Physiological Modes of Action across Species and Toxicants: The Key to Predictive Ecotoxicology
Ashauer R & Jager T (2018): Physiological Modes of Action across Species and Toxicants: The Key to Predictive Ecotoxicology. Environmental Sciences: Processes & Impacts. (link to paper, open access)
As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.
Toxicology across scales: Cell population growth in vitro predicts reduced fish growth
Environmental risk assessment of chemicals is essential but often relies on ethically controversial and expensive methods. We show that tests using cell cultures, combined with modeling of toxicological effects, can replace tests with juvenile fish. Hundreds of thousands of fish at this developmental stage are annually used to assess the influence of chemicals on growth. Juveniles are more sensitive than adult fish, and their growth can affect their chances to survive and reproduce. Thus, to reduce the number of fish used for such tests, we propose a method that can quantitatively predict chemical impact on fish growth based on in vitro data. Our model predicts reduced fish growth in two fish species in excellent agreement with measured in vivo data of two pesticides. This promising step toward alternatives to fish toxicity testing is simple, inexpensive, and fast and only requires in vitro data for model calibration. (Published in Science Advances, open access)
Clustering of toxicodynamic parameters
We found that toxicodynamic parameters cluster according to chemical class. Clustering of toxicodynamic parameters according to chemical MOA is more pronounced for GUTS-IT (panels C, D) than for GUTS-SD (panels A, B). (A) Parameters z and kr in GUTS-SD, (B) Parameters kr and z in GUTS-SD, (C) Parameters α and β in GUTS-IT, (D) Parameters kr and α in GUTS-IT. Green squares: baseline toxicity, blue hexagons: uncoupling of oxidative phosphorylation, orange triangles: AChE inhibition (carbamate), red circles: AChE inhibition (organophosphates), purple diamonds: reactive toxicity.
This suggests toxicodynamic parameters as novel phenotypic anchors for in vitro to in vivo toxicity extrapolation. Toxicity extrapolation from in vitro to in vivo systems should aim at predicting TK-TD model parameters on the organism level as they have a biological interpretation and appear to reflect the biochemical mechanisms of toxicity. (read more: Environmental Science & Technology, open access)