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Keywords:

  • Daphnia pulex;
  • Optical tracking;
  • Neonicotinoid;
  • Acetylcholinesterase inhibitor;
  • Sublethal

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

Many emerging contaminants tend to be biologically active at very low concentrations, occur in water as part of complex mixtures, and impact biota in ways that are not detected using traditional toxicity tests (e.g., median lethal concentration). To evaluate emerging contaminants, the authors developed a method for detecting sublethal behavioral effects by quantifying the swimming behavior of Daphnia pulex, a model organism for studying aquatic toxicity. This optical tracking technique is capable of measuring many swimming parameters, 2 of which—cumulative distance and angular change—are presented. To validate this technique, 2 prototypical compounds that exhibit different modes of action as well as corresponding insecticides that are commonly found in surface waters were investigated. The acetylcholinesterase (AChE) inhibitor physostigmine was used as the prototypical compound for the large number of AChE inhibitor insecticides (e.g., chlorpyrifos). Nicotine was used as the prototypical compound for neonicotinoid insecticides (e.g., imidacloprid). Results demonstrate that this assay is capable of detecting sublethal behavioral effects that are concentration-dependent and that insecticides with the same mode of action yield similar results. The method can easily be scaled up to serve as a high-throughput screening tool to detect sublethal toxic effects of a variety of chemicals. This method is likely to aid in enhancing the current understanding of emerging contaminants and to serve as a novel water-quality screening tool. Environ Toxicol Chem 2014;33:144–151. © 2013 SETAC


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

With advances in analytical techniques, the number of new chemicals being detected in surface waters is rapidly increasing. In a study of 139 streams throughout the United States evaluated between 1999 and 2000 [1], 82 out of 95 target organic waste contaminants were detected in 80% of the waterways investigated. Chemicals detected included prescription and nonprescription drugs, antibiotics, reproductive hormones, detergent metabolites, disinfectants, plasticizers, fire retardants, insecticides, and insect repellants. Collectively, these substances are now commonly referred to as “emerging contaminants” [2]. The number of substances detected that are classified as emerging contaminants continues to expand [3]. Further complicating assessments of toxicity, these chemicals are present in the environment as part of a complex mixture of compounds [4]. Evaluating the toxicity of emerging contaminants is challenged by limited means of assessment, testing procedures that are time-consuming and expensive, and limited understanding of what biological end points to use to evaluate human or ecosystem health. To obtain a more complete understanding of the toxicity of aquatic pollutants, a rapid and inexpensive method for quantifying sublethal effects is required. The present study focuses on addressing this need through the development of a high-throughput optical screening assay capable of quantifying sublethal effects on behavior in Daphnia pulex.

Even when compounds appear to be safe based on conventional testing, there is a growing body of literature documenting a broad range of sublethal effects such as reproductive and behavioral changes in fish, reptiles, mammals, and invertebrates [5]. For example, a dramatic decline in wildlife populations in the Indian subcontinent caused by emerging contaminants has been reported in the literature [6]. These observations are increasing concern over potential human exposure and resulting impacts on public health [7, 8]. Epidemiological studies suggest that significant impacts on human development can already be detected [9, 10]. While data collected thus far are inconclusive, the risk of chronic low-level exposure to humans through drinking water, food, or recreation is an area of active research.

Traditional methods for evaluating toxicity have primarily focused on determining median lethal concentrations (LC50s). However, significant impacts occur on organisms at concentrations well below LC50 levels, such as altered motor function and effects on development and reproduction. Such sublethal effects can impact the fitness and survival of target organisms and affect ecosystem function [11]. Differentiating sublethal from lethal toxic effects and determining how the concentration and duration of exposure influence these outcomes are critical to understanding the toxicity of emerging contaminants and complex mixtures. As a result, there is increasing interest in the development of high-throughput screening assays for evaluating the toxicity of the large number of chemical contaminants and mixtures (e.g., National Toxicology Program [http://ntp.niehs.nih.gov], Computational Toxicology Research [http://www.epa.gov/comptox/]). One approach that has been employed is the use of optical assays. For example, zooplankton have been optically tracked in larger-volume assay systems (>150 mL) with a primary focus on the study of swimming behavior relevant to function in aquatic ecosystems [12]. Such assay systems are very important to our understanding of zooplankton behavior but limited in their utility for high-throughput toxicity screening. A more recent study by Richendrfer et al. [13] incorporated the use of a high-throughput imaging system to demonstrate the effect of subchronic concentrations of chlorpyrifos on zebrafish larvae in a 6-well plate.

