Article pubs.acs.org/est
Unifying Prolonged Copper Exposure, Accumulation, and Toxicity from Food and Water in a Marine Fish Fei Dang,† Wen-Xiong Wang,*,† and Philip S. Rainbow‡ †
Division of Life Science, The Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Kowloon, Hong Kong Department of Zoology, The Natural History Museum, Cromwell Road, London SW7 5BD, United Kingdom
‡
S Supporting Information *
ABSTRACT: The link between metal exposure and toxicity is complicated by numerous factors such as exposure route. Here, we exposed a marine fish (juvenile blackhead seabream Acanthopagrus schlegelii schlegelii) to copper either in a commercial fish diet or in seawater. Copper concentrations in intestine/liver were correlated linearly with influx rate, but appeared to be less influenced by uptake pathway (waterborne or dietary exposure). Influx rate best predicted Cu accumulation in the intestine and liver. However, despite being a good predictor of mortality within each pathway, influx rate was not a good predictor of mortality across both exposure pathways, as waterborne Cu caused considerably higher mortality than dietary Cu at a given influx rate. We show that the use of gill Cu accumulation irrespective of the exposure route as a model for observed fish mortality provided a clear relationship between accumulation and toxicity. Investigation of gill Cu accumulation may shed light on the different accumulation strategies from the two exposure pathways. This correlation offers potential for the use of branchial Cu concentration as an indicator of long-term Cu toxicity, allowing for differences in the relative importance of the uptake pathways in different field situations.
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influx rate under various environmental conditions.7 The control of growth rate on Cu accumulation by growth dilution appears less important relative to elimination rate.8 Therefore, influx rate could potentially serve as a more appropriate indicator of Cu bioaccumulation for both exposure routes. Acute dissolved metal toxicity in fish is manifested when a critical amount of metal binds to a physiological target site on the surface of the fish gill.9 Numerous data of metal acute toxicity are available for a variety of metals in aquatic organisms across different water chemistries. For instance, the physiological mechanism of acute dissolved Cu toxicity involves disrupting Na+ and Cl− uptake in fish.10,11 Conversely, a growing number of different toxic effects of laboratory-derived long-term dietary Cu exposure has also been observed in fish (summarized in refs 6 and 12), including digestive physiology changes,13−15 hepatic biochemical effects,16,17 behavior responses,17 and growth inhibition.13,18 At present, compared to the well-known dissolved acute toxic mechanism, the physiological mechanisms of long-term dietary Cu toxicity remain less well understood.12 In this study, we have employed biokinetic principles to investigate relationships among Cu exposure, time-dependent
INTRODUCTION Copper contamination of estuarine environments in southwest England1 and China2 raises concern about Cu bioaccumulation and toxicity in marine fish. Environmental risks of metals depend greatly on exposure, but the linkage between exposure and toxicity varies with metal, species, and exposure route.3−5 Currently, daily dose better correlates Cu exposure and toxicity rather than dietary metal concentrations.6 However, assessment of potential metal toxicity works on the premise of accurate estimation of metal bioavailability leading to accumulation. Therefore, further consideration of metal bioavailability on the basis of daily dose may provide a more precise measure of metal exposure and a better link among metal exposure, bioaccumulation, and toxicity. Specifically, given the simultaneous exposure of fish to waterborne and dietary Cu, it is useful to seek a universal predictor for Cu bioaccumulation and toxicity, which is applicable to both exposure routes, and finally to produce a simplified tool for the evaluation of concurrent exposure. The biokinetic model has been used to forecast successfully metal concentrations in field-collected organisms, based on measured biokinetic parameters, i.e., metal influx rate, elimination rate, and organism growth rate.3 Influx rate characterizes the physiological processes of bioavailable metal delivery via membrane transport and thus links metal exposure and bioaccumulation. Elimination rate could also modify metal bioaccumulation by metal loss, but it is usually less variable than © 2012 American Chemical Society
