Abstract
Extensive use of antibiotics in human healthcare as well as in agricultural and environmental settings has led to the emergence and spread of antibiotic-resistant bacteria, rendering many infections increasingly difficult to treat. Coupled with the limited development of new antibiotics, the rise of antimicrobial resistance (AMR) has caused a major health crisis worldwide, which calls for immediate action. Strengthening AMR surveillance systems is, therefore, crucial to global and national efforts in combating this escalating threat. This review explores the potential of metagenomics, a sequenced-based approach to analyze entire microbial communities without the need for cultivation, as a transformative and rapid tool for improving AMR surveillance strategies as compared to traditional cultivation-based methods. We emphasize the importance of monitoring mobile genetic elements (MGEs), such as integrons, transposons, plasmids, and bacteriophages (phages), in relation to their critical role in facilitating the dissemination of genetic resistance determinants via horizontal gene transfer (HGT) across diverse environments and clinical settings. In this context, the strengths and limitations of current bioinformatic tools designed to detect AMR-associated MGEs in metagenomic datasets, including the emerging potential of predictive machine learning models, are evaluated. Moreover, the controversial role of phages in AMR transmission is discussed alongside the potential of phage therapy as a promising alternative to conventional antibiotic treatment.