An Agent Based Model Shows How Mixed Infections Drive Multi-Year 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. We use here 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 to integrate long and short scale transmission, primary and secondary infections, and within-host pathogen competition in mixed infections. The study focusses on the tobamovirus-pepper pathosystem. Model simulations allowed to integrate pleiotropic effects of resistance-breaking mutations on different virus life-history traits into net costs of resistance-breaking, allowing predictions on multi-year pathotype dynamics. We also explored the effects of two control measures, the use of host resistance and roguin 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.