Trace levels of sewage effluent are sufficient to increase class 1 integron prevalence in freshwater biofilms without changing the core community.
IWA Publishing & Elsevier
© 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Most river systems are impacted by sewage effluent. It remains unclear if there is a lower threshold to the concentration of sewage effluent that can significantly change the structure of the microbial community and its mobile genetic elements in a natural river biofilm. We used novel in situ mesocosms to conduct replicated experiments to study how the addition of low-level concentrations of sewage effluent (nominally 2.5 ppm) affects river biofilms in two contrasting Chalk river systems, the Rivers Kennet and Lambourn (high/low sewage impact, respectively). 16S sequencing and qPCR showed that community composition was not significantly changed by the sewage effluent addition, but class 1 integron prevalence (Lambourn control 0.07% (SE ± 0.01), Lambourn sewage effluent 0.11% (SE ± 0.006), Kennet control 0.56% (SE ± 0.01), Kennet sewage effluent 1.28% (SE ± 0.16)) was significantly greater in the communities exposed to sewage effluent than in the control flumes (ANOVA, F = 5.11, p = 0.045) in both rivers. Furthermore, the difference in integron prevalence between the Kennet control (no sewage effluent addition) and Kennet sewage-treated samples was proportionally greater than the difference in prevalence between the Lambourn control and sewage-treated samples (ANOVA (interaction between treatment and river), F = 6.42, p = 0.028). Mechanisms that lead to such differences could include macronutrient/biofilm or phage/bacteria interactions. Our findings highlight the role that low-level exposure to complex polluting mixtures such as sewage effluent can play in the spread of antibiotic resistance genes. The results also highlight that certain conditions, such as macronutrient load, might accelerate spread of antibiotic resistance genes.
This work was funded by the NERC Centre for Ecology & Hydrology National Capability funding through the CEH Thames Initiative (NEC04877) and the NERCeKnowledge Transfer (PREPARE) Initiative contract NE/F009216/1. Thanks to Heather Wickham, Linda Armstrong and Sarah Harman for providing nutrient levels, Gareth Old and Colin Roberts for providing the Boxford data as part of the NERC funded CEH Lambourn Observatory, to John Hounslow (Action for the River Kennet) for access to his land and to Alan Grafen for advice on statistical methods.
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.
Vol. 106, pp. 163 - 170
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