Received: Revised: Accepted: Published: 3465
November 5, 2011 February 20, 2012 February 28, 2012 February 28, 2012 dx.doi.org/10.1021/es203951z | Environ. Sci. Technol. 2012, 46, 3465−3471
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overnight to decrease the moisture content to the original value (6.2(±1.4)%). The control fish diet (8 μg g−1) was prepared in the same way as above but with only nanopure water added. All the prepared fish diets were kept in plastic bags at −20 °C for fish feeding and Cu analysis. Dietary influx rate varies as a function of assimilation efficiency (AE, %), ingestion rate (IR, g g−1 dw d−1) and food concentration (Cf, μg g−1, 4, 7). Conversely, waterborne influx rate is a product of dissolved uptake rate constant (ku, L kg−1 dw d−1) and dissolved metal concentration (Cw, μg L−1, 7). Dang et al.8 reported for A. schlegelii that Cu ku was 6.24 L kg−1 d−1 and Cu AE from brine shrimp and clam were comparable (9−11%) but 2% when the fish were fed with oyster tissue. In the current study a mean AE value of 10% from brine shrimp and clam was used to represent Cu bioavailability in the commercial fish diet. This assumption seems reasonable because most Cu accumulated in oysters is bound with cellular debris and metal-rich granules (as high as 90%, 2), resulting in abnormally low AE in oysters. The ingestion rate was 0.14 g ww g−1 dw d−1 except at the highest dietary Cu treatment (see below), and a factor of 4 (ww/dw) was used to correct fish mass. Metal concentrations in fish diet and the estimated influx rates are presented in Table 1. To obtain similar influx rates (μg g−1 dw d−1) from water and food, the target dissolved Cu concentrations in seawater were calculated as:
Cu accumulation (gill, intestine, liver, and muscle), and consequent toxicity in a marine fish, the blackhead seabream Acanthopagrus schlegelii schlegelii, during 4-weeks laboratory exposure. This study offers a comparison of accumulation and toxicity arising from dietary or waterborne Cu exposure. Specifically, we attempt to integrate both uptake pathways into a common framework in terms of exposure, accumulation, and toxicity, which may produce a simple but realistic tool for environmental monitoring and risk assessment.
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MATERIALS AND METHODS Fish Diet and Experimental Design. Field-collected juvenile blackhead seabream Acanthopagrus schlegelii schlegelii (7−8 cm in length, initially approximately 1.2 μg Cu g−1 dw) were obtained from a fish farm in Sai Kung, Hong Kong, which is a pristine area close to Clear Water Bay. After transportation to the laboratory in Clear Water Bay, they were reared in sandfiltered Clear Water Bay seawater (pH 8.0, salinity = 33 psu, DOC = 4.2 mg L−1, dissolved Cu = 2.93 ± 1.37 μg L−1) at 23 °C under a 14 h light:10 h dark regime. The same aerated sandfiltered seawater was used in all the experiments. Fish were fed fish diet pellets (purchased from a company in Xiamen, China) three times a day at a ratio of 0.035 wet weight per wet weight of fish per day. Fish could consume the diet rapidly within 1 h. The measured Cu concentration in the diet was 7.73 ± 0.14 μg g−1 with macronutrient contents of 42% crude protein, 3% fat, and 16% crude ash. To eliminate the effects of other metals on Cu toxicity, we chose Cu-spiked commercial fish diet rather than a naturally contaminated live diet containing multiple metals. Three environmentally relevant Cu concentrations were selected (50, 250, and 1000 μg g−1 nominally, but see Table 1) as Cu
