Environ. Sci. Technol. 1999, 33, 4069-4072
Modeling the Bioconcentration of Organic Compounds by Fish: A Novel Approach HENK J. M. VERHAAR,* JOOST DE JONGH, AND JOOP L. M. HERMENS Research Institute of Toxicology, Utrecht University, P.O. Box 80.176, NL-3508 TD Utrecht, The Netherlands
Bioconcentration is generally assumed to be similar to the partitioning of compounds between an aqueous and lipoid phase. In the case of bioconcentration lipoid phase is thought to consist of the lipid and lipoid tissues of an organism, e.g. a fish. However, it is frequently observed that for highly lipophilic compounds, defined as compounds with a high octanol-water partition coefficient, or log Kow, that simple view seems to break down. At low and intermediate log Kow there seems to be a linear relationship between bioconcentration, expressed as log BCF, and log Kow. At high log Kow deviations are seen, generally indicating that for these compounds BCF increases less than proportionally with increasing log Kow. Many different explanations and accompanying correlation models have been proposed to date. We present here a model that is capable of explaining the different shapes of the BCF/ Kow relationships empirically observed, based on the effect of the presence of tiny amounts of different types of organic material in the aqueous phase. The actual shape of the nonlinear curve simply depends on the amount of organic material in the water, the difference in “affinity” for hydrophobic compounds of the organic material in water and lipid in fish, and to a lesser extent the amount of lipid in fish. The model presented also fits a large dataset of experimental BCF values with fitted parameter values that are consistent with the biology and physical chemistry of the described system.
Introduction Bioconcentration of xenobiotic organic chemicals, such as pollutants, from water into fish, or other aquatic biota, is a very important process in the chain of events leading to toxic effects of many such compounds in the environment. Furthermore, bioconcentration kinetics is one of the processes that govern the function of LC50-vs-time behavior (1-4). Numerous authors have in the past observed that bioconcentration factors (log BCF) show a positive linear correlation with the log Kow of numerous compounds (see e.g. refs 5 or 6). Of course, as a first order approximation, this is only to be expected, since the assumption is that the more hydrophobic a compound is, the more it will eventually end up in lipoid tissues in aquatic organisms. It has also been observed frequently that at the high log Kow end of the range * Corresponding author fax: +31-70-4260001; e-mail: verhaar.h@ oag.nl. Current address: OpdenKamp Adviesgroep, Koninginnegracht 23, 2514 AB The Hague, The Netherlands. 10.1021/es980709u CCC: $18.00 Published on Web 10/07/1999
1999 American Chemical Society
(see e.g. ref 7) as well as at the very low end (8), the linear correlation of BCF with log Kow seems to break down, resulting in a constant BCF at the hydrophilic end and in a leveling off or even decreasing BCF at the hydrophobic end of the range. A similar effect has been observed in numerous quantitative structure-activity relationships (QSAR) for several pharmacological endpoints, in which cases authors suggested using bilinear or even parabolic functions of log Kow to model endpoints. It has to be noted here that in pharmacology the fact that effects are generally recorded at a single restricted timepoint after administering a single, or sometimes multiple discrete, dose(s) is for a large part responsible for these observations (9). In studies of the correlation of BCF with log Kow a number of explanations have been suggested to explain the above mentioned nonlinear relationships (5, 10-15). Explanations range from simple considerations of nonequilibrium for highly lipophilic compounds to size limitations (13), suggesting that an upper limit exists on a molecule’s effective diameter, above which no molecule is able to pass membrane pores, and to increased (induced) biodegradation or biotransformation. Some authors have indicated that the decreased bioavailability of highly lipophilic compounds might explain this behavior (15, 16). For example Gobas et al. (15) have shown that a reduction in bioavailability may result in a strong underestimation of BCF. Here we report on a more general mathematical model that is capable of explaining this BCF/log Kow behavior based on the assumption of a reduced bioavailability.
