Evolution of antimicrobial resistance (AMR) in the Mycobacterium tuberculosis complex
Predicted AMR profiles of M. bovis whole genome sequences
Estimated prevalence of AMR M. bovis in human, cattle and wildlife hosts
Estimated fitness effects of AMR mutations in samples from hosts with distinct selection pressures: humans treated with tuberculosis specific drugs, cattle treated with non-tuberculosis specific drugs and wildlife that have never been treated with antimicrobials.
Conducted genome-wide epistasis analyses to identify mutations linked to resistance-causing protein-altering mutations, which may restore protein structure.
Used forward genetic simulation to show that epistatic compensatory mutations and clonal progeny skew can increase the probability of resistance evolution in the absence of the selection pressure caused by antimicrobial use.
M. bovis within host evolutionary dynamics
Evaluated the empirical distribution of M. bovis mutations evolved within hosts during infection for signals of adaptation
Used forward genetic simulation to find that the combined diversity reducing forces of population bottlenecks and clonal progeny skew and a rapid mutation rate could describe the empirical distribution of de novo evolved mutations during infection
M. bovis pangenomics
de novo assembled and annotated 3000+ M. bovis genomes
Identified gene annotation errors associated with short read sequencing inflates accessory genome count and erroneously led others to claim M. bovis has an open pangenome
Found indel variation could be useful in outbreak investigation when outbreak sequences have similar SNP patterns
link to publication
Time series analysis of disease progression
Developed a continuous time hidden Markov model to describe Johne’s disease progression in cattle.
Implemented a modified Baum-Welch expectation maximization algorithm and Newton-Raphson estimation for parameter estimation
Found two distinct progression patterns among infected animals, with a minority of infected animals that do not progress to clinical Johne’s disease
link to publication
Shark Conservation Genomics, Stanhope Lab
Analyzed historical population dynamics of the great hammerhead and shortfin mako using the first complete genomes of the species
Detected genetic signatures of inbreeding and found high levels of homozygosity in the great hammerhead
Studying the molecular evolution of electroreception in elasmobranchs by analyzing signatures of convergent evolution in ion channels
Studying the recent demographic history of the great hammerhead using low coverage sequence data from geographically distinct populations
link to publication
FDA Vet-LIRN – Cornell Microbial Genomics
Characterized pangenomic diversity and gene flow of E. coli samples from dog and human hosts
Used association mining to describe regional antibiogram patterns of E. coli samples from dog hosts
Conducted microbial pangenome wide association analysis of genes associated with antimicrobial resistance in E. coli samples from dog hosts
Additional projects
Dated the introductions and characterize geospatial spread of M. bovis into the Dominican Republic as part of a collaborative project with the USDA National Veterinary Services Laboratories
Analyzed the diagnostic performance of a new canine brucellosis test developed by the Wagner Lab at the Animal Health Diagnostic Center in the absence of a gold standard
Convergent evolution analysis of Feline Infections Peritonitis Virus link to publication
Conducted temporal dating and host dynamics analysis of a canine coronavirus with recent zoonotic spillover link to publication
Aided in pangenomic analysis of Mycobacterium avium ssp. paratuberculosis link to publication