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Copper interacts with nonylphenol to cancel the effect of nonylphenol on fish chemosensory behaviour
Aquatic Toxicology 142–143 (2013) 203–209
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Aquatic Toxicology journal homepage: www.elsevier.com/locate/aquatox
Copper interacts with nonylphenol to cancel the effect of nonylphenol on fish chemosensory behaviour Ashley J.W. Ward a,∗ , Maria Thistle b , Khashayar Ghandi c , Suzanne Currie b a b c
School of Biological Sciences, University of Sydney, Sydney, NSW, Australia Department of Biology, Mount Allison University, Sackville, NB, Canada Department of Chemistry and Biochemistry, Mount Allison University, Sackville, NB, Canada
a r t i c l e
i n f o
Article history: Received 11 March 2013 Received in revised form 19 August 2013 Accepted 20 August 2013 Keywords: Ecotoxicology Shoaling Sociality Chemical ecology Info-disruption Social attraction
a b s t r a c t The majority of ecotoxicological studies have been concerned with responses of organisms to a single contaminant. While this approach remains valid, the challenge now is to understand the way in which multiple contaminants and stressors interact to produce effects in study organisms. Here we take an integrated biological and physico-chemical approach to understand the effects of 4-nonylphenol and copper on fish (white perch, Morone americana) chemosensory behaviour. We show that a one hour exposure to 2 g L−1 nonylphenol removes chemosensory attraction to conspecific chemical cues, while exposure to 5 g L−1 copper for one hour had no significant effect on the fish’s attraction to these cues. Further, we show that simultaneous exposure to both contaminants at the stated dosage and for the same duration has no significant effect on the chemosensory attraction of white perch to conspecific chemical cues suggesting that copper mediates the effect of nonylphenol on fish in this respect. Physico-chemical data show that copper ions bind to nonylphenol in water, providing a mechanistic explanation for this change in the effect of nonylphenol. Furthermore, the finding that the copper ions bind to the lone pair of O on the nonylphenol molecule offers the tantalising possibility that it is this region of the nonylphenol molecule that plays the key role in disrupting fish chemical communication. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Pollution as a result of human activity presents a range of challenges for the organisms that live in those habitats. The effects of such pollution may sometimes be acute and dramatic, such as the mass deaths that occur periodically in response to major chemical spills. But while these events capture headlines and attention, it is arguably the day-to-day and comparatively low-level contamination of environments which present the greater long term ecological challenge. Ecotoxicological studies have reported a broad range of behavioural, physiological and cellular effects of pollutants on aquatic organisms (Berrill et al., 1993; Little et al., 1990; Sloman and Wilson, 2006). The overwhelming majority of laboratory based ecotoxicology studies have concentrated on the response of organisms to a single chemical at one time. Although it is clearly necessary to understand organismal responses to specific chemicals, a criticism that is sometimes made of this approach is that it fails to capture the complex chemical situation encountered by animals in the wild, where many contaminants may be present simultaneously (Cleveland et al.,
∗ Corresponding author. Tel.: +61 2 9351 4778; fax: +61 2 9351 4778. E-mail address: [email protected] (A.J.W. Ward). 0166-445X/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.aquatox.2013.08.010
1986). Furthermore, there is sometimes a disparity between laboratory and field studies of chemical ecology and ecotoxicology whereby the findings of the latter fail to match the predictions of the former (Archard et al., 2008; Grue et al., 2002; Marentette et al., 2012). This may be because wild populations gradually acclimatize to contaminated habitats, or that the effects of contaminants are exaggerated in the potentially more stressful environment of the laboratory (Marentette et al., 2012). Alternatively it may be because multiple contaminants interact in the field to form chemical complexes that change considerably the toxicological impact that each chemical might produce on an organism in isolation. Specifically, interacting chemicals could conceivably produce either synergistic, additive or antagonistic effects on organisms (An et al., 2004; Wu et al., 2013). Contamination of aquatic habitats through the input of anthropogenic chemicals is a widespread problem and the effects on aquatic organisms are diverse (Harmon, 2009). One particular problem that has been identified in recent years is the propensity of contaminants, even at very low concentrations, to act as ‘info-disruptors’, impairing the chemosensory abilities of aquatic organisms (Lurling and Scheffer, 2007). In fishes, chemical communication supports a suite of social behaviours, including shoaling, territoriality and mate choice (Liley, 1982). Each individual fish has a ‘chemical signature’ that is extremely important for social
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recognition (Sisler and Sorensen, 2008). This signature is strongly influenced by both recent habitat and recent diet (Ward et al., 2004, 2007). Shoaling fish are socially attracted to individuals that smell similar to themselves, suggesting chemical self-referencing (Ward et al., 2005; Webster et al., 2007). Thus, a chemical signature conveys information to other individuals and is of considerable importance in structuring social interactions, allowing fish to operate within their social environment and to gain important local information (Herbert-Read et al., 2010). Chemical cues are also used extensively in courtship (Wyatt, 2003). They enable fish to identify and locate potential mates, and to carry more subtle information that enable discrimination between kin and unrelated individuals (Ward and Hart, 2003). Contaminants in the environment are capable of disrupting fish chemical communication (van der Sluijs et al., 2011), even at levels significantly below legal toxicity limits, and that this can have serious effects on their social behaviour, breaking up shoals (Ward et al., 2008) and damaging their ability to find mates (Fisher et al., 2006). Two key functional groups of aquatic contaminants degrade fish communication: one group, which includes many metallic contaminants, affects the ability of fish to detect and respond to chemical cues by damaging the chemosensory apparatus (Boyd, 2010); the other group, including many lipophilic chemicals, such as nonylphenol, appear to affect the chemical signature of individuals, changing the way they smell to other fish (Fabian et al., 2007; Ward et al., 2006). Copper is a widely used element in aquatic ecotoxicological studies because of its widespread use in human society and hence its common frequency as a contaminant (Pyle and Mirza, 2007). Studies of fish exposed to copper have shown impairment of olfactory responses following a 30 min exposure to 20 g L−1 (McIntyre et al., 2008) or a 3 h exposure to doses as low as 1–2 g L−1 (Sandahl et al., 2007) in juvenile coho salmon (Oncorhynchus kisutch). Copper impairs chemosensory function both by affecting the performance of nerve cells comprising the olfactory bulb and by damaging olfactory receptor cells (Hara et al., 1976; Julliard et al., 1993; Winberg et al., 1992). Similarly, we have previously shown that exposure to low (5 g L−1 ), short-term (1 h) doses of the lipophilic chemical, 4nonylphenol, used widely as a surfactant in a variety of industrial and sewage treatment processes, has no discernible effect on the chemosensory ability of fish, but does affect the responses of conspecifics towards exposed fish (Ward et al., 2008). In this study, representatives of a strongly shoaling species, the banded killifish (Fundulus diaphanus), avoided the normally attractive conspecific chemical cues when a stimulus group of fish had been exposed to nonylphenol. Both copper and nonylphenol are common contaminants of aquatic ecosystems (Dwyer et al., 2005; McIntyre et al., 2012; Soares et al., 2008) and frequently co-occur since both are by-products of many industrial and domestic human activities. Based on these previous studies, we hypothesised that another shoaling species, juvenile white perch (Morone americana), would be attracted to conspecific chemical cues (CCCs) in a control treatment, but would not be attracted to CCCs following the exposure of experimental fish to short-term, low concentrations of (a) 4-nonylphenol, (b) copper and (c) a combination of both 4nonylphenol and copper. Specifically, that fish presented in a flow channel with a plume of conspecific chemical cues (CCCs) and a plume of water without CCCs would spend more time in the CCC plume when the stimulus fish had been exposed for an hour to a control treatment of dilute ethanol, but that no preference for either plume would be expressed when the stimulus fish had been exposed to the 4-nonylphenol and/or copper treatments. Subsequently we used physical chemistry techniques to determine possible interactions between 4-nonylphenol and copper ions in solution.
