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Metabolomic analysis of tissue samples can be applied across multiple fields including medicine, toxicology, and environmental sciences. A thorough evaluation of several metabolite extraction procedures from tissues is therefore warranted. This has been achieved at two research laboratories using muscle and liver tissues from fish. Multiple replicates of homogenous tissues were extracted using the following solvent systems of varying polarities: perchloric acid, acetonitrile/water, methanol/water, and methanol/chloroform/water. Extraction of metabolites from ground wet tissue, ground dry tissue, and homogenized wet tissue was also compared. The hydrophilic metabolites were analyzed using 1-dimensional (1D) 1 H nuclear magnetic resonance (NMR) spectroscopy and projections of 2-dimensional J-resolved (p-JRES) NMR, and the spectra evaluated using principal components analysis. Yield, reproducibility, ease, and speed were the criteria for assessing the quality of an extraction protocol for metabolomics. Both laboratories observed that the yields of low molecular weight metabolites were similar among the solvent extractions; however, acetonitrile-based extractions provided poorer fractionation and extracted lipids and macromolecules into the polar solvent. Extraction using perchloric acid produced the greatest variation between replicates due to peak shifts in the spectra, while acetonitrile-based extraction produced highest reproducibility. Spectra from extraction of ground wet tissues generated more macromolecules and lower reproducibility compared with other tissue disruption methods. The p-JRES NMR approach reduced peak congestion and yielded flatter baselines, and subsequently separated the metabolic fingerprints of different samples more clearly than by 1D NMR. Overall, single organic solvent extractions are quick and easy and produce reasonable results. However, considering both yield and reproducibility of the hydrophilic metabolites as well as recovery of the hydrophobic metabolites, we conclude that the methanol/chloroform/water extraction is the preferred method.

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.

Copper (Cu) is a micronutrient essential for the biochemical functioning of numerous processes in vertebrates but is also often present in the aquatic environment at concentrations able to cause adverse health effects in aquatic organisms. This study investigated the signaling pathways mediating the effects of exposure to Cu using a toxicogenomic approach in a fish model, the stickleback ( Gasterosteus aculeatus ). Freshwater-acclimated male fish were exposed via the water to Cu, including at environmentally relevant concentrations (3.2-128 microg of Cu/L for 4 days), and the biological responses explored through analyses of the hepatic transcriptome and metabolome and phenotypic end points, including assessment of DNA damage in blood cells. The Cu exposures resulted in DNA strand breaks in blood cells at all exposure concentrations and alterations in hepatic gene expression and metabolite concentrations in a concentration-dependent manner (from 10 microg of Cu/L). Genes associated with the cholesterol biosynthesis pathway were significantly over-represented and consistently down-regulated (at 128 microg of Cu/L), similar to that occurring in a mouse model for Wilson's disease. Additionally, inductions in metallothionein and catalase were also observed. The concentrations of NAD(+) and lactate increased significantly with the Cu exposure, consistent with a shift toward anaerobic metabolism, and these aligned closely with changes observed in gene expression. The pathways of Cu toxicity identified in our study support the conserved mechanisms of Cu toxicity from lower vertebrates to mammals, provide novel insights into the deleterious effects of Cu in fish, and further demonstrate the utility of fish as environmental sentinels for chemical impacts on both environmental and human health.

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Mercury is a hazardous pollutant in the Bohai marine environments due to its high toxicity to the marine organisms and subsequent ecological risk. Manila clam Ruditapes philippinarum is one of important sentinel organisms in 'Mussel Watch Program' launched in China and therefore used as a bioindicator in marine and coastal ecotoxicology. There are dominantly distributed three pedigrees of clam (White, Liangdao Red and Zebra) in Yantai population endowed with different tolerances to environmental stressors. In this study, gill tissues were collected from both untreated and mercury exposed White, Liangdao Red and Zebra clams, and the extracts were analyzed by NMR-based metabolomics to compare the original metabolomes and the toxicological effects induced by mercury exposure in three pedigrees. The major abundant metabolites in White clam sample were branchedchain amino acids, lactate, alanine, arginine, acetoacetate, glutamate, succinate, citrate, malonate and taurine, while the metabolite profile of Liangdao Red clam sample comprises relative high levels of alanine, arginine, glutamate, succinate and glycogen. For Zebra clam sample, the metabolite profile exhibited relatively high amount of aspartate, acetylcholine and homarine. After 48 h exposure of 20 lg l -1 Hg 2? , the metabolic profiles from all the three pedigrees of clams commonly showed significant increases in alanine, arginine, glutamate, aspartate, a-ketoglutarate, glycine and ATP/ADP, and decreases in citrate, taurine and homarine. The unique metabolic differences between the metabolomes of gill tissues from Hg 2? -exposed White, Liangdao Red and Zebra clams were found, including elevated acetylcholine and branched-chain amino acids in White clams, and the declined succinate in both White and Liangdao Red samples as well as the declined betaine in Zebra and White clams. Overall, our findings showed the differential toxicological responses to mercury exposure and that White clams could be a preferable bioindicator for the metal pollution monitoring based on the metabolic changes from gill compared with other two (Liangdao Red and Zebra) pedigrees of clams.

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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.