The atypical antipsychotic aripiprazole alters the outcome of disseminated Candida albicans infections.
Parker ReitlerJessica ReganChristian DeJarnetteAshish SrivastavaJen CarnahanKatie M TuckerBernd MeibohmBrian M PetersGlen E PalmerPublished in: bioRxiv : the preprint server for biology (2024)
Invasive fungal infections (IFIs) impose an enormous clinical, social, and economic burden on humankind. For many IFIs, ≥ 30% of patients fail therapy with existing antifungal drugs, including the widely used azole class. We previously identified a collection of 13 approved medications that antagonize azole activity. While gain-of-function mutants resulting in antifungal resistance are often associated with reduced fitness and virulence, it is currently unknown how exposure to azole antagonistic drugs impact C. albicans physiology, fitness, or virulence. In this study, we examined how exposure to azole antagonists affected C. albicans phenotype and capacity to cause disease. We discovered that most of the azole antagonists had little impact on fungal growth, morphology, stress tolerance, or gene transcription. However, aripiprazole had a modest impact on C. albicans hyphal growth and increased cell wall chitin content. It also worsened the outcome of disseminated infections in mice at human equivalent concentrations. This effect was abrogated in immunosuppressed mice, indicating an additional impact of aripiprazole on host immunity. Collectively, these data provide proof-of-principle that unanticipated drug-fungus interactions have the potential to influence the incidence and outcomes of invasive fungal disease.
Keyphrases
- candida albicans
- biofilm formation
- cell wall
- end stage renal disease
- escherichia coli
- pseudomonas aeruginosa
- physical activity
- staphylococcus aureus
- newly diagnosed
- chronic kidney disease
- endothelial cells
- ejection fraction
- peritoneal dialysis
- gene expression
- risk factors
- mental health
- machine learning
- stem cells
- drug induced
- climate change
- prognostic factors
- emergency department
- artificial intelligence
- adverse drug
- mesenchymal stem cells
- big data
- antimicrobial resistance
- heat stress
- patient reported
- genome wide identification
- cell therapy