Developing liquid chromatography tandem mass spectrometry (LC-MS/MS) analyses of (bio)chemicals is both time consuming and challenging, largely because of the large number of LC and MS instrument parameters that need to be optimised. This bottleneck significantly impedes our ability to establish new (bio)analytical methods in fields such as pharmacology, metabolomics and pesticide research. We report the development of a multi-platform, user-friendly software tool MUSCLE (Multi-platform Unbiased optimisation of Spectrometry via Closed Loop Experimentation) for the robust and fully-automated multiobjective optimisation of targeted LC-MS/MS analysis. MUSCLE shortened the analysis times and increased the analytical sensitivities of targeted metabolite analysis which was demonstrated on two different manufacturers LC-MS/MS instruments. Availability: Available at http://www.muscleproject.org CONTACT: email@example.com SUPPLEMENTARY INFORMATION: See Supplementary Data available at the journal's web site.
Increasing use of plant feed ingredients may introduce contaminants not previously associated with farming of salmonids, such as pesticides and PAHs from environmental sources or from thermal processing of oil seeds. To screen for interaction effects of contaminants newly introduced in salmon feeds, Atlantic salmon primary hepatocytes were used. The xCELLigence cytotoxicity system was used to select optimal dosages of the PAHs benzo(a)pyrene and phenanthrene, the pesticides chlorpyrifos and endosulfan, and combinations of these. NMR and MS metabolic profiling and microarray transcriptomic profiling was used to identify novel biomarkers. Lipidomic and transcriptomic profiling suggested perturbation of lipid metabolism, as well as endocrine disruption. The pesticides gave the strongest responses, despite having less effect on cell viability than the PAHs. Only weak molecular responses were detected in PAH-exposed hepatocytes. Chlorpyrifos suppressed the synthesis of unsaturated fatty acids. Endosulfan affected steroid hormone synthesis, while benzo(a)pyrene disturbed vitamin D3 metabolism. The primary mixture effect was additive, although at high concentrations the pesticides acted in a synergistic fashion to decrease cell viability and down-regulate CYP3A and FABP4 transcription. This work highlights the usefulness of 'omics techniques and multivariate data analysis to investigate interactions within mixtures of contaminants with different modes of action.
Perhexiline is thought to modulate metabolism by inhibiting mitochondrial carnitine palmitoyltransferase-1, reducing fatty acid uptake and increasing carbohydrate utilization. This study assessed whether preoperative perhexiline improves markers of myocardial protection in patients undergoing coronary artery bypass graft surgery and analysed its effect on the myocardial metabolome.
Competition is a major force structuring marine planktonic communities. The release of compounds that inhibit competitors, a process known as allelopathy, may play a role in the maintenance of large blooms of the red-tide dinoflagellate Karenia brevis, which produces potent neurotoxins that negatively impact coastal marine ecosystems. K. brevis is variably allelopathic to multiple competitors, typically causing sublethal suppression of growth. We used metabolomic and proteomic analyses to investigate the role of chemically mediated ecological interactions between K. brevis and two diatom competitors, Asterionellopsis glacialis and Thalassiosira pseudonana. The impact of K. brevis allelopathy on competitor physiology was reflected in the metabolomes and expressed proteomes of both diatoms, although the diatom that co-occurs with K. brevis blooms (A. glacialis) exhibited more robust metabolism in response to K. brevis. The observed partial resistance of A. glacialis to allelopathy may be a result of its frequent exposure to K. brevis blooms in the Gulf of Mexico. For the more sensitive diatom, T. pseudonana, which may not have had opportunity to evolve resistance to K. brevis, allelopathy disrupted energy metabolism and impeded cellular protection mechanisms including altered cell membrane components, inhibited osmoregulation, and increased oxidative stress. Allelopathic compounds appear to target multiple physiological pathways in sensitive competitors, demonstrating that chemical cues in the plankton have the potential to alter large-scale ecosystem processes including primary production and nutrient cycling.
Human activities are fundamentally altering the chemistry of the world's oceans. Ocean acidification (OA) is occurring against a background of warming and an increasing occurrence of disease outbreaks, posing a significant threat to marine organisms, communities, and ecosystems. In the current study, (1)H NMR spectroscopy was used to investigate the response of the blue mussel, Mytilus edulis, to a 90-day exposure to reduced seawater pH and increased temperature, followed by a subsequent pathogenic challenge. Analysis of the metabolome revealed significant differences between male and female organisms. Furthermore, males and females are shown to respond differently to environmental stress. While males were significantly affected by reduced seawater pH, increased temperature, and a bacterial challenge, it was only a reduction in seawater pH that impacted females. Despite impacting males and females differently, stressors seem to act via a generalized stress response impacting both energy metabolism and osmotic balance in both sexes. This study therefore has important implications for the interpretation of metabolomic data in mussels, as well as the impact of environmental stress in marine invertebrates in general.
Environmental metabolomics is increasingly used to investigate organismal responses to complex chemical mixtures, including waste water effluent (WWE). In parallel, increasingly sensitive analytical methods are being used in metabolomics studies, particularly mass spectrometry. This introduces a considerable, yet overlooked, challenge that high analytical sensitivity will not only improve the detection of endogenous metabolites in biological specimens but also exogenous chemicals. If these often unknown xenobiotic features are not removed from the "biological" dataset, they will bias the interpretation and could lead to incorrect conclusions about the biotic response. Here we illustrate and validate a novel workflow classifying the origin of peaks detected in biological samples as: endogenous, xenobiotics, or metabolised xenobiotics. The workflow is demonstrated using direct infusion mass spectrometry-based metabolomic analysis of testes from roach exposed to different concentrations of a complex WWE. We show that xenobiotics and their metabolic products can be detected in roach testes (including triclosan, chloroxylenol and chlorophene), and that these compounds have a disproportionately high level of statistical significance within the total (bio)chemical changes induced by the WWE. Overall we have demonstrated that this workflow extracts more information from an environmental metabolomics study of complex mixture exposures than was possible previously.
