Pathogenicity of ethanol tolerant strains of Candida albicans in the oral cavity

Tufts University Boston, Boston MA

Investigators

Abstract

Summary The fungus Candida albicans is an opportunistic pathogen and a common colonizer of the human oral cavity. In healthy individuals, the organism exists in homeostasis with its host as a component of the microbiota. If the host becomes compromised, C. albicans can cause oropharyngeal candidiasis (OPC) and promote the development other types of oral disease such as oral cancer. Patients with a variety of oral diseases are known to harbor C. albicans strains with higher production of secreted degradative enzymes, such as phospholipases and proteases. These enzymes are known virulence factors of C. albicans. Thus, C. albicans strains found in the oral cavity of patients may exhibit elevated virulence. Alcohol use is another factor that favors the development of oral cancer. Alcohol consumption has many effects on the host and could also affect the microbiota of the oral cavity since organisms would be transiently exposed to alcohol. When C. albicans strains with elevated alcohol tolerance were selected by evolution during laboratory culture, the strains were found to upregulate the expression of genes encoding phospholipases, lipases and proteases. These observations suggest the model that strains with elevated expression of degradative enzymes have altered interaction with the host due to high expression of virulence factors. The proposed research will investigate the interaction of alcohol tolerant C. albicans strains with the oral epithelium. The experiments described in Specific Aim 1 will utilize cultured human oral epithelial cells to determine whether alcohol tolerant strains show increased pathogenicity when cocultured with human cells, with or without alcohol. The experiments described in Specific Aim 2 will utilize the cortisone acetate immunosuppressed mouse model of OPC to measure the ability of alcohol tolerant strains to produce damage and disease in an animal model.