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

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 st...

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Autores principales: Sowah, Robert A., Molina, Marirosa, Georgacopoulos, Ourania, Snyder, Blake, Cyterski, Mike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503305/
https://www.ncbi.nlm.nih.gov/pubmed/36144405
http://dx.doi.org/10.3390/microorganisms10091804
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author Sowah, Robert A.
Molina, Marirosa
Georgacopoulos, Ourania
Snyder, Blake
Cyterski, Mike
author_facet Sowah, Robert A.
Molina, Marirosa
Georgacopoulos, Ourania
Snyder, Blake
Cyterski, Mike
author_sort Sowah, Robert A.
collection PubMed
description 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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spelling pubmed-95033052022-09-24 Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA Sowah, Robert A. Molina, Marirosa Georgacopoulos, Ourania Snyder, Blake Cyterski, Mike Microorganisms Article 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. MDPI 2022-09-08 /pmc/articles/PMC9503305/ /pubmed/36144405 http://dx.doi.org/10.3390/microorganisms10091804 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sowah, Robert A.
Molina, Marirosa
Georgacopoulos, Ourania
Snyder, Blake
Cyterski, Mike
Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA
title Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA
title_full Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA
title_fullStr Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA
title_full_unstemmed Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA
title_short Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA
title_sort sources and drivers of args in urban streams in atlanta, georgia, usa
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503305/
https://www.ncbi.nlm.nih.gov/pubmed/36144405
http://dx.doi.org/10.3390/microorganisms10091804
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