Ecotoxicology (2014) 23:221–228 DOI 10.1007/s10646-013-1165-7
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity by binary mixtures of chlorpyrifos and four other insecticides Chen Chen • Yanhua Wang • Xueping Zhao Qiang Wang • Yongzhong Qian
•
Accepted: 12 December 2013 / Published online: 23 December 2013 Ó Springer Science+Business Media New York 2013
Abstract Mixtures of organophosphate (OP) and carbamate (CB) insecticides are commonly detected in freshwater habitats. These insecticides inhibit the activity of acetylcholinesterase (AChE) and have potential to interfere with behaviors that may be essential for survival of species. Although the effects of individual anticholinesterase insecticides on aquatic species have been studied for decades, the combined toxicity of mixtures is still poorly understood. In the present study, we assessed whether pesticides in a mixture act in isolation (resulting in additive AChE inhibition) or whether components interact to produce either antagonistic or synergistic toxicity. Brain AChE inhibition in carp (Cyprinus carpio L.) exposed to a series of concentrations of the OP (chlorpyrifos, malathion and triazophos) as well as the CB (fenobucarb and carbosulfan) were measured. The concentration addition (CA) model and the isobole method were used to determine whether toxicological responses to binary mixtures of pesticides. In 50:50 % effect mixtures, the observed combined toxicity of chlorpyrifos and malathion was significantly higher than observed and was considered as
Chen Chen and Yanhua Wang have contributed equally to this study. C. Chen Y. Qian (&) Key Laboratory of Agro-Product Quality and Safety of Ministry of Agriculture, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing 100081, China e-mail: [email protected] Y. Wang X. Zhao Q. Wang State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control/Key Laboratory for Pesticide Residue Detection of Ministry of Agriculture, Institute of Quality and Standard for Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
synergistic. For equivalent dose mixtures, when chlorpyrifos mixed with fenobucarb or malathion, the observed toxicities were significantly higher than predicted, suggesting synergistic joint actions. The rest five binary combinations exhibited concentration additive or slight antagonistic joint actions. The CA model and the isobole method provided estimates of mixture toxicity that did not markedly underestimate the measured toxicity, therefore these methods are suitable to use in ecological risk assessments of pesticide mixtures. Keywords Organophosphates Carbamates Cyprinus carpio Concentration addition Isobole Combined toxicity
Introduction Mixture exposure is a universal phenomenon. However, assessing the potential toxic effects and quantifying the risks associated with the exposure to chemical mixtures in ecosystems still remains a major challenge for environmental scientists, risk assessors and regulators (Altenburger et al. 2003; Spurgeon et al. 2010). The fact that chemicals can interact with each other makes it difficult to predict the effects chemical mixtures may have on organisms. Consequently, a need has repeatedly been stated to consider the joint effects of pesticide mixtures in a cumulative perspective in the environmental risk. It has therefore been an enduring challenge for environmental health research (Monosson 2005) as well as ecotoxicology (Eggen et al. 2004) for the past decades. There are models that can predict the effect of mixtures that do not interact (Faust et al. 2003), and when it comes to pesticide mixtures in the aquatic environment, these models often prove to describe
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the mixture effects reasonably well (Belden et al. 2007; Deneer 2000; Faust et al. 2001). Concentration addition (CA) is often used as reference standards to detect interaction. If mixture toxicity is more or less than that predicted by the reference models, the mixture exhibits a synergistic or an antagonistic interaction. CA models rely upon the assumption that mixture components contribute to toxicity through a common mechanism of action. Evidence supports the use of the CA model for assessing mixtures toxicity of like-acting chemicals (Altenburger et al. 2000). The model of independent action (IA) assumes that mixture components possess dissimilar modes of action, interacting with different target sites, leading to a common toxicological endpoint via distinct chains or reactions within an organism (Bliss 1939). One common trait of the two models is that they assume non-interaction as the default. Deviation from the prediction is thus an indication of interaction (antagonistic or synergistic effects than predicted). One way to determine whether the toxicity of a mixture deviates from such predictions is to conduct experiments based on the isobole method (Berenbaum 1989). The isobole method has shown its general applicability in predicting combined effects, regardless of the underlying mechanism of action or the shape of the dose–response curves of the chemicals individually. It is based on the assumption that the response surface of zero-interactive mixtures is characterized by straight line isoboles connecting the isoeffective doses of the individual chemicals (Bosgra et al. 2009). Several classes of pesticides have been identified with a common mode of action. Among these are the organophosphate (OP) and N-methyl carbamate (CB) insecticides. These two classes of chemicals inhibit the enzyme acetylcholinesterase (AChE) and thus interfere with cholinergic neurotransmission in insects and other animal species (Chambers 1992; Fulton and Key 2001). Because anticholinesterase agents share a common mode of toxic action, a dose-additive approach was recommended to assessing risks to human infants and children (NRC 1993). The CA model assumes that the cumulative toxicity of the mixture can be estimated from the sum of the individual toxic potencies of each individual component chemical. The assumption of concentration additive inhibition of AChE activity by mixtures of OP and CB insecticides was recently investigated in vitro (Scholz et al. 2006; Laetz et al. 2009). However, in some in vivo studies, antagonistic or synergistic neurotoxicological effects were observed due to toxicokinetic or toxicodynamic interactions among individual chemicals in the mixture (Borgert et al. 2004). To define the extent to which OP and CB insecticides in mixtures interact, in this study we exposed freshwater carp (Cyprinus carpio) to binary combinations of chlorpyrifos mixed with two other OP insecticides (triazophos and malathion), and two CB insecticides (fenobucarb and
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carbosulfan). Chlorpyrifos is an organophosphorus insecticide with a broad spectrum activity and plant protection products containing this substance are registered for application on a variety of commodities in China. The combination of two active substances (i.e., chlorpyrifos plus other OP and CB insecticides) is very often-used in China. The application of these pesticides does therefore typically result in a potential exposure of non-target organisms to a mixture of chemicals. These combination products thereby constitute the specific case of mixtures of pesticides that are deliberately released into the environment. Monitoring programs of surface waters generally find more than seven to eight pesticides in more than half of the samples where at least one pesticide is detected (Martin et al. 2003). The cumulative toxicological impact of pesticide mixtures is of particular concern for freshwater species. Common carp (C. carpio L.) is one of the most economically important omnivorous freshwater fish of the world, and plays a major ecological role in the aquatic food webs. In this study, carp was chosen as the sentinel organism due to its ease of sampling, good adaptability to environmental conditions, and high ecological and economic relevance (Wang et al. 2011). However, the toxicological effects of these mixtures on the health of carps are largely unknown and relatively few studies have explored the effects of OP and CB insecticides on carp brain AChE activity at low, environmentally realistic exposure concentrations. In the present study, concentration–response curves were used for AChE inhibition by individual pesticides to determine the type of joint action that occurred in these mixtures and whether the use of the CA model and the isobole method effectively estimated the risk posed by the pesticide mixtures.
