Abstract
Because of different reported effects of parasitism on the accumulation of metals in fish, it is important to consider parasites while interpreting bioaccumulation data from biomonitoring programmes. Accordingly, the first step is to take parasitism into consideration when simulating metal bioaccumulation in the fish host under laboratory conditions. In the present study, the accumulation of metals in fish-parasite systems was simulated by a one-compartment toxicokinetic model and compared to uninfected conspecifics. As such, metal accumulation in fish was assumed to result from a balance of different uptake and loss processes depending on the infection status. The uptake by parasites was considered an efflux from the fish host, similar to elimination. Physiological rate constants for the uninfected fish were parameterised based on the covalent index and the species weight while the parameterisation for the infected fish was carried out based on the reported effects of parasites on the uptake kinetics of the fish host. The model was then validated for the system of the chub Squalius cephalus and the acanthocephalan Pomphorhynchus tereticollis following 36-day exposure to waterborne Pb. The dissolved concentration of Pb in the exposure tank water fluctuated during the exposure, ranging from 40 to 120 μg/L. Generally, the present study shows that the one-compartment model can be an effective method for simulating the accumulation of metals in fish, taking into account effects of parasitism. In particular, the predicted concentrations of Cu, Fe, Zn, and Pb in the uninfected chub as well as in the infected chub and the acanthocephalans were within one order of magnitude of the measurements. The variation in the absorption efficiency and the elimination rate constant of the uninfected chub resulted in variations of about one order of magnitude in the predicted concentrations of Pb. Inclusion of further assumptions for simulating metal accumulation in the infected chub led to variations of around two orders of magnitude in the predictions. Therefore, further research is required to reduce uncertainty while characterising and parameterising the model for infected fish.
Highlights
Fish have widely been used as bioindicators for metal pollution in aquatic systems [1,2,3,4,5]
For all investigated metals (Fe, Cu, Zn, and Pb), there were no significant differences in the accumulation level in the uninfected chub compared to that in the infected chub as shown by the overlapping ranges of the measured metal concentrations in the uninfected and infected chub (Fig 1)
The concentrations of Fe, Cu, and Zn in the acanthocephalans and in the chub host when the host was not exposed to Pb were similar to those when the host was exposed to Pb (Fig 1)
Summary
Fish have widely been used as bioindicators for metal pollution in aquatic systems [1,2,3,4,5]. Simulation of metal accumulation in fish can provide input required for estimating the risks to fish consumers, especially humans, of exposure to metals via the food chain. Available models for simulating metal accumulation in fish have usually been developed assuming the constancy of the exposure concentration, which does not represent the real conditions either in the laboratory or in the nature [12,13,14]. The PBPK model might provide a more mechanistic understanding of metal toxicity and be reasonably extrapolated across different conditions. These advantages might be outweighed by the requirement for more inputs than the one-compartment model [17]. Different assumptions are required to parameterise the missing factors, which can lead to uncertainties in the model predictions
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.