Molecular responses to acute toxicant exposure can be effective biomarkers, however responses to chronic exposure are less well characterised. The aim of this study was to determine chronic molecular responses to environmental mixtures in a controlled laboratory setting, free from the additional variability encountered with environmental sampling of wild organisms. Flounder fish were exposed in mesocosms for seven months to a contaminated estuarine sediment made by mixing material from the Forth (high organics) and Tyne (high metals and tributyltin) estuaries (FT) or a reference sediment from the Ythan estuary (Y). Chemical analyses demonstrated that FT sediment contained significantly higher concentrations of key environmental pollutants (including polycyclic aromatic hydrocarbons (PAHs), chlorinated biphenyls and heavy metals) than Y sediment, but that chronically exposed flounder showed a lack of differential accumulation of contaminants, including heavy metals. Biliary 1-hydroxypyrene concentration and erythrocyte DNA damage increased in FT-exposed fish. Transcriptomic and (1)H NMR metabolomic analyses of liver tissues detected small but statistically significant alterations between fish exposed to different sediments. These highlighted perturbance of immune response and apoptotic pathways, but there was a lack of response from traditional biomarker genes. Gene-chemical association annotation enrichment analyses suggested that polycyclic aromatic hydrocarbons were a major class of toxicants affecting the molecular responses of the exposed fish. This demonstrated that molecular responses of sentinel organisms can be detected after chronic mixed toxicant exposure and that these can be informative of key components of the mixture.
Oceanic dissolved organic matter (DOM) is an assemblage of reduced carbon compounds, which results from biotic and abiotic processes. The biotic processes consist in either release or uptake of specific molecules by marine organisms. Heterotrophic bacteria have been mostly considered to influence the DOM composition by preferential uptake of certain compounds. However, they also secrete a variety of molecules depending on physiological state, environmental and growth conditions, but so far the full set of compounds secreted by these bacteria has never been investigated. In this study, we analyzed the exo-metabolome, metabolites secreted into the environment, of the heterotrophic marine bacterium Pseudovibrio sp. FO-BEG1 via ultra-high resolution mass spectrometry, comparing phosphate limited with phosphate surplus growth conditions. Bacteria belonging to the Pseudovibrio genus have been isolated worldwide, mainly from marine invertebrates and were described as metabolically versatile Alphaproteobacteria. We show that the exo-metabolome is unexpectedly large and diverse, consisting of hundreds of compounds that differ by their molecular formulae. It is characterized by a dynamic recycling of molecules, and it is drastically affected by the physiological state of the strain. Moreover, we show that phosphate limitation greatly influences both the amount and the composition of the secreted molecules. By assigning the detected masses to general chemical categories, we observed that under phosphate surplus conditions the secreted molecules were mainly peptides and highly unsaturated compounds. In contrast, under phosphate limitation the composition of the exo-metabolome changed during bacterial growth, showing an increase in highly unsaturated, phenolic, and polyphenolic compounds. Finally, we annotated the detected masses using multiple metabolite databases. These analyses suggested the presence of several masses analogue to masses of known bioactive compounds. However, the annotation was successful only for a minor part of the detected molecules, underlining the current gap in knowledge concerning the biosynthetic ability of marine heterotrophic bacteria.
Experimental MS(n) mass spectral libraries currently do not adequately cover chemical space. This limits the robust annotation of metabolites in metabolomics studies of complex biological samples. In-silico fragmentation libraries would improve the identification of compounds from experimental multi-stage fragmentation data when experimental reference data is unavailable. Here we present a freely-available software package to automatically control Mass Frontier software to construct in-silico mass spectral libraries, and to perform spectral matching. Based on two case studies we have demonstrated that HAMMER allows researchers to generate in-silico mass spectral libraries in an automated and high-throughput fashion with little or no human intervention required.
The application of reporting standards in metabolomics allow data from different laboratories to be shared, integrated and interpreted. Although minimum reporting standards related to metabolite identification were published in 2007, it is clear that significant efforts are required to ensure their continuous update and appropriate use by the metabolomics community. These include their use in metabolomics data submission (e.g., MetaboLights) and as a requirement for publication in peer-reviewed journals (e.g., Metabolomics). The Data Standards and Metabolite Identification Task Groups of the international Metabolomics Society are actively working to develop and promote these standards and educate the community on their use.
Phytoplankton exudates play an important role in pelagic ecology and biogeochemical cycles of elements. Exuded compounds fuel the microbial food web and often encompass bioactive secondary metabolites like sex pheromones, allelochemicals, antibiotics, or feeding attractants that mediate biological interactions. Despite this importance, little is known about the bioactive compounds present in phytoplankton exudates. We report a stable-isotope metabolic footprinting method to characterise exudates from aquatic autotrophs. Exudates from (13)C-enriched alga were concentrated by solid phase extraction and analysed by high-resolution Fourier transform ion cyclotron resonance mass spectrometry. We used the harmful algal bloom forming dinoflagellate Alexandrium tamarense to prove the method. An algorithm was developed to automatically pinpoint just those metabolites with highly (13)C-enriched isotope signatures, allowing us to discover algal exudates from the complex seawater background. The stable-isotope pattern (SIP) of the detected metabolites then allowed for more accurate assignment to an empirical formula, a critical first step in their identification. This automated workflow provides an effective way to explore the chemical nature of the solutes exuded from phytoplankton cells and will facilitate the discovery of novel dissolved bioactive compounds.