Materials and methods Fish Carps were obtained from the bird and water flea market in Hangzhou City, China. Following transport to the laboratory, carps were raised and acclimated to the laboratory for 1 week prior to use at the Zhejiang Academy of Agricultural Science. Fish were held in recirculating tanks of tap water (temperature 23 ± 1 °C, pH 7 ± 0.5, dissolved oxygen 8 ± 1 mg/l, total hardness as CaCO3 50 ± 10 mg/l) on a 12 h light–dark schedule. Fish were fed with pellets daily. Fish used in experiments have an average size of 9.0 ± 0.7 cm and weight of 20 ± 2 g. Test chemicals Malathion (CAS No. 121-75-5; 95 % pure) and chlorpyrifos (CAS No. 2921-88-2; 96 % pure) were provided by
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity
Zhejiang Jiahua Chemical Industrial Group (Jiaxing, China), triazophos (CAS No. 24017-47-8; 95 % pure) was supplied by Zhejiang Weierda Agrochemical Co., Ltd (Hangzhou, China), fenobucarb (CAS No. 3766-81-2; 95 % pure) was obtained from Jiangsu Changlong Chemical Industrial Group Co., Ltd (Changzhou, China), and carbosulfan (CAS No. 55285-14-8; 90 % pure) was provided by Zhejiang Pinghu Agrochemical Co., Ltd (Jiaxing, China). Stock and working stock solutions of each chemical were prepared in analytical grade acetone (99 % purity) and stored in a refrigerator at 4 °C. All working stock solutions were made immediately prior to use. Single-pesticide and pesticides mixture exposures Pesticide-containing stock solutions were prepared in acetone and added in 3 ml aliquots to 30 l glass tank. For each treatment, two individual fish were exposed for 96 h on a 24 h static renewal schedule. Carps were not fed during the exposure interval. After exposure, brain tissues were removed, put into plastic microcentrifuge tubes, and kept on ice for subsequent analyses of AChE enzymatic activity. For the tests, two replicates were used for each treatment. In the pilot experiments, the inhibition by individual pesticides was both determined at broad concentrations to ensure capturing possible inhibition effect ranges. Exposure concentrations used for single-pesticide exposures are shown in Table 1. The individual pesticide dose–response curves were done using the EC50 (the concentration estimated to produce a 50 % decrease in AChE activity relative to carrier controls) values of Table 1 as a starting point, testing five to six concentrations with a separation factor of two between doses. The choice of concentration interval ensured a relatively high effect in the highest concentrations and no observable effect in the lowest concentrations. This was set as a validity criterion for all dose–response curves in all experiments. Based on the measured EC50 values calculated from the single exposure studies, a mixture ratio where 50 % of the Table 1 Concentrations used in both single-insecticide exposures and the parameters of the curve fit of the dose–response data for each individual pesticide Pesticides
Concentration range (mg/l)
r2
Slope Best fit value
SEa
EC50 (mg/l) Best fit value
Chlorpyrifos
0.0007–0.50
0.9733
1.85
1.42
0.02
Malathion
0.00457–20.0
0.9601
0.35
0.70
5.4132
Triazophos
0.000137–0.10
0.9652
1.32
0.80
0.007
Fenobucarb
0.000137–0.4
0.9355
0.93
0.77
0.1716
Carbosulfan
0.00914–20.0
0.9880
1.27
1.80
0.4301
a
Standard error of mean
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effect came from each individual pesticide was chosen. The 50:50 % effect mixture ratio was chosen as this is the mixture ratio where the largest deviation from CA can be observed (Nørgaard and Cedergreen 2010). Eight concentrations with a separation factor of two or three were used for the mixture ratio. The single compounds were tested simultaneously. Meanwhile, equivalent dose mixture toxicity test was chosen with either of the two pesticides combinations. Eight concentrations with a separation factor of two or three were used for each mixture. AChE enzyme assays Determination of AChE activity after (Ellman et al. 1960) subject to some modifications. Carp brain tissues were homogenized in 0.1 M sodium phosphate buffer (pH 7.2–7.4). Homogenates were centrifuged, and 0.2 ml of the supernatant was combined with 3 ml of 0.02 mM phosphate-buffered saline, 100 ll of 20 mM DTNB [5,50 dithio-bis(2-nitrobenzioc acid)], and 20 ll of 75 mM acetylthiocholine iodide. The change in absorbance at 412 nm was measured for 3 min at 25 °C using UV–Vis Spectrophotometer (Tu-1810, Beijing Purkinje General Instrument Co., Ltd). AChE activity was quantified as milli-optical density (mOD) per minute per gram of fresh tissue and reported as a percentage of the baseline enzyme activity for fish exposed to carrier alone. Data analysis Statistical analyses were performed with Prism 5.0 software. Tests included nonlinear regression to fit curves of AChE activities, one-way analysis of variance (ANOVA) to establish differences between groups. To allow for a Gaussian distribution of the error around the estimate of median effective concentration (EC50), the nonlinear regression performed by Prism 5.0 uses log transformations of the concentrations and generates an estimate of the log transformation of EC50. AChE activity ¼ 1þ
1
Concentration EC50
ð1Þ
slope
In this equation, EC50 is equivalent to the concentration producing 50 % AChE inhibition. Slope is the steepness of the curve around EC50 value. Determining the type of pesticides mixture joint action by CA model and the isobole method Individual toxic potential for all pesticides were determined from the concentration–response relationship for
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AChE inhibition in single-chemical trials. The joint toxicity of the pesticide mixtures was determined using CA model, which was calculated using Eq. (2) (Faust et al. 2000): !1 n X Pi ECx; mix ¼ ð2Þ ECxi i¼1 where ECx,mix is the effect concentration of the mixture eliciting x% effect, ECx,i denotes the concentration of the ith component when exists individually and elicits the same effect (x%) as the mixture, pi is the relative mass proportions of the ith component in the mixture. The standard isobole diagram developed by Kortenkamp and Altenburger (1998), which enables a statistical determination of whether the experimental isobole deviates from an additive isobole. In the isobole method, the effects of combinations can be plotted against the doses of chemicals A and B in a three-dimensional graph (Fig. 1, left panel). The isobole method is based on the assumption that the response surface of zero-interactive mixtures is characterized by straight line isoboles which are assumed to be straight lines connecting the isoeffective doses of the individual chemicals. Horizontal projection of the response surface into the dose–dose space gives an isobole plot or isobologram (Fig. 1, right panel). The isoboles are given by the equation: d1 d2 þ ¼1 ECx1 ECx2
ð3Þ
where d1 and d2 are the concentrations of chemicals 1 and 2 in a mixture giving the effect x and ECx,1 and ECx,2 are the concentrations of the two chemicals giving the effect of x when tested separately. If the isoboles of zero-interactive
Fig. 1 Demonstration of the isobole method. Left the dose–response curves of chemicals A and B in a three-dimensional graph. Combinations of A and B leading to effect size E are assumed to be on a straight line connecting the individual doses DA and DB which both correspond to the same effect. Right an isobologram is the horizontal
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combinations are straight lines, then for synergistic combinations the left side of Eq. (3) will be smaller than 1 and for antagonistic combinations larger than 1. Determining the type of mixture joint action Significant departures from additive toxicity were used to define antagonistic and synergistic interactions between pesticides in mixtures (Hertzberg and MacDonell 2002). If the observed mixture toxicity value fell within the 95 % confidence intervals of the expected value of the CA model then the mixture was considered to conform to the CA or isobole model. In turn, if an observed mixture toxicity value was outside the 95 % confidence intervals of the expected value then the mixture potentially may not conform to the model. This approach to determining conformity to the model can lead to very small biologically insignificant (albeit statistically significant) deviations from the model being classed as antagonistic or synergistic. Therefore, we also required that the expected and observed values differed in toxicity by at least 30 %. To enable a quantitative estimation of the difference in predicted and measured toxicity, the model deviation ratio (MDR) method (Belden et al. 2007) was used. MDR ¼
ECPRD 100 % ECOBS
ð4Þ
For both models, the MDR was derived by dividing the predicted toxicity value (EC50) by the observed toxicity value. MDR values [1.3 mean that the toxicity of the mixture conforms with synergism while values \0.7 are taken to conform to antagonism. MDR is defined as a ratio of the predictive concentration (ECPRD) by a reference model to the observed concentration (ECOBS).
