Estimation of conditional stability constant for copper binding to fish gill surface with consideration of chemistry of the fish gill microenvironment

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1 Comparative Biochemistry and Physiology Part C 133 (2002) Estimation of conditional stability constant for copper binding to fish gill surface with consideration of chemistry of the fish gill microenvironment Shu Tao*, Guojing Liu, Fuliu Xu, Bo Pan Department of Urban and Environmental Sciences, Peking University, Beijing , PR China Received 24 December 2001; accepted 28 May 2002 Abstract Binding-site concentration and conditional stability constants for copper and fish gill surface interactions were calculated based on the data from the literature. Six scenarios were modeled by including or excluding ph and alkalinity differences between the fish gill microenvironment and the bulk solution and the presence of free mucus in the calculation. We demonstrate that changes in ph or alkalinity, or both, for model input had only a slight influence on the calculated results because of the small difference in ph and alkalinity between the gill microenvironment and the bulk solution under the specific experimental conditions. Inclusion of free mucus in the model, however, led to a large change in the final results. For example, with consideration of free mucus and changes in ph and alkalinity in the model, the calculated site concentration and the stability constant were mmolyg wet tissue and log Ks8.77, respectively, compared to mmolyg wet tissue with log Ks7.78 without free mucus and phyalkalinity change Elsevier Science Inc. All rights reserved. Keywords: Fish; Gills; Copper; Mucus; Conditional stability constant 1. Introduction Although the concept of bioavailability is widely accepted and much progress has been made in understanding the dependence of bioavailability on metal speciation, the basic processes and physiochemical factors governing metal speciation and bioavailability have yet to be fully investigated. Because the gills of fish represent important targets for waterborne metals, a critical issue in aquatic toxicology is to understand the fundamental inter- This paper is the outcome of discussions on the Biotic Ligand Model held during the November 2001 SETAC Annual Meeting in Baltimore, MD, USA. *Corresponding author. Tel.yfax: q address: taos@urban.pku.edu.cn (S. Tao). actions controlling the speciation of metals and their bioavailability to fish gills. Early research indicated that free ions, and probably the hydroxy complexes of copper, are biologically available to fish gills while other soluble copper complexes are non-bioavailable (Welsh et al., 1996). For instance, organic ligands usually prevent copper uptake by the gills through binding (Hollis et al., 1996; Paquin et al., 2000). Based on these and other relevant observations, the free ion activity model (FIAM) provides a mechanistic basis for predicting the toxicity of metals to aquatic biota (Morel, 1983). However, as more information is collected, there is an increasing body of evidence suggesting that the FIAM model is not always a good predictor of /02/$- see front matter 2002 Elsevier Science Inc. All rights reserved. PII: S Ž

2 220 S. Tao et al. / Comparative Biochemistry and Physiology Part C 133 (2002) toxicity across an extensive range of water quality conditions (Meyer et al., 1999; Campbell, 1995). Pagenkopf (1983) proposed a gill surface interaction model suggesting that the gill membrane itself acts as a complexing ligand competing for metal binding and can be characterized by a conditional equilibrium stability constant. This concept established the framework behind the development of the biotic ligand model (BLM) (Meyer et al., 1999). Application of the BLM model to metal uptake at fish gills accounts simultaneously for metal speciation in the exposure water and the competitive binding of metals and other cations to biotic ligands on the gill surface. Based on the BLM, it is believed that the concentration of metals bound to fish gills can serve as a constant predictor of acute toxic effects (Meyer et al., 1999; Hollis et al., 2000; McGeer et al., 2000; Paquin et al., 2000; Santore et al., 2001; Di Toro et al., 2001). Key parameters used for BLM are the conditional stability constants for metal gill binding and the concentration of binding sites on the gills. A practical procedure was developed to calculate such constants for a number of metals including copper (Playle et al., 1993; Playle, 1998; McGeer et al., 2000). Playle et al. (1993) estimated a copper gill equilibrium stability constant for fathead minnows (Pimephales promelas) in synthetic soft water. The fish were