Due to the widespread use of silver nanoparticles (AgNPs), the likelihood of them entering the environment has increased and they are known to be potentially toxic. Currently, there is little information on the dynamic changes of AgNPs in ecotoxicity exposure media and how this may affect toxicity. Here, the colloidal stability of three different sizes of citrate-stabilized AgNPs was assessed in standard strength OECD ISO exposure media, and in 2-fold (media2) and 10-fold (media10) dilutions by transmission electron microscopy (TEM) and atomic force microscopy (AFM) and these characteristics were related to their toxicity towards Daphnia magna. Aggregation in undiluted media (media1) was rapid, and after diluting the medium by a factor of 2 or 10, aggregation was reduced, with minimal aggregation over 24h occurring in media10. Acute toxicity measurements were performed using 7nm diameter particles in media1 and media10. In media10 the EC50 of the 7nm particles for D. magna neonates was calculated to be 7.46?gL(-1) with upper and lower 95% confidence intervals of 6.84?gL(-1) and 8.13?gL(-1) respectively. For media1, an EC50 could not be calculated, the lowest observed adverse effect concentration (LOAEC) of 11.25?gL(-1) indicating a significant reduction in toxicity compared to that in media10. The data suggest the increased dispersion of nanoparticles leads to enhanced toxicity, emphasising the importance of appropriate media composition to fully assess nanoparticle toxicity in aquatic ecotoxicity tests.
Inflammatory arthritis is associated with systemic manifestations including alterations in metabolism. We used nuclear magnetic resonance (NMR) spectroscopy-based metabolomics to assess metabolic fingerprints in serum from patients with established rheumatoid arthritis (RA) and those with early arthritis.
Interactions between epigenome and the environment in biology and in disease are of fundamental importance. The incidence of hepatocellular adenomas in flatfish exceeds 20% in some environments forming a unique opportunity to study environmental tumorigenesis of general relevance to cancer in humans. We report the novel finding of marked DNA methylation and metabolite concentration changes in histopathologically normal tissue distal to tumors in fish liver. A multi-"omics" discovery approach led to targeted and quantitative gene transcription analyses and metabolite analyses of hepatocellular adenomas and histologically normal liver tissue in the same fish. We discovered a remarkable and consistent global DNA hypomethylation, modification of DNA methylation and gene transcription, and disruption of one-carbon metabolism in distal tissue compared to livers of non-tumor-bearing fish. The mechanism of this disruption is linked not to depletion of S-adenosylmethionine, as is often a feature of mammalian tumors, but to a decrease in choline and elevated S-adenosylhomocysteine, a potent inhibitor of DNA methyltransferase. This novel feature of normal-appearing tissue of tumor-bearing fish helps to understand the unprecedentedly high incidence of tumors in fish sampled from the field and adds weight to the controversial epigenetic progenitor model of tumorigenesis. With further studies, the modifications may offer opportunities as biomarkers of exposure to environmental factors influencing disease.
We report a combined theoretical and experimental study of the water octamer-h16. The calculations used the ring-polymer instanton method to compute tunnelling paths and splittings in full dimensionality. The experiments measured extensive high resolution spectra near 1.4 THz, for which isotope dilution experiments and group theoretical analysis support assignment to the octamer. Transitions appear as singlets, consistent with the instanton paths, which involve the breakage of two hydrogen-bonds and thus give tunneling splittings below experimental resolution.
Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an ideal fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm.
Currently there is limited information available on the accuracy and precision of relative isotopic abundance (RIA) measurements using high-resolution direct-infusion mass spectrometry (HR DIMS), and it is unclear if this information can benefit automated peak annotation in metabolomics. Here we characterize the accuracy of RIA measurements on the Thermo LTQ FT Ultra (resolution of 100,000-750,000) and LTQ Orbitrap (R = 100,000) mass spectrometers. This first involved reoptimizing the SIM-stitching method (Southam, A. D. Anal. Chem. 2007, 79, 4595-4602) for the LTQ FT Ultra, which achieved a ca. 3-fold sensitivity increase compared to the original method while maintaining a root-mean-squared mass error of 0.16 ppm. Using this method, we show the quality of RIA measurements is highly dependent on signal-to-noise ratio (SNR), with RIA accuracy increasing with higher SNR. Furthermore, a negative offset between the theoretical and empirically calculated numbers of carbon atoms was observed for both mass spectrometers. Increasing the resolution of the LTQ FT Ultra lowered both the sensitivity and the quality of RIA measurements. Overall, although the errors in the empirically calculated number of carbons can be large (e.g., 10 carbons), we demonstrate that RIA measurements do improve automated peak annotation, increasing the number of single empirical formula assignments by >3-fold compared to using accurate mass alone.
Omic technologies offer unprecedented opportunities to better understand mode(s)-of-toxicity and downstream secondary effects by providing a holistic view of the molecular changes underlying physiological disruption. Crustacean hemolymph represents a largely untapped biochemical resource for such toxicity studies. We sought to characterize changes in the hemolymph metabolome and whole-body transcriptome to reveal early processes leading to chronic toxicity in the indicator species, Daphnia magna, after 24-h sublethal cadmium exposure (18 ?g/L, corresponding to 1/10 LC(50)). We first confirmed that metabolites can be detected and identified in small volumes (?3-6 ?L) of D. magna hemolymph using Fourier transform ion cyclotron resonance mass spectrometry and NMR spectroscopy. Subsequently, mass spectrometry based metabolomics of hemolymph identified disruption to two major classes of metabolites: amino acids and fatty acids. These findings were compared to differentially expressed genes identified by a D. magna 44k oligonucleotide microarray, which included decreased levels of digestive enzymes and increased expression of cuticle proteins and oxidative stress response genes. The combination of metabolic and transcriptional changes revealed through KEGG pathway analysis and gene ontology, respectively, enabled a more complete understanding of how cadmium disrupts nutrient uptake and metabolism, ultimately resulting in decreased energy reserves and chronic toxicity.
