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Pathogenic fungi from the Candida genus are obligate human commensals, which cause disease when host immune systems are compromised. Treating such infections has become increasingly more challenging due to the rise in antifungal resistance. Recently it has been discovered that Candida species generate sub-populations of specialized antifungal tolerant cells when exposed to lethal concentrations of antifungal drugs. It is thought that this drug tolerant state provides an opportunity for cells to acquire the necessary genetic mutation to become antifungal resistant. Indeed, such drug tolerant cells are readily isolated from patients with recurrent Candida infections, underscoring their clinical relevance. However, very little is known about the establishment or maintenance of drug tolerance in Candida spp. Research suggests that drug tolerance is dictated by a unique transcriptional profile within tolerant cells, which is hypothesized to be epigenetically inherited.
This project aims to characterize the tolerant state in the clinically relevant pathogenic yeast, Candida glabrata, and determine whether it is determined by genetic and/or epigenetic mechanisms. This project will investigate the frequency, reproducibility and stability of the drug tolerant state under different antifungal drug regimes. This analysis will be undertaken in both wild-type (WT) C. glabrata as well as in genetically modified strains that lack key regulators of chromatin structure, such as histone acetyl-transferases and histone deacetylases. Next, state-of-the-art RNAseq and DNA sequencing technologies will be used to interrogate the transcriptome and genomes of WT drug tolerant cells respectively. In collaboration with the Wallace lab at the University of Edinburgh, we will analyse these datasets to identify molecular signatures of drug tolerance. Furthermore, taking a Systems Biology approach we will work with the Wallace lab to model our phenotypic and molecular data, to understand the biological variables that contribute to the stability of the drug tolerant state in C. glabrata.
Start Date: 1 October 2022
Duration: 3 years
Skills/experience required:
UG degree in any of the following disciplines: Microbiology/Molecular Biology/Biomedical Science/Biochemistry
Computational/numerical literacy and eagerness to learn bioinformatics, Aseptic technique
Skills desired: Molecular biology laboratory skills, Bioinformatics or data analysis stills (Unix/R/Python)
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