Honors Theses

Date of Award

Spring 5-14-2023

Document Type

Undergraduate Thesis



First Advisor

Wayne Gray

Second Advisor

Ryan Fortenberry

Third Advisor

Patrick Curtis

Relational Format



The coronavirus disease (COVID-19) has created one of the most world-halting events in recent world history. Its effects have reached every corner of the globe and manifested problems within each country’s healthcare and social systems. During the pandemic, many researchers have searched to develop a more robust understanding of the novel virus’s genetic and structural material. In year three since the emergence of COVID-19, these researchers hope to implement new advancements in testing and detection for the presence of the virus.

This thesis intends to produce evidence for the reliability of COVID-19 antibody tests using immunoblot assay detection. These tests are not widely used, yet they provide a more accurate result reading than the currently used method of enzyme-linked immunosorbent assay (ELISA). For the purpose of this experiment, two different structural proteins for the SARS-CoV-2 virus were identified through immunoblot analysis and were assessed on the varying strengths when antibody testing was administered. The COVID-19 spike (S) glycoprotein and the nucleocapsid (N) protein were expressed inside an E. Coli plasmid with a histidine tag and underwent column purification. A chemiluminescent western blot analysis was performed in order to detect the presence of the S and N proteins inside the positive patient sera and the absence of the same proteins within the negative patient sera. The images produced from the experiment showcase the strengths of each viral protein and provides strong evidence for the use of nucleocapsid proteins for antibody detection. This study definitively illustrates the effectiveness of immunoblot testing for antibody detection and strengthens the application of western blotting analysis in future COVID-19 research.

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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.



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