Using Genomic Tools to Predict Antimicrobial Resistance and Markers in Clinical Bacterial Samples

The study uses genomic tools to predict antimicrobial resistance (AMR) and identify resistance markers in hospital-acquired infections (HAIs). It evaluates the genetic profiles of Pseudomonas aeruginosa and Staphylococcus aureus. Results show that genomic tools like CARD-RGI and Solu can accurately identify resistance genes and predict AMR phenotypes. This suggests the potential of genomic approaches in managing resistant infections and developing new antimicrobial strategies.