Abstract
Bacterial chromosomal type I toxin-antitoxin systems consist of a small protein, typically under 60 amino acids, and a small RNA (sRNA) that represses toxin translation. These gene pairs have gained attention over the last decade for their contribution to antibiotic persistence and phage tolerance in bacteria. However, biological functions for many remain elusive as gene deletions often fail to produce an observable phenotype. For many pairs, it is still unknown when the toxin and/or antitoxin gene are natively expressed within the bacterium. We examined sequence conservation of three type I toxin-antitoxin systems, tisB/istR-1, shoB/ohsC, and zor/orz, in over 2,000 Escherichia coli strains, including pathogenic and commensal isolates. Using our custom database, we found that these gene pairs are widespread across E. coli and have expression potential via BLASTn. We identified an alternative, dominant sequence variant of TisB and confirmed that it is toxic upon overproduction. Additionally, analyses revealed a highly conserved sequence in the zorO mRNA untranslated region that is required for full toxicity. We further noted that over 30% of E. coli genomes contain an orz antitoxin gene only and confirmed its expression in a representative strain: the first confirmed report of a type I antitoxin without its cognate toxin. Our results add to our understanding of these systems, and our methodology is applicable for other type I loci to identify critical regulatory and functional features.IMPORTANCEChromosomal type I toxin-antitoxins are a class of genes that have gained increasing attention over the last decade for their roles in antibiotic persistence which may contribute to therapeutic failures. However, the control of many of these genes and when they function have remained elusive. We demonstrate that a simple genetic conservation-based approach utilizing free, publicly available data yields known and novel insights into the regulation and function of three chromosomal type I toxin-antitoxins in Escherichia coli. This study also provides a framework for how this approach could be applied to other genes of interest.