Author(s): Thomas Armond, Thomas Coleman
Mentor(s): Brett E. Pickett
Institution BYU
Escherichia coli (E. coli) is a Gram-negative bacterial species that is an important component of the human gut microbiome. It presents a significant challenge in the realm of antibiotic resistance, particularly concerning foodborne illnesses. While many strains of E. coli are relatively harmless, strains that are pathogenic and/or antibiotic-resistant pose a serious threat to human health, leading to severe infections that are difficult and expensive to treat. Research focused on understanding antibiotic resistance in E. coli and developing strategies to combat it is crucial in addressing this issue. Phage therapy is a growing practice of treating antibiotic resistant bacteria with bacteriophages–small viruses that infect bacteria. To date, there are hundreds of sequenced bacteriophages that infect E. coli, with additional genome sequences regularly being generated by the scientific community. The aim of this study was to better characterize and understand the genetic variation and diversity of these phage genomes by applying robust statistical and computational methods to selected gene products of bacteriophages that infect E. coli. Here, we examined the major capsid proteins of 240 bacteriophages that infect E. coli. The major capsid protein, among others, represents evolutionarily-conserved functions that are encoded by their genomes. These amino acid sequences were obtained from GenBank, and aligned with the MAFFT program. We then reconstructed a phylogenetic tree for 123 sequences of the major capsid proteins from these bacteriophages using the maximum likelihood-based RAxML program. We then examined the sequences for evidence of selection pressure by calculating the ratio of synonymous-to-nonsynonymous mutations at each codon. This was accomplished with the mixed effects model of evolution (MEME) algorithm in the HyPhy software, which potentially provides insight into the variability of the phage major capsid protein and how that affects host range. We anticipate that the results of this study can be used to improve the characterization of bacteriophages that infect E. coli, and to assist future studies in the search for new methods to treat bacterial outbreaks that may be resistant to conventional treatments.