PhD in Engineering: Headspace metabolomics for non-invasive biomarker discovery

Recent developments in advanced mass spectrometry and data treatment tools has led to a boom in the efficient design of point-of-care testing (POCT). Approaches are based on novel disease biomarkers discovery with metabolomics studies and innovative sensor technologies. Breath analysis is an ideal candidate for POCT because of its non-intrusive nature; it is, however, much less developed than blood testing. Nevertheless, diseases as varied as lung and throat cancers, Parkinson’s disease and pulmonary diseases have been shown to possess specific volatile biomarkers “fingerprint” which have been, to date, under-utilised.

Metabolomics studies have mostly been carried out in biological samples such as blood, urine or faeces. There is growing evidence that microbial activities regulate a broad range of functions in the human body and that patients with related illness(es) present different microbiome than healthy subjects. In turns, recent research also demonstrates that the chemical composition of the headspace above a microbial community is representative of the turned-on metabolic and catabolic pathways.

We propose therefore to move metabolomics to the headspace and study the volatilome of microbial communities to explore yet untapped opportunities for diagnostic and screening.

In this project, the student will develop a novel pipeline for biomarker discovery in breath volatilome (volatile metabolites), in clinically-relevant scenarios. Focusing on the oral/gut microbiome (a complex community of bacteria living at the aerobic/anaerobic interface between mucosa and oral cavity), which influences oral health (cariogenesis, periodontitis, gingivitis) and systemic and cardio-metabolic health, we propose a unique transitional approach from bench to clinical practice.

Methodology

The student will first develop analytical methods for non-targeted volatilomics using standard mixtures of representative volatiles metabolites. This will include sampling, GC-MS and data processing methods.

The student will then run batch biofilm fermentation microcosms with various treatment (such as carbon and nitrogen availability), making use of existing in vitro multi-species biofilm models establish in the Ramage Lab. The statistical analysis tool of the pipeline will be adapted from existing tools in the Gauchotte-Lindsay group to the volatilome of these samples and biomarkers that correlate with the variations in treatment will be identified.

Finally, volatilome characterisation will be carried out using the same analytical pipelines in groups of healthy human volunteers and volunteers with periodontitis and obesity-associated endotoxaemia before, during and after an intervention using dietary or pharmacological approaches to modulate the biofilm (in vivo). Here biomarkers that could eventually be employed in point-of-care sensors will be identified.

Project Team: The supervisory team have complementary expertise to bring to this project. Dr Gauchotte-Lindsay is a lecturer in Environmental Engineering in the School of Engineering and has developed worflows for markers identification in complex samples using gas chromatography coupled with mass spectrometry (GC-MS), advanced data processing and multivariate statistical tools and is also currently developing environmental plasmonic biosensors for point-of-use testing. Dr Emilie Combet is a Senior Lecturer in Nutrition in the School of Medicine and has extensive research expertise in the design of analytical assays for human health and has run several human trials. Prof Gordon Ramage is a medical microbiologist working in the Dental School with specialism in developing models of the bacterial and fungal biofilms of the oral cavity. While registered in the School of Engineering, the student will spend time in the well-equipped research laboratories of all three supervisors as required by the project. The project is intended to be truly interdisciplinary and supervisory support will be provided as a team.

Person Specification

This studentship is open to candidates of any nationality – UK, EU or International.

Applicants should demonstrate the following:

• A 1st or 2nd upper class degree, with postgraduate qualification at Merit/Distinction in a relevant subject area
• Knowledge and experience in analytical (bio)chemistry and statistical treatment of data
• Experience of conducting independent research
• Excellent oral and written communication skills

In the first instance, prospective applicants should contact Dr Gauchotte-Lindsay, [Email Address Removed] to discuss your eligibility.