A multi-dimensional framework for selecting antibiotic resistance gene indicators in wastewater surveillance of antimicrobial resistance

Wastewater surveillance is increasingly conducted to monitor antimicrobial resistance (AMR) in human populations, with antibiotic resistance genes (ARGs) serving as key molecular markers. Quantification of select ARGs provides a practical and scalable approach but is limited by inconsistent and context-specific target selection that relies on regional relevance or regulatory guidance rather than systematic selection strategies. Based on a global ARG dataset of 757 wastewater samples from 101 countries, this study establishes a systematic, multi-dimensional framework for indicator ARG selection that integrates global prevalence, regional differentiation, and clinical relevance. The framework establishes tiered indicator panels, that is, minimum, standard, and comprehensive, linking target selection to appropriate analytical platforms and resource capacities, thereby providing practical guidance for AMR wastewater surveillance. Global prevalence was assessed through the identification of core ARGs, which were consistently detected at high abundance and frequency across different regions worldwide. Regional differentiation was examined using multiple algorithms to identify consensus ARGs that drive interregional variation. Clinically relevant ARGs were selected based on their coverage of major drug classes and association with mobile genetic elements. This systematic yet flexible framework supports indicator ARG selection can be tailored to wastewater surveillance objectives by balancing analytical feasibility with epidemiological value.