Environ. Sci. Technol. 2004, 38, 537-543
Accumulation and Toxicity of Cadmium in the Aquatic Oligochaete Tubifex tubifex: A Kinetic Modeling Approach ERIK STEEN REDEKER* AND RONNY BLUST Ecophysiology, Biochemistry and Toxicology Unit, Department of Biology, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerpen, Belgium
Heavy metal pollution is a serious threat to ecosystem functioning. Different approaches have been developed to relate the exposure of heavy metals to their accumulation and toxicity. One approach is to relate metal toxicity to the concentrations of the metals in the whole body or a specific target tissue instead of the external exposure concentrations. To test the usefulness of this approach, the relationship between cadmium exposure, accumulation, and toxicity was investigated using an oligochaete worm and kinetic modeling. The uptake and elimination of cadmium by the aquatic oligochaete Tubifex tubifex from the aqueous phase was studied as function of time at different exposure concentrations using both radioactive and nonradioactive cadmium. A two-compartmental pharmacokinetic model was constructed and parametrized by fitting the model to the measured cadmium body concentrations during exposure to different cadmium concentrations. The uptake rate constants were dependent on the cadmium exposure concentration, and this relation could be welldescribed by incorporation of Michaelis-Menten type uptake kinetics. The toxicity of cadmium was analyzed by determining the lethal exposure concentration associated with a mortality of 50% (LC50) at different time points. LC50 values decreased with increasing exposure time reaching the incipient lethal level after 15 d. Critical body concentrations (CBC) associated with 50% mortality were calculated by combining the model-predicted pharmacokinetic parameters and the measured LC50 values. The predicted mean CBC (0.32 µmol/g wet weight ( 0.02) was in good agreement with the experimentally obtained CBC for cadmium found in T. tubifex (0.37 µmol/g wet weight ( 0.07) and appeared to be independent of exposure time and exposure concentration. Our results show that a pharmacokinetic modeling approach provides a tool to link metal exposure to availability, accumulation, and toxicity under variable exposure scenarios taking into account the kinetics of the processes.
Introduction The pollution of aquatic ecosystems with heavy metals is a serious environmental problem because of their persistence and high toxicity to many aquatic organisms (1). Aquatic * Corresponding author phone: +32 (0)3 218 03 50; fax: +32 (0)3 218 04 97; e-mail:
[email protected]. 10.1021/es0343858 CCC: $27.50 Published on Web 12/11/2003
2004 American Chemical Society
ecosystems are usually monitored for heavy metal pollution using chemical and biological approaches. Chemical analysis of heavy metal concentrations in the environment alone does not provide adequate information concerning the biotoxicity of heavy metals (2). The concentration in the water can only be reliably applied when the relationship between the metal exposure concentration and the concentration at the site of toxic action within the organism is known. Therefore, water quality criteria for heavy metals also have to consider the effects of environmental and organism related conditions on metal toxicity (3, 4). The bioavailable fraction of a metal in the water phase can change due to several factors. It can, for instance, be reduced by the binding of the metal ion to dissolved organic ligands or by competition with other cations present in the water such as H+ and Ca2+ (5). Predictions of metal toxicity that are not based on total metal concentrations but on the free-metal ion activity are more adequate, and recent developments also allow to take into account competitive effects that may ameliorate toxicity (6). One way of doing this is by using the Biotic Ligand Model (BLM), which expresses toxicity in terms of the free metal ion activity and competitive effects at the metal binding sites of the organism. The toxicity of the metal is considered to be proportional to the amount of metal associated to these binding sites. Limitations of the BLM are that it is a static approach that does not take into account differences in exposure time and considers the aqueous phase as the only source of exposure and toxicity. An alternative to metal exposure concentrations as a measure of toxicity is the concentration within the organism that causes an adverse biological effect [i.e., the critical body concentration (CBC) or critical tissue concentration (CTC)]. This approach assumes that the concentration of the toxicant within the whole organism or target tissue that produces a certain effect is independent of exposure conditions and time (7). In this case, a direct relationship should exist between metal tissue concentrations and toxicity over a wide range of conditions. The advantage of expressing toxicity in terms of tissue concentrations is that the effects of differences in exposure scenario and exposure time are integrated. However, aquatic organisms have developed various strategies do deal with metals, including internal storage and active elimination. The first strategy may result in excessive accumulation of metals without the development of toxic effects so that the direct relationship between metal tissue concentrations and toxicity is lost. In the aquatic environment, the benthic fauna is of great importance because it represents an important link in the aquatic food web (8). Any deleterious effects of heavy metals on these organisms are therefore likely to be reflected in the whole ecosystem (9). One of the most widespread benthic groups, ubiquitous in aquatic habitats, are the tubificid oligochaetes (10). Tubifex tubifex, one of the oldest described aquatic oligochaetes (11), is a cosmopolitan aquatic oligochaete with a reputation for being very resistant though not insensitive to pollution. It is found in both nonpolluted and highly polluted waters (12) and is often one of the last to disappear from a contaminated site (13, 14). The oligochaete, which can also adapt to a wide range of environmental conditions (12), is often used as a bioindicator of pollution (14). Although T. tubifex has been used as a test organism for ecotoxicological studies to assess acute toxicity data of various metals (8, 9, 13, 15, 16) and sediments (10, 12, 17, 18), still very few data concerning sublethal toxicity and bioaccumulation are available on this worm. VOL. 38, NO. 2, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
537
The aim of this work was to determine the accumulation kinetics of cadmium by T. tubifex by pharmacokinetic modeling and to explore to what extend the concept of the critical body concentration could be applied to determine toxicity thresholds in this organism for cadmium. Cadmium has a persistent behavior and is considered to be one of the most toxic metals and acute effects in freshwater organisms have been reported for exposure concentrations as low as 0.003 µM (19). The effect of accumulation on the toxicity of cadmium to T. tubifex was determined by relating the internal body concentration with the observed toxic effects. The derived kinetic parameters of the model and toxicity data were used to estimate the associated CBC. Model performance was evaluated by comparing the predicted and the measured values of the critical body concentrations.
