Mathematical Modelling of Antimicrobial and Heavy Metal Resistance in Bacterial Populations Within the Flow of Agricultural Slurry in a UK Dairy Farm

Todman, Henry (2023) Mathematical Modelling of Antimicrobial and Heavy Metal Resistance in Bacterial Populations Within the Flow of Agricultural Slurry in a UK Dairy Farm. PhD thesis, University of Nottingham.

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Antimicrobial resistance (AMR) is a one of the most important global public health problems facing the modern era. Dairy cattle represents one of the largest agricultural industries, with approximately 265 million dairy cows across the globe. These are estimated to produce 3 billion tonnes of manure each year. Dairy slurry represents a major source for environmental contaminations of antimicrobial resistance genes (ARG). The management and storage systems of dairy slurry provide a setting in which bacteria, antibiotic residues, metals and chemicals to mix and may be a locus for selection of AMR. Mathematical modelling offers a powerful tool to explore the impact that changes to farm management practices may have on AMR dynamics, where it would be impossible to empirically explore such changes on a working farm.

We present a mathematical model describing the dynamics of AMR and waste within the slurry management system of a UK dairy farm, and explore the impact that different farm policies have on the selection of AMR within this system. This model is built on a volumetric flow model for the farm based on ethnographic observations of the farm and has been calibrated against metal concentrations in the slurry tank from a longitudinal study of the farm using Bayesian inference methods. We then coupled this model with a bacterial growth and gene transfer model to develop a multiscale, discrete-continuous, compartmental ODE model for the flow of slurry, bacteria, antibiotic residues and metals around the farm. The model found that footbath emptying practices lead to a significant bacteriocidal input in the slurry flow leading to large fluctuations in resistance levels on the farm.

Furthermore, adjusting the model suggested that cephalosporin resistance is more observable when cephalosporin resistance is chromosomally-encoded (rather than on plasmids) - this observation is consistent with studies of a chromosomally encoded ISEcp1 element found on the farm. This work concludes that farm management practices can have a material impact on AMR in dairy slurry, and offers opportunities for farm-specific policies to mitigate the drive and spread of AMR, beyond reduction in antibiotic (Ab) usage.

The farm flow model details the beginnings of a possible pathway for environmental AMR contamination which may affect food crops - It is also important to consider the risk of dietary exposure to ARG/ARBs. The lifelong acquisition (through ARGs in food intake) and persistence of resistance genes in the gut resistome may lead to resistance in endogenous infections (e.g. urinary tract infections), particularly in individuals of older-age. Chapter 4 of this work presents a probabilistic model for the acquisition and persistence of ARGs over an individual's lifespan. We consider potential strategies to reduce the overall resistance load in the microbiome, and the effectiveness of these strategies in countries of different Ab usage. This work surmises that policies considering the ARGs in food intake would be more effective in reducing ARG accumulation than polices that solely consider reducing Ab usage.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Stekel, Dov
Kypraios, Theo
Baker, Michelle
Keywords: antimicrobial resistance, dairy cattle, dairy slurry
Subjects: Q Science > QR Microbiology
S Agriculture > SF Animal culture
T Technology > TD Environmental technology. Sanitary engineering
Faculties/Schools: UK Campuses > Faculty of Science > School of Biosciences
Item ID: 76728
Depositing User: Todman, Henry
Date Deposited: 18 Jan 2024 12:14
Last Modified: 18 Jan 2024 12:14

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