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Alternate Title

Antibiotic Resistance in a Coastal River in Mississippi, USA – Potential Drivers

Document Type

Article

Abstract

Wastewater treatment plants (WWTPs) are major sources of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in water bodies. Most studies on the impact of WWTPs on antibiotic resistance have focused on freshwater systems, with little information on coastal and estuarine waters with variable salinity. This study monitored seasonal levels of ARGs at the effluent and downstream of the Pascagoula— Moss Point WWTP in the lower Pascagoula River, a coastal river in southeastern Mississippi, USA. Surface water samples were collected seasonally at upstream, outflow, and 3 downstream sites from February to November 2016. Bacterial resistance to sulfamethazine, tetracycline, and ciprofloxacin was quantified using selective culture and qPCR. Mixed—effects models were developed to identify potential driving factors of ARG concentrations related to the WWTP and local environmental conditions (salinity, water temperature, and pH). The best model was selected based on the lowest Akaike Information Criterion (AIC) corrected for small sample size. The results show that the genes sul1, sul2, and intI1 were detected, with intI1 having the highest relative concentration. The qPCR analysis suggests a negative relation between ARG levels and temperature and salinity. ARG concentrations peaked immediately downstream of the WWTP and decreased gradually further downstream in some months, but the spatial pattern varied widely between sampling months. The study highlights the complex patterns of environmental ARGs and the importance of accounting for the impact of WWTPs, local environmental factors, and other anthropogenic influences to understand their potential drivers.

First Page

23

Last Page

34

Shen et al. Supplemental Table S1.pdf (179 kB)
Supplemental Table S1

Supplemental Tables S2-S6 for Shen et al final.docx (42 kB)
Supplemental Tables S2-S6

Artificial Intelligence (AI) Use Statement

No artificial intelligence (AI) was used in the preparation of this manuscript

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