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 antibiotics and other 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 it was the epistatic interactions that conferred the observed strong streptomycin resistance in native E. coli isolates. Three ribosomal mutations (rpsED142N, rpsLR86S and rsmGW150fs), 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. The 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. The findings 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 with the resistome profiling and enable more accurate antibiotic resistance monitoring and environmental risk assessment.
Surrogate Neural Architecture Codesign Package (SNAC-Pack)
arXiv:2512.15998v1 Announce Type: cross Abstract: Neural Architecture Search is a powerful approach for automating model design, but existing methods struggle to accurately optimize for real