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Various spatiotemporal, hydraulic, and water quality parameters can affect the microbial community composition of water within drinking water distribution systems (DWDSs). Although some relationships between various paravmeters and microbial growth are known, the effects of spatial and temporal trends on particle-associated microbial communities in chlorinated DWDSs remain poorly understood. The objectives of this study were to characterize the microbial community composition of both particle-associated bacteria (PAB) and total bacteria (TB) within a full-scale chlorinated DWDS, and assess relationships between microbiavvl community and various spatiotemporal, hydraulic, and water quality parameters. Bulk water samples were collected from the treatment plant, a storage tank, and 12 other sites in a rural chlorinated DWDS at varying distances from the treatment plant on four sampling dates spanning six months. Amplicon sequencing targeting the 16S rRNA gene was performed to characterize the microbial community. Gammaproteobacteria dominated the DWDS, and hydraulic parameters were well-correlated with differences in microbial communities between sites. Results indicate that hydraulic changes may have led to the detachment of biofilms and loose deposits, subsequently affecting the microbial community composition at each site. Spatial variations in microbial community were stronger than temporal variations, differing from similar studies and indicating that the highly varied hydraulic conditions within this system may intensify spatial variations. Genera containing pathogenic species were detected, withLegionellaandPseudomonasdetected at every site at least once andMycobacteriumdetected at most sites. However, only one sample had quantifiablePseudomonas aeruginosathrough quantitative polymerase chain reaction (qPCR), and no samples had quantifiableLegionella pneumophilaorMycobacterium avium, indicating a low human health risk. This study establishes spatial variations in PAB associated with varied hydraulic conditions as an important factor driving microbial community within a chlorinated DWDS.

 

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.