Discriminating between Different Acute Chemical Toxicities via Changes in the Daphnid Metabolome

NS Taylor, Ralf Weber, Thomas White, Mark Viant

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)307-317
Number of pages11
JournalToxicological Sciences
Volume118
Issue number1
DOIs
Publication statusPublished - 1 Nov 2010

Keywords

  • predictive toxicology
  • PLS-DA
  • classification
  • ecotoxicogenomics
  • mechanism of action
  • water flea

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