Cw =
treatment
waterborne concn (μg L−1)
estimated influx rate (μg g−1 d−1)
control 50 μg g−1 250 μg g−1 1000 μg g−1 100 μg L−1 500 μg L−1
7.73 ± 0.14 66.9 ± 2.61 273 ± 11.4 997 ± 39.4 7.73 ± 0.14 7.73 ± 0.14
2.93 ± 1.37 2.93 ± 1.37 2.93 ± 1.37 2.93 ± 1.37 99.7 ± 17.1 525 ± 104
0.11 0.94 3.82 6.98b 0.62 3.28
(1)
The calculated dissolved Cu concentrations were therefore 100 and 500 μg L−1, respectively, producing waterborne Cu uptake rates equivalent to the daily influx rates for the nominal 50 and 250 μg g−1 dietary treatments, respectively (Table 1). The dissolved Cu concentrations were slightly higher than those found in the field (e.g., 0.1−176 μg L−1, 1) Few fish could survive the 4-week exposure at high dissolved Cu concentration (1119 μg L−1), equivalent to 1000 μg g−1 dietary treatment in a preliminary experiment. Thus, there was a total of six treatments (control, three dietary levels, and two waterborne levels), each group with three replicate tanks. We defined toxicity as a decrease in either growth rate or survival over the period of exposure. Fish Exposure. Fish were randomly divided into 18 tanks (size of 60 × 29 × 43 cm3, 16 fish per tank) and acclimated under the same conditions as described above for another week until exposure began. The dietary-exposed fish were fed one of the three Cu-spiked fish diets, whereas the waterborne-exposed and control fish were fed control fish diet without Cu spiking. All the fish were fed three times daily, and the ingestion rate was controlled to 0.14 g ww g−1 dw d−1 by the amount of fish diet. One exception was 1000 μg Cu g−1 exposed fish, which were first fed 7% of 1000 μg g−1 diet. After these diets were almost consumed, 7% of control diet was supplemented. This reduced the estimated influx rate to 6.98 μg Cu g−1 d−1 and thus the differences of estimated influx rates between exposure concentrations (50, 250, and 1000 μg g−1) were comparable. The fish diet floated in seawater without sinking during the 1 h feeding regime allowing the fish to feed easily. Fish feeding behavior was monitored in all treatments during the feeding regime and all diet pellets were found to be eaten except in the highest dissolved and dietary exposure groups; uneaten food and feces were then siphoned off. Our calculation based on the
Table 1. Measured Cu Concentrations in Fish Diet (n = 5) and Seawater (n = 8)a dietary concn (μg g−1)
AE × IR × C f ku
The estimated influx rate (μg g−1dw d−1) was calculated by multiplying Cu assimilation efficiency (AE, 10%), ingestion rate (IR, 0.14 g ww g−1 dw d−1) and dietary Cu concentration (Cf, μg g−1 ww) for dietary exposures, or by multiplying dissolved uptake rate constant (ku, 6.24 L kg−1 dw d−1) and dissolved Cu concentrations (Cw, μg L−1) for waterborne exposures. For both dietary and waterborne exposures, the contribution to Cu accumulation from the other route was negligible (see text). Values are means ± SD. bThe ingestion rate was only 7% of 1000 μg Cu g−1 and 7% control diet was also supplemented to fish. a
concentrations from 45 to 662 μg g−1 have been measured in the polychaete Nereis diversicolor (a common prey item of fish) collected from a range of estuaries in southwest England (Dang et al. unpublished data). To obtain the Cu-contaminated fish diets, 800 g fish diet pellets were soaked in 800 mL of Cuspiked solution (as CuCl2, 52, 260, and 1040 mg Cu L−1 in nanopure water for each treatment, respectively) for 6 h and remained intact. Then those pellets were dried at 50 °C 3466
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biokinetic equation ( f = [ku × Cw]/[AE × IR × Cf + ku × Cw], the same variable values as eq 1) and data in preliminary experiments (i.e., 0.10. Thus data from replicates within each treatment were combined and used to seek statistically significant differences among treatments by ANOVA (p < 0.05). All measurements were given as means ± SD.
