Background: The development of easy-to-perform diagnostic methods is highly important for detecting current coronavirus disease (COVID-19). This pilot study aimed at developing a lateral flow assay (LFA)-based test prototype to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in saliva samples. Methods: Mice were immunized using the recombinant receptor-binding domain (rRBD) of SARS-CoV-2 virus spike protein. The combinations of the obtained mouse anti-receptor-binding domain (RBD) polyclonal antibodies (PAbs) and several commercial antibodies directed against the SARS-CoV-2 spike protein were used for enzyme-linked immunosorbent assay (ELISA) to select antibody pairs for LFA. The antibody pairs were tested in a LFA format using saliva samples from individuals with early SARS-CoV-2 infection (n = 9). The diagnostic performance of the developed LFA was evaluated using saliva samples from hospitalized COVID-19 patients (n = 111); the median time from the onset of symptoms to sample collection was 10 days (0–24 days, interquartile range (IQR): 7–13). The reverse transcription-polymerase chain reaction (rRT-PCR) was used as a reference method. Results: Based on ELISA and preliminary LFA results, a combination of mouse anti-RBD PAbs (capture antibody) and rabbit anti-spike PAbs (detection antibody) was chosen for clinical analysis of sample. When compared with rRT-PCR results, LFA exhibited 26.5% sensitivity, 58.1% specificity, 50.0% positive prediction value (PPV), 33.3% negative prediction value (NPV), and 38.7% diagnostic accuracy. However, there was a reasonable improvement in assay specificity (85.7%) and PPV (91.7%) when samples were stratified based on the sampling time. Conclusion: The developed LFA assay demonstrated a potential of SARS-CoV-2 detection in saliva samples. Further technical assay improvements should be made to enhance diagnostic performance followed by a validation study in a larger cohort of both asymptomatic and symptomatic patients in the early stage of infection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.