Genetic variation in resistance and high fecundity impede viral biocontrol of invasive fish

Common carp Cyprinus carpio is one of the top global invasive vertebrates and can cause significant ecological damage. The Australian Government's National Carp Control Program (NCCP) proposes to release Koi herpesvirus (KHV) to eradicate feral carp in one of the largest ecological interventions ever attempted. Ecological and human health risks have been highlighted regarding the release of a highly pathogenic viral biocontrol for an aquatic species. The efficacy of KHV has also been questioned, and it has not been demonstrated to produce lasting population reductions. We developed an individual-based model (IBM) to examine the ecological and evolutionary response of a carp population after KHV release. This simulated the interaction between fish life history, viral epidemiology, host genetic resistance and population demography to critically evaluate the impact of KHV release under optimal conditions and a ‘best-case scenario’ for disease transmission. KHV will rarely result in prolonged reductions or population extinctions. Crucially, realistic scenarios result in a rapidly rebounding population of resistant individuals. Additional measures aimed to reduce carp population recovery rate (e.g. with genetic engineering) require rapid efficacy to significantly reduce carp numbers alongside KHV. Fish fecundity has an overwhelming influence on viral efficacy as a biocontrol agent when combined with genetic resistance within a population. A high probability of population extinction is only met when carp fecundity is reduced to 1% of biological observations. Synthesis and applications. We use an individual-based model to evaluate the efficacy of Koi herpesvirus biocontrol in Common Carp, and find that high host fecundity combined with genetic resistance results in rapid population rebound after initial large fish kills. Biocontrol approaches relying on natural selection lose efficacy over successive generations as resistance genes increase in frequency. Given the intense logistical effort and risks to ecosystems and human health associated with large fish kills after viral release, we suggest that sustained manual removal, alongside ecological restoration to favour recovery of native species, provides a risk-free approach to reducing populations

Pharmaceutical Metabolism in Fish: Using a 3-D Hepatic In Vitro Model to Assess Clearance

At high internal doses, pharmaceuticals have the potential for inducing biological/pharmacological effects in fish. One particular concern for the environment is their potential to bioaccumulate and reach pharmacological levels; the study of these implications for environmental risk assessment has therefore gained increasing attention. To avoid unnecessary testing on animals, in vitro methods for assessment of xenobiotic metabolism could aid in the ecotoxicological evaluation. Here we report the use of a 3-D in vitro liver organoid culture system (spheroids) derived from rainbow trout to measure the metabolism of seven pharmaceuticals using a substrate depletion assay. Of the pharmaceuticals tested, propranolol, diclofenac and phenylbutazone were metabolised by trout liver spheroids; atenolol, metoprolol, diazepam and carbamazepine were not. Substrate depletion kinetics data was used to estimate intrinsic hepatic clearance by this spheroid model, which was similar for diclofenac and approximately 5 fold higher for propranolol when compared to trout liver microsomal fraction (S9) data. These results suggest that liver spheroids could be used as a relevant and metabolically competent in vitro model with which to measure the biotransformation of pharmaceuticals in fish; and propranolol acts as a reproducible positive control

Pharmaceuticals used in substrate depletion experiments using trout liver spheroids.

<p>Substrate decrease over total incubation period (%), depletion rates constant (<i>k</i>; h^-1) and half-life (t_1/2) values are shown as mean ± SD. NSD = no substrate depletion.</p

Substrate depletion kinetics of propranolol by trout liver spheroid cultures prepared from two separate fish livers.

<p>Closed circles denote cultures from fish one; open circles denote cultures from fish two (<i>n</i> = 6 at each time point). Values at each time point are mean ± SE. Substrate depletion kinetics determined using two-parameter, exponential decay curve-fit analysis (non-linear regression; Sigma Plot v12.5, Systat Software, San Jose, USA).</p

Comparison of intrinsic hepatic clearance rates (CL_{INT, HEPATIC}) of propranolol and diclofenac by trout liver spheroids with trout, human S9 and human hepatocytes.

<p>Clearance rates for human S9 and hepatocytes are shown as mean ± SD and taken from studies reviewed previously [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168837#pone.0168837.ref002" target="_blank">2</a>]. Clearance rates for trout S9 are taken from two previous fish <i>in vitro</i> studies [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168837#pone.0168837.ref002" target="_blank">2</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168837#pone.0168837.ref020" target="_blank">20</a>]. Where no SD is provided, the data are collated from multiple studies and the figures provided for an indication of comparable rates.</p

Propranolol depletion over time (%) measured over 24h incubation, calculated depletion rate constants (<i>k</i>; h^-1) and half-life (hours) (t_1/2) for liver spheroid cultures from individual fish experiments.

<p>Values for each individual fish experiment are mean ± sd from combined spheroid cultures (<i>n</i> = 6 wells). Initial measured dose at time zero was 98 ± 4 μg/L (n = 72 wells). Individual differences between fish were analysed by the natural log transform of the % depletion (normally distributed) and a one-way anova with Tukey <i>post hoc</i> to identify individual fish (fish sharing the same letter A through D are not different to one another). Fish number 12 had significantly slower clearance than any other fish (p<0.001), but has not been excluded from the dataset.</p

Prediction of pharmaceutical metabolism in trout liver spheroids based on ‘read-across’ from human metabolism data.

<p>^<b>†</b> Pharmaceuticals are ranked according to the Biopharmaceutics Drug Disposition Classification System (BDDCS) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168837#pone.0168837.ref023" target="_blank">23</a>] where 1 = High solubility / extensive metabolism; 2 = Low solubility / extensive metabolism; 3 = High solubility / poor metabolism. ^<b>+</b> Major CYP enzymes believed responsible for the metabolim of pharmaceuticals in humans (modified from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168837#pone.0168837.ref002" target="_blank">2</a>] with additional data sourced from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168837#pone.0168837.ref044" target="_blank">44</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168837#pone.0168837.ref047" target="_blank">47</a>].</p