The ability of targeted and nontargeted metabolomics to discover chronic ecotoxicological effects is largely unexplored. Fenitrothion, an organophosphate pesticide, is categorized as a "red list" pollutant, being particularly hazardous to aquatic life. It acts primarily as a cholinesterase inhibitor, but evidence suggests it can also act as an androgen receptor antagonist. Whole-organism fenitrothion-induced toxicity is well-established, but information regarding target and off-target molecular toxicities is limited. Here we study the molecular responses of male roach ( Rutilus rutilus ) exposed to fenitrothion, including environmentally realistic concentrations, for 28 days. Acetylcholine was assessed in brain; steroid metabolism was measured in testes and plasma; and NMR and mass spectrometry-based metabolomics were conducted on testes and liver to discover off-target toxicity. O-demethylation was confirmed as a major route of pesticide degradation. Fenitrothion significantly depleted acetylcholine, confirming its primary mode of action, and 11-ketotestosterone in plasma and cortisone in testes, showing disruption of steroid metabolism. Metabolomics revealed significant perturbations to the hepatic phosphagen system and previously undocumented effects on phenylalanine metabolism in liver and testes. On the basis of several unexpected molecular responses that were opposite to the anticipated acute toxicity, we propose that chronic pesticide exposure induces an adapting phenotype in roach, which may have considerable implications for interpreting molecular biomarker responses in field-sampled fish.
Silver nanoparticles (AgNPs) are currently being very widely used in industry, mainly because of their anti-bacterial properties, with applications in many areas. Once released into the environment, the mobility, bioavailability, and toxicity of AgNPs in any ecosystem are dominated by colloidal stability. There have been studies on the stability or the aggregation of various nanoparticles (NPs) under a range of environmental conditions, but there is little information on fully characterised AgNPs in media used in (eco)toxicity studies. In this study, monodisperse 7, 10 and 20 nm citrate-stabilised AgNPs were synthesised, characterised and then fractionated and sized by flow field-flow fractionation (FFF) and measured with dynamic light scattering (DLS) in different dilutions of the media recommended by OECD for Daphnia magna (water flea) toxicity testing. Stability of NPs was assessed over 24 h, and less so over 21 days, similar time periods to the OECD acute and chronic toxicity tests for D. magna. All particles aggregated quickly in the media with high ionic strength (media1), resulting in a loss of colour from the solution. The size of particles could be measured by DLS in most cases after 24h, although a fractogram by FFF could not be obtained due to aggregation and polydispersity of the sample. After diluting the media by a factor of 2, 5 or 10, aggregation was reduced, although the smallest NPs were unstable under all media conditions. Media diluted up to 10-fold in the absence of AgNPs did not induce any loss of mobility or fecundity in D. magna. These results confirm that standard OECD media causes aggregation of AgNPs, which result in changes in organism exposure levels and the nature of the exposed particles compared to exposure to fully dispersed particles. Setting aside questions of dose metrics, significant and substantial reduction in concentration over exposure period suggests that literature data are in the main improperly interpreted and nanoparticles are likely to have far greater biological effects than suggested thus far by poorly controlled exposures. We recommend that the standard OECD media is diluted by a factor of ca. 10 for use with these NPs and this test media, which reduces AgNP aggregation without affecting the viability of the text organism.
The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.
Insertion of folded proteins into the outer membrane of Gram-negative bacteria is mediated by the essential ?-barrel assembly machine (Bam). Here, we report the native structure and mechanism of a core component of this complex, BamE, and show that it is exclusively monomeric in its native environment of the periplasm, but is able to adopt a distinct dimeric conformation in the cytoplasm. BamE is shown to bind specifically to phosphatidylglycerol, and comprehensive mutagenesis and interaction studies have mapped key determinants for complex binding, outer membrane integrity and cell viability, as well as revealing the role of BamE within the Bam complex.
Our previous studies have shown that the nonsteroidal anti-inflammatory drug indomethacin exhibits antileukemic activity in vitro and can inhibit the aldo-keto reductase AKR1C3, which we identified as a novel target in acute myeloid leukemia. However, the antileukemic actions of indomethacin are likely to be complex and extend beyond inhibition of either AKR1C3 or cycloxygenases. To further understand the antileukemic activity of indomethacin we have used untargeted nuclear magnetic resonance-based metabolic analysis to characterize the responses of KG1a and K562 cell lines in both normal culture conditions and in hypoxia, which better represents the tumor environment in vivo. Hypoxia induced dramatic metabolic changes in untreated KG1a and K562, including adaptation of both phospholipid and glycolytic metabolism. Despite these changes, both cell lines sustained relatively unaltered mitochondrial respiration. The administration of indomethacin induced similar metabolic responses regardless of the oxygen level in the environment. Notable exceptions included metabolites associated with de novo fatty acid synthesis and choline phospholipid metabolism. Collectively, these results suggest that leukemia cells have the inherent ability to tolerate changes in oxygen tension while maintaining an unaltered mitochondrial respiration. However, the administration of indomethacin significantly increased oxidative stress in both KG1a and K562, inducing mitochondrial dysfunction, regardless of the oxygenation conditions. These findings emphasize the particular pertinence of the tricarboxylic acid cycle to the survival of cancer cells and may explain why some antileukemic drugs have been discovered and developed successfully despite the use of culture conditions that do not reflect the hypoxic environment of cancer cells in vivo.