Materials and Methods Test Species and Solutions. To perform the accumulation and toxicity tests, the tubificidae were obtained from a local source and the background cadmium tissue levels were determined. The organisms used for the uptake and elimination experiments with radioactive cadmium were collected from the upper layer of the sediment of the Scheldt River, near Kruibeke (Belgium) at low tide. Field-collected organisms were transported to the lab in their natural sediment. The sediments were sieved over a 1-mm sieve, and the tubificidae were selected for equal size and carefully transferred to aquaria with reconstituted freshwater of medium hardness (chemically defined medium hard freshwater containing CaCl2, 2.0 mM; MgSO4, 0.5 mM; NaHCO3, 770 µM; KCl, 77 µM; pH 7.7; hardness, 250 expressed as mg/L CaCO3 according to ref 20). The organisms were allowed to acclimatize in reconstituted freshwater for 4 d prior to the experiments. The water in the aquarium was constantly aerated and kept at 15 °C. The worms were fed a suspension of finely ground TetraMin flakes (Tetra Werke, Germany), and the water was changed daily. The organisms were not fed 24 h before the start of the experiments. All experiments were conducted at 15 °C. The organisms were selected for size and randomly placed in the exposure solutions. During the experiments the animals were not fed, and the water was not aerated. The pH and O2 were recorded daily and remained constant during the experimental period (pH, 7.70 ( 0.2; O2, 9.64 mg/L ( 0.35). Cd was added from a stock solution as CdCl2 (cadmium chloride monohydrate, Merck, extra pure) in reconstituted freshwater. Calculations on the speciation of the cadmium species present in the reconstituted freshwater showed that 73% of the cadmium was present as the free Cd2+ ion in the solution and that this percentage remained constant over the entire used CdCl2 concentration range from 0 to 100 µM. Speciation calculations were performed with the computer program Visual MINTEQ (U.S. EPA version 2.02). Experimental Design. The kinetic parameters required for the pharmacokinetic modeling were derived from the combination of two separate experiments. In the first experiment, the uptake and subsequent elimination was followed using radioactive 109Cd. In the second experiment, the uptake of stable cadmium was followed at different metal exposure concentrations. In the second experiment also the mortality was recorded on a daily basis. Critical body concentrations associated with 50% mortality were determined in two separate ways: values were calculated directly from the measured internal body concentrations associated with 50% mortality and predicted using the estimated pharmacokinetic parameters and the observed mortalities. Model Construction and Data Analysis. A two-compartmental model was constructed and used to describe the uptake and elimination of cadmium by the worms via the 538
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 38, NO. 2, 2004
FIGURE 1. Two-compartmental model for the accumulation of cadmium by Tubifex tubifex. The organism is represented by a central and a peripheral compartment. The coefficients kij and kji represent the transfer rate constants between the different compartments. water phase. Figure 1 shows a schematic representation of the model. The two-compartmental model assumes that cadmium is transferred from an external source, in this case the water phase, to a central compartment. From this central compartment, cadmium is either eliminated or transferred to a second compartment, the peripheral compartment. Although the compartments in the model may represent specific organs or tissues such as the hemolymph, muscle tissue, or the digestive tract (21), they do not necessarily have to represent morphological or physiological entities but can simply characterize the dynamics of the chemical with identifiable kinetics (22). The compartmental model was formulated, solved, and fitted to the experimental data with the commercially available software program SAAM II (SAAM II, version 1.1.1, SAAM Institute, University of Washington, USA). This program for kinetic processes creates a set of differential equations (eqs 2 and 3) from the compartmental model structures and associates the experimental attributes to the equations during the process of fitting (23). With the assumption that the chemical entering the compartment is instantaneously distributed and the compartments are well mixed and kinetically homogeneous, the transfer between the compartments are assumed to follow first-order kinetics according to the following relationship:
