Viruses and their hosts can undergo coevolutionary arms races where hosts evolve increased resistance and viruses evolve counter-resistance. Given these arms race dynamics (ARD), each species is predicted to evolve along a single trajectory as more recently evolved genotypes replace their predecessors. Here, by coupling phenotypic and genomic analyses of coevolving populations of bacteriophage λ and Escherichia coli, we find conflicting evidence for ARD. Virus-host infection phenotypes fit the ARD model, yet whole genome analyses did not. Rather than coevolution unfolding along a single trajectory, cryptic genetic variation emerges during initial virus-host coevolution. This variation is maintained across generations and eventually supplants dominant lineages. Our observations constitute a new type of 'leapfrog' coevolutionary dynamics (LFD), revealing weaknesses in the predictive power of standard coevolutionary models. The findings shed light on the mechanisms that structure coevolving ecological networks and reveal the limits of using phenotypic assays alone in characterizing coevolutionary dynamics.

Phage therapy has been viewed as a potential treatment for bacterial infections for over a century. Yet, the year 2016 marks the first phase I/II human trial of a phage therapeutic -to treat burn wound patients in Europe. The slow progress in realizing clinical therapeutics is matched by a similar dearth in principled understanding of phage therapy. Theoretical models and in vitro experiments find that combining phage and bacteria often leads to coexistence of both phage and bacteria or phage elimination altogether. Both outcomes stand in contrast to the stated goals of phage therapy. A potential resolution to the gap between models, experiments, and therapeutic use of phage is the hypothesis that the combined effect of phage and host immune system can synergistically eliminate bacterial pathogens. Here, we propose a phage therapy model that considers the nonlinear dynamics arising from interactions between bacteria, phage and the host innate immune system. The model builds upon earlier efforts by incorporating a maximum capacity of the immune response and density-dependent immune evasion by bacteria. We analytically identify a synergistic regime in this model in which phage and the innate immune response jointly contribute to the elimination of the target bacteria. Crucially, we find that in this synergistic regime, neither phage alone nor the innate immune system alone can eliminate the bacteria. We confirm these findings using numerical simulations in biologically plausible scenarios. We utilize our numerical simulations to explore the synergistic effect and its significance for guiding the use of phage therapy in clinically relevant applications.