The DAM underestimated EC50 and LC50 values after 120 h of exposure to 2 mg Cu L–1, which suggests that the observed Cu toxicity might be exerted by other underlying processes of toxicity that are not currently included in the model. One such possible process is the accumulation of biological damage during the initial period of exposure. This could induce a stronger toxic response to later chemical stress. The consequences of prolonged or changing exposure may induce cumulative long-term toxicity effects (Ashauer and Escher, 2010; Ashauer et al., 2011). For example, delayed toxicity (or carry-over toxicity) might explain why stronger toxic responses are observed in organisms that have been exposed to the same dose of a toxicant for an extended period. Organisms may sustain damage during the first period of exposure that is carried over when they are later exposed to a chemical or circumstance, resulting in poorer recovery of the earlier physiological impairment. The exposed organism’s recovery time (tr) depends on both
elimination of the chemical and recovery from the damage, calculated as tr
kr
1
(Ashauer et
al., 2007). For juvenile tilapia exposed to 2 mg Cu L–1, tr was estimated at 12.67 days. This suggests that the fish were not able to recover fully during our 120 h bioassay. The cumulative damage therefore presumably persisted, and toxicity increased with the duration of exposure.
We suggest that not only should the current chemical-induced damage level be investigated, but carry-over toxicity resulting from previous exposure should also be taken into consideration when analyzing the levels of chemical exposure that might cause cumulative damage or poor recovery from damage.
Alternatively, we suggest that more complex toxicological processes, endpoint-specific information or subcellular toxicokinetic information be added to the model, if these measurements influence the mode of action or toxicodynamic process and can be parameterized
using available information (Jager and Hansen, 2013). For instance, the relationships between toxicity and total chemical residue are not straightforward, due to the internal compartmentalization of metals, which might result in uncertainties in metal risk assessment (Vijver et al., 2004). Subcellular partitioning of Cu plays a primary role in regulating metal stress in marine and freshwater fish (Kraemer et al., 2005; Dang et al., 2009; et al., 2010). We suggest that future models could benefit from integrating current knowledge of subcellular partitioning of metals to predict the active Cu dose in specific organs (Dang et al., 2009; Higgins et al., 2009; De Boeck et al., 2010; Tsai et al., 2013).
5. Conclusion
This study strongly demonstrates that the response of NKA activity to Cu exposure can serve as a sensitive biomarker. It effectively links Cu exposure and accumulation to induced impairment of osmoregulation and lethality following exposure to environmentally relevant levels (0.2 mg L–
1). However, it does not do so for higher exposure levels in aquaculture farms or contaminated aquatic ecosystems (1 and 2 mg L–1 ). This study provides a novel mechanistic approach to holistically illustrating the sensitivity of branchial NKA activity to external and internal chemical levels, and their relationship to relative toxic endpoints. These findings may be useful for characterizing how fish respond to Cu exposure levels and durations, resulting in their susceptibility, adaptation or acclimation to contaminant levels in an ecosystem over time.
Acknowledgements
This work and Dr. Jeng-Wei Tsai were financially supported by the Taiwan National Science Council, Taiwan (NSC 99-2313-B-039-004-MY3). The authors are grateful to H.L. Chuang, H.L. Wei, and C.L. Lu for their assistance with animal care, laboratory experiments and artwork.
References
Ashauer, R., Boxall, A.B., Brown, C.D., 2007. New ecotoxicological model to simulate survival of aquatic invertebrates after exposure to fluctuating and sequential pulses of pesticides. Environ.
Sci. Technol. 41(4), 1480-6.
Ashauer, R., Escher, B.I., 2010. Advantage of toxicokinetic and toxicodynamic modelling in aquatic ecotoxicology and risk assessment. J. Environ. Monit. 12, 2056-2061. DOI:
10.1039/c0em00234h
Ashauer, R., Hintermeister, A., Caravati, I., Kretschemann, A., Escher, B., 2010. Toxicokinetic and toxicodynamic modeling explains carry-over toxicity from exposure to diazinon by slow organism recovery. Environ. Sci. Technol. 44(10). 3963-3971.
