Date of Award
January 2023
Document Type
Open Access Thesis
Degree Name
Master of Public Health (MPH)
Department
School of Public Health
First Advisor
Elsio Wunder
Abstract
Leptospirosis is an infectious zoonotic disease responsible for about 1 million cases annually. Issues in early diagnosis is a major contributor towards poor health outcomes. Current tests for diagnosis, such as whole-cell ELISA-based diagnostics or the microscopic agglutination test (MAT), importantly lack sensitivity during acute-phase disease. Therefore, creating an ELISA-based diagnostic, which is generally cheaper and easier to perform than the MAT, using highly-conserved targets, that has high sensitivity towards acute-phase disease, would be desirable. This study first attempted to optimize protocols for diagnosis, and next applied the optimized protocol against epitopes derived from hamsters vaccinated with a multi-recombinant protein construct. Cutoffs were created by testing against 50 negative sera samples and then adjusted. These cutoffs would then be used when testing against acute- and convalescent-sera, which would determine individual sensitivities. Vaccine-derived epitopes were also paired with specific recombinant proteins using rabbit polyclonal sera against individual proteins. Two vaccine epitopes were identified as strong candidates, both of which also demonstrated comparable or stronger sensitivity during acute-phase disease compared to the MAT, though both also lacked specificity and convalescent phase sensitivity. No epitopes were able to be definitively paired with vaccine recombinant proteins. Overall, this study provided insights regarding the potential for an epitope-based diagnostic assay for leptospirosis, paving the way to further studies that can offer a highly specific and sensitive ELISA-based diagnostic.
Recommended Citation
Zhao, Kevin Yuhang, "Optimization Of An Elisa-Based Leptospirosis Diagnostic" (2023). Public Health Theses. 2367.
https://elischolar.library.yale.edu/ysphtdl/2367
This Article is Open Access
Comments
This is an Open Access Thesis.