Background and Theory Recently De Jongh and co-workers (17) described a model that estimates the tissue-to-blood partition coefficient for organic chemicals, for use in PB-PK modeling, from log Kow, depending largely on the water and lipid content or the respective compartments. Following the success of that particular model, we realized that the same description that was used in that study to describe the tissue and blood compartmentsviz. two compartments consisting of water and comparable lipids in nonequal ratios and separated by a membrane that is permeable to organic compoundsscan also be used to more accurately describe the water/fish system. The primary difference between our present description of the fish/water system and the system that is implicit in most approaches to estimating BCF from compound hydrophobicity is the explicit inclusion of a “lipidlike” subcompartment in the aqueous compartment. It is of course unthinkable that any real experimental setup in which fish are introduced in an aqueous environment could be described as consisting of fish in a pure aqueous compartment. Even if the water were pure to start with, the introduction of the fish would “instantaneously” provide an amount of dissolved organic matter to the aqueous phase, e.g. originating from their mucous layer or from feces. The approach that we will be presenting is capable of explaining the observed BCF/log Kow behavior even with minute amounts of organic matter in the aqueous compartment. The basic assumptions here is that in any BCF system under consideration there is a “dissolved” organic carbon or “lipid” fraction in the aqueous phase, however small, and that given its nature and especially amount it is experimentally impossible to determine the truly dissolved amount of compound using state-of-the-art procedures. This small amount will be shown subsequently, to make a huge difference in the observed BCF. VOL. 33, NO. 22, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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The model that De Jongh et al. (17) present for mammalian systems is as follows
PCtb ) (Vl,t × Kowa1 + Vw,t/Vl,b × Kowa2 + Vw,b) + B
(1)
with PCtb being the tissue-blood partition coefficient, Vl is the lipid fraction of either tissue or blood, Vw is the water fraction of either tissue or blood (Vl + Vw ) 1 by definition), Kow is the octanol/water partition coefficient, a1 and a2 are Collander coefficients that depend on the similarity between octanol and the lipid in the respective compartments, and B is a factor that is assumed to correct for implicit mechanisms in the fish aqueous fraction (basically it corrects for nonzero intercepts). a1 and a2 are usually set equal to each other for statistical reasons. It is quite easy to see that, when instead of partitioning between two physiological tissues, considering partitioning between water and an organism, the same model can be applied. If we assume that the water compartment consists of pure water and a homogeneous (either dissolved or separate but inseparable) organic carbon (or lipid) fraction and that the fish can be described as a single compartment consisting of water and lipid (again inseparable as far as analysis of the compound under interest is concerned), the model then becomes
FIGURE 1. log BCF vs log Kow for Collander coefficients a1 and a2 equal.
BCF ) (Vl,f × Kowa1 + Vw,f/Vl,w × Kowa2 + Vw,w) + B (2) with BCF being the bioconcentration factor. If we are not satisfied with such a simple description of a fish, we can alternatively use a PBPK model to describe the uptake and elimination of a compound of interest. We can then either use measured physiological partition coefficients for a known compound or the approach described by De Jongh et al. (eq 1) for unknown or hypothetical compounds. The important part is to include a lipoid fraction in the aqueous phase.
Methods One-compartment model calculations were performed in Theorist for Macintosh (18), running on a Macintosh Quadra 650 desktop computer. PB-PK model calculations were performed in MATLAB (19), also running on a Macintosh Quadra 650. The PB-PK model was adapted from Nichols et al. (20). The blood-water and tissue-blood partition coefficients were estimated based on log Kow according to De Jongh et al. (17). Nonlinear least squares estimation of function parameters (fitting to experimental data) was performed within Systat (21).
Results Model Calculations. Figure 1 shows the relation between BCF and Kow for the situation where a1 and a2 are equal and 0.9, an organic fraction of 1 × 10-5 in water, a 5% lipid content in fish, and a B of 0.0. There is a number of interesting observations to make from this graph. First of all, with increasing log Kow, BCF levels off. Basically, it is the lowered availability of the compound in the aqueous phase, due to the presence of a lipoid fraction, that is responsible for this, coupled with the assumption that it is only the total concentration in the aqueous phase (including what is in the lipoid fraction) that can be determined. The position of the upper inflection point depends on the amount of organic carbon in the aqueous phase as well as on the size of a1 (and a2). With a1 larger than 1 the inflection point shifts to lower log Kow, while an a1 smaller than 1 shifts the inflection point to higher log Kow. Given the published values for sediment/ water, organic carbon/water, and dissolved organic carbon/ water partition coefficients (22, 23) it is assumed that values 4070
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FIGURE 2. log BCF vs log Kow log BCF vs log Kow for Collander coefficients a1 larger than a2. for a will vary between at most 0.5 and 1.5. With a1 being 1, the location of the inflection point is at log Kow ) 6. With a decreasing amount of organic material in the aqueous phase, not only the location of the inflection point shifts to higher log Kow but also the maximum BCF attained also gets larger. That, of course is not surprising, since with an ever smaller amount of lipid in the aqueous phase we expect the system to behave even more as a simple partitioning system, with BCF going up “indefinitely” with increasing Kow. Now what happens when a1 and a2 are not the same? If a1 is larger than a2, this basically means that the lipid fraction in fish is more “hydrophobic” than the organic carbon fraction in water and vice versa. Keeping all other parameters constant, we can see from Figure 2 that with a1 larger than a2 BCF tends to keep increasing even after the inflection point. With a1 smaller than a2, we see that BCF decreases with increasing log Kow after going though the inflection point (see Figure 3), precisely the behavior several authors have observed and subsequently tried to model with all kinds of nonlinear correlations. So what if we think a one-compartment, two-fraction description of the physiology of a fish is not sufficiently accurate? Then we can substitute a PB-PK model for the simple fish compartment and use eq 1 for the blood-water partition coefficient as well as the tissue-blood partition coefficients. To this order we adapted the rainbow trout PBTK model by Nichols and co-workers (20) by substituting De Jongh equations for different tissues for the explicit partition coefficients. We then used this model to predict bioconcentration factors (wet weight) at equilibrium situations for log Kow values from -0.5 to 7, in 0.5 unit steps. The results
FIGURE 3. log BCF vs log Kow log BCF vs log Kow for Collander coefficients a1 smaller than a2.
