An Agent-Based Model Shows How Mixed Infections Drive Multiyear Pathotype Dynamics in a Plant-Virus System.

Abstract

Mathematical models are widely used to understand the evolution and epidemiology of plant pathogens under a variety of scenarios. Here, we used this approach to analyze the effects of different traits intrinsic and extrinsic to plant-virus interactions on the dynamics of virus pathotypes in genetically heterogeneous plant-virus systems. For this, we propose an agent-based epidemiological model that includes epidemiologically significant pathogen life-history traits related to virulence, transmission, and survival in the environment and allows for integrating long- and short-distance transmission, primary and secondary infections, and within-host pathogen competition in mixed infections. The study focuses on the tobamovirus-pepper pathosystem. Model simulations allowed us to integrate pleiotropic effects of resistance-breaking mutations on different virus life-history traits into the net costs of resistance breaking, allowing for predictions on multiyear pathotype dynamics. We also explored the effects of two control measures, the use of host resistance and roguing of symptomatic plants, that modify epidemiological attributes of the pathogens to understand how their populations will respond to evolutionary pressures. One major conclusion points to the importance of pathogen competition within mixed-infected hosts as a component of the overall fitness of each pathogen that, thus, drives their multiyear dynamics.