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Systematic genetic analysis of virulence in the human fungal pathogen Cryptococcus neoformans

Abstract

The opportunistic fungal pathogen Cryptococcus neoformans is a leading cause of mortality and morbidity in individuals infected with HIV. However, as with many fungal pathogens, our understanding of the molecular mechanisms that this yeast utilizes to cause disease remains limited. The recent completion of the C. neoformans genome sequencing project now enables the creation of powerful genomic tools and the implementation of large-scale, systematic genetic approaches in this organism, as has been seen in the non-pathogenic model yeast Saccharomyces cerevisiae. To this end, we optimized methods for gene deletion in C. neoformans and utilized the completed genome sequence to construct a large library (~1,200 strains) of targeted gene deletion mutants. We screened this resource in vivo for proliferation in mouse lung tissue and in vitro for three well-recognized virulence attributes - polysaccharide capsule formation, melanization, and growth at human body temperature. We identified dozens of previously uncharacterized genes that affect these known attributes as well as over 40 infectivity mutants without obvious in vitro defects. These mutants have provided numerous insights into the virulence mechanisms of C. neoformans. In particular, we uncovered a previously unknown, capsule-independent pathway for inhibition of phagocytosis that is regulated by a GATA family transcription factor. We identified two parallel β-helix proteins that are required for accurate capsule polysaccharide synthesis. Finally, we demonstrated a link between the homeostatic response to hypoxia and the ability to cause disease. These studies have been enhanced by the creation of whole-genome microarrays to study transcriptional changes. This work demonstrates the enormous potential for harnessing recent genome sequencing efforts to systematically identify and dissect fungal virulence mechanisms and establishes C. neoformans as a leading fungal pathogen model system.

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