exposed to copper in the presence of various competing ligands with known stability constants. The Cu gill binding was characterized based on the free copper concentrations calculated using chemical equilibrium modeling and the measured amount of copper accumulated on the gills. Log Kcu gill thus estimated was 7.4 and the number of copper binding sites on a set y9 of gills (70 mg, wet weight) was ;2=10 mol (Playle et al., 1993). The calculation used the properties of the bulk solution. However, the difference between the bulk solution and the fish gill microenvironment was not taken into account. The water layer near the surface of gills is an important microenvironment that is different from that of the surrounding water, thereby affecting both the speciation and bioavailability of metals. Fish gills release ammonia and carbon dioxide, which tend to make the gill microenvironment more basic or more acidic, respectively (Lloyd and Herbert, 1960). Playle and Wood (1989) measured the ph change in the gill microenvironment of fish by sewing a latex mask around the mouth of a fish and attaching tubing under the opercula to siphon water from near the gills. Both rainbow trout and later fathead minnows were studied (Playle et al., 1992). The observed results implied that ph changes could alter metal speciation andyor solubility. It was suggested that the change in water chemistry in the fish gill microenvironment may need to be considered when modeling the physiological and toxicological effects of some metals (Playle, 1998). As an excretory organ, the gills are covered with a layer of protective mucus which has an abundance of negatively charged surface components. These may serve in both the accumulation and sloughing off of potential toxic ions (Handy, 1989). Mucus in the gill microenvironment exists in either a fixed or a free state. The surface of the gill is always covered with a layer of fixed mucus, which is continuously washed away and replaced by secretions (Randall et al., 1991). The continuously sloughed mucus maintains a presence as free mucus in the gill microenvironment (Eddy and Fraser, 1982). The fixed mucus can be characterized as a binding site on the fish gill for both metal speciation modeling and conditional stability constant calculation (Playle, 1998). It is expected that the metal speciation in the fish gill microenvironment is affected less by the presence of free mucus. By measurement and chemical equilibrium modeling, Tao et al. (2000) demonstrated that as a consequence of changes in ph and alkalinity, in conjunction with occurrences of free mucus, copper speciation in the gill microenvironment is much different from that in the surrounding water. For practical reasons, the binding capacity of free mucus in the fish gill microenvironment should be taken into consideration along with changes in ph and alkalinity to derive accurate conditional stability constants for the biotic ligands. The objective of this study was to estimate the conditional stability constant of fish gills for copper based on the experimental data from the literature by taking into consideration the changes in ph and alkalinity and the presence of free mucus in the gill microenvironment. 2. Methodology 2.1. Data for modeling Data on copper exposure and accumulation collected by Playle et al. (1993) were adopted for

3 S. Tao et al. / Comparative Biochemistry and Physiology Part C 133 (2002) Table 1 Fish gill accumulation of copper after exposure to solutions with various ligands (Playle et al., 1993) Ligand mm Gill Cu Log K Log K (mmyg wet tissue) q (MINEQL ) (MINEQA2) EDTA NTA EN Citrate Oxalate Glutamate Salicylate No ligands No ligands no Cu this analysis. Fathead minnows were exposed to poorly buffered synthetic water with various types of synthetic ligands and various levels of total copper for 3 h (Playle et al., 1993). The amounts of copper accumulated in the fish gills measured after the exposure are listed in Table 1. The last two columns of the table provide the log K values for various ligands used by the two chemical q equilibrium models (MINEQL and MINEQA2) which were either used by Playle et al. (1993) or this study for calculating copper speciation Characterization of the fish gill microenvironment Playle (1998) measured ph values in the gills of fathead minnows exposed to bulk solution of various ph. It was reported that at inspired ph (bulk solution) of 6.2, the expired ph (gill microenvironment) was 6.0. There was a difference of 0.2 log-units in ph between the bulk solution and the fish gill microenvironment for the specific water. This difference was considered for the characterization of the gill copper speciation and binding in this study. Tao et