Mixture toxicity and gene inductions: can we predict the outcome?
As a consequence of the nature of most real-life exposure scenarios, the last decade of ecotoxicological research has seen increasing interest in the assessment of mixture ecotoxicology. Often, mixtures are considered to follow one of two models, concentration addition (CA) or response addition (RA), both of which have been described in the literature. Nevertheless, mixtures that deviate from either or both models exist; they typically exhibit phenomena like synergism, ratio or concentration dependency, or inhibition. Moreover, both CA and RA have been challenged and evaluated mainly for acute responses at relatively high levels of biological organization (e.g., whole-organism mortality), and applicability to genetic responses has not received much attention. Genetic responses are considered to be the primary reaction in case of toxicant exposure and carry valuable mechanistic information. Effects at the gene-expression level are at the heart of the mode of action by toxicants and mixtures. The ability to predict mixture responses at this primary response level is an important asset in predicting and understanding mixture effects at different levels of biological organization. The present study evaluated the applicability of mixture models to stress gene inductions in Escherichia coli employing model toxicants with known modes of action in binary combinations. The results showed that even if the maximum of the dose-response curve is not known, making a classical ECx (concentration causing x% effect) approach impossible, mixture models can predict responses to the binary mixtures based on the single-toxicant response curves. In most cases, the mode of action of the toxicants does not determine the optimal choice of model (i.e., CA, RA, or a deviation thereof).
Dardenne
Freddy
F
Ecophysiology, Biochemisty, and Toxicology Group, Department of Biology, University of Antwerp, Antwerp, Belguim. gosia.freddy@scarlet.be
Nobels
Ingrid
I
De Coen
Wim
W
Blust
Ronny
R
D045424:Complex Mixtures / Q000633:toxicity; D004785:Environmental Pollutants / Q000633:toxicity*; D004926:Escherichia coli / Q000187:drug effects* / Q000235:genetics / Q000378:metabolism*; D020869:Gene Expression Profiling; D015964:Gene Expression Regulation, Bacterial / Q000187:drug effects*; D011401:Promoter Regions, Genetic
D045424:Complex Mixtures; D004785:Environmental Pollutants