In the present study, physostigmine and nicotine were chosen as prototypical compounds to validate the optical assay. In addition to these 2 model compounds, 2 other commonly used pesticides, chlorpyrifos and imidacloprid, were evaluated. Physostigmine has been used extensively as a tool for studying physiological mechanisms, and its pharmacological properties as an acetylcholinesterase (AChE) inhibitor are well characterized [14]. As an AChE inhibitor, physostigmine causes an increase in acetylcholine (ACh) in organisms that can overstimulate the nicotinic and muscarinic receptors. Chlorpyrifos is an organophosphate insecticide that is an AChE inhibitor and, therefore, has a mode of action similar to physostigmine. Nicotine, formerly used as an insecticide [15], acts directly on the nicotinic receptor [16]. Imidacloprid is a neonicotinoid insecticide that is an agonist with greater selectivity for the insect nicotinic receptor. Neonicotinoid insecticides are currently under increased scrutiny because of their possible association with bee colony collapse [17].

Acetylcholine and its receptors are found in both vertebrates and invertebrates [18-20]. Many of the insecticides found in surface waters target cholinergic mechanisms, by either inhibiting AChE (e.g., chlorpyrifos) or directly stimulating ACh receptors (e.g., imidacloprid).

The enzyme AChE normally terminates the bioactive effects of ACh by breaking it down into acetate and choline [14]. As insecticides, AChE inhibitors increase ACh to toxic levels by inhibiting the enzyme responsible for ACh degradation. When the enzyme is inhibited, overstimulation of all ACh receptor subtypes (e.g., muscarinic and nicotinic) is expected to occur; and at sufficient concentrations, this effect is lethal. While there are structural differences between human and insect acteylcholinesterase enzymes [20], insecticides that inhibit AChE can readily inhibit human AChE and cause toxicity.

Neonicotinoids are a class of insecticides that target cholinergic mechanisms through a mode of action different from that of AChE inhibitors. Neonicotinoids are direct ACh receptor agonists that bind directly to the receptor and show selectivity for the insect nicotinic subtype of the ACh receptor [21]. Lethality results from overstimulation of the insect nicotinic ACh receptor subtype. The insecticides referred to as “neonicotinoids” are less toxic to vertebrates relative to the nicotinoids, such as nicotine and epibatidine [21]. However, the insecticides that affect cholinergic function cause overstimulation of ACh receptors. Insecticides that affect cholinergic function are known to be toxic to both vertebrates and invertebrates [14, 22]. The relative potency and probability of toxicity depend on differences in toxicodynamic and toxicokinetic properties [22, 23].

The freshwater crustacean Daphnia is commonly used in aquatic toxicity testing [24]. Daphnia are primary consumers of plankton (e.g., single-cell algae, bacteria, protists), a primary food source for larger invertebrate and vertebrate species and, therefore, considered to be at the base of the food chain in freshwater lakes [11]. The importance of Daphnia as keystone species in freshwater ecosystems is well known, and the genus has been recognized as a model organism for studying aquatic ecosystems over the past several decades. Daphnia are very sensitive to biotic and abiotic changes in their environment and have developed specific adaptation strategies to cope with changes in temperature, water chemistry (e.g., dissolved oxygen), food supply, and predation [25]. The motor function of crustaceans, like Daphnia, is complex. Rhythmic behavior in crustaceans can be seen as the output of nervous system motor programs that are modulated by hormones of the neuroendocrine system [26]. The Daphnia genome has been termed “ecoresponsive” because of the very large number of genes, including many duplicated genes, and its phenotypic plasticity and adaptive responses [27]. Daphnia are ideally suited for studying ecotoxicological effects and are used as a screening tool for potential environmental contamination [24]. Daphnia have been used extensively in the testing of pesticides, often using well-established US Environmental Protection Agency protocols.

