Gene Expression of Diverse Cryptococcus Isolates during Infection of the Human Central Nervous System

ABSTRACT Cryptococcus neoformans is a major human central nervous system (CNS) fungal pathogen causing considerable morbidity and mortality. In this study, we provide the widest view to date of the yeast transcriptome directly from the human subarachnoid space and within cerebrospinal fluid (CSF). We captured yeast transcriptomes from C. neoformans of various genotypes in 31 patients with cryptococcal meningoencephalitis as well as several Cryptococcus gattii infections. Using transcriptome sequencing (RNA-seq) analyses, we compared the in vivo yeast transcriptomes to those from other environmental conditions, including in vitro growth on nutritious media or artificial CSF as well as samples collected from rabbit CSF at two time points. We ranked gene expressions and identified genetic patterns and networks across these diverse isolates that reveal an emphasis on carbon metabolism, fatty acid synthesis, transport, cell wall structure, and stress-related gene functions during growth in CSF. The most highly expressed yeast genes in human CSF included those known to be associated with survival or virulence and highlighted several genes encoding hypothetical proteins. From that group, a gene encoding the CMP1 putative glycoprotein (CNAG_06000) was selected for functional studies. This gene was found to impact the virulence of Cryptococcus in both mice and the CNS rabbit model, in agreement with a recent study also showing a role in virulence. This transcriptional analysis strategy provides a view of regulated yeast genes across genetic backgrounds important for human CNS infection and a relevant resource for the study of cryptococcal genes, pathways, and networks linked to human disease. IMPORTANCE Cryptococcus is the most common fungus causing high-morbidity and -mortality human meningitis. This encapsulated yeast has a unique propensity to travel to the central nervous system to produce disease. In this study, we captured transcriptomes of yeasts directly out of the human cerebrospinal fluid, the most concerning site of infection. By comparing the RNA transcript levels with other conditions, we gained insights into how the basic machinery involved in metabolism and environmental responses enable this fungus to cause disease at this body site. This approach was applied to clinical isolates with diverse genotypes to begin to establish a genotype-agnostic understanding of how the yeast responds to stress. Based on these results, future studies can focus on how these genes and their pathways and networks can be targeted with new therapeutics and possibly classify yeasts with bad infection outcomes.