Identification of Pathogen Genomic Differences That Impact Human Immune Response and Disease during Cryptococcus neoformans Infection.

Patient outcomes during infection are due to a complex interplay between the quality of medical care, host immunity factors, and the infecting pathogen's characteristics. To probe the influence of pathogen genotype on human survival, immune response, and other parameters of disease, we examined isolates collected during the Cryptococcal Optimal Antiretroviral Therapy (ART) Timing (COAT) Trial in Uganda. We measured human participants' survival, meningitis disease parameters, immunologic phenotypes, and pathogen growth characteristics. We compared those clinical data to whole-genome sequences from 38  isolates of the most frequently observed sequence type (ST), ST93, in our Ugandan participant population and to sequences from an additional 18 strains of 9 other sequence types representing the known genetic diversity within the Ugandan clinical isolates. We focused our analyses on 652 polymorphisms that were variable among the ST93 genomes, were not in centromeres or extreme telomeres, and were predicted to have a fitness effect. Logistic regression and principal component analysis identified 40 candidate genes and 3 hypothetical RNAs associated with human survival, immunologic response, or clinical parameters. We infected mice with 17 available KN99α gene deletion strains for these candidate genes and found that 35% (6/17) directly influenced murine survival. Four of the six gene deletions that impacted murine survival were novel. Such bedside-to-bench translational research identifies important candidate genes for future studies on virulence-associated traits in human infections. Even with the best available care, mortality rates in cryptococcal meningitis range from 20% to 60%. Disease is often due to infection by the fungus and involves a complex interaction between the human host and the fungal pathogen. Although previous studies have suggested genetic differences in the pathogen impact human disease, it has proven quite difficult to identify the specific genes that impact the outcome of the human infection. Here, we take advantage of a Ugandan patient cohort infected with closely related strains to examine the role of pathogen genetic variants on several human disease characteristics. Using a pathogen whole-genome sequencing approach, we showed that 40  genes are associated with human disease. Surprisingly, many of these genes are specific to and have unknown functions. We also show deletion of some of these genes alters disease in a mouse model of infection, confirming their role in disease. These findings are particularly important because they are the first to identify genes associated with human cryptococcal meningitis and lay the foundation for future studies that may lead to new treatment strategies aimed at reducing patient mortality.