Ashauer, R., Agatz, A., Albert, C., Ducrot, V., Galic, N., Hendriks, J., Jager, T., Kretschmann, A., O'Connor, I., Rubach, M.N., Nyman, A.M., Schmitt, W., Stadnicka, J., van den Brink, P.J., Preuss, T.G., 2011. Toxicokinetic-toxicodynamic modeling of quantal and graded sublethal endpoints: a brief discussion of concepts. Environ. Toxicol. Chem. 30, 2519-24.
Atli, G., Canli, M., 2007. Enzymatic responses to metal exposures in a freshwater fish Oreochromis niloticus. Comp. Biochem. Physiol. C Toxicol. Pharmacol. 145(2), 282-7.
Atli, G., Canli, M., 2013. Metals (Ag+, Cd2+, Cr6+) affect ATPase activity in the gill, kidney, and muscle of freshwater fish Oreochromis niloticus following acute and chronic exposures. Environ.
Toxicol. 28, 707–717.
Birceanu, O., Chowdhury, M.J., Gillis, P.L., McGeer, J.C., Wood, C.M., Wilkie, M.P., 2008. Modes of metal toxicity and impaired branchial ionoregulation in rainbow trout exposed to mixtures of Pb and Cd in soft water. Aquat. Toxicol. 9(4), 222-31. doi: 10.1016/j.aquatox.2008.07.007.
Boisen, A.M., Amstrup, J., Novak, I., Grosell, M., 2003. Sodium and chloride trans-port in soft water and hard water acclimated zebrafish (Danio rerio). Biochim. Biophys. Acta 1618, 207–218.
Brooks, S., Lyons, B., Goodsir, F., Bignell, J., Thain, J., 2009. Biomarker responses in mussels, an integrated approach to biological effects measurements. J. Toxicol. Environ. Health A 72, 196–
208, http://dx.doi.org/10.1080/15287390802539038.
Carriquiriborde, P., Ronco, A.E., 2008. Distinctive accumulation patterns of Cd(II), Cu(II), and Cr(VI) in tissue of the South American teleost, pejerrey (Odontesthes bonariensis). Aquat. Toxicol. 86,
313-22.
Chen, Y.C., Lee, M.T., Jong, K.J., Wu, S.M., 2013. Diatomite and dietary sodium chloride decrease Cu2+ accumulation and induction of metallothionein expression on tilapia juvenile (Oreochromis mossambicus) upon exposure to waterborne copper. J. Fish. Soc. Taiwan 40, 79-88.
Dang, Z., Lock, R.A.C., Flik, G., Wendelaar Bonga, S.E., 1999. Metallothionein response in gills of Oreochromismossambicusexposed to copper in fresh water. Am. J. Physiol. 277, R320–R331.
Dang, Z.C., Lock, R.A.C., Wendelaar Bonga, S.E., 2000. Na+, K+-ATPase immunoreactivity
in branchial chloride cells of Oreochromis mossambicus exposed to copper. J. Exp. Biol. 203, 379-387.
Dang, F., Zhong, H., Wang, W.X., 2009. Copper uptake kinetics and regulation in a marine fish after waterborne copper acclimation. Aquat. Toxicol. 94, 238-44.
Dang, F., Wang, W.X., Rainbow, P.S., 2012. Unifying prolonged copper exposure, accumulation, and toxicity from food and water in a marine fish. Environ. Sci. Technol. 46(6), 3465-71. doi:
10.1021/es203951z
De Boeck, G., Eyckmans, M., Lardon, I., Bobbaers, R., Sinha, A.K., Blust, R., 2010. Metal accumulation and metallothionein induction in the spotted dogfish Scyliorhinus canicula. Comp.