To enhance our ability to assess the toxicity of emerging contaminants, a scalable method for quantifying sublethal behavior using freely swimming Daphnia was developed. With this aim, 2 hypotheses were evaluated: 1) concentration-dependent behavioral responses in Daphnia can be quantified by measuring changes in their movement, and 2) compounds with similar modes of action elicit similar behavioral responses.

MATERIAL AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

A single D. pulex collected from Lake Michigan in 2008 was reared into a clone and subsequently cultured in the laboratory until these experiments were conducted (2013). The Daphnia were housed in a 4-L jar in an incubator at 20 °C and exposed to equal light/dark cycles lasting 12 h. A 50/50 mixture of Ankistrodesmus falcatus and Chlamydomonas reinhardii algae were provided as food for Daphnia 3 times per week, and their water was changed weekly. Artificial lake water (COMBO) was used as the culture medium as it has been shown to support the growth of both algae and zooplankton [28].

Immediately prior to the experiments, Daphnia were removed from the culture and captured with a mesh screen to ensure animals of uniform size (>1.4 mm in length) and approximately the same age were used during experiments. Select Daphnia were then randomly placed in isolated wells in a translucent 24-well plate. Each well had 256 mm2 in surface area to the air above and contained 3 mL of aqueous solution when full. The 24-well plates allowed for limited natural vertical and horizontal swimming behavior by the Daphnia. For all experiments, a single animal was randomly placed into 1 of 6 wells in the middle of the 24-well plate containing different concentrations of the desired chemical (randomly assigned). On average, setup required approximately 5 min for the 6 Daphnia to be transferred before the experiment could begin. The isolation of animals in these 24-well plates is especially important to avoid animal interaction and enable efficient tracking.

Once the animals were added to the 24-well plate, the plate was placed on a raised platform where a standardized light source was projected from the bottom through a plastic paper diffuser. Fiber optics lighting was used to avoid overheating of the plates and Daphnia. Above the stage containing the 24-well plate, an Infinity2-1M monochrome camera (Lumenera) with an AF Nikkor 28-mm lens was used to capture live video recordings of Daphnia movements. The camera was held at a fixed distance of approximately 56 cm from the plate surface, providing 1280 × 1024 resolution. Live images were captured and recorded on the computer using Infinity Capture software (Lumenera) and saved in AVI format. Video analysis was performed using Image Pro Plus 7 software (Media Cybernetics) using the 2-dimensional (2D) tracking module calibrated to measure animal movement. Prior to conducting experiments, spatial filtration was applied to flatten images and reduce variations in background intensity. The image was then sharpened to enhance fine details. Using this experimental setup, the processing techniques employed resulted in images that were void of background noise. Prior to quantification, images were calibrated to provide 2D distance measurements in millimeters.

The data analysis of videos is described in Figure 1. Daphnia were given a 10-min acclimation period after all animals were placed into individual wells, to reduce the effects of the new environment on their behavior. After the initial 10-min exposure, 5-s videos were recorded every 10 min for 90 min (Figure 1A). With an initial 10-min acclimation period and 90 min of optical tracking, Daphnia were exposed to each chemical for approximately 100 min by the end of each experiment. Every 5-s recording resulted in a total of 145 images (i.e., frames; see Figure 2B), which were then used to track and quantify movement (Figure 1C). The video analysis software was then used to track, measure, and quantify (frame by frame) the movement of Daphnia (Figure 1C). In the example presented in Figure 1, the concentration of physostigmine increased from 0.25 µM in well number 1 to 4 µM in well number 5. The control (concentration = 0) was in well number 6.

image

Figure 1. Sublethal effects measured during 100 min experiments; (A) exposure is initiated 10 min prior to the first image recording at t = 0 min and every 10 min thereafter until the end of the experiment (t = 90 min); (B) during each 5-s recording, a total of 145 images (i.e., frames) are collected, which (C) are used to track and quantify movement.

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image

Figure 2. Example quantification of cumulative distance and change in angle.

