Grantee Research Project Results
2004 Progress Report: Mechanistic Evaluation of the Toxicity of Chemical Mixtures
EPA Grant Number: R829358Title: Mechanistic Evaluation of the Toxicity of Chemical Mixtures
Investigators: LeBlanc, Gerald A.
Institution: North Carolina State University
EPA Project Officer: Hahn, Intaek
Project Period: September 24, 2001 through September 23, 2006
Project Period Covered by this Report: September 24, 2003 through September 23, 2004
Project Amount: $465,281
RFA: Complex Chemical Mixtures (2000) RFA Text | Recipients Lists
Research Category: Environmental Justice , Hazardous Waste/Remediation , Land and Waste Management , Safer Chemicals
Objective:
Evaluating the toxicity of complex chemical mixtures is one of the major challenges facing modern toxicology. The virtually infinite number of chemical combinations that constitute environmentally relevant mixtures renders standard approaches for the toxicity characterization of chemicals irrelevant. The objective of this research project is to test the hypothesis that the toxicity of complex chemical mixtures can be satisfactorily estimated by understanding the mechanism of toxicity of the individual constituents and utilizing algorithms that define interactions based upon these mechanisms. These experiments are being performed with an invertebrate model, Daphnia magna, because both acute and life-cycle toxicity evaluations can be performed with this species with reasonable cost, space, and time consideration.
Progress Summary:
Aim 1: Define the Concentration-Response Curves for the Model Chemicals That Will be Used in the Mixtures Assessment
Status: 100% Complete . A test set of seven chemicals was devised that would allow for the evaluation of all four major categories of chemical interaction (concentration addition, independent joint action, antagonism, synergy). These chemicals and their proposed interactions, based upon known mechanisms of action, are described in Figure 1. Chemicals having the same mechanism of action (2- and 4-chlorophenol or malathion and parathion) were predicted to conform to a model of concentration addition and occupy the same mechanistic cassettes in the mixtures algorithm. The chlorophenols share a cassette for polar narcosis and the organophosphates share a cassette for cholinesterase inhibition. Piperonyl butoxide and pentachlorophenol occupy their own cassettes. The joint toxicity of all cassettes will be predicted using a model for independent joint action. Interactions (synergy and antagonism) were predicted as depicted in Figure 1 and have been confirmed experimentally. The chlorophenols were predicted to synergize with other cassettes because the membrane disruptive properties of these compounds would facilitate uptake of the other compounds. Piperonyl butoxide was predicted and confirmed to antagonize the toxicity of the organophosphates by inhibiting the metabolic activation of these compounds.
Concentration-response curves for these compounds and the modulating effects of the synergists/antagonists on the concentration-response relationships have been determined. Modulating effects were quantified by establishing coefficients of interaction (K values) that describe the degree to which a defined concentration of modulator shifts the concentration-response curve of the targeted chemical.
Figure 1. Chemicals Selected for the Test Mixture That Would Allow for Evaluation of Concentration Addition, Independent Joint Action, Synergy, and Antagonism. Sites of proposed interactions are depicted in this figure.
Aim 2: Develop and Experimentally Validate Algorithms That Define the Acute Toxicity of Binary Combinations of the Chemicals
Status: 90% Complete . Algorithms that define combined toxicity of chemicals within a cassette (concentration addition) and among cassettes (independent joint action) have been developed and binary combinations have been experimentally validated. K values (as described above) currently are being used to describe the modulating effect of one chemical upon another. These expanded models currently are undergoing experimental validation.
Extensive experimentation was performed in an effort to expand our understanding of the mechanisms by which chemicals interact resulting in synergistic interactions. Evaluation of our data and the literature has led us to surmise that synergy can be subcatagorized as either concentration synergy, response synergy, or cooperative synergy. Concentration synergy occurs when one chemical (synergist) increases the concentration of the active toxicant at the site of toxicity. Response synergy occurs when one chemical (synergist) decreases the ability of the organism to cope with the toxicity elicited by the active toxicant. Cooperative synergy occurs when one chemical (synergist) elicits a toxicological response that complements the response elicited by the active toxicant. Identification of different classes of synergy is critical to the full development of the model because different classes of synergy may require distinct modeling approaches.
