Abstract

Viral infections are social processes. Viral replication requires shared gene products that can be used by multiple viral genomes within the same cell, and hence act as public goods. This gives rise to viral cheats, a type of molecular parasite formed by large deletions, that spread by exploiting public goods encoded by full-length viruses. Cheats exist across the viral universe, arise frequently in laboratory infections, and reflect the emergence of evolutionary conflict at the molecular level. In this talk, I will explore two evolutionary consequences of viral cheating that play out at different timescales. Firstly, we will consider the evolution of multipartite viruses, in which the genome is fragmented, and each fragment must separately infect a host. This genome structure comes with clear costs, but has nevertheless evolved multiple times, and today accounts for nearly 40% of known plant viral species. Previous explanations for the evolution of multipartitism have focused on group benefits, but typically require unrealistic rates of coinfection, especially for multipartite viruses with more than two segments. We will argue that cheating provides a contrasting explanation. By combining evolutionary game theory models with agent-based simulations, we will show that the invasion of mutually complementing viral cheats can drive the evolution of multipartitism under far more permissive conditions, including transitions to highly multipartite viruses. This framework shows that multipartitism need not be a group-level adaptation, but can instead emerge as the evolutionary endpoint of the tragedy of the commons. Secondly, we will consider the evolution of cheat-driven extinction in viruses. Cheats emerge spontaneously in laboratory infections of almost all known viruses, driving drastic reductions in viral population sizes. As a result, virologists have long argued that viral infections may be ‘self-limiting’, a claim supported by recent discoveries of cheats in natural viral infections. However, it is unclear whether viral infections provide enough time for viral cheats to emerge, spread, and drive cooperator extinction. Here, we present a birth-death model that incorporates mutation, demographic noise, and a frequency-dependent selective advantage to cheating. We identify qualitatively different dynamical regimes and the timescales under which they lead to viral extinction. We further show that our model can produce characteristic signatures of selection, opening the door to evolutionary biomarkers for predicting the outcome of viral infections from sequencing data. This approach argues that cheating may not only be relevant over long evolutionary timescales, but may also shape viral dynamics in clinically relevant ways, with a close analogy to the emergence of cancer in multicellular organisms.