Fij ) kijQi
(1)
where Fij is the mass flux (µmol d-1) of Cd from the ith to the jth compartment, Qi is the mass transfer (µmol) from the ith to the jth compartment at time t, and kij is the transfer rate constants (d-1). The differential equations for the different compartments are
δC ) k01W + k21P - (k10 + k12)C δt δP ) k12C - k21P δt
(2) (3)
where C and P are the concentrations of Cd in the central and the peripheral compartment (µmol/g), respectively, and W is the amount of Cd in the water phase (µM). Assuming that the behavior of cadmium, once inside the compartment, does not change and is not dependent on the outside exposure concentration, the transfer between the central and the peripheral compartments follows first-order kinetics, and the transfer rate constants k12 an k21 are constant for all exposure concentrations. To obtain a consistent set of parameters, the data obtained from the different Cd concentrations in the water phase were fitted simultaneously to the same model. To describe the relationship between the cadmium concentration in the
exposure solution and the uptake rates, a Michaelis-Menten type uptake model was used:
J01 )
(Jmax[Cd]) (Km + [Cd])
(4)
where J01 is the uptake rate of Cd (k01[Cd] (µmol d-1 L-1)), Jmax is the maximum uptake rate of cadmium (µmol d-1 L-1), Km is the half-saturation constant (µM), and [Cd] is the cadmium concentration in the water (µM). The set of differential equations was solved numerically using the Rosenbrock integrator with a relative error of 0.001. To provide the best fit, the program iteratively minimizes an objective function during the fitting based on the residual sums of squares. The best data fit was chosen based on the Akaike information criterion (AIC) and the Schwarz-Bayesian information criterion (BIC) both calculated and provided by the program. These criteria are used to compare models and to discriminate between different models with a different number of adjustable parameters. Both the AIC and BIC are a function of the goodness of fit, the number of adjustable parameters, and the total number of data points. Between two rival models, the model with the lowest number of AIC and BIC is considered to be the one that better explains and describes the data with the least number of parameters. The simultaneous fit is the best fit for all exposure concentrations. The variation explained by the model was evaluated by calculating the coefficients of determination (R 2). Critical Body Concentrations. The critical body concentration concept assumes that there is a relationship between internal body concentrations of a toxicant and toxic end points and that toxicity occurs when a certain threshold concentration of the toxicant in the tissues has been reached. Metal accumulation is a time-dependent process and the combined result of uptake and elimination. So the amount of toxicant that accumulates in the organism Ct is a function of both the concentration in the exposure medium [Cd] and the duration of the exposure t: Ct ) f([Cd],t). Using this relationship, CBC50 values can be calculated by using the LC50 as the exposure concentration [Cd] and the time t for which this LC50 value is calculated. Using the estimated kinetic parameters for the uptake and elimination of the compartmental model that describes this relationship, simulations of the critical body concentration were made for the different calculated LC50 values at the different time points with the software program SAAM II. To compare the model-predicted values with the actual critical values in the organisms, the CBC was also calculated directly from the measured cadmium body burden of the exposed animals using the trimmed Spearman-Karber method (24). Bioaccumulation and Toxicity Tests. As a preliminary range finding experiment, an acute toxicity test was performed. Ten animals were exposed to 0, 0.5, 1, 2.5, 5, 10, 25, 50, 75, and 100 µM cadmium in 500-mL polypropylene beakers containing 400 mL of exposure solution, and the experiments were run in three replicates. Worms were observed daily for 4 d, and the number of dead animals was recorded. Animals were considered dead when there was no response to physical stimulation. Acute toxicity was determined by measuring the 50% lethal concentration at 24, 48, 72, and 96 h using a trimmed Spearman-Karber method (25). In addition for these time intervals, also the no observed effect concentration (NOEC) and lowest observed effect concentration (LOEC) was calculated using a one-way ANOVA with Graphpad Prism version 4.00 (GraphPad Software, Inc.) On the basis of the results of the range finding acute toxicity tests, a bioaccumulation experiment was conducted at sublethal concentrations of cadmium. For this experiment, 15 groups of 10 animals were exposed to 0, 1, 2.5, 5, and 10 µM Cd for up to 15 d in 500-mL polypropylene beakers