projection of the three-dimensional graph. The combination shown (dA, dB) is on a straight line between DA and DB, and is expected to be isoeffective to either DA or DB. [Adapted from Bosgra et al. (2009)]
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity
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Combined effects of the mixture by the CA model and the isobole method
Results Single pesticides Exposure to individual pesticides for 96 h resulted in sublethal, concentration dependent decreases in brain AChE activity among carps. No mortality was observed at any of the single-chemical exposure concentrations. No significant differences were found in baseline AChE activity between unexposed fish and those exposed to solvent alone (one-way ANOVAs, p [ 0.2). Concentration–response relationships were fit using a nonlinear regression. The resulting curve fit parameters for individual pesticides are reported in Table 1. According to EC50 values for AChE inhibition, the relative potencies of five pesticides vary, with the decreasing order as: triazophos [ chlorpyrifos [ fenobucarb [ carbosulfan [ malathion. Pesticide mixtures The individual toxicity (EC50) values of chlorpyrifos, triazophos, malathion, carbosulfan, and fenobucarb were used to set the concentrations used in the toxicity tests with mixtures. For each binary combination test, pesticides were assayed individually over a range of concentrations and together as a single mixture. The dose–response relationships for individual chemicals were used to calculate EC50 values in mixtures. The joint inhibitory effects of binary combinations of chlorpyrifos mixed with triazophos, fenobucarb, carbosulfan, and malathion on carp brain AChE activity are shown in Table 2. For equitoxic mixtures, the toxicity of malathion and carbosulfan ranged between 1.17 and 0.32 mg/l. Fenobucarb was approximately an order of magnitude more toxic than malathion, with EC50 values of 0.088 mg/l. Triazophos was the most toxic with EC50 values several orders of magnitude lower than malathion, its EC50 values was 0.0032 mg/l (Table 2).
Summaries of mixture toxicity assessments for binary pesticide mixtures are listed in Table 3. Combined effects of mixtures determined by the CA model and the isobole method resulted in the same pattern. In 50:50 % effect mixtures, when chlorpyrifos was mixed with fenobucarb and triazophos, the predicted toxicity was not significantly different from observed (MDR values were 0.97 and 1.08, respectively), suggesting concentration additive joint action (Table 3). In contrast, the expected mixture toxicity of chlorpyrifos plus carbosulfan was significantly less than observed, displaying antagonistic joint effect. While for the combination of chlorpyrifos and malathion, the predicted toxicity was higher than observed and the MDR value was [1.3, hence it was considered as synergistic. For equivalent dose mixtures, the observed toxicities of chlorpyrifos mixed with carbosulfan and triazophos were not significantly different from predicted and so was considered conforming to CA. When chlorpyrifos mixed with fenobucarb or malathion, the observed toxicities were significantly higher than predicted and had MDR values [1.3, suggesting a synergistic joint action (Table 3).
Discussion The isobole method is based on the theory of CA and mainly used qualitatively to characterize the effects of combinations, whether or not they show synergy or antagonism (Syberg et al. 2008). It is probably the most favored criterion for chemicals that act by a common mechanism of action, which is mainly used qualitatively to characterize the effects of combinations, whether or not they show synergy or antagonism (Berenbaum 1989). CA and the isobole method are considered equivalent.
Table 2 The concentrations of malathion, triazophos, fenobucarb, and carbosulfan within binary mixtures producing 50 % AChE inhibition (EC50) and the parameters of the curve fits in 50:50 % effect and equivalent dose mixture experiments Pesticide mixtures
Compound
50:50 % effect mixture EC50 (mg/l)
Chlorpyrifos ? triazophos
Equivalent dose mixture Slope (SEa)
EC50 (mg/l)
Slope (SE)
Chlorpyrifos
0.0093
0.85 (0.79)
0.0047
1.34 (1.01)
Triazophos
0.0032
0.85 (0.79)
0.0047
1.34 (1.01)
Chlorpyrifos ? fenobucarb
Chlorpyrifos Fenobucarb
0.0104 0.0884
1.43 (0.93) 1.43 (0.93)
0.0074 0.0074
1.85 (1.06) 1.85 (1.06)
Chlorpyrifos ? carbosulfan
Chlorpyrifos
0.015
1.88 (1.76)
0.016
1.45 (1.18)
Carbosulfan
0.32
1.88 (1.76)
0.016
1.45 (1.18)
Chlorpyrifos
0.0043
0.85 (0.80)
0.0075
1.68 (0.92)
Malathion
1.17
0.84 (0.80)
0.0075
1.68 (0.92)
Chlorpyrifos ? malathion a
Standard error of mean
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Table 3 Summaries of mixture toxicity assessments using the CA model and the isobole method for binary pesticide mixtures in 50:50 % dose mixture experiments Pesticide mixtures
50:50 % effect mixture Predicted EC50 (mg/l)
Observed EC50 (mg/l)
Equivalent dose mixture MDR
Type of combined action
Predicted EC50 (mg/l)
Observed EC50 (mg/l)
MDR
Type of combined action
Chlorpyrifos ? triazophos
0.014
0.0125
1.08
CA
0.010
0.009
1.10
CA
Chlorpyrifos ? fenobucarb
0.095
0.099
0.97
CA
0.036
0.015
2.42
Synergistic
Chlorpyrifos ? carbosulfan
0.224
0.335
0.67
Antagonistic
0.038
0.032
1.19
CA
Chlorpyrifos ? malathion
2.72
1.17
2.32
Synergistic
0.040
0.015
2.66
Synergistic
For the CA model and the isobole method, the model divergence ratio (MDR) is the ratio of the observed and predicted concentration or responses. An MDR value of 1 indicates adherence to the specified model. MDR values [1 indicates greater than expected toxicity and hence synergism among mixture components. MDR values\1 indicates less than expected toxicity and hence antagonism among mixture components. The classification of type of combined action is based on the observed concentration/isobole being outside the expected value, and the MDR reflecting a [30 % deviance from the CA or isobole The CA model and the isobole method gave the same results
