Resistance indicators in sewage microbiota mirror clinical antibiotic use with temporal lag linked to host

Abstract

Wastewater-based surveillance (WBS) offers a promising window into community pathogens but extending it to antibiotic resistance (AR) is complicated by ecological and physical processes within sewer systems. The epidemiological meaning of antibiotic resistance gene (ARG) abundances in sewage remains unclear because signals reflect both human-derived inputs and in-sewer microbial dynamics. Using a unique 5-year dataset of outpatient antibiotic prescriptions and a yearlong, twice-weekly metagenomic survey of a single wastewater treatment plant, we differentiate associations between sewage-borne antibiotic-resistant bacteria and community antibiotic use. We find that ARGs linked to Enterobacteriaceae track closely with antibiotic usage, while those associated with ecologically-distinct Pseudomonadaceae show lagged correlations of 1–3 months. Nested statistical modeling further links Pseudomonas MAG dynamics with lagged sulfamethoxazole/trimethoprim use after accounting for sewage characteristics and seasonality. Our results demonstrate that WBS can capture local patterns of epidemiologically relevant AR when microbial ecological factors shaping sewage signals are considered. Profiles of antibiotic resistance genes in wastewater still often lack epidemiological context. In this study, the authors use wastewater metagenomics and antibiotic use data to reveal a variable lagging association between human antibiotic consumption and antibiotic resistance genes in sewage-derived bacterial hosts.