Principal Supervisor: Dr. Elizabeth Fullam, School of Life Sciences
Co-supervisor: Dr. James Covington, School of Engineering
PhD project title: Exploiting the unique breath signature of tuberculosis for new diagnostics
University of Registration: University of Warwick
Tuberculosis and bovine tuberculosis caused by Mycobacterial pathogens are major global health problems.
Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB) and results in more deaths world-wide from a single infectious agent (1). Mycobacterium bovis is the causative agent of bovine tuberculosis (bTB) in cattle and is a major animal health problem facing the farming industry both in the UK, and globally (2). As well as causing bTB in cattle, M. bovis is a zoonotic pathogen and can infect humans, causing tuberculosis, predominantly through ingestion of meat or unpasteurised dairy products from infected animals (3, 4).
Given the global importance of this pathogens and the increase in anti-microbial resistance, there is an urgent need for the development of rapid, non-invasive, point-of-care diagnostics, that can be utilised in resource poor settings. Giant rats have been shown to be able to detect Mtb in resource poor settings (5) and therefore we are interested in developing a novel chemical nose for the diagnosis of Mtb using the unqiue gas signature emitted from breath.
This PhD project aims to address this highly topical issue and aims to develop a basic understanding the unique gaseous signature produced by mycobacterial species and compare them with other (non-mycobacterial) species, with the long-term of exploiting these pathways to generate an enhanced distinct volatile signal using small molecular probes and a electronic nose for TB detection. In addition, we will use defined antimicrobial Mtb resistant strains with known genotypes to determine how the gas signature differs, which will have important clinical diagnostic implications. We also have access to TB patient breath samples which we can use to compare the breath analysis to that from pure culture. Machine pattern learning will be used to analyse the results data-sets generated.
The aim of the project is to understand the unique volatile ‘breath’ signature produced by Mtb to develop an electronic nose for TB detection in resource poor settings. This will ultimately enable us to exploit the pathways involved in producing these volatile compounds and allow us to develop tools and techniques for diagnosis purposes.
- Davies PD. Tuberculosis in humans and animals: are we a threat to each other? J R Soc Med. 2006;99(10):539-40.
- Thoen CO, Lobue PA, Enarson DA, Kaneene JB, de Kantor IN. Tuberculosis: a re-emerging disease in animals and humans. Vet Ital. 2009;45(1):135-81.
- Mgode GF, Cohen-Bacrie S, Bedotto M, Weetjens BJ, Cox C, Jubitana M, Kuipers D, Machang'u RS, Kazwala R, Mfinanga SG, Kaufmann SH, Drancourt M. Mycobacterium genotypes in pulmonary tuberculosis infections and their detection by trained African giant pouched rats. Curr Microbiol. 2015;70(2):212-8.
BBSRC Strategic Research Priority: Food Security and Molecules, Cells and Systems
Techniques that will be undertaken during the project:
Volatile gas analysis: including gas chromatography techniques
Molecular biology (PCR, cloning, mutagenesis)
Microbiology (targeted gene deletions/overexpression), culturing mycobacteria including CL2 and CL3 containment training to work with pathogenic mycobacteria including M. tuberculosis
Labelling of cultures with small probes
Bioinformatics/machine pattern learning for analysis of large datasets.
Contact: Dr. Elizabeth Fullam, School of Life Sciences