Prediction and assessment of xenoestrogens mixture effects using the in vitro ERα-CALUX assay

Introduction: Many natural or synthetic compounds used in foods, dietary supplements, and food contact materials (FCMs) are suspected endocrine disruptors (EDs). Currently, scientific evidence to predict the impacts on biological systems of ED mixtures is lacking. In this study, three classes of substances were considered: i) phytoestrogens, ii) plant protection products (PPP) and iii) substances related to FCMs. Fourteen compounds were selected based on their potential endocrine activity and their presence in food and FCMs. Methods: These compounds were evaluated using an in vitro gene expression assay, the ERα-CALUX, to characterize their responses on the estrogen receptor alpha. Cells were exposed to fixed ratio mixtures and non-equipotent mixtures of full and partial agonists. The concentration-response curves measured for the three classes of compounds were characterized by variable geometric parameters in terms of maximum response (efficacy), sensitivity (slope) and potency (median effective concentration EC50). To account for these variations, a generic response addition (GRA) model was derived from mass action kinetics. Results: Although GRA does not allow us to clearly separate the concentration addition (CA) and independent action (IA) models, it was possible to determine in a statistically robust way whether the combined action of the chemicals in the mixture acted by interaction (synergy and antagonism) or by additive behavior. This distinction is crucial for assessing the risks associated with exposure to xenoestrogens. A benchmark dose approach was used to compare the response of phytoestrogen blends in the presence and absence of the hormone estradiol (E2). At the same time, 12 mixtures of 2-5 constituents including phytoestrogens, phthalates and PPPs in proportions close to those found in food products were tested. In 95% of cases, the response pattern observed showed a joint and independent effect of the chemicals on ER. Discussion: Overall, these results validate a risk assessment approach based on an additive effects model modulated by intrinsic toxicity factors. Here, the CA and IA approaches cannot be distinguished solely based on the shape of the concentration response curves. However, the optimized GRA model is more robust than CA when the efficacy, potency, and sensitivity of individual chemical agonists show large variations.

Cumulative Risk Meets Inter-Individual Variability: Probabilistic Concentration Addition of Complex Mixture Exposures in a Population-Based Human In Vitro Model

Although humans are continuously exposed to complex chemical mixtures in the environment, it has been extremely challenging to investigate the resulting cumulative risks and impacts. Recent studies proposed the use of “new approach methods,” in particular in vitro assays, for hazard and dose−response evaluation of mixtures. We previously found, using five human cell-based assays, that concentration addition (CA), the usual default approach to calculate cumulative risk, is mostly accurate to within an order of magnitude. Here, we extend these findings to further investigate how cell-based data can be used to quantify inter-individual variability in CA. Utilizing data from testing 42 Superfund priority chemicals separately and in 8 defined mixtures in a human cell-based population-wide in vitro model, we applied CA to predict effective concentrations for cytotoxicity for each individual, for “typical” (median) and “sensitive” (first percentile) members of the population, and for the median-to-sensitive individual ratio (defined as the toxicodynamic variability factor, TDVF). We quantified the accuracy of CA with the Loewe Additivity Index (LAI). We found that LAI varies more between different mixtures than between different individuals, and that predictions of the population median are generally more accurate than predictions for the “sensitive” individual or the TDVF. Moreover, LAI values were generally <1, indicating that the mixtures were more potent than predicted by CA. Together with our previous studies, we posit that new approach methods data from human cell-based in vitro assays, including multiple phenotypes in diverse cell types and studies in a population-wide model, can fill critical data gaps in cumulative risk assessment, but more sophisticated models of in vitro mixture additivity and bioavailability may be needed. In the meantime, because simple CA models may underestimate potency by an order of magnitude or more, either whole-mixture testing in vitro or, alternatively, more stringent benchmarks of cumulative risk indices (e.g., lower hazard index) may be needed to ensure public health protection.