al. (2001) developed a set of equations for estimation of alkalinity and free mucus concentration in the fish gill microenvironment as functions of ph and exposure concentration of copper. Since the alkalinity and free mucus data were not available for the exposure experiment from which other data were borrowed for this study, the empirical statistical models for alkalinity and free mucus concentration were applied to characterize the fish gill microenvironment in this study. The equations used are as follows: Alk(g)s30.30y18.00y(pH(g)y4.60) y0.291 w Cu x Ž. Mucuss2.879= 1ye y1.163 = Ž phy q7.409 where ph(g) is the gill microenvironment and ph is the bulk solution. Alk(g) and mucus are alkaline and the level of free mucus in the fish gill microenvironment with units of mg CaCO3yl and mmol Cuyl (in terms of the maximum amount of

4 222 S. Tao et al. / Comparative Biochemistry and Physiology Part C 133 (2002) copper complexed to unit mucus), respectively. wcux is the total concentration in the solution. The bulk solution chemistry and ph of the gill microenvironment for the modeling was from Playle et al. (1993). Therefore, the total copper concentration was 0.27 mm, the ph value for the bulk solution was 6.2. For the gill microenvironment, the ph was 6.0. When these data were used in the empirical model, the calculated alkalinity of the fish gill microenvironment was mg CaCO3yl (ph 6.0) and the level of free mucus was 1.03 mmol Cuyl (as Cu binding capacity ph 6.0) Binding capacity of free mucus for copper A direct titration procedure was used to characterize the binding capacity of the gill mucus from carp for copper (Pan et al., 2002). The results from the direct titration of the free mucus were used in this study: for Cu-free mucus conditional stability constant, log KwCu mucusx 7.05; for the com- plexation capacity of free mucus presented as Cu concentration per unit of organic carbon, Lts0.158 mmolcuymgc. It is assumed that the composition of fish gill mucus is similar among various species and binding properties Determination of the stability constant and site concentration for the Cu gill binding Estimation of the conditional stability constant was conducted for a number of scenarios, in which differences in ph and alkalinity between the gill microenvironment and the presence of free mucus were either taken into consideration or not. The six scenarios modeled in this study are as follows: 1. the difference between the fish gill microenvironment and the bulk solution and the presence of free mucus was totally omitted; 2. only the ph difference between the fish gill microenvironment and the bulk solution was taken into consideration; 3. only the alkalinity difference between the fish gill microenvironment and the bulk solution was taken into consideration; 4. the differences of both ph and alkalinity between the fish gill microenvironment and the bulk solution were taken into consideration; 5. only the competition of free mucus in the fish gill microenvironment was taken into consideration; and Table 2 Summary of the six scenarios for the modeling, scenario 0 is from Playle et al. (1993) Scenario ph Alkalinity Free mucus mg CaCO3yl mmolcuyl both the differences of ph and alkalinity between the fish gill microenvironment and the bulk solution as well as the presence of free mucus were taken into consideration. The six scenarios are summarized in Table 2. The results were also compared with the values estimated by Playle et al. (1993) in Table 2 as scenario 0 with the exact same inputs but different chemical-equilibrium modeling software as scenario 1. For the scenarios not taking the difference of alkalinity into account (scenario 0 3, 5), alkalinity was calculated automatically by the chemicalequilibrium software. The procedure applied by Playle et al. (1993) was followed for determination of the conditional stability constant and binding site concentration for Cu gill surface interaction. Other parameters, which were identical for all scenarios, include Ts 19 8C, Cu (total)s0.27 mm, Nas70 mm, and Cas35 mm (Playle et al., 1993). The influences of ph, alkalinity, and free mucus in the fish gill microenvironment on the estimated stability constants were evaluated based on the outcomes of the various scenarios. 3. Results and discussion 3.1. Calculation of free copper concentrations for the six scenarios 2q Free Cu concentrations in the fish gill microenvironment were calculated using MINEQA2 for the six scenarios (1 6) based on the parameters listed in Table 2 and other variables including total copper concentration of 0.27 mm. The results for the six scenarios (1 6), together with those (scenario 0) derived by Playle et al. (1993), are presented in Table 3.

