Multi-layered genome defences in bacteria.

Bacteria have evolved a variety of defence mechanisms to protect against mobile genetic elements, including restriction-modification systems and CRISPR-Cas. In recent years, dozens of previously unknown defence systems (DSs) have been discovered. Notably, diverse DSs often coexist within the same genome, and some co-occur at frequencies significantly higher than would be expected by chance, implying potential synergistic interactions. Recent studies have provided evidence of defence mechanisms that enhance or complement one another. Here, we review the interactions between DSs at the mechanistic, regulatory, ecological and evolutionary levels.

Evolutionary barriers to horizontal gene transfer in macrophage-associated Salmonella.

Horizontal gene transfer (HGT) is a powerful evolutionary force facilitating bacterial adaptation and emergence of novel phenotypes. Several factors, including environmental ones, are predicted to restrict HGT, but we lack systematic and experimental data supporting these predictions. Here, we address this gap by measuring the relative fitness of 44 genes horizontally transferred from Escherichia coli to Salmonella enterica in infection-relevant environments. We estimated the distribution of fitness effects in each environment and identified that dosage-dependent effects across different environments are a significant barrier to HGT. The majority of genes were found to be deleterious. We also found longer genes had stronger negative fitness consequences than shorter ones, showing that gene length was negatively associated with HGT. Furthermore, fitness effects of transferred genes were found to be environmentally dependent. In summary, a substantial fraction of transferred genes had a significant fitness cost on the recipient, with both gene characteristics and the environment acting as evolutionary barriers to HGT.

Transcriptomic profiling of Escherichia coli K-12 in response to a compendium of stressors.

Environmental perturbations impact multiple cellular traits, including gene expression. Bacteria respond to these stressful situations through complex gene interaction networks, thereby inducing stress tolerance and survival of cells. In this paper, we study the response mechanisms of E. coli when exposed to different environmental stressors via differential expression and co-expression analysis. Gene co-expression networks were generated and analyzed via Weighted Gene Co-expression Network Analysis (WGCNA). Based on the gene co-expression networks, genes with similar expression profiles were clustered into modules. The modules were analysed for identification of hub genes, enrichment of biological processes and transcription factors. In addition, we also studied the link between transcription factors and their differentially regulated targets to understand the regulatory mechanisms involved. These networks validate known gene interactions and provide new insights into genes mediating transcriptional regulation in specific stress environments, thus allowing for in silico hypothesis generation.