2. Materials and methods 2.1. Study animals and collection area Juvenile white perch (M. americana, Gmelin) were collected using a beach seine from Silver Lake, a small (130 ha) impounded lake, located near Sackville, New Brunswick, Canada (45◦ 55 N, 64◦ 21 W). Fish were transported to Mount Allison University where they were held in 1300 L tanks fitted with an aerated, flow-through, well water system maintained at 13 ± 1 ◦ C. Fish experienced a 14 h:10 h light:dark cycle and were fed ad libitum daily with defrosted frozen bloodworm for a period of 20 days prior to the commencement of experiments. We used fish that were visually free of parasites and measured 30 ± 5 mm in all experimental trials. The white perch is a common species in eastern North American water bodies, inhabiting a range of aquatic environments from brackish water estuaries to freshwater ponds and rivers (Scott and Scott, 1988) and form into large shoals as juveniles (Bigelow and Schroeder, 2002). 2.2. Treatments and dosing protocol We dosed both stimulus fish and focal fish for each trial and each treatment using 12 L glass dosing aquariums as in Ward et al. (2008). Before each trial, 10 fish were added to each aquarium and allowed to acclimatize for 1 h. The aquarium contained aged well water, aerated by an air stone. After the acclimatization period, the fish were subjected to one of four chemical treatment groups: ethanol (vehicle control, 10%, v/v solution), 4-NP (2 g L−1 ), copper (5 g L−1 , copper (II) sulphate pentahydrate, Sigma–Aldrich, St. Louis, MO), and 4-NP and copper (concentrations as before). These concentrations were achieved by adding 10 mL of stock solutions to the 12 L of clean water in the dosing aquaria. Stock solutions were made by dissolving each chemical in a 10% ethanol/90% water solution. The dosage levels were selected on the basis of previous experiments on the effects of these contaminants on chemosensory function in fishes (McIntyre et al., 2008; Ward et al., 2008). Fish were exposed to the treatment for 1 h, after which they were removed from the dosing aquarium and rinsed in aged well water to remove any excess water from the dosing aquarium. Stimulus fish were then added to a reservoir bucket in the flow channel apparatus. Focal fish were held in aged well water until the beginning of their trial. None of the fish showed signs of stress during or after the exposure. 2.3. Experimental equipment and protocol We used a flow channel and a simple binary choice experiment to assess the individual and cumulative effects of copper and 4-nonylphenol (4-NP) on social recognition behaviour in juvenile white perch. The flow channel was the same as used in Ward et al. (2008) and measured 71 cm × 38 cm × 20 cm (L × W × D) and was constructed from Perspex. Removable mesh barriers divided the flow channel into three compartments, with the middle compartment measuring 34 cm × 38 cm × 20 cm (L × W × D) (see Fig. 1). The bottom of the central compartment was covered with a thin layer of sand substrate. A flow-through water system entered the chamber at two locations – the top left and top right corners – from two 15 L reservoir buckets at a rate of 380 ± 20 mL min−1 and exited at the bottom left and right corners through two holes drilled into the walls. In this way, two parallel streams were created within the flow channel. We placed baffles within the currents, perpendicular to the flow of water, to help maintain the integrity of the two parallel plumes. This flow regime was tested repeatedly with coloured dye to ensure the plumes remained parallel and that mixing between the plumes was minimized. Using this protocol, we defined three
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Fig. 1. Aerial view of experimental apparatus.
equally sized zones within the flow channel–a neutral zone in the centre and a zone for each plume (see Fig. 1). For each trial, we added 10 stimulus fish to one of the reservoir buckets. Stimulus fish were rinsed with clean water prior to being added to the reservoir tank in order to reduce the transfer of excess chemical to the bucket. In keeping with results from the coloured dye experiments, we waited 30 min for cues from the stimulus fish to fully develop a chemical plume in the flow channel, after which we added a single focal fish to the neutral zone. The focal fish was exposed to the same dosing treatment and protocol as the stimulus fish. The focal fish was placed in a 10 cm diameter mesh cylinder and allowed to acclimatize for 5 min. Following the 5 min, the mesh cylinder was raised by a pulley, the focal fish was released, and the timed trial began. Focal fish were observed for 150 s, during which we recorded the total time spent in each of the three zones. The focal fish and stimulus fish were removed following the trial and were not used in subsequent trials. We waited 30 min between trials to allow any residual chemical cues to flow through the channel. We alternated which reservoir bucket containing the stimulus fish between trials. In total, 16 replicates were conducted per treatment. 2.4. Data analysis To examine whether or not focal fish spent more time in the plume containing CCCs than in the blank water plume we used paired sample t-tests within each of our four treatments. Secondly, we tested whether the time spent by focal fish in the plume containing CCCs differed across treatments using ANOVA with a Student Newman Keuls (SNK) post hoc procedure. All analyses were performed in SPSS v.19 using an alpha level of 0.05. 2.5. Physicochemical analysis In order to investigate the possibility of interaction between nonylphenol and copper in solution we employed two physicochemical techniques, IR spectroscopy and fluorescence spectroscopy. All materials were obtained from Sigma–Aldrich. 4-NP was analytical grade. CuSO4 was anhydrous powder ≥99.99%. 2.5.1. IR spectroscopy We carried out IR spectroscopy to examine the aromatic OH (ArOH) vibrational changes as concentrations of CuSO4 were increased in the solutions. A change in frequency would indicate
different bond character and can experimentally confirm the possibility of copper complex formation with the alkyl phenol. A stock solution was made for 4-NP with concentration 882.4 mg L. A stock solution of CuSO4 was made with concentration of 637.6 mg L. Separate sample solutions were made by mixing 10, 4, 2, and 1 mL nonylphenol and 4-methylphenol with 10 and 20 mL of the CuSO4 stock solution respectively and diluting to 25 mL of 18.2 M deionized water. The molar ratios of the phenol to copper salts are in the range of 1:1–1:20. All spectra were recorded on a Thermo Nicolet FT-Infrared 200 spectrometer at ambient temperature. Pellets were made using 200 mg of potassium bromide and one drop of sample solution. A torque of 25 foot pounds was applied for one minute to compress salt into pellets. 2.5.2. Fluorescence spectroscopy We carried out fluorescence spectroscopy in order to study potential micelle formation in aqueous solutions of 4-NP at concentrations 0.5 g L, 1.0 g L, 2.0 g L, 3.0 g L, 4.0 g L. In addition, we made a solution of CuSO4 in distilled deionized water at concentration 5 g L and added incremental amounts of 4-NP. We monitored fluorescence spectra throughout to determine whether the 4-NP was interacting with the copper ions. Both fluorescence and excitation spectra were recorded at ambient temperature to measure the changes in intensities with respect to concentration. Fluorescence spectra were taken under an excitation wavelength of 260 nm and recorded emissions from 200 nm to 770 nm. Excitation spectra were taken with excitation wavelengths of 200–700 nm and emissions were monitored at 300 nm. 2.5.3. Computational analysis To gain a better understanding of the binding of copper ions to phenols and the implications on IR spectra, we carried out computational studies of vibrational and binding energies of phenols to Cu2+ ions using ortho- and para-isomers of alkyl phenols with various alkyl chain lengths as models. For all of the models with the positively charged form, the formal charge was considered to be +1 and the spin multiplicity was considered to be 1. For all models of neutral molecules the charge was set to 0, and spin multiplicity to 1. All of the quantum chemistry calculations were performed using G03W. Geometry optimization and frequency calculations were performed using density functional theory (Parr and Yang, 1989)
Mean (± SE) me (s) spent in odour plumes
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100
**
*
Ethanol (control)
Copper
**
80
60
40
20
0
4-np
Copper + 4-np
Treatment Fig. 2. Mean (± SE) time (s) spent by juvenile white perch in conspecific odour plume (grey shading) and in blank odour plume (no shading) in each of four treatments. Two asterisks indicate a significant difference between time spent in the two plumes at the 0.01 level, one asterisk indicates a significant difference at the 0.05 level based on a paired t-test of time spent in each plume within each treatment. N = 16 for each treatment.
