Metabolomic investigations of Mycobacterium bovis infection of cattle

Abstract

Metabolomics, characterising the metabolites within a biological system is a relatively novel area of research which has been applied to a range of disease for diagnostic purposes, including human tuberculosis. Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is widely regarded as one of the greatest problems that livestock farming faces in the UK today. Aside from animal welfare implications, control of the disease incurs signifcant cost nationally and can have major socio-economic impacts in rural communities. Accurate diagnosis is a signifcant obstacle to diseasee control. A selection of validated diagnostics exist, yet suboptimal accuracy limits detection of all infected animals. Furthermore, current Government policy is to licence the TB vaccine BCG for use in cattle, however, the effcacy of BCG is and can compromise the routine diagnostic performance of the main diagnostics. Consequently a diagnostic that can diferentiate between infected and vaccinated animals (so-called DIVA tests) will be required before vaccination can be used as a control tool in GB. This thesis applies metabolomics to samples from experimental models of M. bovis infection to identify potential novel biomarkers of the disease and that could have DIVA potential. A number of metabolites were identifed that could have diagnostic and DIVA potential. Further characterisation of metabolomic changes in experimental infection models identifed shifts in the metabolome that both mirrored changes identifed in human TB along with novel fndings which provide an insight into the host-pathogen interaction. Overall this novel study indicates that metabolomics has the potential to aid bTB control and improve our understanding of the infection process. The fndings, particularly in respect to novel biomarkers, require further validation in naturally infected cattle in real-world situations where factors such as age, gender, breed, nutritional status, pregnancy, lactation status and concurrent disease may compromise their performance.

Date of Award	2022
Original language	English
Awarding Institution	Aberystwyth University
Supervisor	Luis Mur (Supervisor) & Glyn Hewinson (Supervisor)