Presentation Type

Poster

Faculty Mentor’s Full Name

Travis Wheeler

Faculty Mentor’s Department

Department of Computer Science

Abstract

Pseudomonas aeruginosa is an opportunistic bacterium that can cause serious infections in individuals with compromised immune systems or conditions such as cystic fibrosis. Pseudomonas infections are known to become worse after the bacterial population in a patient has been infected by a group of prophages, a type of virus that insert its genetic sequence into its host’s genome. To help researchers investigate and understand why these viral sequences have this effect on Pseudomonas, we have developed a software pipeline that identifies and analyzes viral insertions into bacterial genomes. This pipeline searches Pseudomonas genomes against the sequences of 50 phages known to target the bacterium, recording the length of a match, its location in its host’s genome, and which strand it occurs on. In addition to gathering summary statistics, our software generates plots showing which portions of each virus are most often found inserted into Pseudomonas genomes; in these graphs, each viral genome is labeled with known protein families and domains. These gathered data will support understanding of prophage insertion patterns and correlation with virulence, possibly aiding in developing treatment regimes.

Category

Life Sciences

Share

COinS
 
Apr 17th, 3:00 PM Apr 17th, 4:00 PM

A Software Pipeline for Analyzing Viral Sequences in Bacterial Genomes

UC South Ballroom

Pseudomonas aeruginosa is an opportunistic bacterium that can cause serious infections in individuals with compromised immune systems or conditions such as cystic fibrosis. Pseudomonas infections are known to become worse after the bacterial population in a patient has been infected by a group of prophages, a type of virus that insert its genetic sequence into its host’s genome. To help researchers investigate and understand why these viral sequences have this effect on Pseudomonas, we have developed a software pipeline that identifies and analyzes viral insertions into bacterial genomes. This pipeline searches Pseudomonas genomes against the sequences of 50 phages known to target the bacterium, recording the length of a match, its location in its host’s genome, and which strand it occurs on. In addition to gathering summary statistics, our software generates plots showing which portions of each virus are most often found inserted into Pseudomonas genomes; in these graphs, each viral genome is labeled with known protein families and domains. These gathered data will support understanding of prophage insertion patterns and correlation with virulence, possibly aiding in developing treatment regimes.