containing 400 mL of exposure solution. Each sampling day, 10 organisms were removed from each exposure solution. The organisms were washed with reconstituted freshwater to remove loosely adsorbed metal. Previous preliminary experiments performed in our lab with other organisms (26) showed that washing with metal binding ligands (EDTA or 8-hydroxyquinoline-5-sulfonic acid) and washing for different durations did not influence the effect of rinsing as compared to rinsing with deionized water or reconstituted freshwater. The worms were weighed using an electrobalance (Cahn model 4100, Cahn/Ventro Corp.) to the nearest 0.01 mg, dried in an oven (Heraeus Type T5060) at 60 °C for 24 h, and weighed again. Samples were stored at -20 °C until further analysis. The dry tissue was solubulized using 70% HNO3 and 30% H2O2 (15:1) in a regular microwave oven (Philips SpaceCube M760). Samples were diluted after digestion with deionized water. Digested samples were stored at -20 °C until further analysis. Cd concentrations were measured by graphite furnace atomic absorption spectroscopy (Varian, SpectrAA 800, 228.8 nm). Digestion efficiency and possible contamination were checked by using standard reference material (Bovine Liver, BCR, Community Bureau of Reference) and process blanks, digested and analyzed in the same way as the samples. In a simultaneously conducted experiment, the mortality as a function of time was recorded under the same exposure conditions and concentrations in 3 replicates during 17 d. The acute toxicity of cadmium was expressed as the percentage of mortality and by determining the LC50 values over the experimental period using a trimmed SpearmanKarber method. To determine the uptake and the elimination rate of cadmium, the organisms were exposed to a solution of 0.1 µM cadmium spiked with 200 kBq/L of radiotracer 109Cd (γ emitter, half-life 462 d; cadmium chloride in 0.1 M HCl, carrier free, (37 MBq/mL; Amersham Pharmacia Biotech UK Limited). Ten organisms were added to 50 mL of exposure solution in 100-mL polypropylene beakers. Periodically, the worms were removed from the solution, rinsed with reconstituted freshwater, counted for their radioactivity with a gamma counter (Minaxi auto-gamma 5000 series, Packard) for 5 min and returned to the solution. After exposure for 4 d, the worms were placed in a solution with the same cadmium concentration but without addition of radiotracer and periodically counted for their radioactivity for an additional 8 d. The experiments were run in 3 replicates.
Results Acute Toxicity. In a preliminary experiment, an acute toxicity test was performed by exposing the organisms to Cd solutions ranging from 0 to 100 µM. The LC50 values decreased with increasing exposure time. At 24 h of exposure, the calculated LC50 value was 70.8 µM (95% CI: 57.9-86.5 µM), and at the end of the 96 h exposure time, the value decreased to 14.7 µM (95% CI: 12.2-17.8 µM). The highest exposure concentration for which the difference in mortality with the control group was not statistically significant (NOEC, p < 0.001) was 50 µM after 24 h of exposure and 10 µM after 48-96 h of exposure. The lowest exposure concentration for which the mortality was significantly different from the mortality in the control group (LOEC, p < 0.001) was 75 µM after 24 h of exposure and 25 µM after 48-96 h of exposure. The calculated LC50, NOEC, and LOEC values for cadmium at the different time intervals are presented in Table 1. To calculate a reliable LC50 value, the exposure concentrations used in the cadmium accumulation experiments must cover a wide range of concentrations resulting in over 50% mortality at the highest exposure levels. On the other hand, sufficient organisms must survive the test to determine VOL. 38, NO. 2, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
539
TABLE 1. LC50 Values of Cadmium (µM) and Their Corresponding 95% Confidence Limits and the NOEC and LOEC Values at 24, 48, 72, and 96 h in Reconstituted Freshwatera LC50 Cd (µM) 95% conf. limit NOEC (µM) LOEC (µM) a
24 h
48 h
72 h
96 h
70.8 57.94-86.46 50 75
22.47 17.73-28.49 10 25
15.58 12.12-20.03 10 25
14.75 12.20-17.84 10 25
pH 7.7, hardness 250 expressed as mg/L CaCO3, and temperature 15 °C.
