Undergraduate Student Report 2020

Fungal colonization of voice-prosthesis biofilms and its use as a predictor of device longevity in total-laryngectomy patients. 

Alaina Cockerell, University of Exeter

I am a 4^th year physics student studying for an MPhys at the University of Manchester. Last summer, I was given the great opportunity to undertake a BMS-funded summer project in the groups of Dr Alexandra Brand and Dr David Richards at the University of Exeter.

Dr Brand’s group in the MRC Centre for Medical Mycology had already undertaken a study of the organisms that form biofilms on voice prostheses, devices that enable head and neck cancer patients who have undergone total laryngectomies to speak.  These devices are made from soft polymer and so can easily become compromised by the formation of a biofilm.  In particular, infestation by fungi can cause them to swell and stiffen, contributing to the mechanical failure of the device (Figure 1).  Frequent changes of these devices are both taxing on the patient and costly to the health service.

The purpose of my project was to use a computational approach to analyse the existing dataset of over 800 fungi and bacterial isolates from voice prostheses donated by a cohort of total-laryngectomy patients.  The aim was to identify positive and negative relationships between the isolates and probe the dataset for indictors that would act as a predictor of device longevity in these patients.

The study involved a cohort of 14 study participants who submitted both their voice prostheses and oral rinse samples over a period of 13 months.  Participant factors included in the analysis included whether the participant used dentures, antacids, nystatin (an antifungal) or antibiotics.  From the 66 voice prostheses and 61 oral rinse samples, 885 microbial isolates were identified, representing 11 species of fungi and 70 species of bacteria.

My first task was to identify a core profile of microbes for each participant and to investigate whether this was consistent throughout the participant cohort.  After trying various options, I found that the most useful definition of a core profile were those organisms that were present in more than half of the samples.  My analysis showed that participants carried a core profile over time that was specific to each individual.

With guidance from Dr Richards, I then used MATLAB (a computer programming environment) to carry out a number of statistical tests between both the participant factors and the organisms themselves.  Although the sample size was relatively small, by analysing data over time from both voice prosthesis and oral rinse samples, my analysis revealed a number of associations between microbes and patient factors that can be investigated in future studies.

I then calculated the phi coefficient (a measure of the correlation between pairs of organisms) for all pairs of organisms, with a colour-map used to translate the coefficient to a colour for ease of visualisation.  Finally, the organisms with the most positive and most negative coefficients were selected to be included in a correlation network figure.  This showed which organisms were likely to be found together, such as, for example, co-colonisation of voice prostheses by Candida krusei and C. tropicalis.

I would like to thank the BMS for the opportunity of a Summer Bursary, particularly during this time when Covid-19 has made traditional biology projects difficult to pursue (Figure 2).  The award has contributed to a manuscript soon to be submitted for publication by the Brand group and, excitingly, the experience in MATLAB programming and data analysis with Dr Richards has enabled me to obtain a PhD position in computational biology at the University of Exeter that will start this October.  I would also like to acknowledge the work of Dr Ijeoma Okoliegbe, who collected the dataset during her PhD with Dr Brand, and the ENT Clinic staff at Aberdeen Royal Infirmary through whom the study was conducted.

BMS Undergraduate Student Bursary, 2020