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The cumulative distance Daphnia traveled and their angular change in direction were used to quantify movement (Figure 2). Cumulative distance was measured by summing the incremental distance moved between frames (n = 145) over the course of a 5s video. The change in angle was measured by comparing the change in the direction of vectors from one frame to the next. For example, an initial vector can be defined by the change in position of the animal between frames 1 and 2 and a second vector can be defined by the change in position of the animal between frames 2 and 3 (Figure 2). The angle between these 2 vectors is the change in angle. For this analysis, the change in angle reported is the average of the measure collected during each 5-s recording period (145 frames).

Stock solutions of 1 mM (physostigmine, nicotine) and 10 mM (chlorpyrifos, imidacloprid), as well as subsequent serial dilutions, were made on the same day experiments were performed. The chlorpyrifos stock solution was made by dissolving the insecticide in acetone. All other chemicals used in the present study were dissolved directly in COMBO. The highest concentration of chlorpyrifos (0.25 µM) studied contained 0.0025% acetone, and lower concentrations of chlorpyrifos (0.06 µM, 0.3 µM, 0.6 µM, 0.12 µM) contained proportionally less acetone. The control solution used for experiments with chlorpyrifos contained 0.0025% acetone in COMBO water.

To establish behaviorally relevant concentration ranges for the optical assay, Daphnia were exposed to 10 to 12 different concentrations of each chemical in 24-well plates and observed visually. Behavioral movements were observed continuously for 2 h and then again for a few minutes at 24 h and 48 h. The 6 concentrations selected for the optical analysis were based on visual observations, and bracketed LC50 values are reported [29]. The effects of the AChE inhibitors physostigmine and chlorpyrifos, the prototypical compound nicotine, and the neonicotinoid imidacloprid were examined in 5 trials for each individual chemical (n = 30 animals per chemical).

All statistical analyses were performed using Statistica (version 10; StatSoft). The dependent variables were cumulative distance and change in angle. These measures were obtained at 10-min intervals during 90 min of optical tracking. Independent variables included time (0–90 min), concentration, well number, treatment (chemical), and temperature. Repeated-measures analysis (time) was used to identify significant changes in the dependent variable (average cumulative distance or average angle) resulting from exposure to a certain chemical on Daphnia over the 90-min experiment. Analysis of covariance (ANCOVA) was conducted to control for variation in basal animal motor activity. The covariate in this case was the level of activity at time 0. By utilizing measures at t = 0 min as a covariate, the reduction in error variance increased the statistical power of the analysis. A least significant difference post hoc test was used to evaluate differences among means when there was a significant main or interaction effect in ANCOVA [30]. In the analysis of the data, each 24-well plate was considered a trial, and each plate held 6 animals. A typical experiment included 5 to 7 plates (30–42 animals).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

Physostigmine and chlorpyrifos

There was a significant concentration-dependent and chemical-dependent effect on the average cumulative distance resulting from altered swimming behavior (concentration × chemical interaction, p < 0.05; Table 1). For physostigmine, cumulative distances at concentration levels 2, 3, and 4 (0.5 µM, 1 µM, and 2 µM) were significantly greater than control (Figure 3A). The mean value at the 4-µM concentration was significantly lower than that at the 2-µM concentration, and the 4-µM concentration was not significantly different from control (time 0). However, optical tracking of the highest concentration of physostigmine (4 µM) at 90 min demonstrated that 3 of the animals were immobile (moving less than 5 mm in 5 s) and 2 of them were hardly moving (Figure 4). Motor function was optically observed through the daphnid exoskeleton after exposure of single animals to 4 µM physostigmine at a magnification of 40×; the swimming antennae and appendages no longer showed spontaneous movement, but the heart was still beating (D.K. Pitts, unpublished data).

Table 1. Repeated-measures analysis of covariance of cumulative distance for physostigmine versus chlorpyrifos
EffectSum of squaresDegrees of freedomMean squareFp
Intercept27 944127 94466.7690.0000
Covariate (time 0)4101141019.8000.0030
Concentration level14 143528296.7680.0001
Chemical18 805118 80544.9320.0000
Concentration × chemical5649511302.7000.0317
Error19 67147419  
Time197882471.6320.1141
Time × covariate153381921.2650.2606
Time × concentration6018401500.9930.4864
Time × chemical111881400.9220.4978
Time × concentration × chemical7699401921.2710.1329
Error56 963376152  
image

Figure 3. Behavioral responses of Daphnia pulex to acetylcholinesterase inhibitor and neonicotinoids. Concentration levels 0 to 5 were, respectively, 0 µM, 0.25 µM, 0.5 µM, 1 µM, 2 µM, and 4 µM for physostigmine (n = 5); 0 µM, 0.016 µM, 0.3 µM, 0.06 µM, 0.12 µM, and 0.25 µM for chlorpyrifos (n = 5); 0 µM, 1 µM, 4 µM, 16 µM, 64 µM, and 256 µM for nicotine (n = 6); and 0 µM, 4 µM, 16 µM, 64 µM, 256 µM, and 1024 µM for imidacloprid (n = 5). Error bars are the standard error. Asterisks indicate significant (p < 0.05, least significant difference test) difference for each chemical relative to the control. Asterisks along the axis indicate a significant (p < 0.05, least significant difference test) difference in the response observed between compounds with the same mode of action.

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image

Figure 4. Mean response, with standard error, during optical tracking for the 3 highest concentrations of (A) physostigmine, with control (n = 6), and (B) nicotine, with control (n = 6). Asterisks indicate statistically significant (p < 0.05, least significant difference test) difference from control. Note: At the 90-min time point for physostigmine (A), immobility was observed for 3 animals at 4 µM physostigmine, and a 2-sample Student's t test indicated that the mean value for physostigmine (8.8 ± 3.5 mm) was statistically different from control (21.1 ± 3.8 mm, p < 0.001).

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The cumulative distance response to chlorpyrifos resembled that of physostigmine (Figure 3A), with the highest concentration causing immobilization. However, in contrast to physostigmine, there was not a significant concentration-dependent increase in cumulative distance caused by midrange concentrations of chlorpyrifos (concentration by chemical interaction, p < 0.05, Table 1; least significant difference test, Figure 3A). Low concentrations of chlorpyrifos have also been shown to significantly affect the swimming behavior of zebrafish in a developmental study by Richendrfer et al. [13] that involved longer exposure periods and slightly lower concentrations. These results suggest that the motor behavior of zebrafish and D. pulex can be affected at similarly low concentrations of chlorpyrifos and that assays that compare these species may be very useful in assessing aquatic toxicity in invertebrate and vertebrate models.

A significant concentration-dependent increase in angle was found for physostigmine and chlorpyrifos (concentration main effect, p < 0.001; Table 2), which did not differ significantly across chemicals (Table 2, concentration by chemical interaction p > 0.20). At the highest concentration of physostigmine (level 5, 4 µM) where immobility was observed, there was a significant increase in average angle (Figure 3C, least significant difference test); and a similar situation occurred for chlorpyrifos at the highest concentration level (0.25 µM; Figure 3C, least significant difference test).

Table 2. Repeated-measures analysis of covariance of change in angle for physostigmine versus chlorpyrifos
EffectSum of squaresDegrees of freedomMean squareFp
Intercept341 1391341 139142.5130.0000
Covariate (time 0)13 865113 8655.7920.0201
Concentration level105 041521 0088.7760.0000
Chemical11 425111 4254.7730.0339
Concentration by chemical329256590.2750.9245
Error112 506472394  
Time27 924834918.4130.0000
Time × covariate766889592.3100.0199
Time × concentration37 684409422.2710.0000
Time × chemical450085631.3560.2145
Time × concentration × chemical17 398404351.0480.3955
Error1 555 993376415  

For cumulative distance, interactions with time were not significant (Table 1, p > 0.10). In Figure 4A, the effect of physostigmine on the cumulative distance Daphnia travel over time is broken down to show an example of the effect over time. The average of all means over time for a given concentration in Figure 4A is mathematically equal to the single mean for a concentration in Figure 3A. Contrast analysis (all means) indicated that the response observed during exposure to 1 µM and 2 µM of physostigmine was significantly different from the control (p < 0.005), while the response observed during exposure to 4 µM of physostigmine was not significantly different from the control (p > 0.20) (Figure 4A).

