Second PhD student cohort – 2019-20
The second cohort of PhD students funded by the Medical Research Foundation. Twelve students undertaking multidisciplinary PhD projects are based in UKRI cross-council funded AMR consortia in 9 universities across the UK.
Our second cohort are:
Jonny Burnett (SWON ALLIANCE consortium)
Supervised by Professor Chris Dowson, University of Warwick
Next generation inhibitors to tackle penicillin resistance (AMR)
Broad spectrum resistance mechanisms mean that drug classes with new modes of action are the best option to circumvent resistance. Understanding how resistance is brought about in penicillin binding proteins (PBPs), through kinetic analysis of mutant strains and modelling of poorly understood loop dynamics, could aid our future antibiotic drug design. Our focus is on Neisseria gonorrhoeae PBP2, chosen due to the rapid emergence of ‘super’ drug resistant strains which make gonorrhoea (a sexually transmitted infection) caused by these strains very difficult to treat. Design and synthesis of new inhibitors is inspired by the mode of action of β-lactams, but which are insensitive to resistance mediated by β-lactamases and alterations to PBPs typically conferring resistance, such as cyclic boronates. Our interest also spans to novel small molecules designed to inhibit the trans-glycosylase domain of multifunctional PBPs.
Jennifer Brazier (EVAL FARMS consortium)
Supervised by Professor Dov Stekel, University of Nottingham
Modelling the risks of AMR from agricultural waste to animal and human health
Application of slurry and manure from livestock production to arable land creates a potential exposure route in humans to antimicrobial resistant genes and bacteria. The slurry tank environment is a potential driver of AMR development, creating a reservoir of antimicrobial resistance genes and bacteria that is regularly disseminated into the environment. The level of background risk that this produces is largely unquantified and remains a potentially neglected area of AMR control. Our project uses Bayesian Network modelling to help quantify the background risk and identify potential intervention points that could mitigate the risk of transfer of AMR through non-animal based food products.
Supervised by Professor Henry Buller, University of Exeter and Dr Kristen Reyher, University of Bristol
Herd Health Planning and the Management of Antimicrobials in Livestock Systems
Reducing the use of unnecessary antimicrobial medicines in livestock farming has become an important component in the growing global drive to address antimicrobial resistance (AMR) in human and animal pathogens. Farm specific herd health plans and standard operating procedures (SOPs) aid record-keeping, monitoring and decision making in anticipating, planning for and implementing on-farm responses to animal disease.
In this research we aim to use social science approaches to investigate veterinary and on-farm practice to examine the role of herd health planning and SOPs, in promoting responsible antimicrobial use on UK dairy farms. Working with veterinarians and dairy farmers the research will track the use of herd health plans and SOPs and assess the role of these within the contexts of environment, livestock and disease history on-farm, in conjunction with the processes of farmer/veterinarian negotiation in the setting and meeting of plan requirements and objectives. We aim to investigate whether herd health plans and SOPs are an effective management tool in tackling the issue of antimicrobial use on UK dairy farms and contribute to the development of effective tools for achieving sustainable medicine use on livestock farms.
Tyler Ferguson (STEP-UP consortium)
Supervised by Dr David Eyre, Big Data Institute, University of Oxford
Using machine learning and statistical prediction models to improve empirical antibiotic prescribing
Antibiotic use is a key driver of antimicrobial resistance. Often, clinicians need to prescribe antibiotics before knowing which would be the most effective. The last few decades have seen the increased collection and availability of electronic health data – giving a detailed medical history of many patients. This data raises the possibility of using modern machine learning techniques, already in use in medicine and other disciplines, to help identify resistant infections and make antibiotic recommendations that reduce the risk of mismatched treatment. Our research will develop models and tools using machine learning technology to help augment the decision making process used by clinicians when empirically prescribing antibiotics.
Winnie Lee (OH-STAR consortium)
Supervised by Professor Matthew Avison, University of Bristol
Predicting empiric antimicrobial prescribing from local surveillance of active and potential AMR mechanisms
Bloodstream infections (BSIs) in hospitalised patients, predominantly caused by Escherichia coli, are associated with high mortality and morbidity. BSIs can lead to sepsis where empirical antibiotic treatment is crucial within a few hours of diagnosis of sepsis to reduce fatality. Therefore, antimicrobials are administered in the absence of a microbiological culture. This often leads to inadequate empirical therapy, resulting in treatment failure. Our research will involve optimising empirical therapy. With the power of whole genome sequencing (WGS) and bioinformatics analyses, surveillance of resistance can be conducted through manipulation of genomic datasets generated from sequencing. Patterns of resistance can be identified in real-time within the community including the potential for resistance, which can be used to guide empiric therapy.
