Fungal diseases are an increasing problem worldwide. Current anti-fungal drugs are limited by their spectrum of activity or toxicity, and resistance is an emerging issue. Cryptococcus gattii, a basidiomycete yeast is an emerging agent of cryptococcosis in healthy individuals. Current treatment of cryptococcosis involves induction with amphotericin B (AMB) plus 5-flucytosine, with maintenance using fluconazole (FLC). However some C. gattii strains have been found to be inherently FLC resistant. Chong et al (2010) found very high inherent resistance by C. gattii strain 97/170, with intermediate resistance found in additional strains. We have begun to explore novel synergistic methods to improve the efficacy of FLC and reduce resistance using Iron (Fe) chelators. Our group is using fungal gene expression networks during a synergistic antifungal response to understand the synergistic process.

We have sequenced C. gattii strain 97/170 using Illumina next generation sequencing. Four additional C. gattii strains of varying resistance levels were also sequenced, (average genome size ~ 17.5 Mb), to allow a comprehensive analysis of the influence of species, strain and inherent antifungal resistance on potential synergy with Fe chelators. We used both de novo and comparative genome annotation methods with the gene prediction tool Augustus to define an average of 7300 gene models across the C. gattii genomes. The quality of gene prediction for strain 97/170 was validated using RNA-Seq data generated for this strain. Comparative genomics analysis was carried out using genome based alignment tools Mauve and mummer, and protein ortholog clustering tool orthoMCL. The highly collinear genomes contained low levels of repetitive DNA. Proteins specific to individual strains, and those with varying conservation patterns across the strains were highlighted.

These high-resolution draft genomes will be used as references in the RNA-seq-based differential expression analysis, leading into the development of co-expression networks for genes influenced by drug-chelator synergy.