Mixture Math: Deciding What to Add in a Cumulative Risk Assessment

Component-based approaches for cumulative risk assessment provide an important tool for informing public health policy. While current quantitative cumulative risk assessments focus narrowly on pesticides that share a mechanism of action, growing scientific evidence supports expansion of their application to encompass stressors that target a common disease. Case studies have demonstrated dose additive effects of chemicals with different mechanisms of action on liver steatosis, craniofacial malformations, and male reproductive tract developmental disruption. Evidence also suggests that nonchemical stressors such as noise or psychosocial stress can modify effects of chemicals. Focused research attention is required before nonchemical stressors can routinely be included in quantitative cumulative risk assessments.

It More than Adds Up: Interaction of Antibiotic Mixing and Temperature

Use of antibiotics for the treatment and prevention of bacterial infections in humans, agri- and aquaculture as well as livestock rearing leads to antibiotic pollution of fresh water and these antibiotics have an impact on free-living bacteria. While we know which antibiotics are most common in natural environments such as rivers and streams, there is considerable uncertainty regarding antibiotics’ interactions with one another and the effect of abiotic factors such as temperature. Here, we used an experimental approach to explore the effects of antibiotic identity, concentration, mixing and water temperature on the growth of Pseudomonas fluorescens, a common, ubiquitous bacterium. We exposed P. fluorescens to the four antibiotics most commonly found in surface waters (ciprofloxacin, ofloxacin, sulfamethoxazole and sulfapyridine) and investigated antibiotic interactions for single and mixed treatments at different, field-realistic temperatures. We observed an overall dependence of antibiotic potency on temperature, as temperature increased efficacy of ciprofloxacin and ofloxacin with their EC₅₀ lowered by >75% with a 10 °C temperature increase. Further, we show that mixtures of ciprofloxacin and ofloxacin, despite both belonging to the fluoroquinolone class, exhibit low-temperature-dependent synergistic effects in inhibiting bacterial growth. These findings highlight the context dependency of antibiotic efficacy. They further suggest antibiotic-specific off-target effects that only affect the bacteria once they enter a certain temperature range. This has important implications as freshwater systems already contain multi-drug antibiotic cocktails and are changing temperature due to environmental warming. These factors will interact and affect aquatic food webs, and hence this creates an urgent need to adapt and improve laboratory testing conditions to closer reflect natural environments.

Risk Assessment of Pesticide Mixtures in Australian Rivers Discharging to the Great Barrier Reef

Rivers discharging to the Great Barrier Reef carry complex pesticide mixtures. Here we present a first comprehensive ecotoxicological risk assessment using species sensitivity distributions (SSDs), explore how risk changes with time and land use, and identify the drivers of mixture risks. The analyzed data set comprises 50 different pesticides and pesticide metabolites that were analyzed in 3741 samples from 18 river and creek catchments between 2011 and 2016. Pesticide mixtures were present in 82% of the samples, with a maximum of 23 pesticides and a median of five compounds per sample. Chemical-analytical techniques were insufficiently sensitive for at least seven pesticides (metsulfuron-methyl, terbutryn, imidacloprid, clothianidin, ametryn, prometryn, and thiamethoxam). The classical mixture concepts of concentration addition and independent action were applied to the pesticide SSDs, focusing on environmental threshold values protective for 95% of the species. Both concepts produced almost identical risk estimates. Mixture risk was therefore finally assessed using concentration addition, as the sum of the individual risk quotients. The sum of risk quotients ranges between 0.05 and 122 with a median of 0.66. An ecotoxicological risk (i.e., a sum of individual risk quotients exceeding 1) was indicated in 38.5% of the samples. Sixteen compounds accounted for 99% of the risk, with diuron, imidacloprid, atrazine, metolachlor, and hexazinone being the most important risk drivers. Analysis of land-use patterns in catchment areas showed an association between sugar cane farming and elevated risk levels, driven by the presence of diuron.

