Sensitive and Specific Monoclonal Antibody-Based Capture Enzyme Immunoassay for Detection of Nucleocapsid Antigen in Sera from Patients with Severe Acute Respiratory Syndrome
Open Access
- 1 June 2004
- journal article
- Published by American Society for Microbiology in Journal of Clinical Microbiology
- Vol. 42 (6) , 2629-2635
- https://doi.org/10.1128/jcm.42.6.2629-2635.2004
Abstract
A rapid antigen test for the diagnosis of severe acute respiratory syndrome (SARS) is essential for control of this disease at the point of management. The nucleocapsid (N) protein of SARS-associated coronavirus (SARS-CoV) is abundantly expressed in infected-cell culture filtrate as demonstrable by Western blotting using convalescent-phase sera from patients with SARS. We used monoclonal antibodies specifically directed against N protein to establish a sensitive antigen capture sandwich enzyme-linked immunosorbent assay (ELISA) for the detection of SARS-CoV. The assay employed a mixture of three monoclonal antibodies for capture and rabbit polyclonal antibodies for detection of serum antigen in 32 cases of clinically probable SARS as defined by the World Health Organization during the epidemic in Guangzhou, China. Recombinant N protein was used as a standard to establish a detection sensitivity of approximated 50 pg/ml. The linear range of detection in clinical specimens was from 100 pg/ml to 3.2 ng/ml. Using a panel of sera collected at different points in time, the amount of circulating N antigen was found to peak 6 to 10 days after the onset of symptoms. The sensitivity of the assay was 84.6% in 13 serologically confirmed SARS patients with blood taken during the first 10 days after the onset of symptoms (11 of 13). The specificity of the assay was 98.5% in 1,272 healthy individuals (1,253 of 1,272). There was no cross-reaction with other human and animal coronaviruses in this assay. In conclusion, a sensitive and quantitative antigen capture ELISA was established for the early diagnosis and disease monitoring of SARS-CoV infection.Keywords
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