We initially hypothesized that the chlorophenols in the selected chemical mixture would synergize with the other mixture constituents by modifying the membrane integrity of cells, resulting in increased uptake of the other chemicals by the organisms (as described under aim 1). This synergy would be classified as concentration synergy. Extensive experimentation during Year 3 of the project, however, has revealed that the accumulation of malathion by daphnids is not altered by coexposure to chlorophenols. Therefore, we rejected the hypothesis that the chlorophenols exhibit concentration synergy. Experiments currently are underway to determine whether the chlorophenols exhibit either response or cooperative synergy.
Aim 3: Predict the Acute Toxicity of Complex Chemical Mixtures Using the Developed Algorithms in Combination
Status: 0% Complete . This aim will be completed once the mechanism of synergy by the chlorophenols is established and appropriately described in the model (aim 2).
Aim 4: Expand the Modeling Approach To Predict the Toxicity of Environmentally Relevant Chemical Mixtures Resulting From Chronic Exposure
Status: 100% Complete . A study was completed in which nine chemicals were chosen from a recent report on surface water concentrations of a variety of xenobiotics to test the hypothesis that the toxicity of the chemical mixture could be estimated using the modeling approach developed under the previous aims. Concentration-response curves for the endpoints of lifespan reduction, growth rate reduction, and fecundity reduction were experimentally generated for each chemical using Daphnia magna. These data were used in our mathematical model to predict toxicity of the mixture at various levels at which the ratio of the chemicals within the mixture was maintained at the same ratio reported for median detectable environmental levels. Toxicity of the mixture at various levels then was determined experimentally and compared to the model predictions. The model accurately predicted the most sensitive endpoint as well as the lowest toxic effect levels of the mixture. Results demonstrated that for this mixture of chemicals, toxicity was not significantly influenced by interactions among the chemicals and toxicity was dominated by a single constituent. According to model predictions, the median detectable environmental concentration of chemicals constituting this mixture provide no margin of safety. Furthermore, this study demonstrated the utility of the mathematical model for use in assessing the chronic toxicity of chemical mixtures.
Future Activities:
Aim 2 and 3 : We will continue experiments to establish the mechanism by which chlorophenols synergize with other mixture constituents. Once mechanistically characterized, this interaction will be built into the model and toxicity of various combinations of the test chemical set will be modeled and compared to experimentally determined toxicity.
Aim 4: We will continue to further establish the value of the heuristic model in evaluating the chronic toxicity of chemical mixtures. Mixtures will be evaluated over the next year, which will allow for the modeling of sublethal toxicity (i.e., reproductive impairment, growth reduction). Chemical mixtures also will be selected in which synergistic interactions likely are to occur.
Journal Articles on this Report : 3 Displayed | Download in RIS Format
Other project views: | All 29 publications | 21 publications in selected types | All 17 journal articles |
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Mu XY, LeBlanc GA. Synergistic interaction of endocrine-disrupting chemicals: model development using an ecdysone receptor antagonist and a hormone synthesis inhibitor. Environmental Toxicology and Chemistry 2004;23(4):1085-1091. |
R829358 (2003) R829358 (2004) R829358 (Final) R826129 (Final) |
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Mu XY, LeBlanc GA. Cross communication between signaling pathways: juvenoid hormones modulate ecdysteroid activity in a crustacean. Journal of Experimental Zoology Part A–Comparative Experimental Biology 2004;301A(10):793-801. |
R829358 (2004) R829358 (Final) R826129 (Final) R831300 (2004) |
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Mu XY, Rider CV, Hwang GS, Hoy H, LeBlanc GA. Covert signal disruption: anti-ecdysteroidal activity of bisphenol A involves cross talk between signaling pathways. Environmental Toxicology and Chemistry 2005;24(1):146-152. |
R829358 (2004) R829358 (Final) R831300 (2004) R831300 (Final) R832739 (2008) |
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Supplemental Keywords:
hazard assessment, narcotics, computational toxicology, toxicity, complex chemical mixtures, chemicals, chlorophenols, organophosphates, cassettes, compounds, analytical models, biodegradation, contaminated sediments, hazardous organic substances,, RFA, Scientific Discipline, Waste, Ecosystem Protection/Environmental Exposure & Risk, Environmental Chemistry, chemical mixtures, Fate & Transport, Hazardous Waste, Ecology and Ecosystems, Hazardous, complex mixtures, contaminated sediments, fate and transport, fate and transport , biodegradation, hazardous organic substances, toxicity testing, environmental transport and fate, chemical kinetics, hazardous chemicals, complex toxic chemical mixtures, mechanisitic research, analytical modelsRelevant Websites:
http://www.tox.ncsu.edu/faculty/leblanc/ Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.