Quantitative prediction of mixture toxicity of AgNO3 and ZnO nanoparticles on Daphnia magna

Once metal-based engineered nanoparticles (NPs) are released into the aquatic environment, they are expected to interact with other existing co-contaminants. A knowledge gap exists as to how the interaction of NPs with other co-contaminants occurs. Here we selected ZnO NPs among various NPs, with Ag ion existing as a contaminant in the aquatic environment by Ag NPs widely used. A novel modeling strategy was demonstrated enabling quantitative and predictive evaluation of the aqueous mixture nanotoxicity. Individual and binary mixture toxicity tests of ZnO NPs and silver (as AgNO3) on Daphnia magna were conducted and compared to determine whether the presence of Ag ions affects the toxicity of ZnO NPs. Binary mixture toxicity was evaluated based on the concentration addition (CA) and independent action models. The CA dose-ratio dependent model was found to be the model of best fit for describing the pattern of mixture toxicity. The MIX I and MIX III suspensions (higher ratios of ZnO NPs to AgNO3) showed a synergism, whereas the MIX II suspension (lower ratio of ZnO NPs to AgNO3) showed an antagonism. The synergistic mixture toxicity at higher ratios of ZnO NPs to AgNO3 was caused by either the physiological or metabolic disturbance induced by the excessive ionic Zn or increased transport and accumulation in D. magna via the formation of complex of ionic Ag with ZnO NPs. Therefore, the toxicity level contributed via their aggregation and physicochemical properties and the dissolved ions played a crucial role in the mixture toxicities of the NPs.

Novel Segmented Concentration Addition Method to Predict Mixture Hormesis of Chlortetracycline Hydrochloride and Oxytetracycline Hydrochloride to Aliivibrio fischeri

Hormesis is a concentration-response phenomenon characterized by low-concentration stimulation and high-concentration inhibition, which typically has a nonmonotonic J-shaped concentration-response curve (J-CRC). The concentration addition (CA) model is the gold standard for studying mixture toxicity. However, the CA model had the predictive blind zone (PBZ) for mixture J-CRC. To solve the PBZ problem, we proposed a segmented concentration addition (SCA) method to predict mixture J-CRC, which was achieved through fitting the left and right segments of component J-CRC and performing CA prediction subsequently. We selected two model compounds including chlortetracycline hydrochloride (CTCC) and oxytetracycline hydrochloride (OTCC), both of which presented J-CRC to Aliivibrio fischeri (AVF). The seven binary mixtures (M1-M7) of CTCC and OTCC were designed according to their molar ratios of 12:1, 10:3, 8:5, 1:1, 5:8, 3:10, and 1:12 referring to the direct equipartition ray design. These seven mixtures all presented J-CRC to AVF. Based on the SCA method, we obtained mixture maximum stimulatory effect concentration (ECm) and maximum stimulatory effect (Em) predicted by SCA, both of which were not available for the CA model. The toxicity interactions of these mixtures were systematically evaluated by using a comprehensive approach, including the co-toxicity coefficient integrated with confidence interval method (CTCICI), CRC, and isobole analysis. The results showed that the interaction types were additive and antagonistic action, without synergistic action. In addition, we proposed the cross point (CP) hypothesis for toxic interactive mixtures presenting J-CRC, that there was generally a CP between mixture observed J-CRC and CA predicted J-CRC; the relative positions of observed and predicted CRCs on either side of the CP would exchange, but the toxic interaction type of mixtures remained unchanged. The CP hypothesis needs to be verified by more mixtures, especially those with synergism. In conclusion, the SCA method is expected to have important theoretical and practical significance for mixture hormesis.

