Abstract
Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.
Highlights
Understanding the drivers of antibiotic resistance is essential if we are to combat the problem of rapidly emerging multi-resistant pathogens
A series of integrating gene cassettes into a variable region; to simulations based on these models were used to date they are over 130 gene cassettes conferring a evaluate the impact of wastewater-treatment plant (WWTP) type, size and distance range of antibiotic-resistant phenotypes, the from sample site combined with the surrounding land presence of a class 1 integron gives the bacteria the cover, weather, temporal changes and river water ability to become resistant to a range of antibiotics chemistry on the environmental resistome
Class 1 integron prevalence in River Thames basin There was a significant difference in class 1 integron prevalence between different sites in the River Thames basin (Figure 3; analysis of variance, F 1⁄4 6.845; Po0.001), these could be grouped into five homogenous subsets following a post hoc Tukey’s honest significant difference test (Table 1)
Summary
Understanding the drivers of antibiotic resistance is essential if we are to combat the problem of rapidly emerging multi-resistant pathogens. It has been well established in the clinic that increasing antibiotic usage escalates resistance levels (McGowan, 1983), yet it is less clear how current usage both in veterinary and human medicine has had an impact (Stalder et al, 2014). A series of integrating gene cassettes into a variable region; to simulations based on these models were used to date they are over 130 gene cassettes conferring a evaluate the impact of WWTP type, size and distance range of antibiotic-resistant phenotypes, the from sample site combined with the surrounding land presence of a class 1 integron gives the bacteria the cover, weather, temporal changes and river water ability to become resistant to a range of antibiotics chemistry on the environmental resistome. We hypothesise that class 1 integron prevalence can be used as a proxy for antibiotic resistance
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