However, in toxicological and pharmacological risk assessment, a method of dose addition (Bosgra et al. 2009) is widely used to calculate the cumulative effect of common mechanism chemicals, which is based on the assumption that any dose of B can be replaced by an equally effective dose of A in the mixture. According to Bosgra et al. (2009), if a combination is found to be zerointeractive by the isobole method, it is commonly assumed that dose addition may be used to calculate the cumulative effect, but the underlying assumptions differ between the methods. They could give the same prediction for chemicals with parallel dose–response curves on log-dose scale. But many factors determine the shape of the dose–response curves, and a common mechanism of action does not necessarily lead to parallel curves. In these cases, dose addition has different solutions depending on the index chemical chosen, while the isobole method has only one solution. These two methods are not equivalent in the field of toxicology and pharmacology. As recommended by Bosgra et al. (2009), the solution of outcomes of a mixture experiment may be compared to the situation of linear isoboles, then for synergistic combinations the left side of Eq. (4) will be smaller than 1 and for antagonistic combinations larger than 1. OP and CB insecticides are the most important AChE inhibitors and often called anticholinesterases. In the presence of these inhibitors, AChE becomes progressively inhibited and is not further capable of hydrolyzing ACh to choline and acetic acid (Jokanovic and Maksimovic 1997). Consequently, ACh accumulates at cholinergic receptor sites and affects cholinergic receptors throughout the central and peripheral nervous system (Jokanovic 2009). AchE has been used as a bioindicator of OP and CB pesticide exposures and linked to toxicity (Belden and Lydy 2000). In the present study, AChE activity was a sensitive indicator of
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OP and CB pesticide exposure and generally followed a dose-dependent relationship consistent with toxicity. Following the 96 h exposure to the pesticides, AChE activity decreased proportionally to exposure concentrations. In the present study, it is shown that in vivo exposures to binary mixtures of OP and CB pesticides produced different AChE inhibition types in the brains of carps (Table 3). However, in some other investigations, the OP, including their oxon metabolites, and CB insecticides do not interact in vitro, where their combinatorial inhibition of AChE can be explained by CA (Scholz et al. 2006). The departure from CA for some pesticide combinations in vivo could be explained if OP and CB insecticides act on other biochemical targets. Carboxylesterases (CaEs) are candidate enzymes that may underlie the OP and CB pesticide interactions (Laetz et al. 2009). CaEs play an important role in the detoxification of the OP and CB insecticides via hydrolysis (Jokanovic 2001; Wheelock et al. 2005; Laetz et al. 2009). CaEs may functionally protect AChE from insecticide toxicity by direct binding and sequestration, thereby preventing or delaying interaction between the insecticide and AChE (Jokanovic 2001). In Daphnia magna and in mammalian liver salmonids, the inhibition of CaEs was also observed to significantly enhance the toxicity of OP and CB pesticides (Barata et al. 2004). For all the insecticides, the concentrations that produce 50 % brain AChE inhibition in carps (Table 2) are generally much higher than the levels typically detected in surface water monitoring studies (Hoffman et al. 2000; Gilliom 2007; Verro et al. 2009). Our results show that 4 out of 8 pesticide combinations produce additive toxicity at low concentrations. Moreover, some certain combinations showed a pattern of synergism. For example, when chlorpyrifos was mixed with fenobucarb or malathion at equivalent effect levels, synergism is likely to occur at low
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity
exposure concentrations. Where synergism occurs, additional safety factors could then be assigned to protect the health of aquatic species. With the exception of safety factors for synergism, this process is similar to how the FQPA mandates evaluating the human health risks of OP and CB mixtures (FQPA 1996). Although only four pesticides were investigated, it would be straightforward to establish concentration–response relationships for AChE inhibition for other authorized OP and CB insecticides in current use. The link between exposure level and toxicity has been criticized due to the variability factors including size of the organism, environmental conditions, species and individual variation, sampling type and storage, and laboratory techniques (Sturm et al. 1999; Sandahl and Jenkins 2002), which influence the reliability of the mixture toxicity prediction. It is an important factor when aiming at establishing a predictive mixture toxicity assessment in the regulatory environmental risk assessment context. Belden et al. (2007) found that more than eighty percent of all experiments that evaluated the CA model had observed effective concentrations within a factor of 2 of predicted values. In the current study, 5 out of 8 binary combinations were found to have MDR values between 0.67 and 1.19. Cedergreen et al. (2007) stated that the reproducibility of mixture experiments can hardly be guaranteed, given the impact of the large heterogeneity in the input data base due to variation among laboratories, test protocols, test species. This will not only depend on the setup but also on the species that is tested. If we consider clone individuals as test species experiments will have more chances to be reproducible than if the test organisms have genetically variability among specimens.
Conclusion Pesticide mixtures continue to pose major challenges for natural environments. Our results have important implications for ecological risk assessments, particularly those that focus on the toxicity of individual pesticide as the basis for estimating impacts to aquatic fish. The toxicity toward AChE activity inhibition in carp brains and the type of joint actions of four binary mixtures of five pesticides (chlorpyrifos, malathion, triazophos, fenobucarb, and carbosulfan) with the same modes of action to the activity of AChE were determined using the CA model and the isobole method. Both methods are based on the same theory in the field of ecotoxicological risk assessment. The pesticide mixtures were classed as antagonistic, additive and synergistic. These two methods do not markedly underestimate the toxicity of any tested mixture. Therefore, it is more appropriate to use to estimate the toxicity of mixtures.
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Acknowledgments This Project was supported by Zhejiang Provincial Natural Science Foundation of China (No. LY13C03006), the opening Project Fund of State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control (No. 2010DS700124KF1306) and the Innovation Project of Zhejiang Academy of Agricultural Sciences. Conflict of interest of interest.
