Integrating whole-genome sequencing into antimicrobial resistance surveillance: methodologies, challenges, and perspectives

Antimicrobial resistance (AMR) poses a significant threat to global public health. Surveillance is a fundamental method for controlling AMR and guiding clinical decisions, public health interventions, and policymaking. Whole-genome sequencing (WGS) provides a comprehensive and accurate understanding of AMR mechanisms, gene profiling, and transmission dynamics. Public health authorities, academic scholars, hospitals, and laboratories have increasingly employed WGS-based surveillance for retrospective, real-time, and prospective monitoring of AMR and investigations of outbreaks. WGS-based surveillance has improved the accuracy and effectiveness of disease and AMR surveillance by identifying hidden transmissions and sources missed by conventional methods and by rapidly investigating and deploying infection control interventions. However, WGS analysis involves a complex combination of workflows of next-generation sequencing and bioinformatics data analysis, making it difficult to effectively compare surveillance results. It is crucial to understand the limitations of our existing WGS analyses by implementing rigorous validation practices across different WGS analyses, developing practice guidelines, and establishing appropriate quality assurance measures. These efforts will aid in the development of reliable and robust WGS systems, the harmonization and standardization of surveillance programs, and the development of public data sharing and governance frameworks. Despite these challenges, the expansion of WGS-based AMR surveillance is expected to be driven by technological advances, standardization efforts, and the recognition of its advantages among stakeholders. The integration of genomic data with nongenomic information, as well as interdisciplinary collaborations will further enhance knowledge regarding AMR and promote the development of countermeasures.