with the B3LYP functional (Becke, 1993, Lee et al., 1988) and the 6-311G(d) basis set. Initial calculations were done in gas phase. To take the solvent into account, calculations were completed using the polarizable continuum model (PCM), specifically the integral equation formalism model, further referenced as IEFPCM (Tomasi et al., 2005) which includes solvent dielectric effects. 3. Results 3.1. Flow channel experiments Focal fish in the ethanol control spent more time in the plume containing conspecific chemical cues than in the blank water plume, as did those in the copper treatment and those in the combined copper and 4-NP treatments (ethanol control: paired T-test: T = 3, n = 16, p < 0.01; copper: paired T-test: T = 2.35, n = 16, p = 0.03; combined copper & 4-np: paired T-test: T = 2.88, n = 16, p = 0.01). Focal fish in the 4-NP treatment did not spend more time in the plume containing conspecific chemical cues than in the blank water plume (paired T-test: T = 0.3, n = 16, p = 0.77). There was a significant difference in the amount of time that focal fish spent in the plume containing conspecific chemical cues across the four treatments (ANOVA: F3,60 = 3.51, p = 0.02; see Fig. 2). The SNK test determined that the time spent by focal fish in the plume containing CCCs was significantly lower in the 4-NP treatment than in the other three treatments. 3.2. Physicochemical analysis The IR spectra of the nonylphenol solutions had a broad peak at ∼3500 cm−1 . A new peak at ∼2970 cm−1 was always observed when CuSO4 was added to the nonylphenol. The peak intensity was increased by increasing the copper concentration, which is suggestive of the binding of the copper to nonylphenol. To better understand this putative binding of copper to nonylphenol, quantum chemical calculations were performed. The optimized structures of nonylphenols and their bound geometry to copper are presented in Fig. 3(a)–(d). The data in Table 1 includes some of the computational results, in particular the vibrational OH stretching frequencies for nonylphenol and its bound state to copper, and the associated geometrical parameters and binding energies.
The experimental observation of the new (relatively sharp) peak shifted by more than 500 cm−1 to a smaller vibrational frequency compared to the broad H-bonding peak of the OH coincides with the computational data in Table 1 and suggests binding between Cu2+ and nonylphenol. The binding energy of copper to paranonylphenol is also very large as shown in Table 1. Computational data indicate that in the presence of explicit water molecules, different types of binding can be noticed with different frequencies in the 3700 cm−1 range (Table 1). This accounts for the broad H-bonded peak. As we increased the number of explicit water molecules, the binding energy decreased. Upon taking the spectra for the mixture of ortho- and paranonylphenol isomers with different concentrations of copper we observed peaks around 2900–3000 cm−1 . The optimized geometries in water (continuum model) are presented in Fig. 3(e) and (f). The binding of copper to ortho-nonylphenol is energetically unfavourable according to our computational data and does not shift the OH stretching to smaller frequencies significantly (unlike the para-nonylphenol isomer evidenced by our computational data). Both of these results when compared to our vibrational spectra suggest that copper will bind significantly more to the para- than the ortho-nonylphenol isomer. The OH bond length in the bound complex to ortho-nonylphenol isomer is 0.9818 A˚ (Table 1) which is smaller than the OH bond length in the bound complex to the para˚ This is while the CO bond length nonylphenol isomer (1.0073 A). and CuOH bond angle in the ortho-nonylphenol isomer are larger than in para-nonylphenol isomer hence the CO bond is weaker in the ortho-nonylphenol isomer. The larger angle (∼10◦ ) is partially responsible for the steric effect in ortho isomer that would make the binding of copper to ortho isomer unlikely. Different binding of copper to para vs. ortho isomers could mediate the effects of combinations of nonylphenol and copper on fish chemosensory behaviour. The fluorescence intensities of the aqueous nonylphenol solution decreased as the concentration increased up to approximately 3 g L−1 , indicating the aggregation of nonylphenol into micelles. Once the number of these aggregates began to rise at concentrations of near 4.0 g L−1 the intensity also rose due to the increase in the formed aggregates (Fig. 4). In the presence of CuSO4 a similar trend of micelle formation in nonylphenol was observed, suggesting that despite copper binding to the nonylphenol it does not prevent micelle formation although it shifts the concentration for micelle formation. The solution of CuSO4 produced three peaks with wavelengths from 200 to 300 nm. As the nonylphenol was added these peaks were displaced by a larger, broad peak at 310 nm. When emissions were monitored at 260 nm peaks were observed at ∼250 nm, 550 nm and a broad peak in the range of 300–400 nm. The peak at 550 nm was shifted upon addition of 4-NP. These results are also suggestive of interaction of copper ions with nonylphenol and are consistent with the IR and computational measurements.