New Insight Regarding the Relationship Between Enantioselective Toxicity Difference and Enantiomeric Toxicity Interaction from Chiral Ionic Liquids

Chirality is an important property of molecules. The study of biological activity and toxicity of chiral molecules has important theoretical and practical significance for toxicology, pharmacology, and environmental science. The toxicological significance of chiral ionic liquids (ILs) has not been well revealed. In the present study, the enantiomeric joint toxicities of four pairs of chiral ILs 1-alkyl-3-methylimidazolium lactate to Allivibrio fischeri were systematically investigated by using a comprehensive approach including the co-toxicity coefficient (CTC) integrated with confidence interval (CI) method (CTCICI), concentration-response curve (CRC), and isobole analysis. The direct equipartition ray (EquRay) design was used to design five binary mixtures of enantiomers according to molar ratios of 1:5, 2:4, 3:3, 4:2, and 5:1. The toxicities of chiral ILs and their mixtures were determined using the microplate toxicity analysis (MTA) method. Concentration addition (CA) and independent action (IA) were used as the additive reference models to construct the predicted CRC and isobole of mixtures. On the whole, there was an enantioselective toxicity difference between [BMIM]D-Lac and [BMIM]L-Lac, and [HMIM]D-Lac and [HMIM]L-Lac, while no enantioselective toxicity difference was observed for [EMIM]D-Lac and [EMIM]L-Lac, and [OMIM]D-Lac and [OMIM]L-Lac. Thereinto, the enantiomer mixtures of [BMIM]D-Lac and [BMIM]L-Lac, and [HMIM]D-Lac and [HMIM]L-Lac presented antagonistic action, and the enantiomer mixtures of [EMIM]D-Lac and [EMIM]L-Lac, and [OMIM]D-Lac and [OMIM]L-Lac overall presented additive action. Moreover, the greatest antagonistic toxicity interaction occurred at the equimolar ratio of enantiomers. Based on these results, we proposed two hypotheses, (1) chiral molecules with enantioselective toxicity difference tended to produce toxicity interactions, (2) the highest or lowest toxicity was usually at the equimolar ratio and its adjacent ratio for the enantiomer mixture. These hypotheses will need to be further validated by other enantiomer mixtures.

Integrative Assessment of Mixture Toxicity of Three Ionic Liquids on Acetylcholinesterase Using a Progressive Approach from 1D Point, 2D Curve, to 3D Surface

The joint toxicities of [BMIM]BF₄, [BMIM]PF₆, and [HMIM]BF₄ on acetylcholinesterase (AChE) were systematically investigated by using a progressive approach from 1D single effect point, 2D concentration-response curve (CRC), to 3D equivalent-surface (ES) level. The equipartition equivalent-surface design (EESD) method was used to design 10 ternary mixtures, and the direct equipartition ray (EquRay) design was used to design 15 binary mixtures. The toxicities of ionic liquids (ILs) and their mixtures were determined using the microplate toxicity analysis (MTA) method. The concentration addition (CA), independent action (IA), and co-toxicity coefficient (CTC) were used as the additive reference model to analyze the toxic interaction of these mixtures. The results showed that the Weibull function fitted well the CRCs of the three ILs and their mixtures with the coefficient of determination (R²) greater than 0.99 and root-mean-square error (RMSE) less than 0.04. According to the CTC integrated with confidence interval (CI) method (CTCICI) developed in this study, the 25 mixtures were almost all additive action at 20% and 80% effect point levels. At 50% effect, at least half of the 25 mixtures were slightly synergistic action, and the remaining mixtures were additive action. Furthermore, the ESs and CRCs predicted by CA and IA were all within the CIs of mixture observed ESs and CRCs, respectively. Therefore, the toxic interactions of these 25 mixtures were actually additive action. The joint toxicity of the three ILs can be effectively evaluated by the ES method. We also studied the relationship between the mixture toxicities and component concentration proportions. This study can provide reference data for IL risk assessment of combined pollution.