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RESULTS The intestinal and hepatic Cu concentrations increased linearly over a range of dietary and waterborne influx rates from 0.11 to 6.98 μg Cu g−1 d−1 after 2- or 4-weeks exposure (Figure 1). At
Figure 1. Copper tissue concentrations in A. schlegelii exposed for 2 or 4 weeks to dissolved or dietary Cu. Each regression line represents data from both exposure routes at a time point (solid line for 2-weeks exposure or dashed line for 4-weeks exposure). Note that D2 and D4 represent dietary exposure for 2 weeks and 4 weeks, respectively, while W2 and W4 represent waterborne exposure for 2 weeks and 4 weeks. Estimated influx rate is listed in Table 1. Values are means ± SD (n = 6).
similar influx rates, Cu burdens in intestine and liver after waterborne exposure were comparable to those after dietary exposure. Furthermore, hepatic and intestinal Cu concentrations were significantly correlated (p = 0.02 for 2-weeks exposure and p < 0.001 for 4-weeks exposure). On the basis of measured Cu levels in gill, muscle, intestine, and liver and tissue weights, Cu contents in intestine and liver accounted for more than 70% of the total Cu burden in exposed fish irrespective of exposure routes, indicating the importance of intestine and liver during Cu accumulation. When both exposure routes were considered, no relationships with influx rate were observed in gill and muscle (Figure 1). Copper concentrations in the gill upon 28-day exposure to dissolved Cu were 1.1- or 4.9-fold (i.e., 0.8 vs 0.7 μg g−1, 8.8 vs 1.8 μg g−1, respectively) higher than those of dietary exposure with comparable influx rates. Over the entire exposure period, Cu in the muscle fluctuated from 0.7 to 1.5 μg g−1 and changed little with increased influx rate. The dietary-exposed blackhead seabream (6.98 μg Cu g−1 −1 d ) first showed evidence of sublethal toxicity in terms of decreased consumption rates after 6 days exposure: a small 3467
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to be independent of exposure pathway. In particular, regardless of exposure routes, intestinal and hepatic Cu accumulation remained comparable (p > 0.05) at similar influx rate, although only two pairs of comparable influx rates from food and seawater were examined (Figure 1). The intestinal Cu concentrations derived from food and seawater were comparable at similar influx rates examined, highlighting the importance of the intestine as an organ for dissolved Cu uptake in marine fish, which drink a substantial volume of seawater for osmotic homeostasis.21 Indeed the dissolved uptake rate via the intestine has been shown to be approximately 10-fold higher than that via the gills in juvenile blackhead seabream.21 Although dose-dependent dietary Cu accumulation in the intestine was observed, Cu is likely to be stored in the intestinal mucosa rather than be transferred into the intestine, because mucus acts to effectively trap Cu in the gut lumen and transportation across intestinal cells appears to be a limiting step for Cu uptake by internal tissues.22 Subcellular fractionations may provide insights on intestinal Cu accumulation. After intestinal uptake, dietary-derived Cu is probably delivered directly to the liver by the hepatic portal system,23 as evidenced by the significant relationship between hepatic and intestinal Cu concentrations. Thereafter, Cu is distributed throughout the body (e.g., gill and muscle), resulting in high Cu concentrations in intestine and liver, followed by gill and muscle (Figure 1). Copper concentrations in gill or muscle are not strongly influenced by dietary influx rate. The gill is directly exposed to waterborne Cu, while dietary-derived Cu accumulated in the gill would result from Cu redistribution after intestinal uptake. Therefore, waterborne exposure appears to result in higher Cu levels in gills compared to its counterpart. Finally, between the two exposure routes