FIGURE 5. Comparison of experimental BCF data for 132 randomly selected compounds with the Kow/BCF relationship presented in the current paper (data from ref 24).
TABLE 1. Function Parameters for Eq 2 Fit to Data from Ref 24
FIGURE 4. log BCF vs log Kow when using a PBPK model; Collander coefficients a1 and a2 (water to blood) equal. of this exercise have been depicted in Figure 4. This figure clearly shows that there is almost no difference between the PB-PK results and the results of the simple one-compartment model (Figure 1). We therefore believe it is fair to use the simple one-compartment, two-fraction BCF model to both qualitatively and quantitatively predict the dependence of BCF on Kow. Data Correlation. To show that the BCF model presented here is at least as good as currently adopted models for fitting and predicting experimental log BCF values from log Kow, we fit the model to a set of 132 log BCF values reported by Nendza (24). The results are depicted in Figure 5; the fitted values for the parameters from eq 2 are presented in Table 1. The fitted line, according to the one-compartment, twofraction model, fits the data reasonably well, at least as good as the polynomial and bilinear models presented by Nendza (24) and others. The main advantage of our model is that there actually is a theory (or hypothesis) behind it that governs its shape as well as having physical meaning. If we next take a look at the fitted parameter values, the first thing that can be noticed is that we chose to keep a1 and a2 the same. We have seen previously that the ratio of a1 and a2 influences the shape of the curve at the high log Kow end of the correlation, with the curve assuming a horizontal course when the ratio a1/a2 is unity. If we consider the Nendza data, we can only conclude that at the high log Kow range the uncertainty, or spread, in the data is such that a horizontal “upper” part of the curve seems the only sensible assumption. Assuming nonequality of a1 and a2 would introduce an extra parameter to be fitted, whose fit value would basically depend on the few scattered datapoints at the high log Kow end. Because this is not a sound statistical
parameter
value
remarks
Vl,f Vw,f Vl,w Vw,w a1 a2 B
13.3% 86.7% 2.4e-5% 99.999976% 1.055 1.055 NA
fit ) 100 - Vl,f fit ) 100 - Vl,w fit ) a1 forced to 0
approach, we assumed equality of the two Collander coefficients. Second, the fractions of lipid in fish and “organic carbon” in water that were fitted from the BCF data are very reasonable values. For fish lipid we find a value of 13%, which is somewhat at the high end but not unreasonable (see e.g. refs 25 and 26). The organic carbon fraction in the aqueous compartment is estimated at 2.4 × 10-5% or 240 nL organic carbon per L of water. Roughly speaking, this amounts a concentration of some 200 µg L-1 DOC in water, which again is a very reasonable value. If we consider the recommendations for BCF experiments in the 1991 OECD guidelines documents, we see that the recommended biomass “concentration” for bioconcentration tests is 1 g fish per liter of water. If we for the moment assume that fish in BCF tests were responsible for “introducing” organic carbon material into the aqueous medium, 200 µg organic carbon per liter of water would then amount to no more than about 0.02% of the fish biomass. This is probably at the lower end of what we would expect the fish to actually contribute to the DOC load. Besides, it shows that the underlying “mechanism” could very well hold for surface waters and even for the tap water to be used for BCF experiments. Van Loon et al. (27) e.g. showed DOC concentrations in surface water samples varying between 700 µg L-1 and 15 mg L-1. A drinking water sample had a DOC content of 1500 µg L-1.
Discussion A reduction in bioavailability has been suggested earlier by Gobas et al. (15) as one of the potential causes for nonlinearity in BCF-Kow relations. They estimated the available solute fraction from the ratio of observed and expected uptake rate constants and concluded that the bioavailable concentration can be as low as 3% for very hydrophobic compounds. In this paper we assume the same hypothesis and present it in a mathematical model that explains and predicts the nonlinear BCF-Kow relations of highly lipophilic compounds VOL. 33, NO. 22, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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from water to fish. It shows that, given the fact that there will always be some organic matter in an aqueous system, a nonlinear behavior of BCF vs Kow is actually expected. The actual shape of the nonlinear curve simply depends on the amount of organic material in the water, the difference in “affinity” for hydrophobic compounds of the organic material in water and lipid in fish, and to a lesser extent the amount of lipid in fish. We have also shown that we can fit this model to a set of 132 BCF data that is frequently used to develop all sorts of BCF/Kow QSAR models (24) and that not only the relationship found does more right to the actual distribution of the datapoints (no reason exists to assume anything other than a horizontal leveling off of the BCF at high log Kow) but also the actual fitted parameters (lipid content of fish, organic carbon content of water, and Collander coefficient) make sense numerically.
Acknowledgments Part of this work was carried out within the framework of the EC Project Fate and Activity Modeling of Environmental Pollutants using structure-activity relationships (FAME), contract no. ENV4-CT96-0221.
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Received for review July 14, 1998. Revised manuscript received August 5, 1999. Accepted August 16, 1999. ES980709U
