Antimicrobial resistance (AMR) is a growing public health crisis, highlighting the urgent need for rapid and reliable diagnostic methods. Traditional microbiological assays for detecting drug-resistant bacteria are often time-consuming, while molecular approaches rely on prior knowledge of resistance genes. To address these limitations, we have developed a nanopore-based sequencing method that enables rapid assessment of cellular fitness and antimicrobial resistance. Our approach leverages RNA metabolism signatures to facilitate the early identification of AMR in clinical bacterial isolates, offering a promising alternative for faster and more comprehensive resistance detection.