BackgroundNew methods are needed for research into non-model organisms, to monitor the effects of toxic disruption at both the molecular and functional organism level. We exposed earthworms (Lumbricus rubellus Hoffmeister) to sub-lethal levels of copper (10–480 mg/kg soil) for 70 days as a real-world situation, and monitored both molecular (cDNA transcript microarrays and nuclear magnetic resonance-based metabolic profiling: metabolomics) and ecological/functional endpoints (reproduction rate and weight change, which have direct relevance to population-level impacts).ResultsBoth of the molecular endpoints, metabolomics and transcriptomics, were highly sensitive, with clear copper-induced differences even at levels below those that caused a reduction in reproductive parameters. The microarray and metabolomic data provided evidence that the copper exposure led to a disruption of energy metabolism: transcripts of enzymes from oxidative phosphorylation were significantly over-represented, and increases in transcripts of carbohydrate metabolising enzymes (maltase-glucoamylase, mannosidase) had corresponding decreases in small-molecule metabolites (glucose, mannose). Treating both enzymes and metabolites as functional cohorts led to clear inferences about changes in energetic metabolism (carbohydrate use and oxidative phosphorylation), which would not have been possible by taking a 'biomarker' approach to data analysis.ConclusionMultiple post-genomic techniques can be combined to provide mechanistic information about the toxic effects of chemical contaminants, even for non-model organisms with few additional mechanistic toxicological data. With 70-day no-observed-effect and lowest-observed-effect concentrations (NOEC and LOEC) of 10 and 40 mg kg-1 for metabolomic and microarray profiles, copper is shown to interfere with energy metabolism in an important soil organism at an ecologically and functionally relevant level.

In this study, we addressed the question of whether an omic approach could genuinely be useful for biomarker profile analysis across different field sites with different physicochemical characteristics. We collected earthworms (Lumbricus rubellus) from seven sites with very different levels of metal contamination and prevailing soil type and analyzed tissue extracts by 1H nuclear magnetic resonance spectroscopy. Pattern recognition analysis of the data showed that both site- and contaminant-specific effects on the metabolic profiles could be discerned. Zinc was identified as the probable major contaminant causing a metabolic change in the earthworms. Individual sites could be resolved on the basis of NMR spectral profiles by principal component analysis; these site differences may also have been caused by additional abiotic factors such as soil pH. Despite an inevitable degree of confounding between site and contaminant concentrations, it was possible to identify metabolites which were correlated with zinc across all different sites. This study therefore acts as a proof of principle for the use of NMR-based metabolic profiling as a diagnostic tool for ecotoxicological research in polluted field soils.

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Purpose: Weight gain in women receiving chemotherapy for breast cancer is associated with a higher risk of recurrence but its mechanisms are poorly understood. Experimental Design: To investigate this, we assessed the metabolic, cytokine, and appetite-related peptide alterations during adjuvant chemotherapy for early breast cancer in postmenopausal women, and correlated these with body mass measurements. Specifically, we performed global metabolic profiling using 1 H-nuclear magnetic resonance spectroscopy of sequential sera, examined ghrelin immunoreactivity, RIAs for GLP-1 and peptide YY, and electrochemiluminescent cytokine analyses (tumor necrosis factor-α and interleukin-6) on sequential samples. Results: In those who gained >1.5 kg, several metabolite levels were positively associated with weight gain, specifically lactate, which was 63.5% greater in patients with increased body weight during chemotherapy compared with those with no weight gain (P < 0.01; the prespecified primary end point). A strong correlation (r = 0.7, P < 0.001) was detected between the rate of weight change and serum lactate levels, and on average, lactate levels exhibited the greatest metabolic response to chemotherapy, increasing by up to 75%. Normalized levels of peptide YY were also observed to be elevated in patients not gaining weight posttreatment (+30% compared with -7% for the weight gain group; P < 10 -4 ). Baseline lactate, alanine, and body fat were all prognostic for weight gain (area under the receiver operator characteristic curves, >0.77; P < 0.05). No associations were observed between any other parameter and weight gain, including cytokine levels. Conclusions: Metabonomics identifies excess energy expenditure pathways perturbed during chemotherapy for breast cancer, and establishes a significant association between serum lactate, body fat, and substantive weight gain during chemotherapy. (Clin Cancer Res 2009;15(21):6716-23)