banchial Cu levels did not show a consistent relationship with influx rates (Figure 1). Muscle Cu concentrations remained comparable among dietary influx rates, as shown here and in earlier studies.14,24 When both exposure pathways are considered, influx rate could not predict Cu levels in gill and muscle, a different scenario from the intestine and liver. Influx Rate and 28-Day Toxicity. Copper influx rate from water or food has previously been shown to predict toxicity in acute exposures.4,25 This is consistent with our observation for a single uptake pathway during prolonged exposure (Figure 2). However, when both uptake pathways are considered, Cu bioavailability estimated by influx rate is not an accurate reflection of Cu toxicity. Between both exposure routes there was no consistent relationship of mortality with influx rate (Figure 2). This could be due to Cu regulation by intestine and liver, which is not taken into account in measures of influx rate. In addition, Cu elimination and detoxification rate (e.g., metallothionein induction) are crucial to toxicity prediction.3 For instance, Dang et al.8 reported a high Cu elimination rate constant (0.091 d−1) and demonstrated the significance of Cu elimination in a long-term exposure. The incorporation of metal assimilation efficiency into daily dose (i.e., influx rate) provides a more accurate estimation of metal accumulation. This is particularly important when summarizing metal accumulation from different food sources because metal assimilation efficiency varies among food types (e.g., copepods, barnacles, clams, mussels, fish viscera, 26). Additional experimental work is, however, required to quantify the Cu AE of the commercial fish diet and the fish ingestion
amount of the contaminated diet and most of the control diet was uneaten. But the ingestion rate was not corrected for uneaten food as this was not quantified. Meanwhile, most fish at the higher dissolved Cu influx rate (3.28 μg Cu g−1 d−1) reduced their consumption rates on day 2 and rejected food completely on day 4. At a similar rate of Cu influx, fish exposed to either food or water for 14 days showed comparable physiological responses (e.g., wet weight, length, CF, LSI and SGR) with the exception of a higher mortality rate (10%) at a dissolved influx rate of 3.28 μg g−1 d−1 (Table S1 in the Supporting Information). After 28-day exposure, low influx rates (0.94 vs 0.62 μg g−1 d−1) did not produce significant differences in any physiological parameter between exposure pathways. However, in contrast to the dietary exposure counterpart (3.82 μg Cu g−1 d−1, Table S1 in the Supporting Information), 11%, 12%, and 83% reductions in mean condition factor (CF), liver somatic index (LSI), and specific growth rate (SGR) were observed at the dissolved influx rate (3.28 μg Cu g−1 d−1), partially due to food rejection in this waterborne group. Furthermore, mortality rate increased by 5-fold to 31%. Under dietary Cu exposure, the influence of influx rate did not follow a constant trend for all physiological parameters (e.g., wet weight, length, condition factor, liver somatic index, and specific growth rate) except for an increasing trend of mortality rate. The highest dietary influx rate of 6.98 μg Cu g−1 d−1 was associated with a 36% decrease in SGR and an induced 8.3% mortality rate compared to the control. Interestingly, there appeared to be a time lag for toxicity manifestation, as reflected in SGR and mortality over the last 14 days, suggesting that the exposed fish suffered long-term toxicity at high Cu influx rates rather than acute toxicity. Overall, no relationship between dietary influx rate and physiological parameters (wet weight, length, CF, LSI, and SGR) was observed, except for a significant correlation with the mortality rate observed (0− 8.3%, Figure 2).
Figure 2. Relationship between Cu influx rate and mortality rate in A. schlegelii exposed to dissolved or dietary Cu for 4 weeks.