5 S. Tao et al. / Comparative Biochemistry and Physiology Part C 133 (2002) Table 3 Free Cu concentrations in the fish gill microenvironment at various scenarios 2q No Ligand Concentration Cu (mm) (mm) EDTA NTA EN Citrate Oxalate Glutamate Salicylate Without ligands Without ligands or Cu For free copper concentration calculation, 0.27 mm was used as the total copper concentration for all cases except no. 24, in which the measured baseline copper concentration of mm was adopted. The calculated results for scenario 1 of this study are very close to those calculated by Playle et al. (1993) under the identical conditions (as scenario 0 in Table 3). However, different software q packages (MINEQL and MINEQA2) were used for the modeling. The stability constant values for the ligands involved in this study are not identical for the database of the two packages, though they are very similar to each other (Table 1). As a result, the calculated free copper concentrations at various conditions are not exactly the same. The biggest difference is for citrate where the log K values used were most different (7.3 vs. 7.26). Of the six modeled scenarios in Table 2, the calculated free copper concentrations for the first four (scenario 1 4) are very similar to one another. However, the difference between these four (1 4) and the last two (5 6) scenarios are large, especially for the ligands with relatively low log K values and low ligand concentrations. The common feature of scenarios 5 and 6 is the presence of free mucus. It is evident that the complexation of copper by mucus affected remarkably the copper speciation in the fish gill microenvironment. This has been demonstrated in one of our previous studies, where we found that Cu mucus is one of the dominant species in the gill microenvironment of carp (Tao et al., 2000) Estimation of the stability constant and site concentration for the Cu gill binding The following equation was used to calculate the conditional stability constant and binding site concentration for the Cu gill surface interaction based on data listed in Table 1 and Table 3. wcux wcux 1 s q (3) wcuygillx L L=K t t

6 224 S. Tao et al. / Comparative Biochemistry and Physiology Part C 133 (2002) Fig. 1. Scatchard plot for scenario 1 to 6. where wcux is free copper concentration in the fish gill microenvironment (Table 3) and wcu gillx represents copper accumulated in the gills (Table 1). Following Scatchard s procedure (Scatchard, 1949), the term on the left side of the equation can be calculated based on the data shown in Table 1 and Table 3 for various cases. The calculated result was used in a linear regression as the 2q dependent variable, while Cu concentration was used as the independent variable. The conditional stability constants and concentrations of binding site could be calculated based on the slopes and the interceptions derived from the linear regression. The Scatchard Plots for each scenario (scenario 1 6) are shown in Fig. 1. For the six scenarios, the final results are listed in Table 4. For comparison, the constants predicted by Playle are shown as scenario 0 in the table. There is a slight difference between log K values of the scenarios 0 and 1. Although the same variables were used for the calculation, the difference was introduced by the two sets of conditional stability constants for various ligands especially q for citrate in the databases of MINEQL and MINEQA2 (Table 1). This was consistent with the 2q calculated results of Cu concentrations in the fish gill microenvironment shown in Table 3. When ph or alkalinity, or both, were modified to fit the specific condition in the fish gill microenvironment (scenario 2 4), the calculated log K and L were very close to the results based on bulk t solution chemistry (scenario 1). It was because the ph values in the fish gill microenvironment (6.0) and the bulk solution (6.2) for the specific case were very close to each other, as was the alkalinity. However, it does not necessarily mean Table 4 Calculated stability constants and site concentrations for various scenarios Scenario Log K L t (mgyg wet tissue)

