S5.3a Unraveling the genetic determinants of virulence in Cryptococcus neoformans

Abstract

S5.3 Cellular pleomorphism and fungal virulence, September 22, 2022, 3:00 PM - 4:30 PM Cryptococcus neoformans is a human pathogenic basidiomycete yeast that can cause cryptococcal meningitis (CM), predominantly in immunocompromised individuals. The patient outcome depends on both host and pathogen-specific factors, including C. neoformans genetics. A groundbreaking 2012 study was the first to show that patient outcome is associated with genetic differences between C. neoformans isolates. Subsequent population-wide sequencing studies have revealed over 100 sequence types (ST) of C. neoformans that are associated with both geographic location and clinical outcome. All these studies have been broad, examining the severity of disease cryptococcal phenotypes in a collection of highly diverse strains. We chose a narrow focus and collected various genotypic and phenotypic data from a single ST: ST93. ST93 is a common sequence type isolated from patients globally and is the most common clinical isolate found in the sub-Saharan African country of Uganda. Previously, we performed whole genome sequencing on 38 ST93 Ugandan clinical isolates. We identified 652 unique SNPs in this ST93 population compared to the H99 reference genome. We also showed that ST93 contained two subpopulations: ST9A and ST93B. In the current study, we further characterized the genotypic, phenotypic, and virulence differences between these 38 clinical isolates. Using Illumina sequence data, we identified a pattern of linkage disequilibrium that suggested that ST93A and ST93B are evolving separately. We performed long-read sequencing on each isolate to investigate chromosomal changes and large structural variations, allowing us to identify a chromosomal translocation event wherein parts of chromosome 11 had recombined with chromosome 3. Additionally, we characterized several in vitro phenotypes for each isolate and identified three distinct phenotypic clusters based on cell wall challenge and growth experiments. Next, we infected mice with 35 isolates and observed eight different disease manifestations, including isolates that caused non-CNS infections. Overall, by working within a single sequence type, we can gain a deeper understanding of how some small genetic changes can impact strain-specific phenotypes while others have no discernable effect. Eventually, these data can be used to provide valuable information about how each clinical isolate impacts patient outcomes.