Currently, there is widespread interest in exploiting "omics" approaches to screen the toxicity of chemicals, potentially enabling their rapid categorization into classes of defined mode of action (MOA). Direct infusion Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) metabolomics provides a sensitive and nontargeted analysis of potentially a thousand endogenous metabolites. Our previous work has shown that mass spectra can be recorded from whole-organism homogenate or hemolymph of single adult Daphnia magna. Here we develop multivariate models and discover perturbations to specific metabolic pathways that can discriminate between the acute toxicities of four chemicals to D. magna using FT-ICR MS metabolomics. We focus on model toxicants (cadmium, fenvalerate, dinitrophenol, and propranolol) with different MOAs. First, we confirmed that a toxicant-induced metabolic effect could be determined for each chemical in both the hemolymph and the whole-organism metabolome, with between 9 and 660 mass spectral peaks changing intensities significantly, dependent upon toxicant and sample type. Subsequently, supervised multivariate models were built that discriminated significantly all four acute metabolic toxicities, yielding mean classification error rates (across all classes) of 3.9 and 6.9% for whole-organism homogenates and hemolymph, respectively. Following extensive peak annotation, we discovered toxicant-specific perturbations to putatively identified metabolic pathways, including propranolol-induced disruption of fatty acid metabolism and eicosanoid biosynthesis and fenvalerate-induced disruption of amino sugar metabolism. We conclude that the metabolic profiles of whole-daphnid homogenates are more discriminatory for toxicant action than hemolymph. Furthermore, our findings highlight the capability of metabolomics to discover early-event metabolic responses that can discriminate between the acute toxicities of chemicals.
To improve the outcome of orthotopic liver transplantation (OLT), knowledge of early molecular events occurring upon ischemia/reperfusion is essential. Powerful approaches for profiling metabolic changes in tissues and biofluids are now available. Our objective was to investigate the applicability of two technologies to a small but well-defined cohort of patients undergoing OLT: consecutive liver biopsies by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and microdialysates of extracellular fluid by coulometric electrochemical array detection (CEAD). FT-ICR MS detected reproducibly more than 4,000 peaks, revealing hundreds of significant metabolic differences between pre- and postreperfusion grafts. These included increased urea production, bile acid synthesis and clearance of preservation solution upon reperfusion, indicating a rapid resumption of biochemical function within the graft. FT-ICR MS also identified successfully the only graft obtained by donation-after-cardiac-death as a "metabolic outlier." CEAD time-profile analysis showed that there was considerable change in redox-active metabolites (up to 18 h postreperfusion), followed by their stabilization. Collectively these results verify the applicability of FT-ICR MS and CEAD for characterizing multiple metabolic pathways during OLT. The success of this proof-of-principle application of these technologies to a clinical setting, considering the potential metabolic heterogeneity across only eight donor livers, is encouraging.
Crude oil spills from tankers remain a serious threat along coastal California. Resource managers require information on the acute toxicity of treated and untreated oil, and their sublethal effects on wildlife. This investigation compared the toxic actions of the water-accommodated fraction (WAF) and the chemically-enhanced WAF (CEWAF; Corexit 9500) of Prudhoe Bay crude oil in pre-smolt Chinook salmon (Oncorhynchus tshawytscha) via nuclear magnetic resonance (NMR)-based metabolomics. Metabolite profiles from muscle samples, after 96h exposures, were measured using 1D (1)H NMR and compared via principal component analysis. It was determined that both WAF and CEWAF produced similar profiles in which amino acids, lactate and ATP comprised the highest intensity signals. Overall, metabolic substrates and growth measurements did not show residual effects of short-term exposure on long-term development. In conclusion, the 96h LC(50)s indicate dispersant application significantly decreased hydrocarbon potency and identified metabolites may be bio-indicators of hydrocarbon stress from hydrocarbon exposure.
Metabolic pathway diagrams provide a wealth of information on how reactions combine to perform biological functions. While pathway diagrams are arranged in a way that allows a specific area of metabolism to be visualised, the inherent complexity of each pathway makes it difficult to identify the sets of reactions linking groups of compounds; a common task for researchers attempting to explain observed correlations or looking for further compounds of potential interest to use in validation work. Here we introduce Linked Metabolites, a tool that identifies sets of reactions linking groups of compounds in the context of the KEGG pathway diagrams.
Toxicological studies in sentinel organisms frequently use biomarkers to assess biological effect. Development of "omic" technologies has enhanced biomarker discovery at the molecular level, providing signatures unique to toxicant mode-of-action (MOA). However, these signatures often lack relevance to organismal responses, such as growth or reproduction, limiting their value for environmental monitoring. Our primary objective was to discover metabolic signatures in chemically exposed organisms that can predict physiological toxicity. Marine mussels (Mytilus edulis) were exposed for 7 days to 12 and 50 microg/l copper and 50 and 350 microg/l pentachlorophenol (PCP), toxicants with unique MOAs. Physiological responses comprised an established measure of organism energetic fitness, scope for growth (SFG). Metabolic fingerprints were measured in the same individuals using nuclear magnetic resonance-based metabolomics. Metabolic signatures predictive of SFG were sought using optimal variable selection strategies and multivariate regression and then tested upon independently field-sampled mussels from rural and industrialized sites. Copper and PCP induced rational metabolic and physiological changes. Measured and predicted SFG were highly correlated for copper (r(2) = 0.55, P = 2.82 x 10(-7)) and PCP (r(2) = 0.66, P = 3.20 x 10(-6)). Predictive metabolites included methionine and arginine/phosphoarginine for copper and allantoin, valine, and methionine for PCP. When tested on field-sampled animals, metabolic signatures predicted considerably reduced fitness of mussels from the contaminated (SFG = 6.0 J/h/g) versus rural (SFG = 15.2 J/h/g) site. We report the first successful discovery of metabolic signatures in chemically exposed environmental organisms that inform on molecular MOA and that can predict physiological toxicity. This could have far-reaching implications for monitoring impacts on environmental health.
In this commentary we present the findings from an international consortium on fish toxicogenomics sponsored by the U.K. Natural Environment Research Council (Fish Toxicogenomics-Moving into Regulation and Monitoring, held 21-23 April 2008 at the Pacific Environmental Science Centre, Vancouver, BC, Canada).
