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Data driven volatilomics and metabolomics analyses of sebum for odour based diagnostics of tuberculosis

Department of Chemistry

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Dr D K Trivedi , Dr S Fowler , Prof P Barran No more applications being accepted Funded PhD Project (European/UK Students Only)

About the Project

One million children (<14yrs) contracted TB in 2017[1]. Current diagnostic tests for TB in children includes bacteriological tests (culture, molecular tests, microscopy) on sputum or gastric aspirates, or signs and symptoms of TB, including X-ray. However, children have difficulties to produce sufficient quantity of sputum and often paucibacillary disease (low bacterial count). The bacteriological tests have limited sensitivity (mainly microscopy), or are slow and costly (culture). Hence there is a clear need for rapid point of care diagnostics in order to guide targeted treatment, improve prognosis/treatment success, reduce spread of disease, and facilitate further investigation where TB is excluded.

In an ongoing pilot study with our collaborators Prof Perdita Barran (The University of Manchester) and Apopo, a non-profit in Tanzania, Joy Milne, a super smeller[2] has described a unique smell associated with TB in sputum. Joy has successfully demonstrated that smell of biofluids can be linked to one’s disease state[3]. This project will investigate sputum along with breath, urine and sebum to discover TB based odorous compounds that Joy is able to smell. Very little is understood about the role of sebum as a diagnostic bio-fluid. Sebum has been hypothesised as a sink to odourous compounds that can be hallmark of many diseases such as Parkinson’s disease[4]. Sebum reflects many underlying metabolic activities in health and disease and using high resolution analytical techniques allows for accurate measurement of these activities. These odorous molecules obtained non-invasively will be ideal candidates for early diagnostic test since we have demonstrated that body odour changes before presentation of clinical symptoms in disease such as Parkinson’s[5]. Using advanced chemometrics and machine learning approaches, data dependent models will be investigated for classification and prediction of disease from a simple skin swab, integrating patient information, metadata and other clinical observations.

Academic background of candidates:
The Trivedi group is looking for an PhD applicant to join an exciting new interdisciplinary research group focused on data driven investigation of analytical data for disease diagnosis. Applicants must have obtained, or expect to obtain, a first or 2.1 UK honours degree, or equivalent for degrees obtained outside the UK, in biomedical science, physical chemistry or analytical chemistry. The student should be highly motivated, independent, with strong problem solving abilities and the ability to work as part of a team.

As a PhD candidate you will have access to high resolution analytical instruments from Waters, Thermo and Agilent house at the Michael Barber Centre for Collaborative Mass Spectrometry (MBCCMS). You will have the opportunity to work within an interdisciplinary environment at Manchester Institute of Biotechnology. You will work with post-doctoral researchers within the group to learn sample handling, sample extraction and use of high resolution mass spectrometry. You will gain training in chemometrics analysis of big analytical data and apply machine learning algorithms suitable for different types of data.

Contact for further Information:
Enquiries and applications should be directed to Dr Trivedi ([Email Address Removed]).

Funding Notes

This is a 3 year funded studentship, covering fees and stipend (£15,285 in 2020-21)

Open to UK applicants only.

It is anticipated that the PhD Studentship will start in January 2021.


1. World Health Organization (WHO) (2017), ‘Global Tuberculosis Report 2017. Geneva: World Health Organization’, WHO/HTM/TB/2017.23.World Health Organization
2. Morgan J (2016), ‘Joy of super smeller: sebum clues for PD diagnostics’, Lancet Neurology, DOI: 10.1016/S1474-4422(15)00396-8
3. Trivedi DK et al (2019), ‘Discovery of Volatile Biomarkers of Parkinson’s Disease from Sebum’, ACS Central Science, 5 (4), 599-606
4. Sinclair et al (2020), ‘Sebum: A Window into Dysregulation of Mitochondrial Metabolism in Parkinson’s Disease’, ChemRxiv. Preprint.
5. PCT Filing (2019), PCT/GB2019/052169 Biomarkers and Uses thereof

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