Selecting for infectivity across metapopulations can increase virulence in the social microbe Bacillus thuringiensis:data set.

Passage experiments that sequentially infect hosts with parasites have long been used to manipulate virulence. However, for many invertebrate pathogens passage has been applied naively without a full theoretical understanding of how best to select for increased virulence and this has led to very mixed results. Understanding the evolution of virulence is complex because selection on parasites occurs across multiple spatial scales with potentially different conflicts operating on parasites with different life-histories. For example, in social microbes, strong selection on replication rate within hosts can lead to cheating and loss of virulence, because investment in public goods virulence reduces replication rate. In this study we tested how varying mutation supply and selection for infectivity or pathogen yield (population size in hosts) affected evolution of virulence against resistant hosts in the specialist insect pathogen Bacillus thuringiensis, aiming to optimize methods for strain improvement against a difficult to kill insect target. We show that selection for infectivity using competition between sub-populations in a metapopulation prevents social cheating, acts to retain key virulence plasmids and facilitates increased virulence. Increased virulence was associated with reduced efficiency of sporulation, and possible loss of function in putative regulatory genes but not with altered expression of the primary virulence factors. Selection in a metapopulation provides a broadly applicable tool for improving the efficacy of biocontrol agents. Moreover, a structured host population can facilitate artificial selection on infectivity, while selection on life history traits such as faster replication or larger population sizes can reduce virulence in social microbes.This dataset consists of raw experimental data (bioassays, toxin profiles, spore producitivty, mutation analysis) pertaining to a paper accepted in Evolutionary Applications doi: 10.1111/eva.13529. This project also received funding from the Leverhulme Trust grant number RPG-2014-25