TABLE 2. Parameter Estimates of Transfer Rate Constants for Two-Compartmental Model Applied to the Bioaccumulation Data after Exposure to Different Concentrations of Cadmium in Time
k01 k01 k01 k01 k01 k10 k12 k21 a
FIGURE 2. Uptake and elimination of cadmium by Tubifex tubifex after exposure to a 0.1 µM cadmium solution (solid dots) and the model fits (line). Error bars represent the standard deviations of 3 replicates, each consisting of 10 pooled organisms. The elimination period was started after 4 d. The coefficient of determination R 2 was calculated for the entire curve describing both uptake and elimination. The insert shows the relative elimination during the first 10 h. cadmium body concentrations. On the basis of these criteria and the results of the acute toxicity tests, a concentration range was chosen for a bioaccumulation experiment with concentrations ranging from 0.1 to 10 µM. Cadmium Accumulation. In a first experiment the accumulation of cadmium by T. tubifex was determined by exposing the organisms to a 0.1 µM cadmium solution spiked with radioactive 109Cd for 4 d followed by an elimination period of 8 d after transferring the organisms to solutions without radiotracer. The results of the uptake and elimination experiment are shown in Figure 2. T. tubifex showed a rapid accumulation of cadmium during the first 8 h followed by a slower accumulation phase. The uptake rate constant was 0.117 d-1 (SD ( 0.018). The elimination also showed a rapid phase during the first 8 h followed by a slower elimination phase. At the start of the elimination, 0.0067 µmol/g was accumulated. At the end of the elimination period of 8 d, still 0.0053 µmol/g cadmium (78%) was present in the body, which corresponds to an approximate half-life of 15 d. The overall elimination constant k10 was 14.57 d-1 (SD ( 3.72). In a second experiment, the accumulation of cadmium was determined by exposing the organisms to 0, 1, 2.5, 5, and 10 µM cadmium over a 15-d period. Figure 3 shows the measured internal body concentrations of cadmium as function of time for the different exposure concentrations and the model fits for the accumulation of cadmium. Parametrization of the model was done by simultaneously fitting the model to the data obtained from both the cadmium radiotracer and the stable cadmium experiments. In this way, a consistent set of parameters was obtained. The twocompartmental model provided a good fit to the observed cadmium uptake and elimination data over a wide range of exposure concentrations. The coefficients of determination (R 2) for the fittings ranged from 0.61 (p < 0.001) to 0.97 (p 540
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 38, NO. 2, 2004
exposure Cd (µM)
parameter estimate (d-1)
SDa
CVb
0.1 1 2.5 5 10 all all all
0.117 0.106 0.085 0.066 0.045 14.6 2.277 0.045
0.018 0.017 0.013 0.010 0.007 3.719 0.294 0.009
15.0 15.6 15.6 15.6 15.7 25.5 12.9 20.3
SD, standard deviation of the estimate. b CV, coefficient of variation.
< 0.001). Table 2 represents the parameter values obtained for the different transfer rate coefficients. The uptake transfer rates were dependent on the cadmium exposure concentration and followed Michaelis-Menten saturation kinetics. The kinetic parameters of the MichaelisMenten equation and the fitting were determined by nonlinear regression (Figure 4). The maximum uptake rate Jmax was 0.707 µmol d-1 L-1 (SE ) 0.0058, p < 0.0001) with a half-saturation constant Km of 5.78 µM (SE ) 0.096, p < 0.0001, R 2 > 0.99). Cadmium Toxicity. The mortality of the worms was followed during 17 d parallel to the 15-d bioaccumulation experiment. The LC50 values based on the exposure concentrations were dependent on the exposure duration, and the values decreased from 70.78 µM at 24 h to 1.68 µM (95% CI: 1.49-1.90 µM) after 17 d (Figure 5). CBCs for cadmium were determined in two ways and plotted as a function of time (Figure 6). First, the CBCs were derived directly from the measured internal body concentrations and the associated mortality. This was done for every observation time with a mortality of at least 50%. The average value of the internal cadmium body concentration associated with a 50% mortality was 0.37 µmol/g wet weight (SD ( 0.07, n ) 9). Second, the CBCs were simulated by combining the kinetic parameters obtained from the pharmacokinetic model. The LC50 values determined for the different exposure times were used as input exposure concentrations in the pharmacokinetic model. The cadmium body concentrations corresponding to these LC50 values were then estimated by the model. The mean model-predicted output value was 0.32 µmol/g wet weight (SD ( 0.02, n ) 12), which is in good agreement with the measured value. Most importantly, the CBC calculated in this way was independent of the duration of the exposure. Figure 7 shows the percentage of mortality plotted against the measured cadmium body concentrations. The graph represents a superposition of the different internal body concentration-mortality relationships for all the time points and exposure concentrations. This combined data was fitted with a sigmoidal dose-response function with a variable slope using the computer program Graphpad Prism version 4.00 (GraphPad Software, Inc.). Fitting this sigmoidal function
FIGURE 3. Accumulation of cadmium over time by Tubifex tubifex after exposure to 1, 2.5, 5, and 10 µM cadmium solution (dots) and the model fittings (lines). Each data point represents the average cadmium whole body concentration of the pooled life organisms.
FIGURE 4. Effect of cadmium concentration in the exposure solution on the kinetics of the uptake by Tubifex tubifex. J01 is the uptake rate (µmol d-1 L-1) of Cd, Jmax is the maximum uptake rate of cadmium (µmol d-1 L-1), and Km is the half-saturation constant (µmol L-1). Data points represent the uptake rates at different concentrations; the solid line represents the Michaelis-Menten type model fit according to eq 4. to the data resulted in a 50% CBC value of 0.38 µmol/g wet weight (SD ( 0.02) with a Hill slope of 4.19 (SD ( 0.87, R 2 ) 0.66).