The authors declare that they have no conflict
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228 Joint algal toxicity of 16 dissimilarly acting chemicals is predictable by the concept of independent action. Aquat Toxicol 63:43–63 Food Quality Protection Act (FQPA) (1996) Public Law, pp 104–170 Fulton MH, Key PB (2001) Acetylcholinesterase inhibition in estuarine fish and invertebrates as an indicator of organophosphorus insecticide exposure and effects. Environ Toxicol Chem 20:37–45 Gilliom RJ (2007) Pesticides in US streams and groundwater. Environ Sci Technol 41:3409–3414 Hertzberg R, MacDonell M (2002) Synergy and other ineffective mixture risk definitions. Sci Total Environ 288:31–42 Hoffman RS, Capel PD, Larson SJ (2000) Comparison of pesticides in eight US urban streams. Environ Toxicol Chem 19:2249–2258 Jokanovic M (2001) Biotransformation of organophosphorus compounds. Toxicol 166:139–160 Jokanovic´ M (2009) Medical treatment of acute poisoning with organophosphorus and carbamate pesticides. Toxicol Lett 190:107–115 Jokanovic M, Maksimovic M (1997) Abnormal cholinesterase activity: understanding and interpretation. Eur J Clin Chem Clin Biochem 35:11–16 Kortenkamp A, Altenburger R (1998) Synergisms with mixtures of xenoestrogens: a reevaluation using the method of isoboles. Sci Total Environ 221:59–73 Laetz CA, Baldwin DH, Collier TK, Hebert V, Stark JD, Scholz NL (2009) The synergistic toxicity of pesticide mixtures: implications for risk assessment and the conservation of endangered Pacific salmon. Environ Health Perspect 117:348–353 Martin JD, Crawford CG, Larson SJ (2003) Pesticides in streams. Water Res 33:3441–3446 Monosson E (2005) Chemical mixtures: considering the evolution of toxicology and chemical assessment. Environ Health Perspect 113:383–390 Nørgaard KB, Cedergreen N (2010) Pesticide cocktails can interact synergistically on aquatic crustaceans. Environ Sci Pollut Res Int 17:957–967
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C. Chen et al. NRC (National Research Council) (1993) Pesticides in the diets of infants and children. National Academy Press, Washington, DC Sandahl JF, Jenkins JJ (2002) Pacific Steelhead (Oncorhynchus mykiss) exposed to chlorpyrifos: benchmark concentration estimates for acetylcholinesterase inhibition. Environ Toxicol Chem 21:2452–2458 Scholz NL, Truelove NK, Labenia JS, Baldwin DH, Collier TK (2006) Dose-additive inhibition of chinook salmon acetylcholinesterase activity by mixtures of organophosphate and carbamate insecticides. Environ Toxicol Chem 25:1200–1207 Spurgeon DJ, Jones OAH, Dorne JLCM, Svendsen C, Swain S, Stu¨rzenbaum SR (2010) Systems toxicology approaches for understanding the joint effects of environmental chemical mixtures. Sci Total Environ 408:3725–3734 Sturm A, Wogram J, Hansen PD, Liess M (1999) Potential use of cholinesterase in monitoring low levels of organophosphates in small streams: natural variability in three-spined stickleback (Gasterosteus aculeatus) and relation to pollution. Environ Toxicol Chem 18:194–200 Syberg K, Elleby A, Pedersen H, Cedergreen N, Forbes VE (2008) Mixture toxicity of three toxicants with similar and dissimilar modes of action to Daphnia magna. Ecotoxicol Environ Saf 69:428–436 Verro R, Finizio A, Otto S, Vighi M (2009) Predicting pesticide environmental risk in intensive agricultural areas. II: screening level risk assessment of complex mixtures in surface waters. Environ Sci Technol 43:530–537 Wang X, Xing H, Li X, Xu S, Wang X (2011) Effects of atrazine and chlorpyrifos on the mRNA levels of IL-1 and IFN-c2b in immune organs of common carp. Fish Shellfish Immunol 31:126–133 Wheelock CE, Shan G, Ottea J (2005) Overview of carboxylesterases and their role in metabolism of insecticides. J Pest Sci 30:75–83
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity by binary mixtures of chlorpyrifos and four other insecticides Chen Chen • Yanhua Wang • Xueping Zhao Qiang Wang • Yongzhong Qian
•
Accepted: 12 December 2013 / Published online: 23 December 2013 Ó Springer Science+Business Media New York 2013
Abstract Mixtures of organophosphate (OP) and carbamate (CB) insecticides are commonly detected in freshwater habitats. These insecticides inhibit the activity of acetylcholinesterase (AChE) and have potential to interfere with behaviors that may be essential for survival of species. Although the effects of individual anticholinesterase insecticides on aquatic species have been studied for decades, the combined toxicity of mixtures is still poorly understood. In the present study, we assessed whether pesticides in a mixture act in isolation (resulting in additive AChE inhibition) or whether components interact to produce either antagonistic or synergistic toxicity. Brain AChE inhibition in carp (Cyprinus carpio L.) exposed to a series of concentrations of the OP (chlorpyrifos, malathion and triazophos) as well as the CB (fenobucarb and carbosulfan) were measured. The concentration addition (CA) model and the isobole method were used to determine whether toxicological responses to binary mixtures of pesticides. In 50:50 % effect mixtures, the observed combined toxicity of chlorpyrifos and malathion was significantly higher than observed and was considered as
Chen Chen and Yanhua Wang have contributed equally to this study. C. Chen Y. Qian (&) Key Laboratory of Agro-Product Quality and Safety of Ministry of Agriculture, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing 100081, China e-mail: [email protected] Y. Wang X. Zhao Q. Wang State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control/Key Laboratory for Pesticide Residue Detection of Ministry of Agriculture, Institute of Quality and Standard for Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
synergistic. For equivalent dose mixtures, when chlorpyrifos mixed with fenobucarb or malathion, the observed toxicities were significantly higher than predicted, suggesting synergistic joint actions. The rest five binary combinations exhibited concentration additive or slight antagonistic joint actions. The CA model and the isobole method provided estimates of mixture toxicity that did not markedly underestimate the measured toxicity, therefore these methods are suitable to use in ecological risk assessments of pesticide mixtures. Keywords Organophosphates Carbamates Cyprinus carpio Concentration addition Isobole Combined toxicity
Introduction Mixture exposure is a universal phenomenon. However, assessing the potential toxic effects and quantifying the risks associated with the exposure to chemical mixtures in ecosystems still remains a major challenge for environmental scientists, risk assessors and regulators (Altenburger et al. 2003; Spurgeon et al. 2010). The fact that chemicals can interact with each other makes it difficult to predict the effects chemical mixtures may have on organisms. Consequently, a need has repeatedly been stated to consider the joint effects of pesticide mixtures in a cumulative perspective in the environmental risk. It has therefore been an enduring challenge for environmental health research (Monosson 2005) as well as ecotoxicology (Eggen et al. 2004) for the past decades. There are models that can predict the effect of mixtures that do not interact (Faust et al. 2003), and when it comes to pesticide mixtures in the aquatic environment, these models often prove to describe
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the mixture effects reasonably well (Belden et al. 2007; Deneer 2000; Faust et al. 2001). Concentration addition (CA) is often used as reference standards to detect interaction. If mixture toxicity is more or less than that predicted by the reference models, the mixture exhibits a synergistic or an antagonistic interaction. CA models rely upon the assumption that mixture components contribute to toxicity through a common mechanism of action. Evidence supports the use of the CA model for assessing mixtures toxicity of like-acting chemicals (Altenburger et al. 2000). The model of independent action (IA) assumes that mixture components possess dissimilar modes of action, interacting with different target sites, leading to a common toxicological endpoint via distinct chains or reactions within an organism (Bliss 1939). One common trait of the two models is that they assume non-interaction as the default. Deviation from the prediction is thus an indication of interaction (antagonistic or synergistic effects than predicted). One way to determine whether the toxicity of a mixture deviates from such predictions is to conduct experiments based on the isobole method (Berenbaum 1989). The isobole method has shown its general applicability in predicting combined effects, regardless of the underlying mechanism of action or the shape of the dose–response curves of the chemicals individually. It is based on the assumption that the response surface of zero-interactive mixtures is characterized by straight line isoboles connecting the isoeffective doses of the individual chemicals (Bosgra et al. 2009). Several classes of pesticides have been identified with a common mode of action. Among these are the organophosphate (OP) and N-methyl carbamate (CB) insecticides. These two classes of chemicals inhibit the enzyme acetylcholinesterase (AChE) and thus interfere with cholinergic neurotransmission in insects and other animal species (Chambers 1992; Fulton and Key 2001). Because anticholinesterase agents share a common mode of toxic action, a dose-additive approach was recommended to assessing risks to human infants and children (NRC 1993). The CA model assumes that the cumulative toxicity of the mixture can be estimated from the sum of the individual toxic potencies of each individual component chemical. The assumption of concentration additive inhibition of AChE activity by mixtures of OP and CB insecticides was recently investigated in vitro (Scholz et al. 2006; Laetz et al. 2009). However, in some in vivo studies, antagonistic or synergistic neurotoxicological effects were observed due to toxicokinetic or toxicodynamic interactions among individual chemicals in the mixture (Borgert et al. 2004). To define the extent to which OP and CB insecticides in mixtures interact, in this study we exposed freshwater carp (Cyprinus carpio) to binary combinations of chlorpyrifos mixed with two other OP insecticides (triazophos and malathion), and two CB insecticides (fenobucarb and
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carbosulfan). Chlorpyrifos is an organophosphorus insecticide with a broad spectrum activity and plant protection products containing this substance are registered for application on a variety of commodities in China. The combination of two active substances (i.e., chlorpyrifos plus other OP and CB insecticides) is very often-used in China. The application of these pesticides does therefore typically result in a potential exposure of non-target organisms to a mixture of chemicals. These combination products thereby constitute the specific case of mixtures of pesticides that are deliberately released into the environment. Monitoring programs of surface waters generally find more than seven to eight pesticides in more than half of the samples where at least one pesticide is detected (Martin et al. 2003). The cumulative toxicological impact of pesticide mixtures is of particular concern for freshwater species. Common carp (C. carpio L.) is one of the most economically important omnivorous freshwater fish of the world, and plays a major ecological role in the aquatic food webs. In this study, carp was chosen as the sentinel organism due to its ease of sampling, good adaptability to environmental conditions, and high ecological and economic relevance (Wang et al. 2011). However, the toxicological effects of these mixtures on the health of carps are largely unknown and relatively few studies have explored the effects of OP and CB insecticides on carp brain AChE activity at low, environmentally realistic exposure concentrations. In the present study, concentration–response curves were used for AChE inhibition by individual pesticides to determine the type of joint action that occurred in these mixtures and whether the use of the CA model and the isobole method effectively estimated the risk posed by the pesticide mixtures.
