PropertyValue
?:abstract
  • Serological test is a valuable diagnostic tool for coronavirus disease 2019 (COVID-19). However, considerable improvements to these tests are needed, especially in the detection sensitivity. In this study, six recombinant nucleocapsid and spike proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were prepared and evaluated, including three prokaryotic expression nucleocapsid proteins (rN, rN1, rN2) and three eukaryotic expression spike proteins (rS1, rS-RBD, rS-RBD-mFc). The recombinant proteins with the highest ELISA titers (rS1 and rS-RBD-mFc) were selected to develop a double-antigen sandwich colloidal gold immunochromatography assay (GICA) to detect total antibodies against SARS-CoV-2. The clinical evaluation results showed that the sensitivity and specificity of GICA were 92.09% (419/455) and 99.44% (706/710), respectively. Moreover, a significant number (65.63%, 21/32) of COVID-19 patients with undetectable viral RNA were correctly diagnosed by the GICA method. In conclusion, the eukaryotic expression spike proteins (rS1 and rS-RBD-mFc) are more suitable than the prokaryotic expression nucleocapsid proteins for serological diagnosis of SARS-CoV-2. The proposed GICA for detection of total antibodies could be a powerful complement to the current RNA tests for COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10096-020-04102-4.
is ?:annotates of
?:creator
?:doi
?:doi
  • 10.1007/s10096-020-04102-4
?:journal
  • Eur_J_Clin_Microbiol_Infect_Dis
?:license
  • no-cc
?:pdf_json_files
  • document_parses/pdf_json/07eed5279a999775ce64c679c660d83dc51bf31b.json
?:pmc_json_files
  • document_parses/pmc_json/PMC7661101.xml.json
?:pmcid
?:pmid
?:pmid
  • 33184753.0
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • Medline; PMC
?:title
  • Development and evaluation of a serological test for diagnosis of COVID-19 with selected recombinant spike proteins
?:type
?:year
  • 2020-11-12

Metadata

Anon_0  
expand all