1. Performance of Recombinant Nucleocapsid Protein-Based Constructs for Serological Diagnosis of SARS-CoV-2 Infection
- Author
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Natasha Rodrigues de Oliveira, Francisco Denis Souza Santos, Amilton Clair Pinto Seixas Neto, Liana Nunes Barbosa, Miguel Andrade Bilhalva, Ana Vitória Costa, Rafael Amaral Donassolo, Rafael Rodrigues Rodrigues, Mariliana Luiza Ferreira Alves, Marcos Roberto Alves Ferreira, Clóvis Moreira Júnior, Marcus Vinícius Guimarães de Lacerda, Gisely Cardoso de Melo, Odir Antônio Dellagostin, Alan John Alexander McBride, Luciano da Silva Pinto, Ângela Nunes Moreira, and Fabrício Rochedo Conceição
- Subjects
COVID-19 ,serodiagnosis ,Nucleocapsid protein ,ELISA ,recombinant protein ,Biotechnology ,TP248.13-248.65 - Abstract
Abstract Since the inception of COVID-19 pandemic, there has been a challenging race for the development of precise diagnostic tests. Specific SARS-CoV-2 serological assays are the main tools used to estimate the rate of past infections or herd immunity in epidemiological studies, in addition to being helpful in guiding public health management policies. In this study, an in-house ELISA based on the construct of SARS-CoV-2 nucleocapsid (N) proteins, named rCoV2, rCoV4, and rCoV7, showed diagnostic performance for the detection of IgG antibodies. Sensitivity was evaluated in serum samples from patients with mild to moderate or severe COVID-19 infections, which were collected at different time points, while specificity was evaluated using pre-pandemic sera. In samples from mild to moderate cases obtained ≥16 days after the onset of symptoms, the sensitivities for rCoV2, rCoV4, and rCoV7 were 66.7%, 75%, and 77.8%, respectively. For samples from severe cases, the sensitivity was above 80% for all constructs. All proteins showed high specificity (94-98%). Overall, rCoV7 (C-terminus N-protein portion) showed better diagnostic performance, with 62.3% sensitivity in moderate and severe cases and 96.6% specificity. The SARS-CoV-2 ELISA using N-protein-based constructs could be a promisor tool for investigate the epidemiology of COVID-19 and monitor population-level serosurveillance.
- Published
- 2024
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