Sequential infection can decrease virulence in a fish-bacterium-fluke interaction: Implications for aquaculture disease management

Abstract

Hosts are typically infected with multiple strains or genotypes of one or several parasite species. These infections can take place simultaneously, but also at different times, i.e. sequentially, when one of the parasites establishes first. Sequential parasite dynamics are common in nature, but also in intensive farming units such as aquaculture. However, knowledge of effects of previous exposures on virulence of current infections in intensive farming is very limited. This is critical as consecutive epidemics and infection history of a host could underlie failures in management practices and medical intervention of diseases. Here, we explored effects of timing of multiple infections on virulence in two common aquaculture parasites, the bacterium Flavobacterium columnare and the fluke Diplostomum pseudospathaceum. We exposed fish hosts first to flukes and then to bacteria in two separate experiments, altering timing between the infections from few hours to several weeks. We found that both short-term and long-term differences in timing of the two infections resulted in significant, genotype-specific decrease in bacterial virulence. Second, we developed a mathematical model, parameterized from our experimental results, to predict the implications of sequential infections for epidemiological progression of the disease, and levels of fish population suppression, in an aquaculture setting. Predictions of the model showed that sequential exposure of hosts can decrease the population-level impact of the bacterial epidemic, primarily through the increased recovery rate of sequentially infected hosts, thereby substantially protecting the population from the detrimental impact of infection. However, these effects depended on bacterial strain-fluke genotype combinations, suggesting the genetic composition of the parasite populations can greatly influence the degree of host suppression. Overall, these results suggest that host infection history can have significant consequences for the impact of infection at host population level, potentially shaping parasite epidemiology, disease dynamics and evolution of virulence in farming environments.

Keywords: dynamic infection; epidemiology; multiple infections; sequential infection; spatiotemporal variation.

Figure 1

Mean survival times (±SE) of rainbow trout co‐exposed simultaneously (Sim, open boxes) or sequentially (Seq, grey boxes) to three strains of the bacterium Flavobacterium columnare (1–3) and three genotypes of the fluke Diplostomum pseudospathaceum (A–C) in all possible combinations in the first experiment. No Diplostomum indicates survival of fish exposed only to F. columnare. Boxes show data for fish that died during the experiment. Black dots indicate the percentage of fish surviving in each combination

Figure 2

Mean survival times (±SE) of rainbow trout previously unexposed (Unexp., open boxes) or exposed to Diplostomum pseudospathaceum (Exposed, grey boxes) when re‐exposed to three strains of the bacterium Flavobacterium columnare (1–3) and three genotypes of the fluke D. pseudospathaceum (D–F) in all possible combinations in the second experiment. No Diplostomum indicates survival of fish exposed only to F. columnare. Boxes show data for fish that died during the experiment. Black dots indicate the percentage of fish surviving in each combination

Figure 3

Model predictions of the end‐of‐season (day 70) total host abundance as a function of increasing cercarial force of infection (Γ), for each bacterial strain–fluke genotype combination, parameterized using data from Experiment 1. Solid black line = host abundance in the presence of both bacteria and fluke (“B&F”), dashed blue line = host abundance in the presence of just the bacteria (“B only”), dashed green line = host abundance in the absence of both bacteria and fluke (“Neither”). Other parameters: initial number of hosts = 100, initial number of bacteria‐infected hosts = 10, β_B = 0.001

Figure 4

As in Figure 3, but ignoring any effect of fluke infection on recovery from bacterial infection (prior or subsequent fluke fish are assumed to recover from bacterial infection at the same rate as bacteria‐only infected fish; any effects of fluke infection on host survival time are retained, as in Figure 3)