Abstract
Wastewater treatment plants (WWTPs) receive a confluence of sewage containing antimicrobials, antibiotic resistant bacteria, antibiotic resistance genes (ARGs), and pathogens and thus are a key point of interest for antibiotic resistance surveillance. WWTP monitoring has the potential to inform with respect to the antibiotic resistance status of the community served as well as the potential for ARGs to escape treatment. However, there is lack of agreement regarding suitable sampling frequencies and monitoring targets to facilitate comparison within and among individual WWTPs. The objective of this study was to comprehensively evaluate patterns in metagenomic-derived indicators of antibiotic resistance through various stages of treatment at a conventional WWTP for the purpose of informing local monitoring approaches that are also informative for global comparison. Relative abundance of total ARGs decreased by ∼50% from the influent to the effluent, with each sampling location defined by a unique resistome (i.e., total ARG) composition. However, 90% of the ARGs found in the effluent were also detected in the influent, while the effluent ARG-pathogen taxonomic linkage patterns identified in assembled metagenomes were more similar to patterns in regional clinical surveillance data than the patterns identified in the influent. Analysis of core and discriminatory resistomes and general ARG trends across the eight sampling events (i.e., tendency to be removed, increase, decrease, or be found in the effluent only), along with quantification of ARGs of clinical concern, aided in identifying candidate ARGs for surveillance. Relative resistome risk characterization further provided a comprehensive metric for predicting the relative mobility of ARGs and likelihood of being carried in pathogens and can help to prioritize where to focus future monitoring and mitigation. Most antibiotics that were subject to regional resistance testing were also found in the WWTP, with the total antibiotic load decreasing by ∼40–50%, but no strong correlations were found between antibiotics and corresponding ARGs. Overall, this study provides insight into how metagenomic data can be collected and analyzed for surveillance of antibiotic resistance at WWTPs, suggesting that effluent is a beneficial monitoring point with relevance both to the local clinical condition and for assessing efficacy of wastewater treatment in reducing risk of disseminating antibiotic resistance.
Highlights
Antibiotic resistance is a complex health threat that requires both global and local action
We examined the core resistome, discriminatory resistomes (i.e., antibiotic resistance genes (ARGs) that separate the influent from effluent), specific ARGs of clinical concern, and resistome risk scores and compared these to independent qPCR measurements of target ARGs, antibiotic measurements, and local clinical resistance data
Two industries contribute to the inflow at the WWTP: (1) a machine and fabrication plant discharging an average of 15,000 gallons per day (GPD) and (2) an environmental waste industry discharging an average of 1,600 GPD out of an allowed 14,000 GPD
Summary
Antibiotic resistance is a complex health threat that requires both global and local action. Recent research demonstrates that ARGs that enter a given WWTP are reflective of various attributes of the local population, including antibiotic use patterns and socioeconomic factors (Hendriksen et al, 2019). These ARGs may exist on mobile genetic elements (MGEs), such as plasmids and transposons (Kim et al, 2014), which can facilitate their spread between different bacteria, including human pathogens. An effective surveillance scheme will serve to capture the breadth and depth of the full ARG profile as it changes through each stage of treatment, while providing the ability to link the observed ARG patterns to clinical antibiotic resistance concerns, both on a local and global scale (Huijbers et al, 2019)
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