Development of analytical methods for NMR spectra and application to a 13 C toxicology study
ABSTRACT Metabolomics offers the potential to assess the effects of toxicants on metabolite levels. To fully realize this potential,
a robust analytical workflow for identifying and quantifying treatment-elicited changes in metabolite levels by nuclear magnetic
resonance (NMR) spectrometry has been developed that isolates and aligns spectral regions across treatment and vehicle groups
to facilitate analytical comparisons. The method excludes noise regions from the resulting reduced spectra, significantly
reducing data size. Principal components analysis (PCA) identifies data clusters associated with experimental parameters.
Cluster-centroid scores, derived from the principal components that separate treatment from vehicle samples, are used to reconstruct
the mean spectral estimates for each treatment and vehicle group. Peak amplitudes are determined by scanning the reconstructed
mean spectral estimates. Confidence levels from Mann–Whitney order statistics and amplitude change ratios are used to identify
treatment-related changes in peak amplitudes. As a demonstration of the method, analysis of 13C NMR data from hepatic lipid extracts of immature, ovariectomized C57BL/6 mice treated with 30 μg/kg 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) or sesame oil vehicle, sacrificed at 72, 120, or 168 h, identified 152 salient peaks. PCA clustering showed
a prominent treatment effect at all three time points studied, and very little difference between time points of treated animals.
Phenotypic differences between two animal cohorts were also observed. Based on spectral peak identification, hepatic lipid
extracts from treated animals exhibited redistribution of unsaturated fatty acids, cholesterols, and triacylglycerols. This
method identified significant changes in peaks without the loss of information associated with spectral binning, increasing
the likelihood of identifying treatment-elicited metabolite changes.
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ABSTRACT: The integration of different 'omics' technologies has already been shown in several in vivo studies to offer a complementary insight into cellular responses to toxic challenges. Being interested in developing in vitro cellular models as alternative to animal-based toxicity assays, we hypothesize that combining transcriptomics and metabonomics data improves the understanding of molecular mechanisms underlying the effects caused by a toxic compound also in vitro in human cells. To test this hypothesis, and with the focus on non-genotoxic carcinogenesis as an endpoint of toxicity, in the present study, the human hepatocarcinoma cell line HepG2 was exposed to the well-known environmental carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Transcriptomics as well as metabonomics analyses demonstrated changes in TCDD-exposed HepG2 in common metabolic processes, e.g. amino acid metabolism, of which some of the changes only being confirmed if both 'omics' were integrated. In particular, this integrated analysis identified unique pathway maps involved in receptor-mediated mechanisms, such as the G-protein coupled receptor protein (GPCR) signaling pathway maps, in which the significantly up-regulated gene son of sevenless 1 (SOS1) seems to play an important role. SOS1 is an activator of several members of the RAS superfamily, a group of small GTPases known for their role in carcinogenesis. The results presented here were not only comparable with other in vitro studies but also with in vivo studies. Moreover, new insights on the molecular responses caused by TCDD exposure were gained by the cross-omics analysis.BMC Systems Biology 08/2011; 5:139. · 2.98 Impact Factor
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ABSTRACT: Metabonomics has become a very valuable tool and many research fields rely on results coming out from this combination of analytical techniques, chemometric strategies, and biological interpretation. Moreover, the matrices are more and more complex and the implications of the results are often of major importance. In this context, the need for pertinent validation strategies comes naturally. The choice of the appropriate chemometric method remains nevertheless a difficult task due to particularities such as: the number of measured variables, the complexity of the matrix and the purposes of the study. Consequently, this paper presents a detailed metabonomic study on human urine with a special emphasis on the importance of assessing the data's quality. It also describes, step by step, the statistical tools currently used and offers a critical view on some of their limits. In this work, 29 urine samples among which 15 samples obtained from tetrahydrocannabinol (delta-9-tetrahydrocannabinol)-consuming athletes, 5 samples provided by volunteers, and 9 samples obtained from athletes were submitted to untargeted analysis by means of ultra high-pressure liquid chromatography-electrospray ionization-time-of-flight mass spectrometry. Next, the quality of the obtained data was assessed and the results were compared to those found in databases. Then, unsupervised (principal component analysis (PCA)) and supervised (ANOVA/PCA, partial least-square-discriminant analysis (PLS-DA), orthogonal PLS-DA) univariate and multivariate statistical methods were applied.Analytical and Bioanalytical Chemistry 07/2013; · 3.66 Impact Factor
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ABSTRACT: 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) elicits a broad spectrum of species-specific effects that have not yet been fully characterized. This study compares the temporal effects of TCDD on hepatic aqueous and lipid metabolite extracts from immature ovariectomized C57BL/6 mice and Sprague-Dawley rats using gas chromatography-mass spectrometry and nuclear magnetic resonance-based metabolomic approaches and integrates published gene expression data to identify species-specific pathways affected by treatment. TCDD elicited metabolite and gene expression changes associated with lipid metabolism and transport, choline metabolism, bile acid metabolism, glycolysis, and glycerophospholipid metabolism. Lipid metabolism is altered in mice resulting in increased hepatic triacylglycerol as well as mono- and polyunsaturated fatty acid (FA) levels. Mouse-specific changes included the induction of CD36 and other cell surface receptors as well as lipases- and FA-binding proteins consistent with hepatic triglyceride and FA accumulation. In contrast, there was minimal hepatic fat accumulation in rats and decreased CD36 expression. However, choline metabolism was altered in rats, as indicated by decreases in betaine and increases in phosphocholine with the concomitant induction of betaine-homocysteine methyltransferase and choline kinase gene expression. Results from these studies show that aryl hydrocarbon receptor-mediated differential gene expression could be linked to metabolite changes and species-specific alterations of biochemical pathways.Toxicological Sciences 09/2011; 125(1):41-55. · 4.33 Impact Factor