Influence of Seasonality and Pollution on the Presence of Antibiotic Resistance Genes and Potentially Pathogenic Bacteria in a Tropical Urban River

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Abstract

Background/Objectives: This study investigates how seasonality, pollution, and sample type (water and se diment) influence the presence and distribution of antibiotic resistance genes (ARGs), with a focus on plas mid-associated resistance in a tropical urban river, a topic still underexplored in these ecosystems. Methods: Samples were collected from three sites along a pollution gradient in the Virilla River, Costa Rica, during three seasonal campaigns (wet 2021, dry 2022, and wet 2022). ARGs in water and sediment samples were quantified using qPCR, and metagenomic sequencing was used to analyze chromosomal and plasmid- associated resistance profiles in sediments. Tobit and linear regression models, along with multivariate or dination, evaluated spatial and seasonal trends. Results: During the wet season 2021, the abundance of sul-1, intl-1, and tetA in water samples decreased sig nificantly, likely due to dilution, while intl-1 and tetQ increased in sediments, suggesting particle-bound accumulation. In the wet season 2022, intl-1 remained low in water, qnrS increased, and sediments showed significant increases in tetQ, tetA, and qnrS, along with decreases in sul-1 and sul-2. Metagenomic analysis revealed that chromosomal ARGs exhibited strong spatial variation, particularly elevated at the most pol luted site (Site 3). In contrast, plasmid-associated ARGs showed seasonal fluctuations, with increases during the wet seasons. Potential pathogenic taxa also varied spatially, with greater plasmid-associated diversity and potential pathogens found in the most contaminated sediments. Conclusions: Seasonality and pollution gradients jointly shape ARG dynamics in this tropical river. Plasmid- mediated resistance responds rapidly to environmental changes and is enriched at polluted sites, while sed iments act as long-term ARG reservoirs. These findings support plasmid-based monitoring as a sensitive tool for antimicrobial resistance surveillance in aquatic systems.

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