7 S. Tao et al. / Comparative Biochemistry and Physiology Part C 133 (2002) that the difference in ph and alkalinity should not be taken into account for speciation modeling. When fish are exposed to water with ph far away from the crossover point, the difference in ph may become much larger than 0.2 log-units (Playle, 1998; Tao et al., 2001); therefore, it would be expected that the effect of such a change could be significant. The most substantial influence on the calculated results is, of course, the inclusion of free mucus. When free mucus in the fish gill microenvironment is taken into consideration, the derived log K increased approximately one order of magnitude. The complexation of copper by free mucus altered copper speciation in the gill microenvironment and the inclusion of free mucus in copper speciation calculation and copper gill surface interaction modeling provides a more accurate result. That is, the inclusion of mmolcuymgc binding sites for free mucus, with a log KCu mucuss7.05. It should be indicated that for using the predicted Cu gill binding parameters in the modeling of the copper speciation and bioavailability, the presence of free mucus and the changes in ph and alkalinity in the gill microenvironment should also be included. 4. Conclusion When differences in ph and alkalinity between the fish gill microenvironment and the bulk solution and the presence of free mucus are taken into account, the predicted log K and Lt values are different from those calculations based on the properties of the bulk solution. The binding site was mmolyg wet tissue with log K of 8.77 based on the conditions of the fish gill microenvironment, compared to mmolyg wet tissue with log K of 7.78 based on the bulk solution. Acknowledgments We thank Dr Richard Playle for his valuable comments on this manuscript. Funding provided by ICA (TPT0604) and NSFC ( , ). References Campbell, P.G.C., Interactions between trace metals and aquatic organisms: a critique of the free-ion activity model. In: Tessier, A., Turner, D.R. (Eds.), In Metal Speciation and Bioavailability in Aquatic Systems. Wiley, Chichester, pp Di Toro, D.M., Allen, H.E., Bergman, H.L., Meyer, J.S., Paquin, P.R., Santore, R.C., Biotic ligand model of the acute toxicity of metals. 1. Technical basis. Environ. Toxicol. Chem. 20, Eddy, F.B., Fraser, J.E., Sialic acid and mucus production in rainbow trout (Salmo gairdneri Richardson) in response to zinc and seawater. Comp. Biochem. Physiol. 73C, Handy, R.D., The ionic composition of rainbow trout body mucus. Comp. Biochem. Physiol. 93A, Hollis, L., Burnison, K., Playle, R.C., Does the age of metal-dissolved organic carbon complexes influence binding of metals to fish gills? Aquatic Toxicol. 35, Hollis, L., McGeer, J.C., McDonald, D.G., Wood, C.M., Effects of long term sublethal Cd exposure in rainbow trout during soft water exposure: implications for biotic ligand modelling. Aquatic Toxicol. 51, Lloyd, R., Herbert, D.W.M., The influence of carbon dioxide on the toxicity of un-ionized ammonia to rainbow trout Salmo gairdneri Richardson. Ann. Appl. Biol. 48, McGeer, J.C., Playle, R.C., Wood, C.M., Galvez, F., A physiologically based biotic ligand model for predicting the acute toxicity of waterborne silver to rainbow trout in freshwaters. Environ. Sci. Technol. 34, Meyer, J., Santore, R., Bobbitt, J., Debrey, L., Boese, C., Paquin, P., et al., Binding of nickel and copper to fish gills predicts toxicity when water hardness varies, but freeion activity does not. Environ. Sci. Technol. 33, Morel, F., Principles of Aquatic Chemistry. Wiley, New York. Pagenkopf, G.K., Gill surface interaction model for trace-metal toxicity to fishes: role of complexation, ph and water hardness. Environ. Sci. Technol. 17, Pan, B., Cao, J., Liu, G.J., Tao, S., Characteristics of common carp gill mucus complexed with copper. Environ. Chem. 21, Paquin, P.R., Santore, R.C., Wu, K.B., Kavvadas, C.D., Di Toro, D.M., The biotic ligand model: a model of the acute toxicity of metals to aquatic life. Environ. Sci. Policy 3, S175 S182. Playle, R.C., Modelling metal interactions at fish gills. Sci. Total Environ. 219, Playle, R.C., Dixon, D.G., Burnison, K., Copper and cadmium binding to fish gills: estimates of metal gill stability constants and modelling of metal accumulation. Can. J. Fish Aquatic Sci. 50, Playle, R.C., Wood, C.M., Water chemistry changes in the gill micro-environment of rainbow trout: experimental observations and theory. J. Comp. Physiol., B 159, Playle, R.C., Gensemer, R.W., Dixon, D.G., Copper accumulation on gills of fathead minnows: influence of water hardness, complexation and ph of the gill microenvironment. Environ. Toxicol. Chem. 11, Randall, D., Lin, H., Wright, P.A., Gill water flow and the chemistry of the boundary layer. Physiol. Zool. 64,

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