Discussion The first objective of this work was to determine the pharmacokinetic parameters for the bioaccumulation of cadmium by the aquatic oligochaete T. tubifex and to relate this to the toxicity. The organism was modeled as a twocompartmental system consisting of a central compartment and a peripheral compartment. In this model, uptake and elimination take place through the central compartment, and the peripheral compartment is assumed not to be in direct contact with the environment. This model adequately describes the bioaccumulation of cadmium for T. tubifex over a wide range of exposure concentrations from 0.1 to 10 µM. The uptake rate constants determined range from 0.117
FIGURE 5. Time dependency of 50% lethal exposure concentrations of cadmium to Tubifex tubifex. Error bars represent the 95% confidence levels. d-1 for the exposure to 0.1 µM Cd for 0.045 d-1 for the exposure to 10 µM Cd. The concentration dependency of the cadmium uptake rates for T. tubifex was well-explained by a MichaelisMenten-type uptake model. This model gives a mechanistic description of the uptake process characterized by a transport system with a maximum rate of transport (Jmax) of 0.707 µmol d-1 L-1 and a half-saturation constant Km of 5.78 µM. A lower Km, which indicates a measure of the affinity of the transporter for the metal species, indicates a higher affinity of this transport system (27). The use of pharmacokinetic modeling is a powerful tool to describe toxicant accumulation and effects under various exposure scenarios and exposure durations. The uptake rates depend on the functional characteristics of the exposure systems involved, the exposure concentrations and routes, and the environmental conditions including the chemical speciation of the metals, water hardness, hydrogen ion activity, and water temperature (4, 28). However, information concerning the bioaccumulation kinetics does not provide information on toxicity. Therefore, metal bioavailability, VOL. 38, NO. 2, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
541
TABLE 3. Summary of Different Cadmium Toxicity Data for Tubifex tubifex LC50 (µM) 24 h
48 h
72 h
96 h
0.03 0.56 0.68 >0.89 6.9 10.68 10.68
0.02 0.28 0.40 0.57 4.1 6.41 8.01
0.41
0.27
0.53
27.49 57.82 70.8 87.18 674.84
13.01 32.03 22.47 57.82 532.51
21.35 15.58 48.04
0.36 2.85 9.18 15.12 14.75 28.47 422.82
a
Hardness expressed as CaCO3 (mg L-1).
b
temp (°C) 20 20 20 20 24 20 22 20 22 15 22 30
pH
hardnessa
Ca/Mg
ref
6.3 6.85 7.2 nrb 7 7.32 nr nr 7.8 7.8-8.3 7.7 7.8-8.3 7.6
(0.1 34.2 34.2 no Ca nr 261 119-137 5.3 80 119-137 250 119-137 770
no Mg 2.7 2.7 no Mg nr 9.7 nr nr no Mg nr 4 nr 1.1
9 9 9 8 29 9 12 30 1 12 c 12 16
nr, not reported. c This study.
exposure media. This makes it difficult to compare lethal exposure concentrations of cadmium to T. tubifex among studies and to interpret species-specific sensitivity for a toxicant.
FIGURE 6. Model-predicted values of the critical body concentrations using pharmacokinetic parameters and LC50 values as the exposure concentrations (line) plotted against critical body concentrations observed in experimental toxicity tests (dots).
FIGURE 7. Percentage mortality as a function of the internal body concentrations of cadmium. Dots represent body concentrations of the surviving organisms at different time points. The solid line represents the fitting of the sigmoidal function. accumulation, and effects should be linked in a dynamic manner. The calculated LC50 values decreased with increasing exposure time reaching an incipient level of 1.68 µM (95% CI: 1.49-1.9) after 17 d of exposure. Comparison with LC50 values from literature showed that there is much diversity and variation in lethal concentrations of cadmium for T. tubifex, with reported LC50 values ranging from 0.03 to 674.84 µM (Table 3). The LC50 values found in this study fall within this wide range of toxicity values. The studies listed differ much in experimental conditions and composition of the 542
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 38, NO. 2, 2004
A possible alternative for the exposure concentration of the toxicant as a measure of toxicity is the internal body or tissue concentration of the toxicant. The hypothesis is that, irrespective of the exposure conditions, concentrations, and time, toxicity occurs when a critical internal level is reached (31). The derived pharmacokinetic parameters of the twocompartmental model were used to estimate this CBC based upon cadmium water exposure experiments, and these estimations were compared with the directly measured whole-body values. The average model-estimated 50% CBC value was 0.32 µmol/g wet weight (SD ( 0.02, n ) 14) from 4 to 17 d. This value is close to the directly measured body concentration associated with a mortality of 50%. These whole-body concentrations of cadmium found in T. tubifex were essentially constant: 0.37 µmol/g wet weight (SD ( 0.07, n ) 9) from 6 to 15 d (Figure 6) and appeared to be independent of exposure concentration and exposure time. It should be noted that the whole-body concentrations were measured in living organisms because of difficulties in accurately determining the wet weights of dead organisms due to rapid degradation of the tissues. This may give rise to an underestimation of the experimentally determined CBC. Enserink et al. (32) reported that the LC50 for cadmium, calculated after 21 d of exposure, was associated with a body concentration of 0.98 µmol/g wet weight for daphnids (calculated from reported dry weight assuming a water content of 90%). Borgmann et al. (33) found cadmium body concentrations