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- Title
- Development of a time-resolved fluorescence-based lateral flow immunoassay for rapid and sensitive diagnosis of Middle East respiratory syndrome
- Author(s)
- Mi Jeong Kim; H Y Kim; Minhye Kim; E Y Shin; Wooyoung Kim; H Kim; K B Ku; J H Lee; S I Kim; Edmond Changkyun Park
- Bibliographic Citation
- Scientific Reports, vol. 15, pp. 27036-27036
- Publication Year
- 2025
- Abstract
- Middle East respiratory syndrome (MERS) is a viral respiratory infection caused by the MERScoronavirus (MERS-CoV). Due to its high mortality and lack of a vaccine or treatment, MERS has remained on the WHO’s priority list of diseases with the highest public health risk since 2012. Although rapid diagnosis is essential for interrupting transmission, initiating timely treatment, and maintaining public health systems, no rapid diagnostic method currently exists for MERS. In this study, a sensitive and specific lateral flow immunoassay (LFIA)-based rapid antigen diagnostic test for MERS was developed using time-resolved fluorescence (TRF) technology. Monoclonal antibodies specific for the MERS-CoV N protein were generated, and optimal pairs were selected through affinity measurement. A TRF-LFIA using Europium nanoparticles was then constructed based on these pairs. The TRF-LFIA showed a detection limit of 0.1 ng/ml MERS-CoV N protein and 5 × 104 copies/ml of MERS-CoV, demonstrating a 25-fold sensitivity increase relative to the cellulose nanobeads (CNB)LFIA. Furthermore, it displayed high specificity without cross-reactivity to the N proteins of SARS-CoV, SARS-CoV-2, or influenza virus. Consequently, these findings indicate that the TRF-LFIA platform is a promising approach for rapid diagnosis of MERS-CoV infection, with potential for broader application through enhanced sensitivity.
- Keyword
- MERSNucleocapsid proteinRapid diagnostic testTime-resolved fluorescenceEuropium
- ISSN
- 2045-2322
- Publisher
- Springer-Nature Pub Group
- Full Text Link
- http://dx.doi.org/10.1038/s41598-025-09832-z
- Type
- Article
- Appears in Collections:
- Division of A.I. & Biomedical Research > Immunotherapy Research Center > 1. Journal Articles
- Files in This Item:
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