Journal
MOLECULAR BIOSYSTEMS
Volume 8, Issue 4, Pages 1206-1221Publisher
ROYAL SOC CHEMISTRY
DOI: 10.1039/c1mb05366c
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Funding
- Natural Science Foundation of the State [90709019]
- National Key Program on the Subject of Drug Innovation [2009ZX09502-005]
- National Specific Program on the Subject of Public Welfare [200807014]
- National Program for Key Basic Research Projects in China [2005CB523406]
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Chuanwu (CW), a valuable traditional Chinese medicine (TCM), is the mother root of Aconitum carmichaelii Debx. The cause of CW-induced toxicity is still under ongoing research, although this is limited by the lack of sensitive and reliable biomarkers. Ingenuity pathway analysis (IPA) was performed to analyzing global metabolomics in order to characterize the phenotypically biochemical perturbations and potential mechanisms of the CW-induced toxicity. CW was administered to Wistar rats (0.027 g/200 g and 0.108 g/200 g bw, oral) for 6 months and urine samples were collected. The urinary metabolomics was performed by UPLC-Q-TOF-HDMS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition methods (PCA, PLS-DA, and OPLS-DA), revealing a time-and dose-dependency of the biochemical perturbations induced by CW toxicity. As a result, several metabolites responsible for pentose and glucuronate interconversions, alanine, aspartate and glutamate metabolism, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, purine metabolism, tryptophan metabolism, taurine and hypotaurine metabolism, fructose and mannose metabolism, fatty acid metabolism were characterized, and it was confirmed that biochemical perturbations can be foreseen from these biomarkers. The urinary metabolomics based IPA with pattern recognition methods also revealed that CW produced serious heart and liver toxicity, consistent with clinical biochemistry and histopathology. Significant changes of 17 metabolites were identified and validated as phenotypic biomarkers of CW toxicity. Overall, our work demonstrated the metabolomics has brought enormous opportunities for improved detection of toxicity and biomarker discovery, highlighting the powerful predictive potential of the IPA to study of drug toxicity.
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