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DISCUSSION
Influx Rate and Accumulation. Conceptually, influx rates result from the interaction between bioavailable metal concentrations and mechanistic characteristics (e.g., binding affinity and capacity) of biological transport systems,7 and thus provide a plausible link between exposure and accumulation. Its strong correlations with intestinal/hepatic Cu concentrations (Figure 1) suggest that influx rate as tested here can provide an acceptable model of whole body fish Cu accumulation, as Cu in liver and intestine accounted for more than 70% of total Cu burden in exposed fish at the whole body level. Moreover, the predictive capability of influx rates to Cu accumulation is likely 3468
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gill is more susceptible to Cu (Figure 3, inset). It does not support the general proposal that the gut is the major target organ of toxicity in dietary exposure.12 Furthermore, when both waterborne and dietary exposure are considered, the observed mortality correlated linearly with gill Cu levels, suggesting that gill Cu burden may serve as a good predictor of Cu toxicity (Figure 3). When compared to influx rate, gill Cu accumulation reveals the different metal distribution patterns between uptake pathways. The observed significant correlation between mortality and gill Cu concentrations in the present study indicates a possibility of the extension of a fish gill modeling approach from waterborne to dietary exposure in future study, but raises questions about the mechanism of dietary Cu toxicity. Predicting dietary Cu toxicity by gill Cu levels in the present study is somewhat akin to the prediction of dissolved metal toxicity by gill metal concentrations in the framework of the biotic ligand model (BLM) demonstrated in previous studies, i.e., higher metal concentrations in gill predicted greater toxicity. In previous studies lethal accumulation (LA50), expressed as gill metal concentrations (e.g., in 3 or 24 h), could predict 50% mortality in acute (e.g., 96 h, 27) or chronic (e.g., 30 d, 28) dissolved exposure. And a slight increase of gill Cu concentration (i.e., 13 ng Cu g−1 ww) could result in 50% mortality in rainbow trout during acute dissolved exposure,29 suggesting that the gill is extremely sensitive to Cu exposure. Although the dietary exposures only resulted in mortality rates from 0% to 8% and up to 31% for dissolved Cu exposures, our results suggest that higher branchial Cu concentrations cause greater mortality. Moreover, fish mortality observed here shows a linear correlation across the range of gill Cu burdens examined irrespective of exposure route. If the target site for dietary Cu toxicity is the gill, then this relationship should be expected. This was, for instance, demonstrated in tilapia Oreochromis mossambicus exposed to dietary Cd with increased apoptosis in the gill.30 Further work is, however, warranted to evaluate this relationship over a wider range of mortality rates and a better overlap between dissolved and dietary exposures. The toxic effect of dietary Cu in marine fish remains less clear, but the plausible relationship between mortality and gill Cu levels is on par with the trend summarized from the few available studies (i.e., increasing sublethal toxicity of dietary Cu with branchial Cu levels). For example, a dietary Cu exposure for 3 months, resulting in less than 6 μg Cu g−1 gill concentration, did not significantly increase the gill MT concentration, but increased the gill surface area leading to increased respiration efficiency in rainbow trout Oncorhynchus mykiss.17 No morphological change in gill of tilapia Oreochromis niloticus was observed with 11 μg g −1 branchial Cu concentrations after dietary Cu exposure.31 But 30-day exposure resulted in a 19 μg g−1 gill Cu concentration, significant lipid peroxidation, and an increase trend of total glutathione concentration in the gill of African walking catfish Clarias gariepinus, suggesting that the fish suffered oxidative stress, although the gill showed a normal histology.15 The fundamental differences in gill characteristics between marine and freshwater fish may constrain the extrapolation of the current understanding of dietary Cu effects on freshwater fish gill to marine fish. Marine fish exhibit significant osmoregulatory disturbance on prolonged Cu exposure,32 but probably as a result of inhibition of components other than Na+/K+-ATPase in the gill,33 a situation different from that in freshwater fish. Despite dietary exposure being recognized as an
