Department of Pediatrics and Epidemiology
Support
This summer I had the opportunity to work independently on a project within the Katharine Walter lab uncovering the genomic nature of Coccidioides, a fungal pathogen that causes Valley fever upon inhaling its spores. Residing in dry arid soils within southwestern America and part of Africa, the endemic region of the fungus is expected to expand with climate change, and effect greater populations of the immunocompromised and manual labor force. While bacteria’s host diversity’s effect on antibiotic resistance has been well studied, fungal diversity and antifungal resistance has been largely overlooked. This project pioneered the use of sequencing data from Coccidioides-positive isolates to investigate patient infections of Valley fever. Single Nucleotide Polymorphisms (SNPs) were identified from the sequences and used in determining sample homology to quantify the pathogen diversity within infections. This information is crucial in the rising concern for antifungal resistance and understanding the development of the Coccidioides species C. immitis and C. posadasii.
My project involved quantifying and analyzing SNP differences between isolates, which greatly strengthened my R studio coding experience. I generated various histograms to understand the distribution of pairwise SNP differences between within-host and across-host isolate comparisons, and built phylogenetic trees to visualize isolate homology. Fitting regression models to scatterplots gave my team valuable insights and provided me the opportunity to apply skills from academic coursework. I worked alongside my PI Katharine Walter throughout the summer, investigating this dataset by building upon findings and asking new questions as I generated results. My work this summer advances our understanding of pathogenic fungal evolution, gives momentum to the overlooked issue of antifungal resistance, and fuels my growing passion for the field of biostatistics.