Artificial Selection for Pathogenicity Mutations in Identifies Novel Factors Relevant to Chronic Infection.

Adaptation of to host microenvironments during chronic infection involves spontaneous mutations, yet changes underlying adaptive phenotypes remain incompletely explored. Here, we employed artificial selection and whole-genome sequencing to better characterize spontaneous chromosomal mutations that alter two pathogenicity phenotypes relevant to chronic infection in : intracellular invasiveness and intracellular cytotoxicity. We identified 23 genes whose alteration coincided with enhanced virulence, 11 that were previously known and 12 (52%) that had no previously described role in pathogenicity. Using precision genome editing, transposon mutants, and gene complementation, we empirically assessed the contributions of individual genes to the two virulence phenotypes. We functionally validated 14 of 21 genes tested as measurably influencing invasion and/or cytotoxicity, including 8 newly implicated by this study. We identified inactivating mutations (, , and a hypothetical membrane protein) and gain-of-function mutations ( Thr182Ile, Thr74Ile, and Asp486Glu in a hypothetical peptidase) in previously unrecognized virulence genes that enhance pathogenesis when introduced into a clean genetic background, as well as a novel activating mutation in the known virulence regulator gene (Ala106Thr). Investigation of potentially epistatic interactions identified a mutation (Ala271Val) that enhances virulence only in the context of purine operon repressor gene () inactivation. This project reveals a functionally diverse range of genes affected by gain- or loss-of-function mutations that contribute to adaptive virulence phenotypes. More generally, the work establishes artificial selection as a means to determine the genetic mechanisms underlying complex bacterial phenotypes relevant to adaptation during infection.