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Selection and Binding Validation of Aptamers against Nucleocapsid Protein of SARS-COV-2 Using Capillary Electrophoresis

The Coronavirus disease 2019 (COVID-19) pandemic has highlighted the critical need for accurate and sensitive diagnostic tools for detecting the SARS-CoV-2 virus. The nucleocapsid (N) protein is essential for virus replication and plays vital roles in virus assembly, packaging, and RNA transcription. This protein is a crucial component of the viral particle and is less prone to mutations than the other essential proteins in SARS-COV-2. All of these make the N protein a reliable target for virus detection. Aptamers, single-stranded oligonucleotides that can specifically bind to target molecules, have been proposed as a promising alternative to antibodies for detecting and treating viral infections. This study aimed to select DNA aptamers against the N protein of SARS-CoV-2 using capillary electrophoresis (CE) and validate the binding specificity of the aptamers.

After selecting seven clones, a preliminary binding validation was performed, and the two best binding clones were identified as ECK4 and ECK6. The structures of the aptamers were then modified by removing the primer regions from the original sequence, and the binding capacity of the truncated aptamers was confirmed. Dissociation constant (KD) values were calculated to provide further supportive information for the quality of the two clones. Additionally, Biolayer interferometry (BLI) was used to calculate Apparent KD as an alternative technique and provided consistent results with CE.

Our results demonstrate the successful selection of aptamers for the N protein of SARS-CoV-2 using CE-SELEX. Confirming the aptamers' binding capacity to N protein paves the way for developing aptamer-based diagnostics for COVID-19.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/45485
Date28 September 2023
CreatorsGu, Yuxuan
ContributorsBerezovski, Maxim
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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