Research Projects

Fungal infections and diseases result in approximately 3.8 million deaths worldwide each year1. The World Health Organization (WHO) put forth a fungal pathogen priority list, categorising major fungal pathogens as critical, high, and medium priority2. Of these, Cryptococcus neoformans belongs to the critical priority. Cryptococcal meningitis has an annual incidence of ~194,000 and a treated mortality rate of 60%1. Candida albicans is the most prevalent Candida pathogen, and about 1,565,000 people suffer from a Candida bloodstream infection or invasive candidiasis, with 995,000 deaths annually1. Candidozyma auris is an emerging multidrug-resistant fungal species. C. auris infections have been reported in more than 40 countries, with a mortality rate of 30-60%3. Candida tropicalis is responsible for nosocomial infections, especially in patients with haematological malignancies4 . The hurdles in efficiently managing fungal infections include limited antifungal compounds in clinical use and rising resistance against the existing drugs. Cellular alterations resulting in genome instability have been implicated in human disease conditions like cancer5. However, in primarily asexual fungal pathogens, such changes can be advantageous as they rely on genome plasticity to withstand and thrive under hostile conditions like exposure to antifungal compounds. The machinery facilitating such events is vital for the pathogens’ survival and evolution. Our knowledge of this machinery can facilitate novel drug discovery and better fungal disease management. One approach to identifying such factors is an overexpression screen in which increased expression of selected genes can result in dosage-based genome instability (dGIN). Resistance to chemicals like fluconazole, a widely used antifungal compound and thiabendazole, a microtubule depolymerising agent, will be used as reporter systems to identify genome instability factors in pathogens belonging to Candida sp. Similar genetic screens have been used successfully in model systems like Saccharomyces cerevisiae to identify genome stability factors6. We intend to utilise a fluorophore-based overexpression library to identify genome stability factors in C. albicans and leverage phylogenetic relatedness to extend the scope of characterising ‘dGIN hits’ in related pathogens like C. tropicalis and C. auris. We also propose to generate a conditional promoter-based overexpression library for C. neoformans chromatin modifiers, as such a resource will be unique, first of its kind, and thus have the potential to find novel dGIN factors. Further characterisation of these factors that are fungal-specific using cell biology and biochemical techniques will help us identify potential targets, the first step in the process of antifungal drug discovery. (References are listed in the document 'OTD' under references for project summary).