Assessing the Potential for Interaction in Insecticidal Activity Between MON 87751 × MON 87701 Produced by Conventional Breeding

Pyramiding (combining) of plant incorporated protectants (PIPs) with insecticidal activity in genetically engineered crops is a strategy used to improve efficacy as well as delay potential resistance for a specific group of targets. In some countries, a regulatory risk assessment is required for breeding "stacks" expressing multiple PIPs and these countries may require an assessment of potential interaction among the PIPs. This study evaluated whether combining soybean events MON 87551 and MON 87701 results in a toxicological interaction that effects a species that is controlled by each event. MON 87751 coexpresses the Cry1A.105 and Cry2Ab2 proteins and MON 87701 expresses the Cry1Ac protein. EC50 values for MON 87751 and MON 87701 were comparable in diet-incorporation bioassays using corn earworm (Lepidoptera: Noctuidae, Helicoverpa zea) and the observed combined activity of the stack was consistent with predictions of additivity (i.e., no interaction). Under the concentration and response addition models, predicted and observed median effect levels differed by <10%. These results demonstrate independent action at the median effect level between the insecticidal activity of MON 87751 and MON 87701. Taken together, no interaction between these PIPs and acceptable margins of safety for the individual proteins to nontarget organisms, it is appropriate to bridge back to the risk assessments for the individual products that demonstrated environmental safety of stack products containing both MON 87751 and MON 87701.

Investigation of the Synergistic Toxicity of Binary Mixtures of Pesticides and Pharmaceuticals on Aliivibrio fischeri in Major River Basins in South Korea

This work introduces the potential synergistic toxicity of binary mixtures of pesticides and pharmaceuticals, which have been detected in substantial amounts in major river basins in South Korea. Different dose-response curve functions were employed in each experimental toxicity dataset for Aliivibrio fischeri. We tested the toxicity of 30 binary mixtures at two effect concentrations: high effect concentration [EC₅₀] and low effect concentration (EC₁₀) ranges. Thus, the toxicological interactions were evaluated at 60 effected concentration data points in total and based on model deviation ratios (MDRs) between predicted and observed toxicity values (e.g., three types of combined effects: synergistic (MDR > 2), additive (0.5 ≤ MDR ≤ 2), and antagonistic (MDR < 0.5)). From the 60 data points, MDRs could not be applied to 17 points, since their toxicities could not be measured. The result showed 48%-additive (n = 20), 40%-antagonistic (n = 17), and 12%-synergistic (n = 6) toxicity effects from 43 binaries (excluding the 17 combinations without MDRs). In this study, EC₁₀ ratio mixtures at a low overall effect range showed a general tendency to have more synergistic effects than the EC₅₀ ratio mixtures at a high effect range. We also found an inversion phenomenon, which detected three binaries of the combination of synergism at low concentrations and additive antagonism at high concentrations.

Medicines, shaken and stirred: a critical review on the ecotoxicology of pharmaceutical mixtures

Analytical monitoring surveys routinely confirm that organisms in the environment are exposed to complex multi-component pharmaceutical mixtures. We are hence tasked with the challenge to take this into consideration when investigating the ecotoxicology of pharmaceuticals. This review first provides a brief overview of the fundamental approaches for mixture toxicity assessment, which is then followed by a critical review on the empirical evidence that is currently at hand on the ecotoxicology of pharmaceutical mixtures. It is concluded that, while the classical concepts of concentration addition and independent action (response addition) provide a robust scientific footing, several knowledge gaps remain. This includes, in particular, the need for more and better empirical data on the effects of pharmaceutical mixtures on soil organisms as well as marine flora and fauna, and exploring the quantitative consequences of toxicokinetic, toxicodynamic and ecological interactions. Increased focus should be put on investigating the ecotoxicology of pharmaceutical mixtures in environmentally realistic settings.