Materials and methods Fish Carps were obtained from the bird and water flea market in Hangzhou City, China. Following transport to the laboratory, carps were raised and acclimated to the laboratory for 1 week prior to use at the Zhejiang Academy of Agricultural Science. Fish were held in recirculating tanks of tap water (temperature 23 ± 1 °C, pH 7 ± 0.5, dissolved oxygen 8 ± 1 mg/l, total hardness as CaCO3 50 ± 10 mg/l) on a 12 h light–dark schedule. Fish were fed with pellets daily. Fish used in experiments have an average size of 9.0 ± 0.7 cm and weight of 20 ± 2 g. Test chemicals Malathion (CAS No. 121-75-5; 95 % pure) and chlorpyrifos (CAS No. 2921-88-2; 96 % pure) were provided by
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity
Zhejiang Jiahua Chemical Industrial Group (Jiaxing, China), triazophos (CAS No. 24017-47-8; 95 % pure) was supplied by Zhejiang Weierda Agrochemical Co., Ltd (Hangzhou, China), fenobucarb (CAS No. 3766-81-2; 95 % pure) was obtained from Jiangsu Changlong Chemical Industrial Group Co., Ltd (Changzhou, China), and carbosulfan (CAS No. 55285-14-8; 90 % pure) was provided by Zhejiang Pinghu Agrochemical Co., Ltd (Jiaxing, China). Stock and working stock solutions of each chemical were prepared in analytical grade acetone (99 % purity) and stored in a refrigerator at 4 °C. All working stock solutions were made immediately prior to use. Single-pesticide and pesticides mixture exposures Pesticide-containing stock solutions were prepared in acetone and added in 3 ml aliquots to 30 l glass tank. For each treatment, two individual fish were exposed for 96 h on a 24 h static renewal schedule. Carps were not fed during the exposure interval. After exposure, brain tissues were removed, put into plastic microcentrifuge tubes, and kept on ice for subsequent analyses of AChE enzymatic activity. For the tests, two replicates were used for each treatment. In the pilot experiments, the inhibition by individual pesticides was both determined at broad concentrations to ensure capturing possible inhibition effect ranges. Exposure concentrations used for single-pesticide exposures are shown in Table 1. The individual pesticide dose–response curves were done using the EC50 (the concentration estimated to produce a 50 % decrease in AChE activity relative to carrier controls) values of Table 1 as a starting point, testing five to six concentrations with a separation factor of two between doses. The choice of concentration interval ensured a relatively high effect in the highest concentrations and no observable effect in the lowest concentrations. This was set as a validity criterion for all dose–response curves in all experiments. Based on the measured EC50 values calculated from the single exposure studies, a mixture ratio where 50 % of the Table 1 Concentrations used in both single-insecticide exposures and the parameters of the curve fit of the dose–response data for each individual pesticide Pesticides
Concentration range (mg/l)
r2
Slope Best fit value
SEa
EC50 (mg/l) Best fit value
Chlorpyrifos
0.0007–0.50
0.9733
1.85
1.42
0.02
Malathion
0.00457–20.0
0.9601
0.35
0.70
5.4132
Triazophos
0.000137–0.10
0.9652
1.32
0.80
0.007
Fenobucarb
0.000137–0.4
0.9355
0.93
0.77
0.1716
Carbosulfan
0.00914–20.0
0.9880
1.27
1.80
0.4301
a
Standard error of mean
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effect came from each individual pesticide was chosen. The 50:50 % effect mixture ratio was chosen as this is the mixture ratio where the largest deviation from CA can be observed (Nørgaard and Cedergreen 2010). Eight concentrations with a separation factor of two or three were used for the mixture ratio. The single compounds were tested simultaneously. Meanwhile, equivalent dose mixture toxicity test was chosen with either of the two pesticides combinations. Eight concentrations with a separation factor of two or three were used for each mixture. AChE enzyme assays Determination of AChE activity after (Ellman et al. 1960) subject to some modifications. Carp brain tissues were homogenized in 0.1 M sodium phosphate buffer (pH 7.2–7.4). Homogenates were centrifuged, and 0.2 ml of the supernatant was combined with 3 ml of 0.02 mM phosphate-buffered saline, 100 ll of 20 mM DTNB [5,50 dithio-bis(2-nitrobenzioc acid)], and 20 ll of 75 mM acetylthiocholine iodide. The change in absorbance at 412 nm was measured for 3 min at 25 °C using UV–Vis Spectrophotometer (Tu-1810, Beijing Purkinje General Instrument Co., Ltd). AChE activity was quantified as milli-optical density (mOD) per minute per gram of fresh tissue and reported as a percentage of the baseline enzyme activity for fish exposed to carrier alone. Data analysis Statistical analyses were performed with Prism 5.0 software. Tests included nonlinear regression to fit curves of AChE activities, one-way analysis of variance (ANOVA) to establish differences between groups. To allow for a Gaussian distribution of the error around the estimate of median effective concentration (EC50), the nonlinear regression performed by Prism 5.0 uses log transformations of the concentrations and generates an estimate of the log transformation of EC50. AChE activity ¼ 1þ
1
Concentration EC50
ð1Þ
slope
In this equation, EC50 is equivalent to the concentration producing 50 % AChE inhibition. Slope is the steepness of the curve around EC50 value. Determining the type of pesticides mixture joint action by CA model and the isobole method Individual toxic potential for all pesticides were determined from the concentration–response relationship for
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AChE inhibition in single-chemical trials. The joint toxicity of the pesticide mixtures was determined using CA model, which was calculated using Eq. (2) (Faust et al. 2000): !1 n X Pi ECx; mix ¼ ð2Þ ECxi i¼1 where ECx,mix is the effect concentration of the mixture eliciting x% effect, ECx,i denotes the concentration of the ith component when exists individually and elicits the same effect (x%) as the mixture, pi is the relative mass proportions of the ith component in the mixture. The standard isobole diagram developed by Kortenkamp and Altenburger (1998), which enables a statistical determination of whether the experimental isobole deviates from an additive isobole. In the isobole method, the effects of combinations can be plotted against the doses of chemicals A and B in a three-dimensional graph (Fig. 1, left panel). The isobole method is based on the assumption that the response surface of zero-interactive mixtures is characterized by straight line isoboles which are assumed to be straight lines connecting the isoeffective doses of the individual chemicals. Horizontal projection of the response surface into the dose–dose space gives an isobole plot or isobologram (Fig. 1, right panel). The isoboles are given by the equation: d1 d2 þ ¼1 ECx1 ECx2
