The fittest versus the flattest: experimental confirmation of the quasispecies effect with subviral pathogens

Abstract

The "survival of the fittest" is the paradigm of Darwinian evolution in which the best-adapted replicators are favored by natural selection. However, at high mutation rates, the fittest organisms are not necessarily the fastest replicators but rather are those that show the greatest robustness against deleterious mutational effects, even at the cost of a low replication rate. This scenario, dubbed the "survival of the flattest", has so far only been shown to operate in digital organisms. We show that "survival of the flattest" can also occur in biological entities by analyzing the outcome of competition between two viroid species coinfecting the same plant. Under optimal growth conditions, a viroid species characterized by fast population growth and genetic homogeneity outcompeted a viroid species with slow population growth and a high degree of variation. In contrast, the slow-growth species was able to outcompete the fast species when the mutation rate was increased. These experimental results were supported by an in silico model of competing viroid quasispecies.

Figure 1. Competition Experiments among CChMVd and CSVd under Normal and Mutagenic Environmental Conditions

Black dots represent +UVC treatment while open dots represent control treatment. Each dot represents the median of the ratios estimated for multiple plants. Error bars represent the jackknife estimate of the standard error of the median. The lines represent the best fit to the non-linear model described in Materials and Methods.

Figure 2. Characterization of the Genetic Diversity of the Competing Viroid Populations

Two measures of the genetic diversity (± SEM) of the CChMVd (open symbols) and CSVd (solid symbols) populations 6 wk after initiation of the competition experiments. Three plants were analyzed for each treatment (20 clones of each viroid per plant). Circles represent the averages from control plants and squares the averages from UVC-treated plants. Arrows indicate the direction of the UVC effect.

Figure 3. Results from the Simulation Model of Competing Bit String Populations

The best solution obtained by searching over parameter space is shown (s_CSVd = 0.33, s_CChMVd = 0.05, μ = 0.016, μ^UVC = 0.063, and k_c = 3). (A) Population dynamics under control and UVC conditions, sampled over five different replicates over 40 generations. (B) Average Hamming distance among sampled digital viroids (± SEM). Solid bars correspond to the control conditions, open bars to UVC conditions, and gray bars to UVC conditions after exclusion of the 66.5% CSVd lethal genotypes from the computations. (C) The survival-of-the-flattest effect is shown here using the two populations that evolved separately with increasing mutation rates. The average fitness for each population is plotted against mutation rate. Using the above s_CSVd, s_CChMVd, and k_c values, the mutation rate was allowed to vary from μ = 0.001 to μ = 0.15. At a given critical mutation rate (here μ_crit = 0.059), the average fitness of digital-CSVd (solid dots and continuous line) starts to decay below the one shown by digital-CChMVd (open dots and dashed line). The domain where the flattest wins over the fittest is indicated as a gray area. (D) Shows a cartoon interpretation of the observed effect of high mutation rate on average fitness and variability.