A concentration addition model to assess activation of the pregnane X receptor (PXR) by pesticide mixtures found in the French diet

French consumers are exposed to mixtures of pesticide residues in part through food consumption. As a xenosensor, the pregnane X receptor (hPXR) is activated by numerous pesticides, the combined effect of which is currently unknown. We examined the activation of hPXR by seven pesticide mixtures most likely found in the French diet and their individual components. The mixture's effect was estimated using the concentration addition (CA) model. PXR transactivation was measured by monitoring luciferase activity in hPXR/HepG2 cells and CYP3A4 expression in human hepatocytes. The three mixtures with the highest potency were evaluated using the CA model, at equimolar concentrations and at their relative proportion in the diet. The seven mixtures significantly activated hPXR and induced the expression of CYP3A4 in human hepatocytes. Of the 14 pesticides which constitute the three most active mixtures, four were found to be strong hPXR agonists, four medium, and six weak. Depending on the mixture and pesticide proportions, additive, greater than additive or less than additive effects between compounds were demonstrated. Predictions of the combined effects were obtained with both real-life and equimolar proportions at low concentrations. Pesticides act mostly additively to activate hPXR, when present in a mixture. Modulation of hPXR activation and its target genes induction may represent a risk factor contributing to exacerbate the physiological response of the hPXR signaling pathways and to explain some adverse effects in humans.

Currently used pesticides and their mixtures affect the function of sex hormone receptors and aromatase enzyme activity

The endocrine-disrupting potential of pesticides is of health concern, since they are found ubiquitously in the environment and in food items. We investigated in vitro effects on estrogen receptor (ER) and androgen receptor (AR) transactivity, and aromatase enzyme activity, of the following pesticides: 2-methyl-4-chlorophenoxyacetic acid (MCPA), terbuthylazine, iodosulfuron-methyl-sodium, mesosulfuron-methyl, metsulfuron-methyl, chlormequat chloride, bitertanol, propiconazole, prothioconazole, mancozeb, cypermethrin, tau fluvalinate, malathion and the metabolite ethylene thiourea (ETU). The pesticides were analyzed alone and in selected mixtures. Effects of the pesticides on ER and AR function were assessed in human breast carcinoma MVLN cells and hamster ovary CHO-K1 cells, respectively, using luciferase reporter gene assays. Effects on aromatase enzyme activity were analyzed in human choriocarcinoma JEG-3 cells, employing the classical [(3)H](2)O method. Five pesticides (terbuthylazine, propiconazole, prothioconazole, cypermethrin and malathion) weakly induced the ER transactivity, and three pesticides (bitertanol, propiconazole and mancozeb) antagonized the AR activity in a concentration-dependent manner. Three pesticides (terbuthylazine, propiconazole and prothioconazole) weakly induced the aromatase activity. In addition, two mixtures, consisting of three pesticides (bitertanol, propiconazole, cypermethrin) and five pesticides (terbuthylazine, bitertanol, propiconazole, cypermethrin, malathion), respectively, induced the ER transactivity and aromatase activity, and additively antagonized the AR transactivity. In conclusion, our data suggest that currently used pesticides possess endocrine-disrupting potential in vitro which can be mediated via ER, AR and aromatase activities. The observed mixture effects emphasize the importance of considering the combined action of pesticides in order to assure proper estimations of related health effect risks.

Contrasting theories of interaction in epidemiology and toxicology

BACKGROUND

Epidemiologists and toxicologists face similar problems when assessing interactions between exposures, yet they approach the question very differently. The epidemiologic definition of "interaction" leads to the additivity of risk differences (RDA) as the fundamental criterion for causal inference about biological interactions. Toxicologists define "interaction" as departure from a model based on mode of action: concentration addition (CA; for similarly acting compounds) or independent action (IA; for compounds that act differently).

OBJECTIVES

We compared and contrasted theoretical frameworks for interaction in the two fields.

METHODS

The same simple thought experiment has been used in both both epidemiology and toxicology to develop the definition of "noninteraction," with nearly opposite interpretations. In epidemiology, the "sham combination" leads to a requirement that noninteractive dose-response curves be linear, whereas in toxicology, it results in the model of CA. We applied epidemiologic tools to mathematical models of concentration-additive combinations to evaluate their utility.