4. Discussion White perch showed a strong preference for a plume containing conspecific cues in the ethanol control treatment, demonstrating that social attraction is mediated by chemical cues in this species. However, fish that had been exposed to 4-NP showed no preference for either plume, a finding consistent with Ward et al. (2008), suggesting that nonylphenol, even at these very low concentrations, interferes with chemical recognition. Unexpectedly, copper did not produce any marked effect on species recognition, most likely as a result of the low dosage and short exposure time. Copper has been shown to affect fish olfaction at concentrations at or below
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Fig. 3. Optimized molecular structures of Cu2+ and nonylphenol. The grey spheres are C atoms, red spheres are O, orange spheres are Cu2+ ions and the white spheres are H atoms. (a) para nonylphenol: (b) para nonylphenol bound to Cu2+ ; (c) para nonylphenol in water (continuum model); (d) para nonylphenol nonylphenol in water (continuum model) bound to Cu2+ ; (e) optimised structure of ortho nonylphenol in water; (f) optimized structure of ortho nonylphenol in water (continuum model) bound to Cu2+ . (For interpretation of the references to color in the artwork, the reader is referred to the web version of the article.)
5 g L−1 , but after 3 h of exposure (e.g. Baldwin et al., 2011; Sandahl et al., 2007). Our data indicate that a 1 h exposure to 5 g L−1 is not long enough to elicit any negative effects on fish olfaction as determined from our behavioural assay in this particular species. However, when fish were dosed with copper and nonylphenol in concert, they showed an apparently undiminished ability to be able to recognise and occupy the conspecific plume, suggesting that the chemicals interact to decrease toxicity. Our physicochemical results suggest a mechanism for this interaction, indicating that copper ions bind to nonylphenol in water. Based on the combination of our vibrational spectra and computational data, it is likely that these metal ions bind only to the pararather than the ortho-isomer. Since the ions bind to the lone pair of O in nonylphenol (Fig. 3 and Table 1), and since the combination of copper ions and nonylphenol cancels out the effect of nonylphenol on the fish, it suggests that it is the lone pair of O in nonylphenol that has the key info-disruptive effect on fish. To the best of our knowledge, this is the first time this has been identified as most often, any negative effects of 4-NP have been attributed to its estrogenic potential. In our earlier work, we demonstrated that the effect of 4-NP on the chemical signature of the fish was not attributable to its action as an environmental estrogen, as we saw no effect in treatments with 17-estradiol (Ward et al., 2008). A
future study on ortho-NP and copper on the fish can further evaluate this mechanism. The natural environment is seldom contaminated by a solitary chemical compound. Rather, pollution usually occurs as a result of broad ranging and complex human domestic or industrial processes in which many separate chemicals may be implicated. These may interact to produce unpredictable effects on the behaviour or physiology of affected organisms (An et al., 2004; Wu et al., 2013) or may augment the effects of other environmental stressors (Coors and De Meester, 2008; Kimberly and Salice, 2013). The results here indicate that chemicals may interact agonistically to cancel out the deleterious effects that they might produce in isolation, at least on the sensory behaviour of fish. The possibility remains, of course, that new compounds formed may produce new and unforeseen effects at the physiological or histological level. While this possibility cannot be ruled out based on the present study, behaviour is a highly sensitive indicator of physiological stress and it seems unlikely that effects on one could occur without implications for the other (Clotfelter et al., 2004; Scott and Sloman, 2004). The constant challenge for laboratory-based ecotoxicological studies is to incorporate as much ecological relevance into the experimental design as possible while retaining the essential controls that allow proper interpretation of results. However, the task
Table 1 Summary of computational results for para-nonylphenol (the bond lengths are in Angstrom). Compound
Nonylphenol Nonylphenol (water:continuum)
OH stretching frequency (cm−1 )
Non-complexed bond length
Complexed bond length
Bond angle
Non complexed
Complexed
O H
O H
Cu O H
3700 3701
3694 2995
0.9716 0.9716
0.97247 1.00727
116 114.2
Binding energy (Kcal/mol)
−566.2 −540
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Excitaon intensity at
Max
500
400
300
200 0
1
2
3
4
Concentraon (μg·l) Fig. 4. Excitation intensity at the wavelength of maximum intensity (max ) around 305 nm for para nonylphenol in water at different concentrations. The black diamonds are data in the absence of copper, while clear squares are data in the presence of copper.
of experimentally assessing the effects of huge numbers of contaminant chemicals, both separately and in combination, is daunting, if not impossible. One approach to this problem will be to consider functional groups of chemicals, or chemicals with different modes of action in an ecotoxicological sense (Escher and Hermens, 2002), as we have done here. Another direction will be to make greater use of computational chemistry to derive testable predictions a priori. Acknowledgements The authors would like to thank Wayne Anderson for his assistance in the laboratory and Alex Duguay for performing the spectroscopic measurements and performing the quantum calculations. In addition, the authors would also like to thank the editor and two anonymous reviewers whose comments greatly improved this manuscript. References An, Y.J., Kim, Y.M., Kwon, T.I., Jeong, S.W., 2004. Combined effect of copper, cadmium, and lead upon Cucumis sativus growth and bioaccumulation. Sci. Total Environ. 326, 85–93. Archard, G.A., Cuthill, I.C., Partridge, J.C., van Oosterhout, C., 2008. Female guppies (Poecilia reticulata) show no preference for conspecific chemosensory cues in the field or an artificial flow chamber. Behaviour 145, 1329–1346. Baldwin, D.H., Tatara, C.P., Scholz, N.L., 2011. Copper-induced olfactory toxicity in salmon and steelhead: Extrapolation across species and rearing environments. Aquatic Toxicology 101, 295–297. Becke, A.D., 1993. A new mixing of Hartree-Fock and local density-functional theories. J Chem Phys 98, 1372–1377. Berrill, M., Bertram, S., Wilson, A., Louis, S., Brigham, D., Stromberg, C., 1993. Lethal and sublethal impacts of pyrethroid insecticides on amphibian embryos and tadpoles. Environ. Toxicol. Chem. 12, 525–539. Bigelow, H.B., Schroeder, W.C., 2002. Bigelow and Schroeder’s Fishes of the Gulf of Maine. Smithsonian, Washington. Boyd, R.S., 2010. Heavy metal pollutants and chemical ecology: exploring new frontiers. J. Chem. Ecol. 36, 46–58. Cleveland, L., Little, E.E., Hamilton, S.J., Buckler, D.R., Hunn, J.B., 1986. Interactive toxicity of aluminum and acidity to early life stages of brook trout. Trans. Am. Fish. Soc. 115, 610–620. Clotfelter, E.D., Bell, A.M., Levering, K.R., 2004. The role of animal behaviour in the study of endocrine-disrupting chemicals. Anim. Behav. 68, 665–676. Coors, A., De Meester, L., 2008. Synergistic, antagonistic and additive effects of multiple stressors: predation threat, parasitism and pesticide exposure in Daphnia magna. J. Appl. Ecol. 45, 1820–1828.
