A comprehensive analysis of pneumococcal two-component system regulatory networks.

Two-component systems are key signal-transduction systems that enable bacteria to respond to a wide variety of environmental stimuli. The human pathogen, (pneumococcus) encodes 13 two-component systems and a single orphan response regulator, most of which are significant for pneumococcal pathogenicity. Mapping the regulatory networks governed by these systems is key to understand pneumococcal host adaptation. Here we employ a novel bioinformatic approach to predict the regulons of each two-component system based on publicly available whole-genome sequencing data. By employing pangenome-wide association studies (panGWAS) to predict genotype-genotype associations for each two-component system, we predicted regulon genes of 11 of the pneumococcal two-component systems. Through validation via next-generation RNA-sequencing on response regulator overexpression mutants, several top candidate genes predicted by the panGWAS analysis were confirmed as regulon genes. The present study presents novel details on multiple pneumococcal two-component systems, including an expansion of regulons, identification of candidate response regulator binding motifs, and identification of candidate response regulator-regulated small non-coding RNAs. We also demonstrate a use for panGWAS as a complementary tool in target gene identification via identification of genotype-to-genotype links. Expanding our knowledge on two-component systems in pathogens is crucial to understanding how these bacteria sense and respond to their host environment, which could prove useful in future drug development.