RESULTS

RDA is equivalent to CA only for linear dose-response curves. Simple models demonstrate that concentration-additive combinations can result in strong synergy or antagonism in the epidemiologic framework at even the lowest exposure levels. For combinations acting through nonsimilar pathways, RDA approximates IA at low effect levels.

CONCLUSIONS

Epidemiologists have argued for a single logically consistent definition of interaction, but the toxicologic perspective would consider this approach less biologically informative than a comparison with CA or IA. We suggest methods for analysis of concentration-additive epidemiologic data. The two fields can learn a great deal about interaction from each other.

Competitive androgen receptor antagonism as a factor determining the predictability of cumulative antiandrogenic effects of widely used pesticides

BACKGROUND

Many pesticides in current use have recently been revealed as in vitro androgen receptor (AR) antagonists, but information about their combined effects is lacking.

OBJECTIVE

We investigated the combined effects and the competitive AR antagonism of pesticide mixtures.

METHODS

We used the MDA-kb2 assay to test a combination of eight AR antagonists that did not also possess AR agonist properties ("pure" antagonists; 8 mix: fludioxonil, fenhexamid, ortho-phenylphenol, imazalil, tebuconazole, dimethomorph, methiocarb, pirimiphos-methyl), a combination of five AR antagonists that also showed agonist activity (5 mix: cyprodinil, pyrimethanil, vinclozolin, chlorpropham, linuron), and all pesticides combined (13 mix). We used concentration addition (CA) and independent action (IA) to formulate additivity expectations, and Schild plot analyses to investigate competitive AR antagonism.

RESULTS

A good agreement between the effects of the mixture of eight "pure" AR antagonists and the responses predicted by CA was observed. Schild plot analysis revealed that the 8 mix acted by competitive AR antagonism. However, the observed responses of the 5 mix and the 13 mix fell within the "prediction window" boundaries defined by the predicted regression curves of CA and IA. Schild plot analysis with these mixtures yielded anomalous responses incompatible with competitive receptor antagonism.

CONCLUSIONS

A mixture of widely used pesticides can, in a predictable manner, produce combined AR antagonist effects that exceed the responses elicited by the most potent component alone. Inasmuch as large populations are regularly exposed to mixtures of antiandrogenic pesticides, our results underline the need for considering combination effects for these substances in regulatory practice.

Generalized concentration addition predicts joint effects of aryl hydrocarbon receptor agonists with partial agonists and competitive antagonists

BACKGROUND

Predicting the expected outcome of a combination exposure is critical to risk -assessment. The toxic equivalency factor (TEF) approach used for analyzing joint effects of dioxin-like chemicals is a special case of the method of concentration addition. However, the TEF method assumes that individual agents are full aryl hydrocarbon receptor (AhR) agonists with parallel dose-response curves, whereas many mixtures include partial agonists.

OBJECTIVES

We assessed the ability of generalized concentration addition (GCA) to predict effects of combinations of full AhR agonists with partial agonists or competitive antagonists.

METHODS

We measured activation of AhR-dependent gene expression in H1G1.1c3 cells after application of binary combinations of AhR ligands. A full agonist (2,3,7,8-tetrachlorodibenzo-p--dioxin or 2,3,7,8-tetrachlorodibenzofuran) was combined with either a full agonist (3,3 ,4,4 ,5-penta-chloro-biphenyl), a partial agonist (2,3,3 ,4,4 -pentachlorobiphenyl or galangin), or an antagonist (3,3 -diindolylmethane). Combination effects were modeled by the TEF and GCA approaches, and goodness of fit of the modeled response surface to the experimental data was assessed using a nonparametric statistical test.