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Interactive effects of contaminants and climaterelated stressors: high temperature increases sensitivity to cadmium. Environ. Toxicol. Chem. 32, 1337–1343. Lee, C., Yang, W., Parr, R.G., 1988. Development of the Colle-Salvetti correlationenergy formula into a functional of the electron density. Phys. Rev. B 37, 785–789. Liley, N.R., 1982. Chemical communication in fish. Can. J. Fish. Aquat. Sci. 39, 22–35. Little, E.E., Archeski, R.D., Flerov, B.A., Kozlovskaya, V.I., 1990. Behavioral indicators of sublethal toxicity in rainbow-trout. Arch. Environ. Contam. Toxicol. 19, 380– 385. Lurling, M., Scheffer, M., 2007. Info-disruption: pollution and the transfer of chemical information between organisms. Trends Ecol. Evol. 22, 374–379. Marentette, J.R., Tong, S., Wang, G., Sopinka, N.M., Taves, M.D., Koops, M.A., Balshine, S., 2012. Behavior as biomarker? Laboratory versus field movement in round goby (Neogobius melanostomus) from highly contaminated habitats. Ecotoxicology 21, 1003–1012. 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The effects of environmental pollutants on complex fish behaviour: integrating behavioural and physiological indicators of toxicity. Aquat. Toxicol. 68, 369–392. Scott, W.B., Scott, M.G., 1988. Atlantic fishes of Canada. University of Toronto Press. Sisler, S.P., Sorensen, P.W., 2008. Common carp and goldfish discern conspecific identity using chemical cues. Behaviour 145, 1409–1425. Sloman, K.A., Wilson, R.W., 2006. Anthropogenic impacts upon behavior and physiology. In: Sloman, K.A., Wilson, R.W., Balshine, S. (Eds.), Behavior and Physiology of Fish. Elsevier Academic Press, San Diego, pp. 413–468. Soares, A., Guieysse, B., Jefferson, B., Cartmell, E., Lester, J.N., 2008. Nonylphenol in the environment: a critical review on occurrence, fate, toxicity and treatment in wastewaters. Environ. Int. 34, 1033–1049. Tomasi, J., Mennucci, B., Cammi, R., 2005. Quantum mechanical continuum solvation models. Chem. Rev. 105, 2999–3093. van der Sluijs, I., Gray, S.M., Amorim, M.C.P., Barber, I., Candolin, U., Hendry, A.P., Krahe, R., Maan, M.E., Utne-Palm, A.C., Wagner, H.J., Wong, B.B.M., 2011. Communication in troubled waters: responses of fish communication systems to changing environments. Evol. Ecol. 25, 623–640. Ward, A.J.W., Duff, A.J., Currie, S., 2006. The effects of the endocrine disrupter 4nonylphenol on the behaviour of juvenile rainbow trout (Oncorhynchus mykiss). Can. J. Fish. Aquat. Sci. 63, 377–382. Ward, A.J.W., Duff, A.J., Horsfall, J.S., Currie, S., 2008. Scents and scents-ability: pollution disrupts chemical social recognition and shoaling in fish. Proc. R. Soc. Lond. B: Biol. Sci. 275, 101–105. Ward, A.J.W., Hart, P.J.B., 2003. The effects of kin and familiarity on interactions between fish. Fish Fish. 4, 348–358.
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Contents lists available at ScienceDirect
Aquatic Toxicology journal homepage: www.elsevier.com/locate/aquatox
Copper interacts with nonylphenol to cancel the effect of nonylphenol on fish chemosensory behaviour Ashley J.W. Ward a,∗ , Maria Thistle b , Khashayar Ghandi c , Suzanne Currie b a b c
School of Biological Sciences, University of Sydney, Sydney, NSW, Australia Department of Biology, Mount Allison University, Sackville, NB, Canada Department of Chemistry and Biochemistry, Mount Allison University, Sackville, NB, Canada
a r t i c l e
i n f o
Article history: Received 11 March 2013 Received in revised form 19 August 2013 Accepted 20 August 2013 Keywords: Ecotoxicology Shoaling Sociality Chemical ecology Info-disruption Social attraction
a b s t r a c t The majority of ecotoxicological studies have been concerned with responses of organisms to a single contaminant. While this approach remains valid, the challenge now is to understand the way in which multiple contaminants and stressors interact to produce effects in study organisms. Here we take an integrated biological and physico-chemical approach to understand the effects of 4-nonylphenol and copper on fish (white perch, Morone americana) chemosensory behaviour. We show that a one hour exposure to 2 g L−1 nonylphenol removes chemosensory attraction to conspecific chemical cues, while exposure to 5 g L−1 copper for one hour had no significant effect on the fish’s attraction to these cues. Further, we show that simultaneous exposure to both contaminants at the stated dosage and for the same duration has no significant effect on the chemosensory attraction of white perch to conspecific chemical cues suggesting that copper mediates the effect of nonylphenol on fish in this respect. Physico-chemical data show that copper ions bind to nonylphenol in water, providing a mechanistic explanation for this change in the effect of nonylphenol. Furthermore, the finding that the copper ions bind to the lone pair of O on the nonylphenol molecule offers the tantalising possibility that it is this region of the nonylphenol molecule that plays the key role in disrupting fish chemical communication. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Pollution as a result of human activity presents a range of challenges for the organisms that live in those habitats. The effects of such pollution may sometimes be acute and dramatic, such as the mass deaths that occur periodically in response to major chemical spills. But while these events capture headlines and attention, it is arguably the day-to-day and comparatively low-level contamination of environments which present the greater long term ecological challenge. Ecotoxicological studies have reported a broad range of behavioural, physiological and cellular effects of pollutants on aquatic organisms (Berrill et al., 1993; Little et al., 1990; Sloman and Wilson, 2006). The overwhelming majority of laboratory based ecotoxicology studies have concentrated on the response of organisms to a single chemical at one time. Although it is clearly necessary to understand organismal responses to specific chemicals, a criticism that is sometimes made of this approach is that it fails to capture the complex chemical situation encountered by animals in the wild, where many contaminants may be present simultaneously (Cleveland et al.,
∗ Corresponding author. Tel.: +61 2 9351 4778; fax: +61 2 9351 4778. E-mail address: [email protected] (A.J.W. Ward). 0166-445X/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.aquatox.2013.08.010
1986). Furthermore, there is sometimes a disparity between laboratory and field studies of chemical ecology and ecotoxicology whereby the findings of the latter fail to match the predictions of the former (Archard et al., 2008; Grue et al., 2002; Marentette et al., 2012). This may be because wild populations gradually acclimatize to contaminated habitats, or that the effects of contaminants are exaggerated in the potentially more stressful environment of the laboratory (Marentette et al., 2012). Alternatively it may be because multiple contaminants interact in the field to form chemical complexes that change considerably the toxicological impact that each chemical might produce on an organism in isolation. Specifically, interacting chemicals could conceivably produce either synergistic, additive or antagonistic effects on organisms (An et al., 2004; Wu et al., 2013). Contamination of aquatic habitats through the input of anthropogenic chemicals is a widespread problem and the effects on aquatic organisms are diverse (Harmon, 2009). One particular problem that has been identified in recent years is the propensity of contaminants, even at very low concentrations, to act as ‘info-disruptors’, impairing the chemosensory abilities of aquatic organisms (Lurling and Scheffer, 2007). In fishes, chemical communication supports a suite of social behaviours, including shoaling, territoriality and mate choice (Liley, 1982). Each individual fish has a ‘chemical signature’ that is extremely important for social
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recognition (Sisler and Sorensen, 2008). This signature is strongly influenced by both recent habitat and recent diet (Ward et al., 2004, 2007). Shoaling fish are socially attracted to individuals that smell similar to themselves, suggesting chemical self-referencing (Ward et al., 2005; Webster et al., 2007). Thus, a chemical signature conveys information to other individuals and is of considerable importance in structuring social interactions, allowing fish to operate within their social environment and to gain important local information (Herbert-Read et al., 2010). Chemical cues are also used extensively in courtship (Wyatt, 2003). They enable fish to identify and locate potential mates, and to carry more subtle information that enable discrimination between kin and unrelated individuals (Ward and Hart, 2003). Contaminants in the environment are capable of disrupting fish chemical communication (van der Sluijs et al., 2011), even at levels significantly below legal toxicity limits, and that this can have serious effects on their social behaviour, breaking up shoals (Ward et al., 2008) and damaging their ability to find mates (Fisher et al., 2006). Two key functional groups of aquatic contaminants degrade fish communication: one group, which includes many metallic contaminants, affects the ability of fish to detect and respond to chemical cues by damaging the chemosensory apparatus (Boyd, 2010); the other group, including many lipophilic chemicals, such as nonylphenol, appear to affect the chemical signature of individuals, changing the way they smell to other fish (Fabian et al., 2007; Ward et al., 2006). Copper is a widely used element in aquatic ecotoxicological studies because of its widespread use in human society and hence its common frequency as a contaminant (Pyle and Mirza, 2007). Studies of fish exposed to copper have shown impairment of olfactory responses following a 30 min exposure to 20 g L−1 (McIntyre et al., 2008) or a 3 h exposure to doses as low as 1–2 g L−1 (Sandahl et al., 2007) in juvenile coho salmon (Oncorhynchus kisutch). Copper impairs chemosensory function both by affecting the performance of nerve cells comprising the olfactory bulb and by damaging olfactory receptor cells (Hara et al., 1976; Julliard et al., 1993; Winberg et al., 1992). Similarly, we have previously shown that exposure to low (5 g L−1 ), short-term (1 h) doses of the lipophilic chemical, 4nonylphenol, used widely as a surfactant in a variety of industrial and sewage treatment processes, has no discernible effect on the chemosensory ability of fish, but does affect the responses of conspecifics towards exposed fish (Ward et al., 2008). In this study, representatives of a strongly shoaling species, the banded killifish (Fundulus diaphanus), avoided the normally attractive conspecific chemical cues when a stimulus group of fish had been exposed to nonylphenol. Both copper and nonylphenol are common contaminants of aquatic ecosystems (Dwyer et al., 2005; McIntyre et al., 2012; Soares et al., 2008) and frequently co-occur since both are by-products of many industrial and domestic human activities. Based on these previous studies, we hypothesised that another shoaling species, juvenile white perch (Morone americana), would be attracted to conspecific chemical cues (CCCs) in a control treatment, but would not be attracted to CCCs following the exposure of experimental fish to short-term, low concentrations of (a) 4-nonylphenol, (b) copper and (c) a combination of both 4nonylphenol and copper. Specifically, that fish presented in a flow channel with a plume of conspecific chemical cues (CCCs) and a plume of water without CCCs would spend more time in the CCC plume when the stimulus fish had been exposed for an hour to a control treatment of dilute ethanol, but that no preference for either plume would be expressed when the stimulus fish had been exposed to the 4-nonylphenol and/or copper treatments. Subsequently we used physical chemistry techniques to determine possible interactions between 4-nonylphenol and copper ions in solution.
2. Materials and methods 2.1. Study animals and collection area Juvenile white perch (M. americana, Gmelin) were collected using a beach seine from Silver Lake, a small (130 ha) impounded lake, located near Sackville, New Brunswick, Canada (45◦ 55 N, 64◦ 21 W). Fish were transported to Mount Allison University where they were held in 1300 L tanks fitted with an aerated, flow-through, well water system maintained at 13 ± 1 ◦ C. Fish experienced a 14 h:10 h light:dark cycle and were fed ad libitum daily with defrosted frozen bloodworm for a period of 20 days prior to the commencement of experiments. We used fish that were visually free of parasites and measured 30 ± 5 mm in all experimental trials. The white perch is a common species in eastern North American water bodies, inhabiting a range of aquatic environments from brackish water estuaries to freshwater ponds and rivers (Scott and Scott, 1988) and form into large shoals as juveniles (Bigelow and Schroeder, 2002). 2.2. Treatments and dosing protocol We dosed both stimulus fish and focal fish for each trial and each treatment using 12 L glass dosing aquariums as in Ward et al. (2008). Before each trial, 10 fish were added to each aquarium and allowed to acclimatize for 1 h. The aquarium contained aged well water, aerated by an air stone. After the acclimatization period, the fish were subjected to one of four chemical treatment groups: ethanol (vehicle control, 10%, v/v solution), 4-NP (2 g L−1 ), copper (5 g L−1 , copper (II) sulphate pentahydrate, Sigma–Aldrich, St. Louis, MO), and 4-NP and copper (concentrations as before). These concentrations were achieved by adding 10 mL of stock solutions to the 12 L of clean water in the dosing aquaria. Stock solutions were made by dissolving each chemical in a 10% ethanol/90% water solution. The dosage levels were selected on the basis of previous experiments on the effects of these contaminants on chemosensory function in fishes (McIntyre et al., 2008; Ward et al., 2008). Fish were exposed to the treatment for 1 h, after which they were removed from the dosing aquarium and rinsed in aged well water to remove any excess water from the dosing aquarium. Stimulus fish were then added to a reservoir bucket in the flow channel apparatus. Focal fish were held in aged well water until the beginning of their trial. None of the fish showed signs of stress during or after the exposure. 2.3. Experimental equipment and protocol We used a flow channel and a simple binary choice experiment to assess the individual and cumulative effects of copper and 4-nonylphenol (4-NP) on social recognition behaviour in juvenile white perch. The flow channel was the same as used in Ward et al. (2008) and measured 71 cm × 38 cm × 20 cm (L × W × D) and was constructed from Perspex. Removable mesh barriers divided the flow channel into three compartments, with the middle compartment measuring 34 cm × 38 cm × 20 cm (L × W × D) (see Fig. 1). The bottom of the central compartment was covered with a thin layer of sand substrate. A flow-through water system entered the chamber at two locations – the top left and top right corners – from two 15 L reservoir buckets at a rate of 380 ± 20 mL min−1 and exited at the bottom left and right corners through two holes drilled into the walls. In this way, two parallel streams were created within the flow channel. We placed baffles within the currents, perpendicular to the flow of water, to help maintain the integrity of the two parallel plumes. This flow regime was tested repeatedly with coloured dye to ensure the plumes remained parallel and that mixing between the plumes was minimized. Using this protocol, we defined three
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Fig. 1. Aerial view of experimental apparatus.
equally sized zones within the flow channel–a neutral zone in the centre and a zone for each plume (see Fig. 1). For each trial, we added 10 stimulus fish to one of the reservoir buckets. Stimulus fish were rinsed with clean water prior to being added to the reservoir tank in order to reduce the transfer of excess chemical to the bucket. In keeping with results from the coloured dye experiments, we waited 30 min for cues from the stimulus fish to fully develop a chemical plume in the flow channel, after which we added a single focal fish to the neutral zone. The focal fish was exposed to the same dosing treatment and protocol as the stimulus fish. The focal fish was placed in a 10 cm diameter mesh cylinder and allowed to acclimatize for 5 min. Following the 5 min, the mesh cylinder was raised by a pulley, the focal fish was released, and the timed trial began. Focal fish were observed for 150 s, during which we recorded the total time spent in each of the three zones. The focal fish and stimulus fish were removed following the trial and were not used in subsequent trials. We waited 30 min between trials to allow any residual chemical cues to flow through the channel. We alternated which reservoir bucket containing the stimulus fish between trials. In total, 16 replicates were conducted per treatment. 2.4. Data analysis To examine whether or not focal fish spent more time in the plume containing CCCs than in the blank water plume we used paired sample t-tests within each of our four treatments. Secondly, we tested whether the time spent by focal fish in the plume containing CCCs differed across treatments using ANOVA with a Student Newman Keuls (SNK) post hoc procedure. All analyses were performed in SPSS v.19 using an alpha level of 0.05. 2.5. Physicochemical analysis In order to investigate the possibility of interaction between nonylphenol and copper in solution we employed two physicochemical techniques, IR spectroscopy and fluorescence spectroscopy. All materials were obtained from Sigma–Aldrich. 4-NP was analytical grade. CuSO4 was anhydrous powder ≥99.99%. 2.5.1. IR spectroscopy We carried out IR spectroscopy to examine the aromatic OH (ArOH) vibrational changes as concentrations of CuSO4 were increased in the solutions. A change in frequency would indicate
different bond character and can experimentally confirm the possibility of copper complex formation with the alkyl phenol. A stock solution was made for 4-NP with concentration 882.4 mg L. A stock solution of CuSO4 was made with concentration of 637.6 mg L. Separate sample solutions were made by mixing 10, 4, 2, and 1 mL nonylphenol and 4-methylphenol with 10 and 20 mL of the CuSO4 stock solution respectively and diluting to 25 mL of 18.2 M deionized water. The molar ratios of the phenol to copper salts are in the range of 1:1–1:20. All spectra were recorded on a Thermo Nicolet FT-Infrared 200 spectrometer at ambient temperature. Pellets were made using 200 mg of potassium bromide and one drop of sample solution. A torque of 25 foot pounds was applied for one minute to compress salt into pellets. 2.5.2. Fluorescence spectroscopy We carried out fluorescence spectroscopy in order to study potential micelle formation in aqueous solutions of 4-NP at concentrations 0.5 g L, 1.0 g L, 2.0 g L, 3.0 g L, 4.0 g L. In addition, we made a solution of CuSO4 in distilled deionized water at concentration 5 g L and added incremental amounts of 4-NP. We monitored fluorescence spectra throughout to determine whether the 4-NP was interacting with the copper ions. Both fluorescence and excitation spectra were recorded at ambient temperature to measure the changes in intensities with respect to concentration. Fluorescence spectra were taken under an excitation wavelength of 260 nm and recorded emissions from 200 nm to 770 nm. Excitation spectra were taken with excitation wavelengths of 200–700 nm and emissions were monitored at 300 nm. 2.5.3. Computational analysis To gain a better understanding of the binding of copper ions to phenols and the implications on IR spectra, we carried out computational studies of vibrational and binding energies of phenols to Cu2+ ions using ortho- and para-isomers of alkyl phenols with various alkyl chain lengths as models. For all of the models with the positively charged form, the formal charge was considered to be +1 and the spin multiplicity was considered to be 1. For all models of neutral molecules the charge was set to 0, and spin multiplicity to 1. All of the quantum chemistry calculations were performed using G03W. Geometry optimization and frequency calculations were performed using density functional theory (Parr and Yang, 1989)
Mean (± SE) me (s) spent in odour plumes
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100
**
*
Ethanol (control)
Copper
**
80
60
40
20
0
4-np
Copper + 4-np
Treatment Fig. 2. Mean (± SE) time (s) spent by juvenile white perch in conspecific odour plume (grey shading) and in blank odour plume (no shading) in each of four treatments. Two asterisks indicate a significant difference between time spent in the two plumes at the 0.01 level, one asterisk indicates a significant difference at the 0.05 level based on a paired t-test of time spent in each plume within each treatment. N = 16 for each treatment.
with the B3LYP functional (Becke, 1993, Lee et al., 1988) and the 6-311G(d) basis set. Initial calculations were done in gas phase. To take the solvent into account, calculations were completed using the polarizable continuum model (PCM), specifically the integral equation formalism model, further referenced as IEFPCM (Tomasi et al., 2005) which includes solvent dielectric effects. 3. Results 3.1. Flow channel experiments Focal fish in the ethanol control spent more time in the plume containing conspecific chemical cues than in the blank water plume, as did those in the copper treatment and those in the combined copper and 4-NP treatments (ethanol control: paired T-test: T = 3, n = 16, p < 0.01; copper: paired T-test: T = 2.35, n = 16, p = 0.03; combined copper & 4-np: paired T-test: T = 2.88, n = 16, p = 0.01). Focal fish in the 4-NP treatment did not spend more time in the plume containing conspecific chemical cues than in the blank water plume (paired T-test: T = 0.3, n = 16, p = 0.77). There was a significant difference in the amount of time that focal fish spent in the plume containing conspecific chemical cues across the four treatments (ANOVA: F3,60 = 3.51, p = 0.02; see Fig. 2). The SNK test determined that the time spent by focal fish in the plume containing CCCs was significantly lower in the 4-NP treatment than in the other three treatments. 3.2. Physicochemical analysis The IR spectra of the nonylphenol solutions had a broad peak at ∼3500 cm−1 . A new peak at ∼2970 cm−1 was always observed when CuSO4 was added to the nonylphenol. The peak intensity was increased by increasing the copper concentration, which is suggestive of the binding of the copper to nonylphenol. To better understand this putative binding of copper to nonylphenol, quantum chemical calculations were performed. The optimized structures of nonylphenols and their bound geometry to copper are presented in Fig. 3(a)–(d). The data in Table 1 includes some of the computational results, in particular the vibrational OH stretching frequencies for nonylphenol and its bound state to copper, and the associated geometrical parameters and binding energies.
