Active Infection & Immunity Genetics & Molecular Biology

Fungal Genomics and Antagonistic Community Interactions

In plain English

AI plain-English summary

Fungal infections from *Candida* species are becoming harder to treat as resistance to key antifungal drugs rises, yet genomic surveillance of these pathogens lags far behind that of bacteria. This project will sequence *Candida* genomes from hospitals, wastewater, and environmental samples across Europe and Australia to map how these fungi spread between clinical and non-clinical settings—a gap that currently leaves transmission routes largely invisible. The researchers will also identify which co-colonising bacteria naturally inhibit high-risk *Candida* strains, revealing how microbial competition shapes fungal survival. If successful, this work could transform infection control by providing hospitals with genomic tools to track outbreaks in real time, much like bacterial surveillance already does. It could also point toward new probiotic or microbiome-based strategies to suppress *Candida* without relying on antifungal drugs, reducing selective pressure for resistance. The project is primarily applied and epidemiological, but its fundamental insights into fungal-bacterial community dynamics may open unexpected avenues for managing other hard-to-treat microbial infections.

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Fungal pathogens within the Candida genus, including C. albicans, C. parapsilosis and C. auris, represent a growing public health concern on a global scale. Resistance to key antifungal drugs, particularly azoles and echinocandins, is on the rise. Increased virulence or resistance is driven by multiple factors including the dual use of antifungals, but our understanding of these drivers is incomplete. The implementation and utility of genomics in Candida epidemiology significantly lags behind its use for bacterial pathogens, and there is little data on the transmission dynamics of these species between clinical and non-clinical (One Health) environments. Moreover, we lack a detailed understanding of how competitive interactions with co-colonising bacterial species impact the survival and spread of pathogenic fungi. This proposal synergises expertise in genomic epidemiology, bioinformatics and microbiome ecology. We will combine existing genomic data with novel genome and metagenome data from clinical and non-clinical settings from Europe and Australia. We will also characterise extensive wastewater and environmental samples from the UK and NL. We will examine hospital transmission dynamics, and link this with the identification of commensal bacteria that are inhibitory to high-risk Candida strains. This data will inform novel intervention strategies to mitigate Candida transmission.

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Researchers

Edward Feil (Principal Investigator)

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Research Grant

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