RESULTS

The GCA and TEF models fit the experimental data equally well for a mixture of two full agonists. In all other cases, GCA fit the experimental data significantly better than the TEF model.

CONCLUSIONS

The TEF model overpredicts effects of AhR ligands at the highest concentration combinations. At lower concentrations, the difference between GCA and TEF approaches depends on the efficacy of the partial agonist. GCA represents a more accurate definition of additivity for mixtures that include partial agonist or competitive antagonist ligands.

Mixtures of estrogenic chemicals enhance vitellogenic response in sea bass

BACKGROUND

The potential impact of natural and synthetic estrogens on aquatic ecosystems has attracted considerable attention because it is currently accepted that their joint effects are more severe when they are present in mixtures. Although it is well-known that they occur as mixtures in the marine environment, there is little information about the combined effects of estrogenic chemicals on marine biota.

OBJECTIVE

In 14-day tests with juvenile sea bass, we analyzed singly and in combination the estrogenic activity of estradiol (E(2)), ethynylestradiol (EE(2)), and bisphenol A (BPA) using vitellogenin induction as an end point.

METHODS

Fish were exposed to each compound, and on the basis of these concentration-response data, we predicted mixture effects by applying the model of concentration addition. The mixtures were tested using a fixed-ratio design, and the resulting mixture effects were compared to the predictions.

RESULTS

EE(2) was the most potent steroid, with an EC(50) (median effective concentration) of 0.029 microg/L, 3.6 times more potent than E(2) (EC(50) = 0.104 microg/L); BPA was the least potent chemical, with an EC(50) of 77.94 microg/L. The comparative assessment yielded a good agreement between observed and predicted mixture effects.

CONCLUSIONS

This study demonstrates the potential hazard of these compounds to seawater life by their ability to act together in an additive manner. It provides evidence that concentration addition can be used as a predictive tool for assessing the combined effects of estrogenic chemicals in marine ecosystems.

An assessment of the model of concentration addition for predicting the estrogenic activity of chemical mixtures in wastewater treatment works effluents

The effects of simple mixtures of chemicals, with similar mechanisms of action, can be predicted using the concentration addition model (CA). The ability of this model to predict the estrogenic effects of more complex mixtures such as effluent discharges, however, has yet to be established. Effluents from 43 U.K. wastewater treatment works were analyzed for the presence of the principal estrogenic chemical contaminants, estradiol, estrone, ethinylestradiol, and nonylphenol. The measured concentrations were used to predict the estrogenic activity of each effluent, employing the model of CA, based on the relative potencies of the individual chemicals in an in vitro recombinant yeast estrogen screen (rYES) and a short-term (14-day) in vivo rainbow trout vitellogenin induction assay. Based on the measured concentrations of the four chemicals in the effluents and their relative potencies in each assay, the calculated in vitro and in vivo responses compared well and ranged between 3.5 and 87 ng/L of estradiol equivalents (E2 EQ) for the different effluents. In the rYES, however, the measured E2 EQ concentrations in the effluents ranged between 0.65 and 43 ng E2 EQ/L, and they varied against those predicted by the CA model. Deviations in the estimation of the estrogenic potency of the effluents by the CA model, compared with the measured responses in the rYES, are likely to have resulted from inaccuracies associated with the measurement of the chemicals in the extracts derived from the complex effluents. Such deviations could also result as a consequence of interactions between chemicals present in the extracts that disrupted the activation of the estrogen response elements in the rYES. E2 EQ concentrations derived from the vitellogenic response in fathead minnows exposed to a series of effluent dilutions were highly comparable with the E2 EQ concentrations derived from assessments of the estrogenic potency of these dilutions in the rYES. Together these data support the use of bioassays for determining the estrogenic potency of WwTW effluents, and they highlight the associated problems for modeling approaches that are reliant on measured concentrations of estrogenic chemicals.

Accurate prediction of the response of freshwater fish to a mixture of estrogenic chemicals

Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration-response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk.