A proposed framework for the identification of indicator genes for monitoring antibiotic resistance in wastewater: Insights from metagenomic sequencing

Abstract

Antibiotic resistance is one of the greatest threats to global human and animal health of our time. Municipal wastewater has been identified as a hotspot of antibiotic resistance contamination to water bodies. However, there are numerous potential antibiotic resistant pathogens and their associated antibiotic resistance genes (ARGs), making it difficult to implement routine monitoring that addresses the breadth of the problem. The objective of this study was to identify candidate indicator ARGs for monitoring antibiotic resistance in wastewater and receiving water bodies. We developed a framework to identify indicator ARGs that incorporated clinical relevance, abundance in wastewater, geographic ubiquity, environmental relevance, ARG mobility, associations with mobile genetic elements, and the availability of quantitative analytical methods. To identify indicator ARGs, published metagenomic sequencing data from 191 wastewater samples originating from 64 countries across the world were obtained from online public repositories. Through ARG annotation and network analysis, this framework revealed 56 candidate indicator ARGs distributed across four modules of strongly correlated ARGs, with one ARG from each module (oqxA, ermB, sul1, and mexE) proposed as a minimally redundant monitoring target. The results of this study provide the basis for antibiotic resistance surveillance and monitoring framework in wastewater and contaminated waterways.