Modeling NMR-based metabolomics data often involves linear methods such as principal component analysis (PCA) and partial least squares (PLS). These methods have the objective of describing the main variance in the data and maximum covariance between the predictor variables and some response variable respectively. If the experiment is designed to investigate temporal biological fluctuations, however, the factors obtained become difficult to interpret in a biological context. Moreover, when these methods are applied to analyze data, an implicit assumption is made that the measurement errors exhibit an iid-normal distribution, often limiting the extent of the information recovered. A method for the linear decomposition of NMR-based metabolomics data by multivariate curve resolution (MCR), which has been used elsewhere for time course transcriptomics applications, is introduced and implemented via a weighted alternating least squares (ALS) approach. Measurement of error information is incorporated in the modeling process, allowing the least squares projections to be performed in a maximum likelihood fashion. As a result, noise heteroscedasticity resulting from pH-induced peak shifts can be modeled, eliminating the need for binning/bucketing. The utility of the method is demonstrated using two sets of temporal NMR metabolomics data, HgCl(2)-induced nephrotoxicity in rat, and fish (Japanese medaka, Oryzias latipes) embryogenesis. Profiles extracted for the nephrotoxicity data exhibit strong correlations with metabolites consistent with temporal fluctuations in glucosuria. The concentration of metabolites such as acetate, glucose, and alanine exhibit a steady increase, which peaks at Day 3 post dose and returns to basal levels at Day 8. Other metabolites including citrate and 2-oxoglutarate exhibit the opposite characteristics. Although the fish embryogenesis data are more complex, the profiles extracted by the algorithm display characteristics that depict temporal variation consistent with processes associated with embryogenesis.
A three-spined stickleback (Gasterosteus aculeatus) cDNA array and one-dimensional 1H nuclear magnetic resonance (NMR) spectroscopy-based metabolomics approach, together with individual biomarkers,were employed to investigate the responses of male sticklebacks to polycyclic aromatic hydrocarbon exposure. Fish were exposed to 1,2:5,6-dibenzanthracene (DbA) at concentrations between 0.01 and 50 microg per liter dissolved in the ambient water for four days, and hepatic transcript and metabolite profiles were determined in comparison with those of solvent-exposed controls. Induction of gene expression was apparent for cytochrome P450 1A (CYP1A) and CYP2-family monooxygenases and these responses were strongly correlated with DbA exposure concentrations (for CYP1A r > 0.996). Expression of suites of genes related to bile acid biosynthesis, steroid metabolism, and endocrine function were also affected, as demonstrated by gene ontology analyses. Expression changes in selected genes were confirmed by real-time PCR. Metabolomics highlighted notable changes in concentrations of taurine, malonate, glutamate, and alanine. These statistically significant responses to environmentally relevant concentrations of DbA at the transcriptomic and metabolomic levels provided sensitive markers characteristic of environmentally relevant low-level DbA exposure. Metabolic pathways were identified where both gene expression and metabolite concentrations were altered in response to DbA.
This paper proposes a novel profiling method for SELDI-TOF and MALDI-TOF MS data that integrates a novel peak detection method based on modified smoothed non-linear energy operator, correlation-based peak selection and Bayesian additive regression trees. The peak detection and classification performance of the proposed approach is validated on two publicly available MS data sets, namely MALDI-TOF simulation data and high-resolution SELDI-TOF ovarian cancer data. The results compared favorably with three state-of-the-art peak detection algorithms and four machine-learning algorithms. For the high-resolution ovarian cancer data set, seven biomarkers (m/z windows) were found by our method, which achieved 97.30 and 99.10% accuracy at 25th and 75th percentiles, respectively, from 50 independent cross-validation samples, which is significantly better than other profiling and dimensional reduction methods. The results show that the method is capable of finding parsimonious sets of biologically meaningful biomarkers with better accuracy than existing methods. Supporting Information material and MATLAB/R scripts to implement the methods described in the article are available at: http://www.cs.bham.ac.uk/szh/SourceCode-for-Proteomics.zip.
NMR spectroscopy remains one of the primary analytical approaches in metabolomics. Although 1D (1)H NMR spectroscopy is versatile, highly reproducible and currently the most widely used technique in NMR metabolomics, analysis of complex biological samples typically yields highly congested spectra with severely overlapping signals making unambiguous metabolite identification and quantification almost impossible. Consequently there is a growing use of 2D NMR methods, in particular (1)H J-resolved (JRES) spectroscopy, which spreads the high signal density into a second dimension. One potentially powerful method to deconvolute these JRES spectra, facilitating metabolite quantification, is via line-shape fitting. However, the mathematical functions describing the JRES NMR line-shape, in particular after applying apodisation functions and JRES specific processing, including tilting and symmetrisation, remain uncharacterised. Furthermore, possible quantitation errors arising from processing JRES spectra have not been evaluated, nor have the potentially adverse quantitative effects of overlapping dispersive tails of closely spaced signals in the 2D spectrum. Here we address these issues and evaluate the suitability of the JRES experiment for accurate complex mixture analysis. Specifically, we have examined changes in NMR line-shape and signal intensity after application of different apodisation functions (SINE and SEM) and JRES specific processing (tilting and symmetrising), comparing simulated and experimental data. We also report a significant quantitation error of up to 33%, dependent upon apodisation, due to overlap of the dispersive tails of closely spaced resonances. Finally, we have validated the use of these mathematical line-shape functions for metabolite quantitation of 2D JRES spectra, by comparison to corresponding 1D NMR datasets, using both gravimetrically-prepared chemically defined mixtures as well as biological tissue extracts.
The majority of acute myeloid leukaemia (AML) patients are over sixty years of age. With current treatment regimens, survival rates amongst these, and also those younger patients who relapse, remain dismal and novel therapies are urgently required. In particular, therapies that have anti-leukaemic activity but that, unlike conventional chemotherapy, do not impair normal haemopoiesis.
