Project Outline

Background

The rapid emergence of fungal diseases is a global threat to animal, plant and our ecosystem, while fungal infections affect billions of people, including >1.5 million global deaths each year. Within a fifteen-year period (1995-2010), fungi have caused species extinction of 39 animal and four plant species [1], and there are only three classes of antifungal drugs available in the clinic in the past four decades. Inevitably, multidrug resistance has become an urgent problem for the agricultural industries and human medicine. Additionally, with climate change, extreme weathers also facilitate the interactions between fungal pathogens and their host (and/or environment), and many environmental fungi now can overcome growth temperature barriers (12–30°C) to affect human [2]. The development of stress (thermo-) tolerance phenotypes likely results from the high genome plasticity in fungal genome, while aneuploidy, an unbalanced genomic state with gain or loss of chromosomes, is prevalent in wild and clinical fungal isolates. Whether and how these genome abnormalities alter the host-fungal-microenvironment interactions to enable adaptive evolution in fungi remain elusive. This project aims to investigate the evolution of host-fungal interactions under environmental stress and to identify novel host and fungal factors contributing to the pathogenicity.

Objectives and Methods

We will use multiple fungal pathogens (mainly Candida species) and animal, cell line infection models to investigate the phenotypic cues governing stress tolerance at the host-pathogen interfaces.

Objective 1: Characterize stress-induced fungal secretory profile

While aneuploid fungi share a unique biophysical signature, hypo-osmotic stress state [3], the increased turgor pressure can lead to a unique secretory profile, including proteins, nucleic acids and metabolites. We aim to systematically identify and characterize their function and contributions to stress tolerance phenotypes and species interactions, using multi-omics approaches. The research outcome of this objective will reveal the mechanistic insights into how fungal pathogens tolerate antiproliferative stress and thrive from the host microenvironment.

Objective 2: Investigate the fungal genomic plasticity at the host-fungal interface

As fungi possess a high level of genome plasticity, we will identify the types of genomic alterations (mutations/CNV/ploidy variations) when fungal pathogens encounter the host and environmental stress in a temporal manner. Importantly, the mutual relationship between each type of genomic abnormalities will be investigated. For example, whether ploidy variations “buffer” or promote DNA damage responses? Both genomics and cell biological methods will be used to reveal the mutational evolution in the adaptive process.

Together, this project will leverage both genomics, proteomics, biochemistry and cell biological approaches to understand the molecular evolution of fungal diseases from the interactions of hosts, fungal pathogens and their microenvironment.

References

1. Fisher, M., Henk, D., Briggs, C. et al. Emerging fungal threats to animal, plant and ecosystem health. Nature 484, 186–194 (2012). https://doi.org/10.1038/nature10947
2. Case NT, Berman J. et al. The future of fungi: threats and opportunities. G3 (Bethesda). 2022 Nov 4;12(11) https://doi.org/10.1093/g3journal/jkac224
3. Tsai, HJ., Nelliat, A.R., Choudhury, M.I. et al. Hypo-osmotic-like stress underlies general cellular defects of aneuploidy. Nature 570, 117–121 (2019). https://doi.org/10.1038/s41586-019-1187-2

Techniques

• Molecular technologies: both basic and high-throughput lab techniques, including genome-wide screening and strain manipulations in automation systems.
• Biochemistry: protein purifications, western blotting and immunoprecipitation assays.
• Cell biological methods: advanced quantitative microscopy, phagocytosis assays and related host-pathogen interactions assays.
• Basic animal model of infections.
• Genomics: genome-sequencing, barcode-sequencing.
• Proteomics: LC/MS-based quantitative proteomics.