Biochem. Physiol. A 155, 503-8.
Dethloff, G.M., Schlenk, D., Jonathan, T.H., Bailey, H.C., 1999. Alteration in physiological parameters of rainbow trout (Oncorhyunchus mykiss) with exposure to copper and copper/znic mixtures. Ecotoxocol. Environ. Saf. 42, 253-264.
Diamond, J.M., Klaine, S.J., Butcher, J.B., 2006. Implications of pulsed chemical exposures for aquatic life criteria and wastewater permit limits. Environ. Sci. Technol. 40, 5132–5138.
Escher, B.I., Hermens, J.L.M., 2004. Internal exposure: linking bioavailability to effects. Environ.
Sci. Technol. 38, 455A-462A.
Finney, D.J., 1978. Statistical method in biological assay. third ed. Cambridge University Press, London, pp. 508.
Green, W.W., Mirza, R.S., Wood, C.M., Pyle, G.G., 2010. Copper binding dynamics and olfactory 25 impairment in fathead minnows (Pimephale promelas). Environ. Sci. Technol. 26, 44:1431-7.
Grosell, M., Boetius, I., Hansen, H.J.M., Rosenkilde, P., 1996. Influence of preexposure to sublethal levels of copper on Cu uptake and distribution among tissues of the European eel (Anguilla anguilla). Comp. Biochem. Physiol. C 114, 229-35.
Grosell, M., Wood, CM., 2002. Copper uptake across rainbow trout gills: mechanisms of apical entry. J. Exp. Biol. 205(Pt 8), 1179-88.
Handy, R.D., Eddy, F.B., Baines, H., 2002. Sodium-dependent copper uptake across epithelia: a review of rationale with experimental evidence from gill and intestine. Biochim. Biophys. Acta.
1566(1-2), 104-15.
Higgins, C.P., Paesani, Z.J., Chalew, T.E., Halden, R.U., 2009. Bioaccumulation of triclocarban in Lumbriculus variegatus. Environ. Toxicol. Chem. 28, 2580-6.
Hughes, G.N., 1984. General anatomy of the gills. In: Hoar, W.S., Randall D.J., (Eds.). Fish physiology vol. 10, part A. Academic Press, Orlando, Fla., p 1-72.
Jager, T., Hansen, B.H., 2013. Linking survival and biomarker responses over time. Environ.
Toxicol. Chem. 32(8), 1842-5. doi: 10.1002/etc.2258.
Kine-Saffran, E., Hülseweh, M., Pfaff, C., Kinne, R.K.H., 1993. Inhibition of Na, K-ATPase by cadmium: different mechanisms in different species. Toxicol. Appl. Pharmacol. 121, 22–29.
Kraemer, L.D., Campbell, P.G.C., Hare, L., 2005. A field study examining metal elimination kinetics in juvenile yellow perch (Perca flavescens). Aquat. Toxicol. 75, 108-26.
Lee, J.H., Peter, F.L., Koh, C,H., 2002. Prediction of time-dependent PAH toxicity in Hyalella azteca using a damage assessment model. Environ. Sci. Technol. 36 (14): 3131-3138.
Lin, C.H., Huang, C.L., Yang, C.H., Lee, T.H., 2004. Time-course changes in the expression of Na, K-ATPase and the morphometry of mitochondria-rich cells in gills of euryhaline tilapia (Oreochromis mossambicus) during freshwater acclimation. J. Exp. Zool. 301A, 85-96.
Lowry, O.H., Rosebrough, N.J., Farr, A.L., Randall, R.J., 1951. Protein measurement with the Folin phenol reagent. J. Biol. Chem. 193 (1), 265–75.
McGeer, J., Brix, K.V., Skeaff, J.M., DeForest, D.K., Brigham, S.I., Adams, B., Green, A., 2003.