ð3Þ
where d1 and d2 are the concentrations of chemicals 1 and 2 in a mixture giving the effect x and ECx,1 and ECx,2 are the concentrations of the two chemicals giving the effect of x when tested separately. If the isoboles of zero-interactive
Fig. 1 Demonstration of the isobole method. Left the dose–response curves of chemicals A and B in a three-dimensional graph. Combinations of A and B leading to effect size E are assumed to be on a straight line connecting the individual doses DA and DB which both correspond to the same effect. Right an isobologram is the horizontal
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combinations are straight lines, then for synergistic combinations the left side of Eq. (3) will be smaller than 1 and for antagonistic combinations larger than 1. Determining the type of mixture joint action Significant departures from additive toxicity were used to define antagonistic and synergistic interactions between pesticides in mixtures (Hertzberg and MacDonell 2002). If the observed mixture toxicity value fell within the 95 % confidence intervals of the expected value of the CA model then the mixture was considered to conform to the CA or isobole model. In turn, if an observed mixture toxicity value was outside the 95 % confidence intervals of the expected value then the mixture potentially may not conform to the model. This approach to determining conformity to the model can lead to very small biologically insignificant (albeit statistically significant) deviations from the model being classed as antagonistic or synergistic. Therefore, we also required that the expected and observed values differed in toxicity by at least 30 %. To enable a quantitative estimation of the difference in predicted and measured toxicity, the model deviation ratio (MDR) method (Belden et al. 2007) was used. MDR ¼
ECPRD 100 % ECOBS
ð4Þ
For both models, the MDR was derived by dividing the predicted toxicity value (EC50) by the observed toxicity value. MDR values [1.3 mean that the toxicity of the mixture conforms with synergism while values \0.7 are taken to conform to antagonism. MDR is defined as a ratio of the predictive concentration (ECPRD) by a reference model to the observed concentration (ECOBS).
projection of the three-dimensional graph. The combination shown (dA, dB) is on a straight line between DA and DB, and is expected to be isoeffective to either DA or DB. [Adapted from Bosgra et al. (2009)]
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity
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Combined effects of the mixture by the CA model and the isobole method
Results Single pesticides Exposure to individual pesticides for 96 h resulted in sublethal, concentration dependent decreases in brain AChE activity among carps. No mortality was observed at any of the single-chemical exposure concentrations. No significant differences were found in baseline AChE activity between unexposed fish and those exposed to solvent alone (one-way ANOVAs, p [ 0.2). Concentration–response relationships were fit using a nonlinear regression. The resulting curve fit parameters for individual pesticides are reported in Table 1. According to EC50 values for AChE inhibition, the relative potencies of five pesticides vary, with the decreasing order as: triazophos [ chlorpyrifos [ fenobucarb [ carbosulfan [ malathion. Pesticide mixtures The individual toxicity (EC50) values of chlorpyrifos, triazophos, malathion, carbosulfan, and fenobucarb were used to set the concentrations used in the toxicity tests with mixtures. For each binary combination test, pesticides were assayed individually over a range of concentrations and together as a single mixture. The dose–response relationships for individual chemicals were used to calculate EC50 values in mixtures. The joint inhibitory effects of binary combinations of chlorpyrifos mixed with triazophos, fenobucarb, carbosulfan, and malathion on carp brain AChE activity are shown in Table 2. For equitoxic mixtures, the toxicity of malathion and carbosulfan ranged between 1.17 and 0.32 mg/l. Fenobucarb was approximately an order of magnitude more toxic than malathion, with EC50 values of 0.088 mg/l. Triazophos was the most toxic with EC50 values several orders of magnitude lower than malathion, its EC50 values was 0.0032 mg/l (Table 2).
Summaries of mixture toxicity assessments for binary pesticide mixtures are listed in Table 3. Combined effects of mixtures determined by the CA model and the isobole method resulted in the same pattern. In 50:50 % effect mixtures, when chlorpyrifos was mixed with fenobucarb and triazophos, the predicted toxicity was not significantly different from observed (MDR values were 0.97 and 1.08, respectively), suggesting concentration additive joint action (Table 3). In contrast, the expected mixture toxicity of chlorpyrifos plus carbosulfan was significantly less than observed, displaying antagonistic joint effect. While for the combination of chlorpyrifos and malathion, the predicted toxicity was higher than observed and the MDR value was [1.3, hence it was considered as synergistic. For equivalent dose mixtures, the observed toxicities of chlorpyrifos mixed with carbosulfan and triazophos were not significantly different from predicted and so was considered conforming to CA. When chlorpyrifos mixed with fenobucarb or malathion, the observed toxicities were significantly higher than predicted and had MDR values [1.3, suggesting a synergistic joint action (Table 3).
Discussion The isobole method is based on the theory of CA and mainly used qualitatively to characterize the effects of combinations, whether or not they show synergy or antagonism (Syberg et al. 2008). It is probably the most favored criterion for chemicals that act by a common mechanism of action, which is mainly used qualitatively to characterize the effects of combinations, whether or not they show synergy or antagonism (Berenbaum 1989). CA and the isobole method are considered equivalent.