associated with 6 weeks survival based LC50 values for Hyalella azteca varied over a narrow range from 0.068 to 0.17 µmol/g wet weight (calculated by ref 34, assuming 80% water content). Crommentuijn et al. (4) reported lethal body concentrations for soil arthropods. They calculated values of 0.065 and 0.13 µmol/g wet weight for the collembola Orchesella cincta and Tomocerus minor, respectively, and 0.42 µmol/g wet weight for the oribatid mite Platynothrus peltifer (calculated from dry weight assuming 80% water content) when exposed to cadmium in the food. Thus, from these results it appears that, at least for these species, lethal concentrations of cadmium in the exposure medium vary by several orders of magnitude while the internal cadmium concentration inducing mortality varies much less. When evaluating toxicity on the basis of critical body or tissue concentrations, differences in bioavailability and exposure conditions are automatically taken into account. The body or tissue concentration of cadmium may provide a better estimate of the dose at the site(s) of toxic action than
the concentration in the exposure medium alone. Metals are preferentially taken up in certain tissues and accumulation and toxicity patterns depend on the organism, the metal, the exposure routes, and the environmental conditions. Aquatic organisms can handle metals in different ways. The internal tissue concentrations of essential metals such as copper or zinc are generally regulated within a narrow concentration window by active regulation of uptake and/or elimination. This means that within certain limits, the internal metal concentration is independent of the exposure concentration. At low or high exposure concentration, the regulatory system fails and internal tissue concentrations vary with the exposure concentration. For nonessential metals such as cadmium, this regulation is usually very limited or absent. Taking into consideration the effects of environmental conditions and exposure routes on metal uptake and accumulation, a more direct relation between external and internal concentrations exists. However, metal accumulation does not necessarily result in metal toxicity. Inside an organism, the metals are distributed among various compartments that process metals in different ways such as the hepatopancreas, the nephridia, or the muscle tissues. Toxicity will occur when the concentration of the metal in one of the tissues reaches a critical level so that one or more essential functions are impaired. Within each tissue compartment, metals are bound by ligands that form kinetically labile and more stabile complexes. This results in the formation of different metal pools within each compartment, some of which remain biologically reactive, while others do not play a role in active metabolism and can be considered as internal metal stores or sinks. For example, for T. tubifex, after exposure to cadmium-contaminated sediments, the concentration of a metallothioneinlike protein, which is thought to sequester unbound metals, was significantly elevated above control level (18). This means that part of the metals present in an organism or specific tissues within an organism does not contribute to toxicity. Therefore, the concept of a critical body or tissue concentration only holds when the formation of stabile and inert complexes is limited and all of the metal present in a certain tissue compartment can be considered to be biologically reactive or that the reactive pool is a constant proportion of the total metal concentration. Thus, if the metals are regulated or trapped in inactive forms, toxic effects can be expected above a certain threshold, when the influx of metals exceeds the regulatory, storage, and detoxifying capacity of the organism. Aquatic organisms have developed various strategies to deal with metals, and there are examples of organisms that have developed very efficient regulatory and detoxifying systems. In many cases, the different strategies are combined to generate maximal tolerance to prevailing exposure conditions. The results obtained with the oligochaete worm T. tubifex show that this organism does not regulate the internal cadmium concentration and that over a wide range of exposure concentrations and time intervals the concept of a CBC appears to apply. Within this context, the pharmacokinetic modeling provides a tool to link metal exposure to availability, accumulation, and toxicity under variable exposure scenarios taking into account the kinetics of the processes. In exposure-based risk assessment, effects are largely based on relating biological effects of metals to concentrations in the environment. This pragmatic approach can be used at the regulatory level to obtain general and to a certain extent also site-specific water quality criteria, but it does not deal with the processes in a mechanistic manner and is therefore less suited to develop criteria on a fundamental basis. The importance of the used pharmacokinetic approach is that it does not only deal with exposure concentrations and exposure time but can also deal with internal compartmentalization, factors that are also critical
in determining metal toxicity. The further development of this approach and dose-based toxicology instead of purely exposure based toxicology can significantly improve our fundamental understanding of the processes leading to metal toxicity and as a consequence also the setting of environmental quality criteria.
Acknowledgments This research was supported by the Flemish government (Vlaams Impulsprogramma Natuurontwikkeling, VLINA 99/ 05).