rate during exposure; in any case, the influx rates could be different from those estimated in this study. Variation in metal AE of the commercial fish diet does not affect the observed relationships between mortality/accumulation and dietary influx rate (Figure S1 in the Supporting Information). The relationship between Cu accumulation and influx rate for both exposure pathways is significant, when AE varies within normal range (5−20%, excluding the abnormally low Cu AE in oyster, Table S2 in the Supporting Information). Additionally, AE differences among exposure concentrations within an experiment are likely too small to significantly influence influx rate.4 As a result of reduced feeding behavior at the highest dietary Cu level, dietary influx rate is slightly overestimated and the relationships between mortality/accumulation and dietary influx rate (Figures 1 and 2) may be modified. Future work is required to evaluate these estimated influx rates and to determine if the relationship holds over a wider range of influx rates. As mentioned previously, it is difficult to directly link exposure and toxicity in the presence of multiexposure routes. Only a portion of bioaccumulated Cu appears to be responsible for long-term toxic effects. As a consequence, a better understanding of internal Cu distribution from both uptake pathways is required. Tissue Cu Concentrations and 28-Day Toxicity. For dietary exposure, our results show that Cu levels in intestine, liver, and gill of blackhead seabream were linearly related to mortality (0−8%, Figure 3). Specifically, the slightly larger correlation coefficient for branchial Cu (e.g., 4.5 in gill >0.06 in liver or 0.04 in intestine after 4-weeks exposure) implies that
Figure 3. Relationship between mortality rate after 4-weeks exposure and tissue-specific Cu concentration (intestine, liver, and gill) at 2 or 4 weeks. The inset shows the relationship between mortality rate after 4weeks dietary exposure only and gill Cu levels. Values are means ± SD (n = 6). 3469
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important pathway for Cu accumulation in fish,8,34 the underlying mechanism of dietary Cu toxicity remains unclear. Further investigation of various toxic end points in gills after chronic dietary exposure and use of in situ perfusion procedures will provide insights in marine fish. Nevertheless, gill Cu concentrations could be indicative of chronic toxicity due to differences in the relative importance of uptake routes in different field settings. To conclude, the present study has provided a first step toward the integration of dietary and waterborne exposure into a framework in terms of prolonged exposure, accumulation, and toxicity. Estimated influx rate quantified Cu exposure and served to forecast Cu accumulation. However, no direct link between influx rate and toxicity was established, probably due to the complication of Cu elimination, detoxification rate, and tissue regulation within the fish. We have proposed a simple approach to predict long-term Cu toxicity, centering on the relationship between gill Cu concentrations and mortality rate, which might offer the opportunity for a detailed mechanistic explanation of Cu toxicity, in particular dietary Cu toxicity, to marine fish. It may also offer potential as a realistic direct tool for environmental monitoring and risk assessment. This relationship, however, remains to be tested in other marine and freshwater organisms using experimental methods allowing accurate measurement of ingestion rate and assimilation efficiency.
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(5) Wang, W.-X. Incorporating exposure into aquatic toxicological studies: An imperative. Aquat. Toxicol. 2011, 105, 9−15. (6) Clearwater, S. J.; Farag, A. M.; Meyer, J. S. Bioavailability and toxicity of dietborne copper and zinc to fish. Comp. Biochem. Physiol. C: Comp. Pharmacol. 2002, 132, 269−313. (7) Luoma, S. N.; Rainbow, P. S. Metal contamination in aquatic environments: Science and lateral management; Cambridge University Press: Cambridge, U.K., 2008. (8) Dang, F.; Zhong, H.; Wang, W.-X. Copper uptake kinetics and regulation in a marine fish after waterborne copper acclimation. Aquat. Toxicol. 