Nicotine and imidacloprid

A significant concentration-dependent effect of these chemicals on cumulative distance was found (concentration main effect, p < 0.001), which did not differ across chemicals (concentration × chemical, p > 0.20; Supplemental Data, Tables S1 and S2). At higher concentrations, cumulative distances at nicotine concentration levels 3 and 4 (16 µM and 64 µM) were significantly greater than the control (Figure 3B). None of the animals were immobilized by the higher concentrations of nicotine over the 100-min period of exposure. The general shape of the cumulative distance response curve to nicotine was strikingly similar to that of the neonicotinoid imidacloprid (chemical main effect, p > 0.10; concentration × chemical effect, p > 0.20; Figure 3B). No sustained immobilization occurred at the highest concentrations of imidacloprid (1024 µM).

To illustrate the complexity of the effects of nicotine on the average cumulative distance, the response over time is depicted in Figure 4B. The interaction between time and concentration was significant (p < 0.001). As discussed previously, the average of all means over time for a given concentration in Figure 4B is mathematically equal to the single mean for a concentration in Figure 3B. For the contrast analysis (all means) depicted in Figure 4B the responses of Daphnia to 16 µM and 64 µM of nicotine were significantly different from the control, while the overall difference in cumulative distance traveled was not significant for exposure to 256 µM versus the control (p > 0.20). However, by examining pairs of means from the 256 µM exposure data set using contrast analysis, the lower-level response observed at t = 10 min and t = 20 min was found to be significantly different from the controls (p < 0.05), and the higher-level response at t = 70 min and t = 80 min was also found to be significantly different from the controls (p < 0.01). This analysis suggests that at the highest nicotine concentration (256 µM), the swimming activity of Daphnia was initially suppressed but the animals were able to, at least partially, overcome this effect by 70 min to 80 min into the exposure period.

When the change in angle was evaluated for nicotine and imidacloprid, a significant concentration-dependent change in angle was found (concentration main effect, p < 0.01), which did not differ across chemicals (concentration by chemical interaction, p > 0.20). The response curves for the change in angle for nicotine and imidacloprid were strikingly similar (Figure 3D).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

As described previously, AChE inhibitors and neonicotinoids were selected in the present study because of their prevalent use and ability to induce sublethal effects [31-34]. Two different dependent variables, cumulative distance and change in angle, were examined to evaluate the sublethal behavioral response of Daphnia to insecticides that affect cholinergic function via 2 modes of action. When the behavioral response patterns were compared, the response profile was found to be similar for compounds with the same mode of action but dissimilar for compounds with different modes of action (Figure 3). After 100 min of exposure, higher concentrations of the AChE inhibitors physostigmine and chlorpyrifos tended to result in immobility and the change in angle in the direction of movement was found to increase significantly. This increase in angular change corresponded to a decrease in cumulative distance (Figure 3). It is worth noting that the concentration of chlorpyrifos used was more than an order of magnitude lower than that of physostigmine because higher concentrations of chlorpyrifos were found to result in very rapid immobility (data not shown).

In contrast, nicotine and imidacloprid did not elicit long-lasting immobility during the study period, even though relatively high concentrations were utilized (maximum concentrations of 256 µM and 1024 µM for nicotine and imidacloprid, respectively). For nicotine and imidacloprid, changes in the cumulative distance and the change in angle appeared to be mirror images of each other, with the maximum cumulative distance occurring at concentrations where the minimum change in angle occurred (Figure 3B and D). When the time course for the cumulative distance response to nicotine was examined (Figure 4B), the highest concentration (256 µM) was found to cause an initial suppression of swimming behavior during the first 20 min of optical tracking, followed by a partial recovery and a significant increase in swimming distance at 70 min to 80 min relative to the control. The observation that the animals could overcome the initial suppressive effects on swimming behavior during the highest nicotine concentration used (256 µM) suggests that Daphnia are able to partially overcome some of the motor effects of nicotine and imidacloprid, at least on a short-term basis. This is supported by the significant increase in cumulative distance (Figure 3B, levels 3 and 4) and a decrease in the change in angle (Figure 3D, level 4). This transient suppressive effect on motor function in Daphnia was not observed for the 2 AChE inhibitors physostigmine and chlorpyrifos. It seems likely, based on the reported actions of AChE inhibitor on invertebrates and vertebrates [22, 35, 36], that intense stimulation of all ACh receptors subtypes by the AChE inhibitor may be responsible for long-lasting immobility and death.

