Mutation-Driven Parallel Evolution during Viral Adaptation.

Convergent evolution has been demonstrated across all levels of biological organization, from parallel nucleotide substitutions to convergent evolution of complex phenotypes, but whether instances of convergence are the result of selection repeatedly finding the same optimal solution to a recurring problem or are the product of mutational biases remains unsettled. We generated 20 replicate lineages allowed to fix a single mutation from each of four bacteriophage genotypes under identical selective regimes to test for parallel changes within and across genotypes at the levels of mutational effect distributions and gene, protein, amino acid, and nucleotide changes. All four genotypes shared a distribution of beneficial mutational effects best approximated by a distribution with a finite upper bound. Parallel adaptation was high at the protein, gene, amino acid, and nucleotide levels, both within and among phage genotypes, with the most common first-step mutation in each background fixing on an average in 7 of 20 replicates and half of the substitutions in two of the four genotypes occurring at shared sites. Remarkably, the mutation of largest beneficial effect that fixed for each genotype was never the most common, as would be expected if parallelism were driven by selection. In fact, the mutation of smallest benefit for each genotype fixed in a total of 7 of 80 lineages, equally as often as the mutation of largest benefit, leading us to conclude that adaptation was largely mutation-driven, such that mutational biases led to frequent parallel fixation of mutations of suboptimal effect.

Phage cocktail strategies for the suppression of a pathogen in a cross-feeding coculture.

Cocktail combinations of bacteria-infecting viruses (bacteriophages) can suppress pathogenic bacterial growth. However, predicting how phage cocktails influence microbial communities with complex ecological interactions, specifically cross-feeding interactions in which bacteria exchange nutrients, remains challenging. Here, we used experiments and mathematical simulations to determine how to best suppress a model pathogen, E. coli, when obligately cross-feeding with S. enterica. We tested whether the duration of pathogen suppression caused by a two-lytic phage cocktail was maximized when both phages targeted E. coli, or when one phage targeted E. coli and the other its cross-feeding partner, S. enterica. Experimentally, we observed that cocktails targeting both cross-feeders suppressed E. coli growth longer than cocktails targeting only E. coli. Two non-mutually exclusive mechanisms could explain these results: (i) we found that treatment with two E. coli phage led to the evolution of a mucoid phenotype that provided cross-resistance against both phages, and (ii) S. enterica set the growth rate of the coculture, and therefore, targeting S. enterica had a stronger effect on pathogen suppression. Simulations suggested that cross-resistance and the relative growth rates of cross-feeders modulated the duration of E. coli suppression. More broadly, we describe a novel bacteriophage cocktail strategy for pathogens that cross-feed.

Lytic bacteriophage have diverse indirect effects in a synthetic cross-feeding community.

Bacteriophage shape the composition and function of microbial communities. Yet it remains difficult to predict the effect of phage on microbial interactions. Specifically, little is known about how phage influence mutualisms in networks of cross-feeding bacteria. We mathematically modeled the impacts of phage in a synthetic microbial community in which Escherichia coli and Salmonella enterica exchange essential metabolites. In this model, independent phage attack of either species was sufficient to temporarily inhibit both members of the mutualism; however, the evolution of phage resistance facilitated yields similar to those observed in the absence of phage. In laboratory experiments, attack of S. enterica with P22vir phage followed these modeling expectations of delayed community growth with little change in the final yield of bacteria. In contrast, when E. coli was attacked with T7 phage, S. enterica, the nonhost species, reached higher yields compared with no-phage controls. T7 infection increased nonhost yield by releasing consumable cell debris, and by driving evolution of partially resistant E. coli that secreted more carbon. Our results demonstrate that phage can have extensive indirect effects in microbial communities, that the nature of these indirect effects depends on metabolic and evolutionary mechanisms, and that knowing the degree of evolved resistance leads to qualitatively different predictions of bacterial community dynamics in response to phage attack.

Synergistic Pleiotropy Overrides the Costs of Complexity in Viral Adaptation.

Adaptive evolution progresses as a series of steps toward a multidimensional phenotypic optimum, and organismal or environmental complexity determines the number of phenotypic dimensions, or traits, under selection. Populations evolving in complex environments may experience costs of complexity such that improvement in one or more traits is impeded by selection on others. We compared the fitness effects of the first fixed mutations for populations of single-stranded DNA bacteriophage evolving under simple selection for growth rate to those of populations evolving under more complex selection for growth rate as well as capsid stability. We detected a cost of complexity manifested as a smaller growth rate improvement for mutations fixed under complex conditions. We found that, despite imposing a cost for growth rate improvement, strong complex selection resulted in the greatest overall fitness improvement, even for single mutations. Under weaker secondary selective pressures, tradeoffs between growth rate and stability were pervasive, but strong selection on the secondary trait resulted largely in mutations beneficial to both traits. Strength of selection therefore determined the nature of pleiotropy governing observed trait evolution, and strong positive selection forced populations to find mutations that improved multiple traits, thereby overriding costs incurred as a result of a more complex selective environment. The costs of complexity, however, remained substantial when considering the effects on a single trait in the context of selection on multiple traits.