Literature Cited (1) Fargasova, A. Biologia 1998, 53, 315-319. (2) Fargasova, A. Gen. Physiol. Biophys. 1999, 18, 48-53. (3) McCarty, L. S.; Mackay, D.; Smith, A. D.; Ozburn, G. W.; Dixon, D. G. Environ. Toxicol. Chem. 1992, 11, 917-930. (4) Crommentuijn, T.; Doodeman, C. J. A. M.; Doornekamp, A.; Van der Pol, J. J. C.; Bedaux, J. J. M.; Van Gestel, C. A. M. Environ. Toxicol. Chem. 1994, 13, 1781-1789. (5) Meyer, J. S.; Boese, C. J.; Collyard, S. A. Comp. Biochem. Physiol., Part C: Pharmacol., Toxicol. Endocrinol. 2002, 133, 99-109. (6) Di Toro, D. M.; Allen, H. E.; Bergman, H. L.; Meyer, J. S.; Paquin, P. R.; Santore, R. C. Environ. Toxicol. Chem. 2001, 20, 2383-2396. (7) Fisher, S. W.; Hwang H.; Atanasoff, M.; Landrum, P. F. Ecotoxicol. Environ. Saf. 1999, 43, 274-283. (8) Lucan-Bouche´, M. L.; Habets, F.; Biagianti-Risbourg, S. V. Ecotoxicol. Environ. Saf. 2000, 46, 246-251. (9) Brokovic-Popovic, I.; Popovic, M. Environ. Pollut. 1977, 13, 65-72. (10) Reynoldson, T. B.; Thompson, S. P.; Bamsey, J. L. Environ. Toxicol. Chem. 1991, 10, 1061-1072. (11) Brinkhurst, R. O. Hydrobiologia 1999, 406, 9-19. (12) Reynoldson, T. B.; Rodriguez, P.; Madrid, M. M. Hydrobiologia 1996, 334, 199-206. (13) Lucan-Bouche´, M. L.; Habets, F.; Biagianti-Risbourg, S. V. Hydrobiologia 1999, 411, 39-44. (14) Lucan-Bouche´, M. L.; Biagianti-Risbourg, S.; Arsac, F.; Vernet, G. Aquat. Toxicol. 1999, 45, 9-17. (15) Fargasova, A. Ecotox. Environ. Saf. 1994, 27, 210-213. (16) Khangarot, B. S. Bull. Environ. Contam. Toxicol. 1991, 46, 906-912. (17) Wiederholm, T.; Milbrink, G. Water Air Soil Pollut. 1987, 36, 131-154. (18) Gillis, P. L.; Diener, L. C.; Reynoldson, T. B.; Dixon, D. G. Environ. Toxicol. Chem. 2002, 21, 1836-1844. (19) 2001 Update of Ambiant Water Quality Criteria for Cadmium; U.S. Environmental Protection Agency: Washington, DC, 2001; EPA 882-R-01-001. (20) Standard Methods for the Examination of Water and Wastewater, 17th ed.; American Public Health Association: Washington, DC, 1989. (21) Wen, Y. H.; Kalff, J.; Peters, R. H. Environ. Rev. 1999, 7, 1-18. (22) Barron, M. G.; Stehly, G. R.; Hayton, W. L. Aquat. Toxicol. 1990, 18, 61-86. (23) Barrett, P. H. R.; Bell, B. M.; Cobelli, C.; Golde, H.; Schumitzky, A.; Vicini, P.; Foster, D. M. Metabolism 1998, 47, 484-492. (24) Hamilton, M. A. Environ. Sci. Technol. 1978, 12, 417-417. (25) Hamilton, M. A.; Russo, R. C.; Thurston, R. V. Environ. Sci. Technol. 1977, 11, 714-719. (26) Bervoets, L.; Blust R. Aquat. Toxicol. 2000, 49, 145-157. (27) Van Ginneken, L.; Chowdhury, M. J.; Blust, R. Environ. Toxicol. Chem. 1999, 18, 2295-2304. (28) Wren, C. D.; Stephenson, G. L. Environ. Pollut. 1991, 71, 205-241. (29) Chen, T.; Furst, A.; Chien, P. K. J. Am. Coll. Toxicol. 1994, 13, 112-120. (30) Chapman, P. M.; Farrell, M. A.; Brinkhurst, R. O. Aquat. Toxicol. 1982, 2, 47-67. (31) Hickie, B. E.; McCarty, L. S.; Dixon, D. G. Environ. Toxicol. Chem. 1995, 14, 2187-2197. (32) Enserink, E. L.; Maas-Diepeveen, J. L.; Van Leeuwen, C. J. Water Res. 1991, 25, 679-687. (33) Borgmann, U.; Norwood, W. P.; Babirad, I. M. Can. J. Fish. Aquat. Sci. 1991, 48, 1055-1060. (34) McCarty, L. S.; Mackay, D. Environ. Sci. Technol. 1993, 27, 1719-1728.
Received for review April 24, 2003. Revised manuscript received October 13, 2003. Accepted October 14, 2003. ES0343858 VOL. 38, NO. 2, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
543
