Evolution of virulence in emerging epidemics

Abstract

Theory predicts that selection for pathogen virulence and horizontal transmission is highest at the onset of an epidemic but decreases thereafter, as the epidemic depletes the pool of susceptible hosts. We tested this prediction by tracking the competition between the latent bacteriophage λ and its virulent mutant λcI857 throughout experimental epidemics taking place in continuous cultures of Escherichia coli. As expected, the virulent λcI857 is strongly favored in the early stage of the epidemic, but loses competition with the latent virus as prevalence increases. We show that the observed transient selection for virulence and horizontal transmission can be fully explained within the framework of evolutionary epidemiology theory. This experimental validation of our predictions is a key step towards a predictive theory for the evolution of virulence in emerging infectious diseases.

Figure 1. Schematic representation of the bacteriophage λ life cycle.

Free viral particles of the wild type virus (green) and the virulent mutant (red) infect susceptible cells . A proportion of successful infections leads to genome integration at rate and to produce infected cells and or results in cell lysis at rate and . Infected cells lyse through spontaneous reactivation of the provirus at rate and for and , respectively. (See Table S1 in Text S1 for the definition and the values of all the parameters of this model).

Figure 2. Theoretical evolutionary epidemiology.

(A) change in prevalence (proportion of infected bacteria). (B) change in the λcI857/λ ratio in the provirus stage. (C) change in the λcI857/λ ratio in the free virus stage. The initial value of the λcI857/λ ratio in the provirus was 1∶1, and two initial prevalence values were considered: 1% (red) and 100% (blue). We ran 10000 simulations of our model (see equations (1) and (2)) allowing some variation over the phenotypic values ( and ) of the two virus strains. The gray envelopes show the range of variation among all simulation runs and colored lines show the median of these simulations (see section S1.3 in Text S1). See Table S1 in supporting Text S1 for other parameter values.

Figure 3. Experimental evolutionary epidemiology.

(A) change in prevalence (proportion of infected bacteria). (B) change in the λcI857/λ ratio in the provirus stage. (C) change in the λcI857/λ ratio in the free virus stage. The initial value of the λcI857/λ ratio in the provirus was 1∶1, and competition was started from two initial prevalence values: 1% (red) and 100% (blue). The data was obtained from the first experiment. The lines are the mean over four chemostats (2 marker/virulence combinations with 2 independent replicates), and the envelopes show the 95% confidence intervals of the log transformed data.

Figure 4. Effect of initial prevalence on transient virulence evolution, in the two life stages of the virus.

We plot the maximal value of the λcI857/λ ratio from our theoretical model (crosses, same parameter values as in Figure 2) and from the second experiment (dots and vertical bars are the means and their 95% confidence intervals over two chemostats of the log transformed data, see supplementary information). The λcI857/λ ratio is shown for both the provirus (black) and the free virus (gray) stages. The λcI857/λ ratio is significantly higher among free viruses than among proviruses, and decreases significantly as the initial prevalence increases (maximal λcI857/λ ratio in the first 15 hours of the second experiment, see also Figure S6).