An established three-spined stickleback (Gasterosteus aculeatus) cDNA array was expanded to 14,496 probes with the addition of hepatic clones derived from subtractive and normalized libraries from control males and males exposed to model toxicants. Microarrays and one-dimensional (1)H nuclear magnetic resonance (NMR) spectroscopy, together with individual protein and gene biomarkers were employed to investigate the hepatic responses of the stickleback to ethinyl-estradiol (EE(2)) exposure. Male fish were exposed via the water to EE(2), including environmentally relevant concentrations (0.1-100ng/l) for 4 days, and hepatic transcript and metabolite profiles, kidney spiggin protein and serum vitellogenin concentrations were determined in comparison to controls. EE(2) exposure did not significantly affect spiggin concentration but significantly induced serum vitellogenin protein at the threshold concentration of 32ng/l. (1)H NMR coupled with robust univariate testing revealed only limited changes, but these did support the predicted modulation of the amino acid profile by transcriptomics. Transcriptional induction was found for hepatic vitellogenins and choriogenins as expected, together with a range of other EE(2)-responsive genes. Choriogenins showed the more sensitive responses with statistically significant induction at 10ng/l. Real-time polymerase chain reaction (PCR) confirmed transcriptional induction of these genes. Phosvitinless vitellogenin C transcripts were highly expressed and represent a major form of the egg yolk precursors, and this is in contrast to other fish species where it is a minor component of vitellogenic transcripts. Differences in inducibility between the vitellogenins and choriogenins appear to be in accordance with the sequential formation of chorion and yolk during oogenesis in fish.
With maritime transport of crude oil from Alaska to California, there is significant potential for a catastrophic spill which could impact migrating salmon. Therefore, this study compared the lethal and sublethal metabolic actions of the water-accommodated fraction (WAF) and the chemically enhanced WAF (CEWAF, via Corexit 9500) of Prudhoe Bay crude oil in smolts of Chinook salmon (Onchorhyncus tshawytscha). After 96-h exposure to the CEWAF, the resulting LC50 was some 20 times higher (i.e., less toxic) than that of the WAF. Muscle and liver samples from surviving fish were collected and low-molecular weight metabolites were analyzed using one-dimensional (1)H and projections of two-dimensional (1)H J-resolved NMR. Principal component analysis (PCA), employed to analyze NMR spectra and identify most variance from the samples, revealed age-related metabolic changes in the fish within the replicated studies, but few consistent metabolic effects from the treatments. However, ANOVA results demonstrated that the dose-response metabolite patterns are both metabolite- and organ-dependent. In general, exposure to either WAF or CEWAF resulted in an increase of amino acids (i.e., valine, glutamine and glutamate) and a decrease of both organic osmolytes (i.e., glycerophosphorylcholine) and energetic substrates (i.e., succinate). The simultaneous increase of formate and decrease of glycerophosphorylcholine in the liver, or the decrease of glycerophosphorylcholine in muscle, may serve as sensitive sublethal biomarkers for WAF or CEWAF exposures, respectively. In conclusion, dispersant treatment significantly decreased the lethal potency of crude oil to salmon smolts, and the NMR-based metabolomics approach provided a sensitive means to characterize the sublethal metabolic actions.
Metabolomics datasets, by definition, comprise of measurements of large numbers of metabolites. Both technical (analytical) and biological factors will induce variation within these measurements that is not consistent across all metabolites. Consequently, criteria are required to assess the reproducibility of metabolomics datasets that are derived from all the detected metabolites. Here we calculate spectrum-wide relative standard deviations (RSDs; also termed coefficient of variation, CV) for ten metabolomics datasets, spanning a variety of sample types from mammals, fish, invertebrates and a cell line, and display them succinctly as boxplots. We demonstrate multiple applications of spectral RSDs for characterising technical as well as inter-individual biological variation: for optimising metabolite extractions, comparing analytical techniques, investigating matrix effects, and comparing biofluids and tissue extracts from single and multiple species for optimising experimental design. Technical variation within metabolomics datasets, recorded using one- and two-dimensional NMR and mass spectrometry, ranges from 1.6 to 20.6% (reported as the median spectral RSD). Inter-individual biological variation is typically larger, ranging from as low as 7.2% for tissue extracts from laboratory-housed rats to 58.4% for fish plasma. In addition, for some of the datasets we confirm that the spectral RSD values are largely invariant across different spectral processing methods, such as baseline correction, normalisation and binning resolution. In conclusion, we propose spectral RSDs and their median values contained herein as practical benchmarks for metabolomics studies.
Several fundamental requirements must be met so that NMR-based metabolomics and the related technique of metabonomics can be formally adopted into environmental monitoring and chemical risk assessment. Here we report an intercomparison exercise which has evaluated the effectiveness of 1H NMR metabolomics to generate comparable data sets from environmentally derived samples. It focuses on laboratory practice that follows sample collection and metabolite extraction, specifically the final stages of sample preparation, NMR data collection (500, 600, and 800 MHz), data processing, and multivariate analysis. Seven laboratories have participated from the U.S.A., Canada, U.K., and Australia, generating a total of ten data sets. Phase 1 comprised the analysis of synthetic metabolite mixtures, while Phase 2 investigated European flounder (Platichthys flesus) liver extracts from clean and contaminated sites. Overall, the comparability of data sets from the participating laboratories was good. Principal components analyses (PCA) of the individual data sets yielded ten highly similar scores plots for the synthetic mixtures, with a comparable result for the liver extracts. Furthermore, the same metabolic biomarkers that discriminated fish from clean and contaminated sites were discovered by all the laboratories. PCA of the combined data sets showed excellent clustering of the multiple analyses. These results demonstrate that NMR-based metabolomics can generate data that are sufficiently comparable between laboratories to support its continued evaluation for regulatory environmental studies.
