Characterising and modelling the sources and drivers of antimicrobial resistance in rural river catchments in Northern England

Abstract

Reducing Antimicrobial Resistance (AMR) in the environment requires adopting a One Health approach. However, most current river catchment monitoring is limited to focused rather than holistic research work, often in more contaminated river catchments. The sources and drivers of AMR in less-impacted rural catchments are not as well defined. Further, studying such catchments can be problematic because wide scale environmental monitoring is expensive, time consuming and currently not standardised. To address such problems, a comprehensive spatial assessment was conducted on AMR in two rural river catchments in the North of England. The work included the Coquet River in Northumberland and the Eden in Cumbria, which both have rural land-use, but different hydrometeorological characteristics. A subsequent focused study was performed on the Coquet catchment that used Fast-Expectation Maximization for Microbial Source Tracking (FEAST), a relatively new approach, for whole community microbial source tracking. The catchment comparison revealed that elevated river flows, rainfall and runoff in the Eden catchment led to a higher abundance and higher diversity of resistance genes (Kruskal Wallis, p<0.05) and clinically relevant ARGs such as blaKPC. The FEAST analysis also revealed the influx of ARGs from wastewater effluent were not sustained down the course of the Coquet river. Microbial communities and resistance genes in these catchments were driven primarily by environmental factors, such as catchment hydrology and nutrient limitation (described through N:P ratios), rather than point sources. These studies highlighted the need for increased monitoring to support these findings, and to inform routine monitoring. Models can be important public health decision tools to support such surveillance. The Soil and Water Assessment Tool (SWAT) was used to simulate E. coli and ESBL E. coli for the Coquet catchment, demonstrating the potential of SWAT to predict E. coli and ESBL E. coli to support on-site monitoring of AMR.