The experimental observation of the new (relatively sharp) peak shifted by more than 500 cm−1 to a smaller vibrational frequency compared to the broad H-bonding peak of the OH coincides with the computational data in Table 1 and suggests binding between Cu2+ and nonylphenol. The binding energy of copper to paranonylphenol is also very large as shown in Table 1. Computational data indicate that in the presence of explicit water molecules, different types of binding can be noticed with different frequencies in the 3700 cm−1 range (Table 1). This accounts for the broad H-bonded peak. As we increased the number of explicit water molecules, the binding energy decreased. Upon taking the spectra for the mixture of ortho- and paranonylphenol isomers with different concentrations of copper we observed peaks around 2900–3000 cm−1 . The optimized geometries in water (continuum model) are presented in Fig. 3(e) and (f). The binding of copper to ortho-nonylphenol is energetically unfavourable according to our computational data and does not shift the OH stretching to smaller frequencies significantly (unlike the para-nonylphenol isomer evidenced by our computational data). Both of these results when compared to our vibrational spectra suggest that copper will bind significantly more to the para- than the ortho-nonylphenol isomer. The OH bond length in the bound complex to ortho-nonylphenol isomer is 0.9818 A˚ (Table 1) which is smaller than the OH bond length in the bound complex to the para˚ This is while the CO bond length nonylphenol isomer (1.0073 A). and CuOH bond angle in the ortho-nonylphenol isomer are larger than in para-nonylphenol isomer hence the CO bond is weaker in the ortho-nonylphenol isomer. The larger angle (∼10◦ ) is partially responsible for the steric effect in ortho isomer that would make the binding of copper to ortho isomer unlikely. Different binding of copper to para vs. ortho isomers could mediate the effects of combinations of nonylphenol and copper on fish chemosensory behaviour. The fluorescence intensities of the aqueous nonylphenol solution decreased as the concentration increased up to approximately 3 g L−1 , indicating the aggregation of nonylphenol into micelles. Once the number of these aggregates began to rise at concentrations of near 4.0 g L−1 the intensity also rose due to the increase in the formed aggregates (Fig. 4). In the presence of CuSO4 a similar trend of micelle formation in nonylphenol was observed, suggesting that despite copper binding to the nonylphenol it does not prevent micelle formation although it shifts the concentration for micelle formation. The solution of CuSO4 produced three peaks with wavelengths from 200 to 300 nm. As the nonylphenol was added these peaks were displaced by a larger, broad peak at 310 nm. When emissions were monitored at 260 nm peaks were observed at ∼250 nm, 550 nm and a broad peak in the range of 300–400 nm. The peak at 550 nm was shifted upon addition of 4-NP. These results are also suggestive of interaction of copper ions with nonylphenol and are consistent with the IR and computational measurements.
4. Discussion White perch showed a strong preference for a plume containing conspecific cues in the ethanol control treatment, demonstrating that social attraction is mediated by chemical cues in this species. However, fish that had been exposed to 4-NP showed no preference for either plume, a finding consistent with Ward et al. (2008), suggesting that nonylphenol, even at these very low concentrations, interferes with chemical recognition. Unexpectedly, copper did not produce any marked effect on species recognition, most likely as a result of the low dosage and short exposure time. Copper has been shown to affect fish olfaction at concentrations at or below
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Fig. 3. Optimized molecular structures of Cu2+ and nonylphenol. The grey spheres are C atoms, red spheres are O, orange spheres are Cu2+ ions and the white spheres are H atoms. (a) para nonylphenol: (b) para nonylphenol bound to Cu2+ ; (c) para nonylphenol in water (continuum model); (d) para nonylphenol nonylphenol in water (continuum model) bound to Cu2+ ; (e) optimised structure of ortho nonylphenol in water; (f) optimized structure of ortho nonylphenol in water (continuum model) bound to Cu2+ . (For interpretation of the references to color in the artwork, the reader is referred to the web version of the article.)
5 g L−1 , but after 3 h of exposure (e.g. Baldwin et al., 2011; Sandahl et al., 2007). Our data indicate that a 1 h exposure to 5 g L−1 is not long enough to elicit any negative effects on fish olfaction as determined from our behavioural assay in this particular species. However, when fish were dosed with copper and nonylphenol in concert, they showed an apparently undiminished ability to be able to recognise and occupy the conspecific plume, suggesting that the chemicals interact to decrease toxicity. Our physicochemical results suggest a mechanism for this interaction, indicating that copper ions bind to nonylphenol in water. Based on the combination of our vibrational spectra and computational data, it is likely that these metal ions bind only to the pararather than the ortho-isomer. Since the ions bind to the lone pair of O in nonylphenol (Fig. 3 and Table 1), and since the combination of copper ions and nonylphenol cancels out the effect of nonylphenol on the fish, it suggests that it is the lone pair of O in nonylphenol that has the key info-disruptive effect on fish. To the best of our knowledge, this is the first time this has been identified as most often, any negative effects of 4-NP have been attributed to its estrogenic potential. In our earlier work, we demonstrated that the effect of 4-NP on the chemical signature of the fish was not attributable to its action as an environmental estrogen, as we saw no effect in treatments with 17-estradiol (Ward et al., 2008). A
future study on ortho-NP and copper on the fish can further evaluate this mechanism. The natural environment is seldom contaminated by a solitary chemical compound. Rather, pollution usually occurs as a result of broad ranging and complex human domestic or industrial processes in which many separate chemicals may be implicated. These may interact to produce unpredictable effects on the behaviour or physiology of affected organisms (An et al., 2004; Wu et al., 2013) or may augment the effects of other environmental stressors (Coors and De Meester, 2008; Kimberly and Salice, 2013). The results here indicate that chemicals may interact agonistically to cancel out the deleterious effects that they might produce in isolation, at least on the sensory behaviour of fish. The possibility remains, of course, that new compounds formed may produce new and unforeseen effects at the physiological or histological level. While this possibility cannot be ruled out based on the present study, behaviour is a highly sensitive indicator of physiological stress and it seems unlikely that effects on one could occur without implications for the other (Clotfelter et al., 2004; Scott and Sloman, 2004). The constant challenge for laboratory-based ecotoxicological studies is to incorporate as much ecological relevance into the experimental design as possible while retaining the essential controls that allow proper interpretation of results. However, the task
Table 1 Summary of computational results for para-nonylphenol (the bond lengths are in Angstrom). Compound
Nonylphenol Nonylphenol (water:continuum)
OH stretching frequency (cm−1 )
Non-complexed bond length
Complexed bond length
Bond angle
Non complexed
Complexed
O H
O H
Cu O H
3700 3701
3694 2995
0.9716 0.9716
0.97247 1.00727
116 114.2
Binding energy (Kcal/mol)
−566.2 −540
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Excitaon intensity at
Max
500
400
300
200 0
1
2
3
4
Concentraon (μg·l) Fig. 4. Excitation intensity at the wavelength of maximum intensity (max ) around 305 nm for para nonylphenol in water at different concentrations. The black diamonds are data in the absence of copper, while clear squares are data in the presence of copper.
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