composition, the tri-carbonic acid (TCA) cycle and γ-aminobutyric acid (GABA) shunt as well as sugar alcohols, amino acids, and storage carbohydrates. The results revealed specific, DON-related susceptibility factors. Wild-type infection resulted in an oxidative burst and the induction of plant programmed cell death, while spread of the DON-deficient mutant was blocked in a jasmonate (JA)-related defense reaction in concert with other factors. Hence, the ∆tri5 mutant is prone to defense reactions that are, in the case of a wild-type infection, not initiated.

Identification of the 2-hydroxyglutarate and isovaleryl-CoA dehydrogenases as alternative electron donors linking lysine catabolism to the electron transport chain of Arabidopsis mitochondria.

The process of dark-induced senescence in plants is relatively poorly understood, but a functional electron-transfer flavoprotein/electron-transfer flavoprotein:ubiquinone oxidoreductase (ETF/ETFQO) complex, which supports respiration during carbon starvation, has recently been identified. Here, we studied the responses of Arabidopsis thaliana mutants deficient in the expression of isovaleryl-CoA dehydrogenase and 2-hydroxyglutarate dehydrogenase to extended darkness and other environmental stresses. Evaluations of the mutant phenotypes following carbon starvation induced by extended darkness identify similarities to those exhibited by mutants of the ETF/ETFQO complex. Metabolic profiling and isotope tracer experimentation revealed that isovaleryl-CoA dehydrogenase is involved in degradation of the branched-chain amino acids, phytol, and Lys, while 2-hydroxyglutarate dehydrogenase is involved exclusively in Lys degradation. These results suggest that isovaleryl-CoA dehydrogenase is the more critical for alternative respiration and that a series of enzymes, including 2-hydroxyglutarate dehydrogenase, plays a role in Lys degradation. Both physiological and metabolic phenotypes of the isovaleryl-CoA dehydrogenase and 2-hydroxyglutarate dehydrogenase mutants were not as severe as those observed for mutants of the ETF/ETFQO complex, indicating some functional redundancy of the enzymes within the process. Our results aid in the elucidation of the pathway of plant Lys catabolism and demonstrate that both isovaleryl-CoA dehydrogenase and 2-hydroxyglutarate dehydrogenase act as electron donors to the ubiquinol pool via an ETF/ETFQO-mediated route.

Metabolomics-assisted breeding: a viable option for crop improvement?

Metabolomics approaches enable the parallel assessment of the levels of a broad range of metabolites and have been documented to have great value in both phenotyping and diagnostic analyses in plants. These tools have recently been turned to evaluation of the natural variance apparent in metabolite composition. Here, we describe exciting progress made in the identification of the genetic determinants of plant chemical composition, focussing on the application of metabolomics strategies and their integration with other high-throughput technologies. Metabolomics represents an important addition to the tools currently employed in genomics-assisted selection for crop improvement.

Dynamic plastid redox signals integrate gene expression and metabolism to induce distinct metabolic states in photosynthetic acclimation in Arabidopsis.

Plants possess acclimation responses in which structural reconfigurations adapt the photosynthetic apparatus to fluctuating illumination. Long-term acclimation involves changes in plastid and nuclear gene expression and is controlled by redox signals from photosynthesis. The kinetics of these signals and the adjustments of energetic and metabolic demands to the changes in the photosynthetic apparatus are currently poorly understood. Using a redox signaling system that preferentially excites either photosystem I or II, we measured the time-dependent impact of redox signals on the transcriptome and metabolome of Arabidopsis thaliana. We observed rapid and dynamic changes in nuclear transcript accumulation resulting in differential and specific expression patterns for genes associated with photosynthesis and metabolism. Metabolite pools also exhibited dynamic changes and indicate readjustments between distinct metabolic states depending on the respective illumination. These states reflect reallocation of energy resources in a defined and reversible manner, indicating that structural changes in the photosynthetic apparatus during long-term acclimation are additionally supported at the level of metabolism. We propose that photosynthesis can act as an environmental sensor, producing retrograde redox signals that trigger two parallel adjustment loops that coordinate photosynthesis and metabolism to adapt plant primary productivity to the environment.

