Characterising the sources and drivers of environmental resistomes over UK landscapes and assessing mitigation under different hydrological regimes

Antimicrobial Resistance (AMR) refers to microbes that become resistant to antibiotics and is becoming a global problem. According to a recent review on AMR, infections that are resistant to treatment are projected to result in 10 million deaths, as well as a financial burden of ~US$100 trillion (O'Neill, 2014). This is related to the wide and rapid spread of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARG)s. For example, the New Delhi meta- -lactamase-1 protein (coded blaNDM-1) which makes bacteria resistant to a range of beta-lactam antibiotics such as penicillin, was first discovered in 2008 in India and has since been recovered from soils in the High Arctic (McCann et al., 2019). Despite there being some level of intrinsic resistance, high abundance of resistance are attributed to anthropogenic sources. Due to pollution in populated areas, the sources of AMR are often difficult to distinguish, but the main sources include wastewater treatment plants and agriculture, which both contribute to pollution in rivers and surrounding landscapes. High river flow rates from storm events have resulted in an increase in the abundance of resistance genes, potentially due to diffuse pollution (Garner et al., 2017). With climate change causing more heatwaves and rainfall events falling outside normal seasonal patterns in the UK, it is currently unclear how this will influence the dissemination of ARB and ARGs in a landscape. Therefore understanding the contribution of sources under different hydrological conditions is important.

This PhD project investigates the contribution of sources that result in the spread of AMR in the UK under different hydrological regimes, aiming to understand the complexity of AMR across UK landscapes. The Environment Agency has selected river catchments in the UK for further study that have different levels of human and waste exposure and are reflective of high and low levels of pollution. These are the Eden in Cumbria and the Coquet in Northumberland. Understanding these catchments will require sampling campaigns of soil and water under contrasting high and low flow regimes. Analysis of the collected samples will include quantifying a large number of ARGs and bacteria using High throughput qPCR. One of the more novel aspects of this project is the use of SourceTracker as a programme to associate downstream sinks with their sources. This will be used to estimate the impact of various interventions under high and low flow regimes, providing useful information for policy makers, such as the Department for Environment, Food and Rural Affairs (DEFRA). Ultimately, this project will answer the question as to which interventions are most useful to limit the spread of antibiotic resistance, through a detailed characterisation of AMR across UK landscapes.


Garner, E. et al. (2017) 'Stormwater loadings of antibiotic resistance genes in an urban stream', Water Research. Elsevier Ltd, 123, pp. 144-152. doi: 10.1016/j.watres.2017.06.046.
McCann, C. M. et al. (2019) 'Understanding drivers of antibiotic resistance genes in High Arctic soil ecosystems', Environment International. Elsevier, 125(November 2018), pp. 497-504. doi: 10.1016/j.envint.2019.01.034.
O'Neill, J. (2014) 'Review on AMR', Antimicrobial Resistance: Tackling a Crisis for the Health and Wealth of Nations. Wellcome Trust.