One striking difference between physostigmine (a carbamate) and chlorpyrifos (an organophosphate) was the significant stimulatory effect of physostigmine on swimming behavior that was seen as an increase in cumulative distance at the midrange concentrations and was absent for chlorpyrifos (Figure 3A). Preliminary results suggest that another AChE inhibitor and insecticide, diazinon (an organophosphate), has a behavioral response profile similar to physostigmine with a stimulatory phase at low concentrations, but with immobilization at higher concentrations (data not shown). It is possible that the stimulatory phase seen with physostigmine, but not chlorpyrifos, could be related to toxicokinetic differences. Kretschmann et al. [37] developed a toxicokinetic model for diazinon in Daphnia magna using the immobility LC50 as the behavioral end point and found that there is a high degree of biotransformation of diazinon in D. magna by cytochrome P450. Studies of vertebrates have shown that the carbamate physostigmine binds to the AChE enzyme and forms a covalent bond, which can be hydrolyzed, the compound released, and the effect reversed [36]. The actions of organophosphate AChE inhibitors are generally more long-lasting than those of the carbamates [38]. Preliminary results from single-animal studies in our laboratory (D.K. Pitts, unpublished data) suggest that the effects of physostigmine on daphnid motor behavior can be at least partially reversed by several hours of perfusion with normal COMBO medium.

The expectation is that this assay method could easily be scaled up to screen a large number of compounds and that the information obtained will complement other assays that focus on different end points, such as reproduction, mortality, and growth rate. It is important to note that even though well plates are not representative of Daphnia's natural environment, standard toxicity tests using Daphnia as model organisms also employ artificial environments. Additionally, nominal concentrations were used for all analyses. With an octanol–water partitioning coefficient (KOW) of 104.7 [39], the concentration at which the toxic effects of chlorpyrifos were observed (e.g., immobility) was likely underestimated due to sorption to the well plate. All other compounds investigated had KOW values less than 101.5 [40]. This use of nominal concentrations was deemed suitable to demonstrate the utility of the optical method. It is expected that the behavioral effects will provide valuable insight into physiological processes in Daphnia. These behavioral effects may occur in the natural environment and translate to other organisms, ultimately resulting in reductions in fitness. Effects on behavioral response can also result in population-level impacts. For example, adverse population-level impacts have occurred in many animal species as a result of behavioral changes associated with chemical exposure, including failure to secure a mate and failure to escape predation [38].

CONCLUSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

The optical assay developed was capable of detecting acute sublethal behavioral effects within the 90-min time period used in the present study. Significant deviations in both the cumulative distance and the change in angle support the first hypothesis posed, that concentration-dependent behavioral responses can be quantified by measuring changes in movement. Similar responses were observed between prototypical compounds and insecticides with the same mode of action. This evidence directly supports the second hypothesis evaluated, that compounds with similar modes of action can produce similar behavioral responses. The method can easily be scaled up to serve as a high-throughput screening tool to detect sublethal toxic effects of a variety of chemicals, chemical concentrations, specific chemical interactions, and the effects of complex mixtures. Because this method can quantify sublethal effects relatively rapidly and inexpensively, it has the potential to enhance our understanding of the toxic effects of emerging contaminants.

Acknowledgment

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

This project was made possible through support provided by Wayne State University Departments of Biological Sciences, Civil and Environmental Engineering, Health Care Sciences (Occupational and Environmental Health Sciences), and Pharmaceutical Sciences. We acknowledge the assistance of Civil and Environmental Engineering student J. Finkelman, Pharmaceutical Sciences graduate student B. Hannan, and Pharmacy students A. Joseph, J. Khami, R. Kassem, H. Mansour, S. Mahajan, S. Mahmutovic, R. Nakhle, M. Varghese, C. Yousif, and L. Zaree. The constructive comments provided by the 3 anonymous reviewers greatly enhanced this manuscript and are appreciated.

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  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIAL AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. CONCLUSION
  8. SUPPLEMENTAL DATA
  9. Acknowledgment
  10. REFERENCES
  11. Supporting Information

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