Inverse relationship between bioconcentration factor and exposure concentration for metals:
implications for hazard assessment of metals in the aquatic environment. Environ. Toxicol.
Chem. 22, 1017-1037.
Minghetti, M., Schnell, S., Chadwick, M.A., Hogstrand, C., Bury, N.R., 2014. A primary FIsh Gill Cell System (FIGCS) for environmental monitoring of river waters. Aquat. Toxicol. 154, 184-92. doi:
10.1016/j.aquatox.2014.05.019.
Newman, M.C., 2009. Fundamentals of ecotoxicology, third ed. Levis Publishers, Florida.
Niyogi, S., Wood, C.M., 2004. Biotic ligand model, a flexible tool for developing site- specific water quality guidelines for metals. Environ. Sci. Technol. 38, 6177-6192.
Pain-Devin, S., Cossu-Leguille, C., Geffard, A., Giambérini, L., Jouenne, T., Minguez, L., Naudin, B., Parant, M., Rodius, F., Rousselle, P., Tarnowska, K., Daguin-Thiébaut, C., Viard, F., Devin, S., 2014. Towards a better understanding of biomarker response in field survey: A case study in eight populations of zebra mussels. Aquat Toxicol. 155, 52-61.
Peles, J.D., Pistole, D.H., Moffe, M.C., 2012. Time-specific and population-level differences in physiological responses of fathead minnows (Pimephales promelas) and golden shiners (Notemigonus crysoleucas) exposed to copper. Aquat. Toxicol. 109, 222-227.
Perry, S.F., Laurent, P., 1993. Environmental effects on fish gill structure and function. In: Rankin, J.C., Jensen, F.B., (Eds.). Fish ecophysiology. Chapman & Hall., London, UK., p 231–264.
Peterson, G.L., 1978. A simplified method for analysis of inorganic phosphate in the presence of interfering substances. Anal. Biochem. 84, 164-172.
Rosabal, M., Hare, L., Campbell, P.G., 2012. Subcellular metal partitioning in larvae of the insect Chaoborus collected along an environmental metal exposure gradient (Cd, Cu, Ni and Zn).
Aquat. Toxicol. 20-121, 67-78.
Sappal, R., Burka, J., Dawson, S., Kamunde, C., 2009. Bioaccumulation and subcellular partitioning of zinc in rainbow trout (Oncorhynchus mykiss): Cross-talk between waterborne and dietary uptake. Aquat. Toxicol, 91(8), 281–290.
Seebaugh, D.R., Wallace, W.G., 2009. Assimilation and subcellular partitioning of elements by grass shrimp collected along an impact gradient. Aquat. Toxicol. 93, 107–115.
Silva, A.O., Martinez, C.B., 2014. Acute effects of cadmium on osmoregulation of the freshwater teleost Prochilodus lineatus: Enzymes activity and plasma ions. Aquat. Toxicol. 156C, 161-168.
doi: 10.1016/j.aquatox.2014.08.009.
Sparks, T., 2000. Statistics in ecotoxicology. Wiley, New York, p.320.
Tennekes, H.A., Sanchez-Bayo, F., 2013. The molecular basis of simple relationships between exposure concentration and toxic effects with time. Toxicology 309, 39-51.
Tennekes, H. A., Sánchez-Bayo, F., 2013. The molecular basis of simple relationship between exposure concentration and toxic effects with time. Toxicology 309, 39-51.
Tsai, J.W., Huang, Y.H., Chen, Y.U., Liao, C.M., 2012. Detoxification and bioregulation are critical for long-term waterborne arsenic exposure risk assessment for tilapia. Environ. Monit. Assess. 184, 561-572.
Tsai, J.W., Ju, Y.R., Huang, Y.H., Deng, Y.S., Chen, W.Y., Wu, C.C., Liao, C.M., 2013. Toxicokinetics of tilapia following high exposure to waterborne and dietary copper and implications for coping mechanisms. Environ. Sci. Pollut. Res. 20(6), 3771-3780. doi: 10.1007/s11356-012-1304-3.
