I’m interested in how bacteria adapt to complex environments, and I study this through a combination of high-throughput fitness assays, genome-wide methylation analysis, and comparative genomics.
In long-term evolution experiments with Escherichia coli, I discovered dynamic adenine methylation patterns associated with adaptation to nutrient depletion. These findings suggest that epigenetic variability may play a role in bacterial survival strategies.
My collaborative work has revealed how semi-stable subpopulations emerge within evolving E. coli communities, with distinct metabolic and genetic signatures. This research integrates fitness data with genomic sequencing to model eco-evolutionary dynamics.
As a research assistant at Georgetown, I investigated how branched-chain fatty acids influence virulence gene regulation. Using molecular tools like GFP reporters and mass spectrometry, we showed that lipid signals modulate the Sae two-component system.
During my undergraduate research, I benchmarked popular tools for microbial community profiling — including mothur, QIIME, and DADA2 — using soil microbiome data. This early experience introduced me to large-scale data analysis and the challenges of reproducibility in bioinformatics.