Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA.
Robert A SowahMarirosa MolinaOurania GeorgacopoulosBlake SnyderMike CyterskiPublished in: Microorganisms (2022)
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 ( int 1), and the ARGs sulI , sulII , tet W, tet M, ampC, and bla SHV 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% ( tet W and tet M), and 49% ( ampC and bla SHV). 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.
Keyphrases
- antibiotic resistance genes
- water quality
- wastewater treatment
- microbial community
- anaerobic digestion
- public health
- machine learning
- drinking water
- risk assessment
- escherichia coli
- endothelial cells
- genome wide
- copy number
- heart failure
- genome wide identification
- mass spectrometry
- heavy metals
- artificial intelligence
- air pollution
- transcription factor
- big data
- acute heart failure
- multidrug resistant
- particulate matter
- neural network
- loop mediated isothermal amplification
- atrial fibrillation
- genome wide analysis