Abstract
Neisseria gonorrhoeae, the bacterium which causes gonorrhea, is a public health threat as recognized by the CDC due to the risk of untreatable gonorrhea due to the high prevalence of resistance to antibiotics in the gonococcal population [1]. Current screening methods for resistance to antibiotics for clinical infections may take up to 2 days to produce results, which could result in delays in treatment, unnecessary follow-up appointments, inappropriate antibiotic prescriptions, and overall poor treatment outcomes [2]. In this study, we utilize RNA sequencing (RNA-seq) to characterize the expression patterns of resistant and susceptible strains of N. gonorrhoeae. Here, we look for transcripts that change their expression in susceptible strains in response to antibiotic treatment, as potentially diagnostic transcripts, with the overall goal of identifying transcripts that can be utilized to screen for resistance at the point of care. Furthermore, we conduct functional KEGG analysis to classify the functional classes of differentially expressed transcripts. Ultimately, a point of care (POC) diagnostic for gonococcal infections will allow for improved health outcomes and reduced misuse of antibiotics, which will help slow the epidemic of treatment resistant infections.
Publication Date
2024
Document Type
Thesis
Student Type
Graduate
Degree Name
Bioinformatics (MS)
Department, Program, or Center
Thomas H. Gosnell School of Life Sciences
College
College of Science
Advisor
Crista Wadsworth
Advisor/Committee Member
Gary R. Skuse
Advisor/Committee Member
Michael V. Osier
Recommended Citation
Bailey, Kinzie, "Differential Expression Analysis of Treatment Resistant and Treatment Susceptible Neisseria gonorrhoeae Paired with Gene Set Enrichment Analysis" (2024). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/11988
Campus
RIT – Main Campus