Table 2 The concentrations of malathion, triazophos, fenobucarb, and carbosulfan within binary mixtures producing 50 % AChE inhibition (EC50) and the parameters of the curve fits in 50:50 % effect and equivalent dose mixture experiments Pesticide mixtures
Compound
50:50 % effect mixture EC50 (mg/l)
Chlorpyrifos ? triazophos
Equivalent dose mixture Slope (SEa)
EC50 (mg/l)
Slope (SE)
Chlorpyrifos
0.0093
0.85 (0.79)
0.0047
1.34 (1.01)
Triazophos
0.0032
0.85 (0.79)
0.0047
1.34 (1.01)
Chlorpyrifos ? fenobucarb
Chlorpyrifos Fenobucarb
0.0104 0.0884
1.43 (0.93) 1.43 (0.93)
0.0074 0.0074
1.85 (1.06) 1.85 (1.06)
Chlorpyrifos ? carbosulfan
Chlorpyrifos
0.015
1.88 (1.76)
0.016
1.45 (1.18)
Carbosulfan
0.32
1.88 (1.76)
0.016
1.45 (1.18)
Chlorpyrifos
0.0043
0.85 (0.80)
0.0075
1.68 (0.92)
Malathion
1.17
0.84 (0.80)
0.0075
1.68 (0.92)
Chlorpyrifos ? malathion a
Standard error of mean
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Table 3 Summaries of mixture toxicity assessments using the CA model and the isobole method for binary pesticide mixtures in 50:50 % dose mixture experiments Pesticide mixtures
50:50 % effect mixture Predicted EC50 (mg/l)
Observed EC50 (mg/l)
Equivalent dose mixture MDR
Type of combined action
Predicted EC50 (mg/l)
Observed EC50 (mg/l)
MDR
Type of combined action
Chlorpyrifos ? triazophos
0.014
0.0125
1.08
CA
0.010
0.009
1.10
CA
Chlorpyrifos ? fenobucarb
0.095
0.099
0.97
CA
0.036
0.015
2.42
Synergistic
Chlorpyrifos ? carbosulfan
0.224
0.335
0.67
Antagonistic
0.038
0.032
1.19
CA
Chlorpyrifos ? malathion
2.72
1.17
2.32
Synergistic
0.040
0.015
2.66
Synergistic
For the CA model and the isobole method, the model divergence ratio (MDR) is the ratio of the observed and predicted concentration or responses. An MDR value of 1 indicates adherence to the specified model. MDR values [1 indicates greater than expected toxicity and hence synergism among mixture components. MDR values\1 indicates less than expected toxicity and hence antagonism among mixture components. The classification of type of combined action is based on the observed concentration/isobole being outside the expected value, and the MDR reflecting a [30 % deviance from the CA or isobole The CA model and the isobole method gave the same results
However, in toxicological and pharmacological risk assessment, a method of dose addition (Bosgra et al. 2009) is widely used to calculate the cumulative effect of common mechanism chemicals, which is based on the assumption that any dose of B can be replaced by an equally effective dose of A in the mixture. According to Bosgra et al. (2009), if a combination is found to be zerointeractive by the isobole method, it is commonly assumed that dose addition may be used to calculate the cumulative effect, but the underlying assumptions differ between the methods. They could give the same prediction for chemicals with parallel dose–response curves on log-dose scale. But many factors determine the shape of the dose–response curves, and a common mechanism of action does not necessarily lead to parallel curves. In these cases, dose addition has different solutions depending on the index chemical chosen, while the isobole method has only one solution. These two methods are not equivalent in the field of toxicology and pharmacology. As recommended by Bosgra et al. (2009), the solution of outcomes of a mixture experiment may be compared to the situation of linear isoboles, then for synergistic combinations the left side of Eq. (4) will be smaller than 1 and for antagonistic combinations larger than 1. OP and CB insecticides are the most important AChE inhibitors and often called anticholinesterases. In the presence of these inhibitors, AChE becomes progressively inhibited and is not further capable of hydrolyzing ACh to choline and acetic acid (Jokanovic and Maksimovic 1997). Consequently, ACh accumulates at cholinergic receptor sites and affects cholinergic receptors throughout the central and peripheral nervous system (Jokanovic 2009). AchE has been used as a bioindicator of OP and CB pesticide exposures and linked to toxicity (Belden and Lydy 2000). In the present study, AChE activity was a sensitive indicator of
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OP and CB pesticide exposure and generally followed a dose-dependent relationship consistent with toxicity. Following the 96 h exposure to the pesticides, AChE activity decreased proportionally to exposure concentrations. In the present study, it is shown that in vivo exposures to binary mixtures of OP and CB pesticides produced different AChE inhibition types in the brains of carps (Table 3). However, in some other investigations, the OP, including their oxon metabolites, and CB insecticides do not interact in vitro, where their combinatorial inhibition of AChE can be explained by CA (Scholz et al. 2006). The departure from CA for some pesticide combinations in vivo could be explained if OP and CB insecticides act on other biochemical targets. Carboxylesterases (CaEs) are candidate enzymes that may underlie the OP and CB pesticide interactions (Laetz et al. 2009). CaEs play an important role in the detoxification of the OP and CB insecticides via hydrolysis (Jokanovic 2001; Wheelock et al. 2005; Laetz et al. 2009). CaEs may functionally protect AChE from insecticide toxicity by direct binding and sequestration, thereby preventing or delaying interaction between the insecticide and AChE (Jokanovic 2001). In Daphnia magna and in mammalian liver salmonids, the inhibition of CaEs was also observed to significantly enhance the toxicity of OP and CB pesticides (Barata et al. 2004). For all the insecticides, the concentrations that produce 50 % brain AChE inhibition in carps (Table 2) are generally much higher than the levels typically detected in surface water monitoring studies (Hoffman et al. 2000; Gilliom 2007; Verro et al. 2009). Our results show that 4 out of 8 pesticide combinations produce additive toxicity at low concentrations. Moreover, some certain combinations showed a pattern of synergism. For example, when chlorpyrifos was mixed with fenobucarb or malathion at equivalent effect levels, synergism is likely to occur at low
The combined toxicity assessment of carp (Cyprinus carpio) acetylcholinesterase activity
exposure concentrations. Where synergism occurs, additional safety factors could then be assigned to protect the health of aquatic species. With the exception of safety factors for synergism, this process is similar to how the FQPA mandates evaluating the human health risks of OP and CB mixtures (FQPA 1996). Although only four pesticides were investigated, it would be straightforward to establish concentration–response relationships for AChE inhibition for other authorized OP and CB insecticides in current use. The link between exposure level and toxicity has been criticized due to the variability factors including size of the organism, environmental conditions, species and individual variation, sampling type and storage, and laboratory techniques (Sturm et al. 1999; Sandahl and Jenkins 2002), which influence the reliability of the mixture toxicity prediction. It is an important factor when aiming at establishing a predictive mixture toxicity assessment in the regulatory environmental risk assessment context. Belden et al. (2007) found that more than eighty percent of all experiments that evaluated the CA model had observed effective concentrations within a factor of 2 of predicted values. In the current study, 5 out of 8 binary combinations were found to have MDR values between 0.67 and 1.19. Cedergreen et al. (2007) stated that the reproducibility of mixture experiments can hardly be guaranteed, given the impact of the large heterogeneity in the input data base due to variation among laboratories, test protocols, test species. This will not only depend on the setup but also on the species that is tested. If we consider clone individuals as test species experiments will have more chances to be reproducible than if the test organisms have genetically variability among specimens.
Conclusion Pesticide mixtures continue to pose major challenges for natural environments. Our results have important implications for ecological risk assessments, particularly those that focus on the toxicity of individual pesticide as the basis for estimating impacts to aquatic fish. The toxicity toward AChE activity inhibition in carp brains and the type of joint actions of four binary mixtures of five pesticides (chlorpyrifos, malathion, triazophos, fenobucarb, and carbosulfan) with the same modes of action to the activity of AChE were determined using the CA model and the isobole method. Both methods are based on the same theory in the field of ecotoxicological risk assessment. The pesticide mixtures were classed as antagonistic, additive and synergistic. These two methods do not markedly underestimate the toxicity of any tested mixture. Therefore, it is more appropriate to use to estimate the toxicity of mixtures.
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Acknowledgments This Project was supported by Zhejiang Provincial Natural Science Foundation of China (No. LY13C03006), the opening Project Fund of State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control (No. 2010DS700124KF1306) and the Innovation Project of Zhejiang Academy of Agricultural Sciences. Conflict of interest of interest.
The authors declare that they have no conflict
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