Whole-cell response of the pennate diatom Phaeodactylum tricornutum to iron starvation.

Marine primary productivity is iron (Fe)-limited in vast regions of the contemporary oceans, most notably the high nutrient low chlorophyll (HNLC) regions. Diatoms often form large blooms upon the relief of Fe limitation in HNLC regions despite their prebloom low cell density. Although Fe plays an important role in controlling diatom distribution, the mechanisms of Fe uptake and adaptation to low iron availability are largely unknown. Through a combination of nontargeted transcriptomic and metabolomic approaches, we have explored the biochemical strategies preferred by Phaeo dactylum tricornutum at growth-limiting levels of dissolved Fe. Processes carried out by components rich in Fe, such as photosynthesis, mitochondrial electron transport, and nitrate assimilation, were down-regulated. Our results show that this retrenchment is compensated by nitrogen (N) and carbon (C) reallocation from protein and carbohydrate degradation, adaptations to chlorophyll biosynthesis and pigment metabolism, removal of excess electrons by mitochondrial alternative oxidase (AOX) and non-photochemical quenching (NPQ), and augmented Fe-independent oxidative stress responses. Iron limitation leads to the elevated expression of at least three gene clusters absent from the Thalassiosira pseudonana genome that encode for components of iron capture and uptake mechanisms.

Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach.

Biomarkers are used to predict phenotypical properties before these features become apparent and, therefore, are valuable tools for both fundamental and applied research. Diagnostic biomarkers have been discovered in medicine many decades ago and are now commonly applied. While this is routine in the field of medicine, it is of surprise that in agriculture this approach has never been investigated. Up to now, the prediction of phenotypes in plants was based on growing plants and assaying the organs of interest in a time intensive process. For the first time, we demonstrate in this study the application of metabolomics to predict agronomic important phenotypes of a crop plant that was grown in different environments. Our procedure consists of established techniques to screen untargeted for a large amount of metabolites in parallel, in combination with machine learning methods. By using this combination of metabolomics and biomathematical tools metabolites were identified that can be used as biomarkers to improve the prediction of traits. The predictive metabolites can be selected and used subsequently to develop fast, targeted and low-cost diagnostic biomarker assays that can be implemented in breeding programs or quality assessment analysis. The identified metabolic biomarkers allow for the prediction of crop product quality. Furthermore, marker-assisted selection can benefit from the discovery of metabolic biomarkers when other molecular markers come to its limitation. The described marker selection method was developed for potato tubers, but is generally applicable to any crop and trait as it functions independently of genomic information.

Involvement of Lactate and Pyruvate in the Anti-Inflammatory Effects Exerted by Voluntary Activation of the Sympathetic Nervous System.

We recently demonstrated that the sympathetic nervous system can be voluntarily activated following a training program consisting of cold exposure, breathing exercises, and meditation. This resulted in profound attenuation of the systemic inflammatory response elicited by lipopolysaccharide (LPS) administration. Herein, we assessed whether this training program affects the plasma metabolome and if these changes are linked to the immunomodulatory effects observed. A total of 224 metabolites were identified in plasma obtained from 24 healthy male volunteers at six timepoints, of which 98 were significantly altered following LPS administration. Effects of the training program were most prominent shortly after initiation of the acquired breathing exercises but prior to LPS administration, and point towards increased activation of the Cori cycle. Elevated concentrations of lactate and pyruvate in trained individuals correlated with enhanced levels of anti-inflammatory interleukin (IL)-10. In vitro validation experiments revealed that co-incubation with lactate and pyruvate enhances IL-10 production and attenuates the release of pro-inflammatory IL-1ß and IL-6 by LPS-stimulated leukocytes. Our results demonstrate that practicing the breathing exercises acquired during the training program results in increased activity of the Cori cycle. Furthermore, this work uncovers an important role of lactate and pyruvate in the anti-inflammatory phenotype observed in trained subjects.

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

BACKGROUND AND AIMS: 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. METHODS: 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. KEY RESULTS: 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. CONCLUSIONS: 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.

Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement.