Beatriz Llamazares (OH-STAR consortium)
Supervised by Professor Matthew Avison and Dr Kristen Reyher, University of Bristol
Reducing antibacterial resistance in dairy farms through the identification of the risk factors that drive resistance during the early life of calves
Farm animals harbour bacteria resistant to highest priority critically important antibacterials (HPCIA) for human health, which hypothetically could be transferred to humans. The highest levels of resistance are found in the youngest animals (calves) that will recycle these resistant bacteria once they join the milking herd as adults. In this research, we are investigating the levels of resistance to HPCIA in Escherichia coli and the genes responsible for it by analysing samples taken from calves and the environment, as well as identifying the risk factors around the early life of the calves that drive resistance as a way of reducing the possibility of transmission to other animals and to humans.
William Matlock (REHAB consortium)
Supervised by Professor Sarah Walker, Nuffield Dept. Medicine, University of Oxford
Genomics and metagenomics of animal, environmental and human samples to understand resistance gene transmission amongst Enterobacteriaceae in Oxfordshire.
Our project aims to understand the dynamics of antimicrobial resistance (AMR) using a large, environmental collection of Enterobacteriaceae isolates and associated plasmids. This family of bacteria frequently carry AMR genes of high clinical significance, often causing human infection. This project employs and develops genomic tools to understand their role in AMR spread. This also includes more fundamental questions about plasmid evolution and biology.
Lucy Miller (STEP UP consortium)
Supervised by Dr Ceire Costelloe, Imperial College London
Health and economic impact of paediatric RSV vaccinations on antibiotic use and resistance
Misuse and overuse of antimicrobials is a key driver of antimicrobial resistance (AMR). The majority of inappropriate antibiotic prescribing nationally occurs within primary care, and predominantly due to self-limiting or viral respiratory tract infections (RTI). Therefore, viral vaccination programmes hold promise to reduce antibiotic prescribing and development of resistance. However, this impact on AMR has yet to be quantified. Focusing on the Respiratory Syncytial Virus (RSV), a viral infection with a significant health burden for young children and infants. Our research aims to develop methodologies and models that can better incorporate the true costs and benefits of paediatric RSV vaccinations, to establish the potential impact on unnecessary antibiotic use and AMR.
Ashleigh Myall (ASPIRES consortium)
Supervised by Professor Mauricio Barahona and Professor Alison Holmes, Imperial College London
Analysis and prediction of carbapenem-resistance in healthcare-associated infections
Carbapenemase-production in the family Enterobacteriaceae (CPE) are a particularly concerning form of antibiotic resistant bacteria. For CPE, much work has been published on the molecular mechanisms for resistance acquisition and risk factors; but many fail to provide data-driven insight to explain its complex behaviour, spread, and persistence. Our research will primarily leverage spatial and temporal observations of CPE in healthcare networks to better understand its transmission dynamics. With this insight, we aim to develop mathematical tools for disrupting further dissemination of CPE across healthcare networks, which may also be applied to other antibiotic resistant species of bacteria.
Cara Patel (CHICKEN or the EGG consortium)
Supervised by Professor Will Gaze and Dr Anne Leonard, University of Exeter (Penryn) and Dr Andrew Singer, UK Centre for Ecology and Hydrology
Linking restoration of natural capital to reduction in selection for and dissemination of AMR in aquatic systems
Our research focuses on the role of environmental pollution in driving selection for and spread of AMR bacteria. Wastewater treatment plant effluents and run-off from agricultural land are known to contribute to spread of AMR, however the relative contributions of humans and animals to environmental reservoirs is poorly understood as is the efficacy of interventions to reduce pharmaceutical and bacterial pollution. The interdisciplinary nature of this project integrates molecular microbiology, evolutionary biology, pollution science and economic theory in valuing natural capital (of river catchments) relating to its role in reducing spread of AMR and translating science into policy.
Rene Raad (AMIS and UMOYA OMUHLE consortia)
Supervised by Dr Justin Dixon and Prof Martin Gorsky, London School of Hygiene and Tropical Medicine, and Dr Graeme Hoddinott, Stellenbosch University
A historical and ethonographic study of efforts to preserve the efficacy of antibiotics for tuberculosis in South Africa
The containment of resistance in tuberculosis (TB) has historically been premised on the very tight control of TB medicines, yet in many countries such as South Africa this has been unsuccessful. Drawing on ethnography, archival analyses and oral history, this PhD project seeks to understand the ways in which TB drugs are implemented and preserved in South Africa, both historically and in the present, to inform future policy and antimicrobial stewardship strategies for TB medicines and other antibiotics. More specifically, our research explores the changing nature of health system responses to TB in terms of treatment, stewardship, and messaging to patients to understand how legacies of the past bear upon contemporary treatment policies and behaviours.
Dr Wezi Sendama (SHIELD consortium)
Supervised by Professor John Simpson, University of Newcastle
The effect of ageing on the resolution of inflammation
As we get older, the cellular processes that sense and fight infections become defective in a manner that leads to chronic inflammation. Chronic inflammation in ageing can damage body tissues, leaving older people susceptible to recurrent infections such as pneumonia that necessitate the repeated use of antibiotics. This repeated use increases the risk of infections that are resistant to antibiotics. Our project aims to use human models of inflammation to explore how we could restore normal function to sentinel immune cells in the lungs that become impaired with age. In doing so, we hope to limit the chronic inflammation that predisposes to recurrent infections in older people.