2009, 94, 238−244. (9) Di Toro, D. M.; Allen, H. E.; Bergman, H. L.; Meyer, J. S.; Paquin, P. R.; Santore, R. C. Biotic ligand model for the acute toxicity of metals. I. Technical basis. Environ. Toxicol. Chem. 2001, 20, 2383− 2396. (10) Laurén, D. J.; McDonald, D. G. Effects of copper on branchial ionoregulation in the rainbow trout, Salmo gairdneri Richardson. J. Comp. Physiol. 1985, 155, 635−644. (11) Laurén, D. J.; McDonald, D. G. Influence of water hardness, pH, and alkalinity on the mechanisms of copper toxicity in juvenile rainbow trout, Salmo gairdneri. Can. J. Fish. Aquat. Sci. 1986, 43, 1488− 1496. (12) Meyer, J. S.; Adams, W. J.; Brix, K. V.; Luoma, S. N.; Mount, D. R.; Stubblefield, W. A.; Wood, C. M., Eds. Toxicity of dietborne metals to aquatic organisms; SETAC Press: Pensacola, Florida, U.S.A., 2005. (13) Berntssen, M. H. G.; Hylland, K.; Wendelaar Bonga, S. E.; Maage, A. Toxic levels of dietary copper in Atlantic salmon (Salmo salar L.) parr. Aquat. Toxicol. 1999, 46, 87−99. (14) Kamunde, C. N.; Grosell, M.; Lott, J. N. A.; Wood, C. M. Copper metabolism and gut morphology in rainbow trout (Oreochromis niloticus) during chronic sublethal dietary copper exposure. Can. J. Fish. Aquat. Sci. 2001, 58, 293−305. (15) Hoyle, I.; Shaw, B. J.; Handy, R. D. Dietary copper exposure in the African walking catfish, Clarias gariepinus: Transient osmoregulatory disturbances and oxidative stress. Aquat. Toxicol. 2007, 83, 62−72. (16) Baker, R. T. M.; Handy, R. D.; Davies, S. J.; Snook, J. C. Chronic dietary exposure to copper affects growth, tissue lipid peroxidation, and metal composition of the grey mullet. Chelon Labrosus. Mar. Environ. Res. 1998, 45, 357−365. (17) Handy, R. D.; Sims, D. W.; Giles, A.; Campbell, H. A.; Musonda, M. M. Metabolic trade-off between locomotion and detoxification for maintenance of blood chemistry and growth parameters by rainbow trout (Oncorhynchus mykiss) during chronic dietary exposure to copper. Aquat. Toxicol. 1999, 47, 23−41. (18) Lanno, R. P.; Slinger, S. J.; Hilton, J. W. Maximum tolerable and toxicity levels of dietary copper in rainbow trout (Salmo gairdneri Richardson). Aquaculture 1985, 49, 257−268. (19) Zhong, H.; Evans, D.; Wang, W. X. Uptake of dissolved organic carbon-complexed 65Cu by the green mussel Perna viridis. Environ. Sci. Technol. 2012, 46, 2383−2390. (20) Brandt, K. K.; Holm, P. E.; Nybroe, O. Evidence for bioavailable copper-dissolved organic matter complexes and transiently increased copper bioavailability in manure-amended soils as determined by bioluminescent bacterial biosensors. Environ. Sci. Technol. 2008, 42, 3102−3108. (21) Zhang, L.; Wang, W.-X. Gastrointestinal uptake of cadmium and zinc by a marine teleost Acanthopagrus schlegelii. Aquat. Toxicol. 2007, 85, 143−153. (22) Handy, R. D.; Musonda, M. M.; Philips, C.; Falla, S. J. Mechanisms of gastrointestinal copper absorption in the African walking catfish: Copper dose-effects and a novel anion-dependent pathway in the intestine. J. Exp. Biol. 2000, 203, 2365−2377. (23) Clearwater, S. J.; Baskin, S. J.; Wood, C. M.; McDonald, D. G. Gastrointestinal uptake and distribution of copper in rainbow trout. J. Exp. Biol. 2000, 203, 2433−2466. (24) Lorentzen, M.; Maage, A.; Julshamn, K. Supplementing copper to a fish meal based diet fed to Atlantic salmon parr affects liver copper and selenium concentrations. Aquacult. Nutr. 1998, 4, 67−72.
ASSOCIATED CONTENT
S Supporting Information *
Table giving the exposure concentrations, estimated influx rate, wet weight, standard length, condition factor, liver somatic index, specific growth rate, and mortality rate of the blackhead seabream Acanthopagrus schlegelii schlegelii, table giving the relationships between intestinal/hepatic Cu concentrations and estimated influx rates at various Cu AE levels, and a figure giving the relationships between intestinal Cu concentrations and dietary influx rate estimated from various AE values. This material is available free of charge via the Internet at http:// pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected] Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We thank the anonymous reviewers for their helpful comments on this work. This study was supported by a General Research Fund from the Hong Kong Research Grants Council (662610).
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REFERENCES
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Environmental Science & Technology
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dx.doi.org/10.1021/es203951z | Environ. Sci. Technol. 2012, 46, 3465−3471