Tomato represents an important source of fiber and nutrients in the human diet and is a central model for the study of fruit biology. To identify components of fruit metabolic composition, here we have phenotyped tomato introgression lines (ILs) containing chromosome segments of a wild species in the genetic background of a cultivated variety. Using this high-diversity population, we identify 889 quantitative fruit metabolic loci and 326 loci that modify yield-associated traits. The mapping analysis indicates that at least 50% of the metabolic loci are associated with quantitative trait loci (QTLs) that modify whole-plant yield-associated traits. We generate a cartographic network based on correlation analysis that reveals whole-plant phenotype associated and independent metabolic associations, including links with metabolites of nutritional and organoleptic importance. The results of our genomic survey illustrate the power of genome-wide metabolic profiling and detailed morphological analysis for uncovering traits with potential for crop breeding.

Teaching (and learning from) metabolomics: the 2006 PlantMetaNet ETNA Metabolomics Research School.

Under the auspices of the European Training and Networking Activity programme of the European Union, a 'Metabolic Profiling and Data Analysis' Plant Genomics and Bioinformatics Summer School was hosted in Potsdam, Germany between 20 and 29 September 2006. Sixteen early career researchers were invited from the European Union partner nations and the so-called developing nations (Appendix). Lectures from invited leading European researchers provided an overview of the state of the art of these fields and seeded discussion regarding major challenges for their future advancement. Hands-on experience was provided by an example experiment - that of defining the metabolic response of Arabidopsis to treatment of a commercial herbicide of defined mode of action. This experiment was performed throughout the duration of the course in order to teach the concepts underlying extraction and machine handling as well as to provide a rich data set with which the required computation and statistical skills could be illustrated. Here we review the state of the field by describing both key lectures given at and practical aspects taught at the summer school. In addition, we disclose results that were obtained using the four distinct technical platforms at the different participating institutes. While the effects of the chosen herbicide are well documented, this study looks at a broader number of metabolites than in previous investigations. This allowed, on the one hand, not only to characterise further effects of the herbicide than previously observed but also to detect molecules other than the herbicide that were obviously present in the commercial formulation. These data and the workshop in general are all discussed in the context of the teaching of metabolomics.

Plant metabolomics: towards biological function and mechanism.

Metabolite profiling is a fast growing technology and is useful for phenotyping and diagnostic analyses of plants. It is also rapidly becoming a key tool in functional annotation of genes and in the comprehensive understanding of the cellular response to biological conditions. Metabolomics approaches have recently been used to assess the natural variance in metabolite content between individual plants, an approach with great potential for the improvement of the compositional quality of crops. Here, we assess the contribution of metabolite profiling to these areas.

Promising Metabolite Profiles in the Plasma and CSF of Early Clinical Parkinson's Disease.

Parkinson's disease (PD) shows high heterogeneity with regard to the underlying molecular pathogenesis involving multiple pathways and mechanisms. Diagnosis is still challenging and rests entirely on clinical features. Thus, there is an urgent need for robust diagnostic biofluid markers. Untargeted metabolomics allows establishing low-molecular compound biomarkers in a wide range of complex diseases by the measurement of various molecular classes in biofluids such as blood plasma, serum, and cerebrospinal fluid (CSF). Here, we applied untargeted high-resolution mass spectrometry to determine plasma and CSF metabolite profiles. We semiquantitatively determined small-molecule levels (≤1.5 kDa) in the plasma and CSF from early PD patients (disease duration 0-4 years; n = 80 and 40, respectively), and sex- and age-matched controls (n = 76 and 38, respectively). We performed statistical analyses utilizing partial least square and random forest analysis with a 70/30 training and testing split approach, leading to the identification of 20 promising plasma and 14 CSF metabolites. These metabolites differentiated the test set with an AUC of 0.8 (plasma) and 0.9 (CSF). Characteristics of the metabolites indicate perturbations in the glycerophospholipid, sphingolipid, and amino acid metabolism in PD, which underscores the high power of metabolomic approaches. Further studies will enable to develop a potential metabolite-based biomarker panel specific for PD.

Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring.

Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson's disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.

Nonsupervised construction and application of mass spectral and retention time index libraries from time-of-flight gas chromatography-mass spectrometry metabolite profiles.

Gas chromatography-mass spectrometry (GC-MS) is routinely applied to the metabolite profiling of biological samples. Time-of-flight (TOF)-GC-MS metabolite profiling is based on highly reproducible electron impact ionization. Single chromatograms may comprise 200-1000 mass spectral components. The nature and composition of these mass spectral components depend on the choice of metabolite extraction, type of biological sample, and experimental condition. The components represent mass spectral tags (MSTs) of volatile metabolites or metabolite derivatives. Identification of MSTs is the major challenge in GC-MS metabolite profiling. We describe methods suitable for the automated construction of mass spectral and retention time index databases from large sets of TOF-GC-MS profiles. Application of these libraries for automated identification by pure reference compounds and classification of hitherto unidentified MSTs from biological sources is demonstrated.

Metabolomic profile and nucleoside composition of Cordyceps nidus sp. nov. (Cordycipitaceae): A new source of active compounds.

Cordyceps sensu lato is a genus of arthropod-pathogenic fungi, which have been used traditionally as medicinal in Asia. Within the genus, Ophiocordyceps sinensis is the most coveted and expensive species in China. Nevertheless, harvesting wild specimens has become a challenge given that natural populations of the fungus are decreasing and because large-scale culture of it has not yet been achieved. The worldwide demand for products derived from cultivable fungal species with medicinal properties has increased recently. In this study, we propose a new species, Cordyceps nidus, which parasitizes underground nests of trapdoor spiders. This species is phylogenetically related to Cordyceps militaris, Cordyceps pruinosa, and a sibling species of Cordyceps caloceroides. It is found in tropical rainforests from Bolivia, Brazil, Colombia and Ecuador. We also investigated the medicinal potential of this fungus based on its biochemical properties when grown on four different culture media. The metabolic profile particularly that of nucleosides, in polar and non-polar extracts was determined by UPLC, and then correlated to their antimicrobial activity and total phenolic content. The metabolome showed a high and significant dependency on the substrate used for fungal growth. The mass intensities of nucleosides and derivative compounds were higher in natural culture media in comparison to artificial culture media. Among these compounds, cordycepin was the predominant, showing the potential use of this species as an alternative to O. sinensis. Furthermore, methanol fractions showed antimicrobial activity against gram-positive bacteria, and less than 3.00 mg of gallic acid equivalents per g of dried extract were obtained when assessing its total phenolic content by modified Folin-Ciocalteu method. The presence of polyphenols opens the possibility of further exploring the antioxidant capacity and the conditions that may enhance this characteristic. The metabolic composition and biochemical activity indicate potential use of C. nidus in pharmaceutical applications.

Synergistic Action of Genistein and Calcitriol in Immature Osteosarcoma MG-63 Cells by SGPL1 Up-Regulation.

BACKGROUND: Phytoestrogens such as genistein, the most prominent isoflavone from soy, show concentration-dependent anti-estrogenic or estrogenic effects. High genistein concentrations (>10 µM) also promote proliferation of bone cancer cells in vitro. On the other hand, the most active component of the vitamin D family, calcitriol, has been shown to be tumor protective in vitro and in vivo. The purpose of this study was to examine a putative synergism of genistein and calcitriol in two osteosarcoma cell lines MG-63 (early osteoblast), Saos-2 (mature osteoblast) and primary osteoblasts. METHODS: Thus, an initial screening based on cell cycle phase alterations, estrogen (ER) and vitamin D receptor (VDR) expression, live cell metabolic monitoring, and metabolomics were performed. RESULTS: Exposure to the combination of 100 µM genistein and 10 nM calcitriol reduced the number of proliferative cells to control levels, increased ERß and VDR expression, and reduced extracellular acidification (40%) as well as respiratory activity (70%), primarily in MG-63 cells. In order to identify the underlying cellular mechanisms in the MG-63 cell line, metabolic profiling via GC/MS technology was conducted. Combined treatment significantly influenced lipids and amino acids preferably, whereas metabolites of the energy metabolism were not altered. The comparative analysis of the log2-ratios revealed that after combined treatment only the metabolite ethanolamine was highly up-regulated. This is the result: a strong overexpression (350%) of the enzyme sphingosine-1-phosphate lyase (SGPL1), which irreversibly degrades sphingosine-1-phosphate (S1P), thereby, generating ethanolamine. S1P production and secretion is associated with an increased capability of migration and invasion of cancer cells. CONCLUSION: From these results can be concluded that the tumor promoting effect of high concentrations of genistein in immature osteosarcoma cells is reduced by the co-administration of calcitriol, primarily by the breakdown of S1P. It should be tested whether this anti-metastatic pathway can be stimulated by combined treatment also in metastatic xenograft mice models.

Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy.

In mass spectrometry-based untargeted metabolomics, rarely more than 30% of the compounds are identified. Without the true identity of these molecules it is impossible to draw conclusions about the biological mechanisms, pathway relationships and provenance of compounds. The only way at present to address this discrepancy is to use in silico fragmentation software to identify unknown compounds by comparing and ranking theoretical MS/MS fragmentations from target structures to experimental tandem mass spectra (MS/MS). We compared the performance of four publicly available in silico fragmentation algorithms (MetFragCL, CFM-ID, MAGMa+ and MS-FINDER) that participated in the 2016 CASMI challenge. We found that optimizing the use of metadata, weighting factors and the manner of combining different tools eventually defined the ultimate outcomes of each method. We comprehensively analysed how outcomes of different tools could be combined and reached a final success rate of 93% for the training data, and 87% for the challenge data, using a combination of MAGMa+, CFM-ID and compound importance information along with MS/MS matching. Matching MS/MS spectra against the MS/MS libraries without using any in silico tool yielded 60% correct hits, showing that the use of in silico methods is still important.

C26:0-Carnitine Is a New Biomarker for X-Linked Adrenoleukodystrophy in Mice and Man.

X-linked adrenoleukodystrophy (ALD), a progressive neurodegenerative disease, is caused by mutations in ABCD1 and characterized by very-long-chain fatty acids (VLCFA) accumulation. Virtually all males develop progressive myelopathy (AMN). A subset of patients, however, develops a fatal cerebral demyelinating disease (cerebral ALD). Hematopoietic stem cell transplantation is curative for cerebral ALD provided the procedure is performed in an early stage of the disease. Unfortunately, this narrow therapeutic window is often missed. Therefore, an increasing number of newborn screening programs are including ALD. To identify new biomarkers for ALD, we developed an Abcd1 knockout mouse with enhanced VLCFA synthesis either ubiquitous or restricted to oligodendrocytes. Biochemical analysis revealed VLCFA accumulation in different lipid classes and acylcarnitines. Both C26:0-lysoPC and C26:0-carnitine were highly elevated in brain, spinal cord, but also in bloodspots. We extended the analysis to patients and confirmed that C26:0-carnitine is also elevated in bloodspots from ALD patients. We anticipate that validation of C26:0-carnitine for the diagnosis of ALD in newborn bloodspots may lead to a faster inclusion of ALD in newborn screening programs in countries that already screen for other inborn errors of metabolism.

GC-MS libraries for the rapid identification of metabolites in complex biological samples.

Gas chromatography-mass spectrometry based metabolite profiling of biological samples is rapidly becoming one of the cornerstones of functional genomics and systems biology. Thus, the technology needs to be available to many laboratories and open exchange of information is required such as those achieved for transcript and protein data. The key-step in metabolite profiling is the unambiguous identification of metabolites in highly complex metabolite preparations with composite structure. Collections of mass spectra, which comprise frequently observed identified and non-identified metabolites, represent the most effective means to pool the identification efforts currently performed in many laboratories around the world. Here, we describe a platform for mass spectral and retention time index libraries that will enable this process (MSRI; www.csbdb.mpimp-golm.mpg.de/gmd.html). This resource should ameliorate many of the problems that each laboratory will face both for the initial establishment of metabolome analysis and for its maintenance at a constant sample throughput.