Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA.

Microorganisms

U.S. EPA, Office of Research and Development, Center for Environmental Measurement and Modeling, 960 College Station Rd., Athens, GA 30605, USA.

Published: September 2022

AI Article Synopsis

  • The study investigates the spread of antibiotic resistance genes (ARGs) in an urban watershed, highlighting the importance of understanding their sources, particularly in relation to human activities and sewage-related molecular markers.
  • Researchers used quantitative polymerase chain reaction (qPCR) to measure the presence of specific ARGs and found that they were prevalent in water samples, with a strong correlation to sewage indicators like HF183 and E. coli.
  • The findings indicate that fecal source loading is the main driver for the presence of ARGs in this urban environment, suggesting that managing fecal contamination is crucial for reducing ARG levels and improving public health.

Article Abstract

The spread of antibiotic resistance genes (ARGs) in the aquatic environment is an emerging concern in the interest of protecting public health. Stemming the environmental dissemination of ARGs will require a better understanding of the sources and drivers of ARGs in the water environment. In this study, we used direct measurement of sewage-associated molecular markers, the class 1 integron gene, standard water quality parameters, and watershed characteristics to evaluate the sources and drivers of ARGs in an urban watershed impacted by a gradient of human activities. Quantitative polymerase chain reaction (qPCR) was used to quantify the abundance of the sewage-associated HF183, the E. coli fecal indicator, class 1 integron gene (int1), and the ARGs sulI, sulII, tetW, tetM, ampC, and blaSHV in stream water samples collected from the Proctor Creek watershed in Atlanta, Georgia. Our findings show that ARGs were widely distributed, with detection frequencies of 96% (sulI and sulII), 82% (tetW and tetM), and 49% (ampC and blaSHV). All the ARGs were positively and significantly correlated (r > 0.5) with the HF183 and E. coli markers. Non-linear machine learning models developed using generalized boosting show that more than 70% of the variation in ARG loads in the watershed could be explained by fecal source loading, with other factors such as class 1 integron, which is associated with acquired antibiotic resistance, and environmental factors contributing < 30% to ARG variation. These results suggest that input from fecal sources is a more critical driver of ARG dissemination than environmental stressors or horizontal gene transfer in aquatic environments highly impacted by anthropogenic pollution. Finally, our results provide local watershed managers and stakeholders with information to mitigate the burden of ARGs and fecal bacteria in urban streams.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503305PMC
http://dx.doi.org/10.3390/microorganisms10091804DOI Listing

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