Temporal Adaptation to Antifungal Treatment in Pathogenic Fungi

What will you investigate? Fungi are amazingly adaptable microorganisms and can even adapt to the antifungal agents we use to kill them. Several studies have identified the mechanisms by which antifungals are effective at killing fungi and the key mechanisms for antifungal resistance. Antifungal treatment is also known to induce significant changes in intracellular ROS [Lee & Lee 2018], in fungal cell walls [Hopke 2016] and can have paradoxical effects on survival in mammalian infections [Lee 2012]. What these studies do not address is how fungi initially sense and respond to antifungal activity. Improving our understanding of these early adaptations to antifungal treatment can highlight the specific cellular stresses to which fungi are responding, thus giving insight into fundamental fungal cell biology under conditions relevant to human health. Therefore, the aim of this project is to build a temporal profile of how fungal cells respond to antifungal agents using the model yeast, Saccharomyces cerevisiae, and the clinically-relevant yeast, Candida glabrata. The focus of this project is to investigate how antifungal exposure over time alters gene expression and protein translation. These datasets will be integrated to identify temporal patterns of responses to antifungal treatment. You will use state-ofthe- art sequencing to perform gene expression and molecular genetic investigations. You will work with Wallace lab colleagues to use bioinformatics and statistical software to analyse transcriptomic and translational data. From the temporal profile, we will make predictions of how fungi are sensing antifungal stress and test these hypotheses using cutting-edge molecular techniques to genetically modify yeast. The resulting yeast strains will be assessed for antifungal sensitivity, cell wall alterations, and for variations in host-pathogen interactions. You will work with Childers lab colleagues to learn pathogenic yeast cultivation, cell wall and phenotypic analysis, and hostpathogen interactions. This project should significantly improve our understanding of the molecular mechanisms behind how fungal cells sense and adapt to antifungals. What training will you receive? You will be trained to become a wellrounded scientist who is able to communicate with scientific and general audiences. You will learn transferable methodologies: microbiological techniques, cell wall and phenotypic analysis, and
modern molecular approaches, including CRISPR-Cas9 gene editing. You will also learn a competitive and highly sought skill from the Wallace lab: how to handle large datasets, extract RNA, and best practices in bioinformatics and statistical analysis. What comes next? Upon completing this project, you will have successfully gained highly competitive skills for the life sciences industry. There is a growing demand for scientists with bioinformatics training and the capacity to make sense of 'big data'. The knowledge you gain of wet-lab research activities and dataset handling will help you drive impactful research in academic or industrial settings. The communication, analysis, and problem-solving skills you learn on this project will be transferable and competitive across employment sectors.