Positive epistasis among ribosomal mutations drives high-level streptomycin resistance in <i>Escherichia coli</i>

ABSTRACT The widespread use of antibiotics has raised serious concerns about the emergence and dissemination of antibiotic resistance in the environment. Studies reveal that environmental exposures to sub-inhibitory level antibiotics and other low-level non-antibiotic pollutants can promote the development of high-level antibiotic resistance via de novo mutations. However, specific genotypes conferring strong resistance in resistant mutants, particularly the roles of co-occurring mutations, remained poorly understood. This study fills this knowledge gap by constructing site-specific Escherichia coli mutants and demonstrating that positive epistasis among ribosomal mutations conferred the observed strong streptomycin resistance in evolved resistant E. coli isolates. Three ribosomal mutations ( rpsE D142N , rpsL R86S , and rsmG W150fs ), which co-evolved under environmentally relevant selection pressures, acted synergistically to confer resistance far exceeding that of each individual mutation. The interactions between the rsmG frameshift mutation and other reported rpsL point mutations were also investigated. These findings unravel the essential but previously overlooked role played by specific co-evolving mutations in the acquisition of both high-level streptomycin resistance and fitness compensation. IMPORTANCE This study reports a strong positive epistatic interaction that evolves under the environmentally relevant conditions, where microbes are exposed to sub-inhibitory concentrations of antibiotics along with other low-level pesticides. It elucidates how such interaction confers high-level streptomycin resistance to bacteria. This phenomenon contributes to the fundamental understanding of antibiotic resistance mechanisms mediated by target-altering mutations in nature. Findings in this study also underscore a strong and increasing need to investigate whole genomes of antibiotic-resistant bacteria and identify potential epistatic mutations conferring resistance phenotypes. The integration of those genetic mutations as antibiotic resistance biomarkers will complement the resistome profiling and enable more accurate antibiotic resistance monitoring and environmental risk assessment.