Direct-infusion electrospray-ionization Fourier transform ion cyclotron resonance mass spectrometry (DI ESI FT-ICR MS) is increasingly being utilized in metabolomics, including the high sensitivity selected ion monitoring (SIM)-stitching approach. Accurate signal quantification and the discrimination of real signals from noise remain major challenges for this approach, with both adversely affected by factors including ion suppression during electrospray, ion-ion interactions in the detector cell, and thermally-induced white noise. This is particularly problematic for complex mixture analysis where hundreds of metabolites are present near the noise level. Here we address relative signal quantification and noise discrimination issues in SIM-stitched DI ESI FT-ICR MS-based metabolomics. Using liver tissue, we first optimized the number of scans (n) acquired per SIM window to address the balance between quantification accuracy versus acquisition time (and thus sample throughput); a minimum of n = 5 is recommended. Secondly, we characterized and computationally-corrected an effect whereby an ions intensity is dependent upon its location within a SIM window, exhibiting a 3-fold higher intensity at the high m/z end. This resulted in significantly improved quantification accuracy. Finally, we thoroughly characterized a three-stage filter to discriminate noise from real signals, which comprised a signal-to-noise-ratio (SNR) hard threshold, then a "replicate" filter (retaining only peaks in r-out-of-3 replicate analyses), and then a "sample" filter (retaining only peaks in >s% of biological samples). We document the benefits of three-stage filtering versus one- and two-stage filters, and show the importance of selecting filter parameters that balance the confidence that a signal is real versus the total number of peaks detected.
Combined bezafibrate (BEZ) and medroxyprogesterone acetate (MPA) exert unexpected antileukaemic activities against acute myeloid leukaemia (AML) and these activities are associated with the generation of reactive oxygen species (ROS) within the tumor cells. Although the generation of ROS by these drugs is supported by preceding studies including our own, the interrelationship between the cellular effects of the drugs and ROS generation is not well understood. Here we report the use of NMR metabolomic profiling to further study the effect of BEZ and MPA on three AML cell lines and to shed light on the underlying mechanism of action. For this we focused on drug effects induced during the initial 24 hours of treatment prior to the onset of overt cellular responses and examined these in the context of basal differences in metabolic profiles between the cell lines. Despite their ultimately profound cellular effects, the early changes in metabolic profiles engendered by these drugs were less pronounced than the constitutive metabolic differences between cell types. Nonetheless, drug treatments engendered common metabolic changes, most markedly in the response to the combination of BEZ and MPA. These responses included changes to TCA cycle intermediates consistent with recently identified chemical actions of ROS. Notable amongst these was the conversion of alpha-ketoglutarate to succinate which was recapitulated by the treatment of cell extracts with exogenous hydrogen peroxide. These findings indicate that the actions of combined BEZ and MPA against AML cells are indeed mediated downstream of the generation of ROS rather than some hitherto unsuspected mechanism. Moreover, our findings demonstrate that metabolite profiles represent highly sensitive markers for genomic differences between cells and their responses to external stimuli. This opens new perspectives to use metabolic profiling as a tool to study the rational redeployment of drugs in new disease settings.
In a search for biomarkers of health in whale sharks and as exploration of metabolomics as a modern tool for understanding animal physiology, the metabolite composition of serum in six whale sharks (Rhincodon typus) from an aquarium collection was explored using (1)H nuclear magnetic resonance (NMR) spectroscopy and direct analysis in real time (DART) mass spectrometry (MS). Principal components analysis (PCA) of spectral data showed that individual animals could be resolved based on the metabolite composition of their serum and that two unhealthy individuals could be discriminated from the remaining healthy animals. The major difference between healthy and unhealthy individuals was the concentration of homarine, here reported for the first time in an elasmobranch, which was present at substantially lower concentrations in unhealthy whale sharks, suggesting that this metabolite may be a useful biomarker of health status in this species. The function(s) of homarine in sharks remain uncertain but it likely plays a significant role as an osmolyte. The presence of trimethylamine oxide (TMAO), another well-known protective osmolyte of elasmobranchs, at 0.1-0.3 mol L(-1) was also confirmed using both NMR and MS. Twenty-three additional potential biomarkers were identified based on significant differences in the frequency of their occurrence between samples from healthy and unhealthy animals, as detected by DART MS. Overall, NMR and MS provided complementary data that showed that metabolomics is a useful approach for biomarker prospecting in poorly studied species like elasmobranchs.
Mass spectrometry is widely used in bioanalysis, including the fields of metabolomics and proteomics, to simultaneously measure large numbers of molecules in complex biological samples. Contaminants routinely occur within these samples, for example, originating from the solvents or plasticware. Identification of these contaminants is crucial to enable their removal before data analysis, in particular to maintain the validity of conclusions drawn from uni- and multivariate statistical analyses. Although efforts have been made to report contaminants within mass spectra, this information is fragmented and its accessibility is relatively limited. In response to the needs of the bioanalytical community, here we report the creation of an extensive manually well-annotated database of currently known small molecule contaminants.
The citric acid cycle (CAC) metabolite fumarate has been proposed to be cardioprotective; however, its mechanisms of action remain to be determined. To augment cardiac fumarate levels and to assess fumarates cardioprotective properties, we generated fumarate hydratase (Fh1) cardiac knockout (KO) mice. These fumarate-replete hearts were robustly protected from ischemia-reperfusion injury (I/R). To compensate for the loss of Fh1 activity, KO hearts maintain ATP levels in part by channeling amino acids into the CAC. In addition, by stabilizing the transcriptional regulator Nrf2, Fh1 KO hearts upregulate protective antioxidant response element genes. Supporting the importance of the latter mechanism, clinically relevant doses of dimethylfumarate upregulated Nrf2 and its target genes, hence protecting control hearts, but failed to similarly protect Nrf2-KO hearts in an in vivo model of myocardial infarction. We propose that clinically established fumarate derivatives activate the Nrf2 pathway and are readily testable cytoprotective agents.
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