4-year PhD Studentship: Exploiting interkingdom bacterial- fungal chemical signaling to tackle antimicrobial resistant fungi

Healthcare-associated infections (HAI) remain an unresolved clinical issue that significantly impacts patients’ lives and global economies. In Europe alone, HAI occur in 4.1 million patients annually at a cost of >€7 billion for direct infection management (1). Candida species are the fourth most common pathogen across all HAI types, with ~700,000 annual cases of invasive Candida infections (ICI) worldwide and a mortality rate as high as 75% (2, 3). Even with existing antifungal therapies, ICI carries up to 60% mortality rate, with longer hospital stays, poor quality of life and increased medical care costs (2, 4). Over 80% of patients dying from ICI could be saved with universal availability of fungal diagnostics and potent antifungal agents based on existing and well documented treatment response data. The emergence of multidrug-resistant Candida species (i.e. Candida auris outbreaks in COVID19 patients), and the serious adverse effects and higher price tags of current antifungal agents, further exemplify the dire need for efficient, cost-effective, and safe antifungal agents to manage ICI. Quorum sensing molecules (QSMs) synthesised by microorganisms to communicate with each other are shown to possess promising antibacterial properties (5, 6). Thus, exploration of their antifungal potential is a timely approach for managing ICI.

Hypothesis: Based on our pilot data showing their strong anti-Candida properties, we propose that ‘Diffusible signalling factor family’ (DSFF) cis-2-unsaturated fatty acids, a widely conserved QSM group in Gram-negative bacteria, can be translated into efficient and cost-effective antifungal agents to manage ICI.

Aim

Characterise DSFF QSMs with anti-Candida properties and their mechanism of action (MOA) at the community, cellular and molecular level.

Objectives

• Identify DSFF QSMs with anti-Candida properties and synergies with current antifungal drugs
• Decode their MOA using a proteomic approach
• Characterise the efficacy of DSFF QSMs and the host response to them using an endothelial cell culture model

Methodology

Building upon strong pilot data, all commercially available DSFF QSMs (7 in total) will be screened for their anti-Candida properties using established in vitro planktonic and biofilm models. C. albicans and C. auris will be used throughout due to their prominent causative role in ICI, outbreaks in COVID19 patients and rising pan-antifungal resistance. Synergies of DSFF QSMs with approved antifungal classes for ICI (3 in total) will also be assessed as above. Candida molecules and pathways modulated by DSFF QSMs will be determined by a cutting-edge, high-throughput proteomic approach; tandem-mass tagging and nano-liquid chromatography and mass spectrometry. Specific Candida molecules and mechanisms identified above will be verified using mutant analyses and quantitative-PCR. The efficacy of chosen DSFF QSMs (+/- antifungals) and host immune/inflammatory reactions will be evaluated using a cell-culture model. This multidisciplinary project spans the areas of mycology, biochemistry, cell biology, genetics, proteomics, and advanced imaging. Thus, the student will acquire a unique skill set during the course of this community-to-cell-to-atom study. Skills include but are not limited to biofilm models, antimicrobial sensitivity testing, phenotypic assays, advanced microscopy imaging, small molecule handling, gene expression, mammalian cell culture, immunological assays, protein expression and big data analyses through bioinformatics.

Keywords

Candida, candida auris, Candida albicans, healthcare-associated infections, bacteria, quorum sensing, antimicrobial resistance, antifungal agents, antifungal resistance, cell-cell communication

How to apply for this project

This project will be based in Bristol Dental School in the Faculty of Health Sciences at the University of Bristol.

Please visit the Faculty of Health Sciences website for details of how to apply