I am interested in understanding our relationship with microorganisms on Earth and in human spaceflight.
Microorganisms (microbes) have fascinating relationships with their environments, be they natural or man-made. These environments include our bodies, our homes and office buildings, our soil, oceans, air, and orbiting laboratories like the International Space Station.
One way to query these microbial communities is through shotgun metagenomic sequencing of the DNA found in samples taken from the environment. These data yield millions of DNA fragments per sample that can tell us which types of microbes are present and what they may be doing.
By additionally measuring variables of interest, such as inflammation, drug resistance, carbon uptake, acidity, we can begin to model the effects of manipulating these microbiomes.
I am also interested in methods for predicting antimicrobial resistance from metagenomic sequencing data, and quantifying the pressures for microbes to maintain resistance.
I studied statistical methods for measuring coevolution at the residue level, given a pair of protein sequence alignments.
Proteins often work together. Yet, amino acid residues (the building blocks of proteins) may naturally vary or come under pressure to change. This could, simply put, “breaks things” for an organism, depending on whether corresponding changes occur at other residues and how important these residues are. We can look across species for a record of these changes. Changes that appear more correlated than expected can suggest the location of an evolutionarily important protein interface—for example, in a bacterial signaling complex, or a potential drug target in a host-virus arms race.
We wrote a paper about how well these types of methods predict interprotein structural contacts.