Histoplasma capsulatum is a primary pathogen that infects approximately 500,000 individuals per year in the U.S., and is a significant source of morbidity and mortality. The goal of this proposal is to revolutionize our understanding of endemic fungal disease by using proteomics and disease models to identify and analyze host pathways that are targeted by Histoplasma virulence factors.
The long-term goal of our research is to elucidate the mechanism of action of key fungal molecules that mediate pathogenesis. In recent years, proteomics technologies and analyses have advanced to the point where comprehensive, genome-wide studies of host-pathogen interactions can be performed. We propose to apply these technologies to identify mammalian host proteins that interact with secreted fungal proteins from the intracellular fungal pathogen Histoplasma capsulatum. This work is a collaboration between a fungal biologist experienced in Histoplasma molecular biology and genetics (Anita Sil, UCSF) and a premiere expert in using proteomics to identify host-pathogen interactions (Nevan Krogan, UCSF). After inhalation into mammalian hosts, Histoplasma senses the temperature of the host and undergoes a morphologic transition to yield yeast-form cells. Yeast cells colonize macrophages and must evade anti-microbial defenses to replicate to high levels within these immune cells. Based on precedent from viral and bacterial pathogens, we hypothesize that secreted factors from Histoplasma yeast cells are likely to interact with intracellular host proteins to manipulate the outcome of infection. We have used experimental data and bioinformatics analyses to identify secreted fungal proteins with preferential expression in the yeast form of Histoplasma. We will use a robust proteomics pipeline developed by the Krogan laboratory to define the network of host proteins that interact with these putative fungal virulence factors. We will then exploit host and pathogen genetics to define the role of these host-pathogen protein-protein interactions during infection. Analysis of the resultant dataset will generate specific hypotheses about mechanisms of pathogenesis that will fuel current and future advances in our understanding of how fungi manipulate host cells. Ultimately, these studies will lead to the development of anti-fungal therapeutics that will target key molecules in ubiquitous fungal pathogen.