Vasić, V., Momić, T., Petković, M., Krstić, D., 2008. Na+, K+-ATPase as the target enzyme for organic and inorganic compounds. Sensors 8, 8321-8360; DOI: 10.3390/s8128321
Vijver, M.G., Van Gestel, C.A.M., Lanno, R.P., Van Straalen, N.M., Peijnenburg, W.J.G.M., 2004.
Internal metal sequestration and its ecotoxicological relevance: a review. Environ. Sci. Technol.
38, 4705–4712.
Wu, S.M., Hwang, P.P., 2003. Copper or cadmium pretreatment increases the protection against cadmium toxicity in tilapia larvae Oreochromis mossambicus. Zool. Stud. 42(1), 179-185.
Wu, S.M., Chen, C.C., Lee, Y.C., Leu, H.T., Lin, N.S., 2006. Cortisol and copper induce metallothonein expression in three tissues of tilapia (Oreochromis mossambicus) in organ culture. Zool. Stud. 45(3), 363-370.
Wu, S.M.,, Ding, H.R., Lin, L.Y., Lin, Y.S., 2008. Juvenile tilapia (Oreochromis mossambicus) strive to maintain physiological functions after waterborne copper exposure. Arch. Environ. Contam.
Toxicol. 54(3):482-92.
Zhou, B., Nichols, J., Playle, R.C., Wood, C.M., 2005. An in vitro biotic ligand model (BLM) for silver binding to cultured gill epithelia of freshwater rainbow trout (Oncorhynchus mykiss). Toxicol Appl. Pharmacol. 202, 25–3
Figure Captions
Figure 1. Schematic representation of the analytical algorithm by using the damage-based modeling approach and experimental data to evaluate the effectiveness of using branchial NKA activity as a biomarker for assessing Cu toxicity (See text for symbol descriptions)
Figure 2. Time series of Cu accumulation in the gill tissues of juvenile tilapia during 120 h of waterborne exposure to 0.2, 1 and 2 mg Cu L–1. Dashed lines show the optimal fit of the bioaccumulation model to measured data. Symbols represent the means of duplicate measurements. Filled circles and errors bars represent the mean and standard deviation of mean values (mean ± SD, n = 12), respectively. Bars with different letters indicate significant differences between measurements (p < 0.05).
Figure 3. Comparison of NKA activity (μmole pi/mg protein/h) and corresponding damage levels (%) in the gill tissues of juvenile tilapia exposed to 0.2, 1 and 2 mg L–1 of waterborne Cu for 120 h.
Each bar gives the mean ± SD (n = 12). Bars with different letters indicate significant differences between measurements (p < 0.05).
Figure 4. Comparison of the damage in branchial NKA activity (μmole pi/mg protein/h) between experimental measurements and values predicted by the damage assessment model (Eq. 2) after exposure to 0.2, 1 and 2 mg Cu L–1 for 120 h. The dashed line represents 100% fit between measured and predicted values.
Figure 5. Temporal trends of median effect concentration (EC50(t)) values, which indicate the level of impairment of osmoregulatory ability (i.e. declines in whole-body Na2+ concentration). Fitted lines show comparisons between the measured data (gray circles with thick solid lines) and the corresponding model predictions using toxicokinetic and toxicodynamic parameters, following exposure to 0.2 (thick solid line), 1 (solid line with triangles), and 2 mg Cu L–1 (thick dashed line) for 120 h.
Figure 5. Temporal trends of median lethal concentration (LC50(t)) values, which indicate mortality at any given time. Fitted lines show the comparisons between the measured data (gray circles with thick solid lines) and corresponding model predictions using toxicokinetic and toxicodynamic parameters, following exposure to 0.2 (thick solid line), 1 (solid line with triangles), and 2 mg Cu L–1 (thick dashed line) for 120 h.