Uncovering the mysteries of antibiotic resistance through phylogenetic analysis
By: Florentine van Nouhuijs, MaryGracy Antony, and Faye Orcales
Department: Cellular & Molecular Biology
Faculty Advisor: Dr. Pleuni Pennings
My project explores the phytools package in R to analyze/estimate the rate of antibiotic resistance evolution in phylogenetic trees. Highly Drug-Resistant Bacteria or Superbugs are a result of Antibiotic Resistance, in which individuals affected with a resistant infection cannot heal by taking antibiotics. The mechanism in which a patient acquires a resistant infection is complicated and not well understood. Antibiotic resistance infections can either be transpired through transmission or via within-host evolution. Transmitted resistance occurs when a patient contracts an already resistant strain. De novo evolution occurs when a patient contracts a susceptible strain which through mutation or horizontal gene transfer evolves to become drug resistant. Knowing the role of transmission and within-host evolution is important to design effective prevention programs. We propose to use phylogenetic trees of bacterial genomes to understand the roles of transmission and within-host evolution of resistance. We are using a publicly available dataset (Kallonen et al., 2017) of E. coli genomes and resistance phenotypes, along with the phytools package in R (Revell, 2012). Phytools is commonly utilized to analyze phylogenetic trees, but hasn’t been used much to understand drug resistance. By using the phytools package, the constructed phylogenetic trees and clade sizes will be compared with one another for resistant phenotypes, determined for different drugs. Preliminary findings show that resistance to the antibiotic Gentamicin, was observed in isolated places on the phylogenetic tree, which suggests that it is not easily transmitted, possibly because it is costly. On the other hand, Amoxicillin resistance was observed in larger clades, which suggests transmission playing a bigger role. Future plans after accomplishing this preliminary step is to eventually estimate rates of within-host evolution and transmission of resistance for different drugs and pathogens.