In:
Science Translational Medicine, American Association for the Advancement of Science (AAAS), Vol. 9, No. 409 ( 2017-09-27)
Kurzfassung:
The recent Zika virus (ZIKV) outbreak demonstrates that cost-effective clinical diagnostics are urgently needed to detect and distinguish viral infections to improve patient care. Unlike dengue virus (DENV), ZIKV infections during pregnancy correlate with severe birth defects, including microcephaly and neurological disorders. Because ZIKV and DENV are related flaviviruses, their homologous proteins and nucleic acids can cause cross-reactions and false-positive results in molecular, antigenic, and serologic diagnostics. We report the characterization of monoclonal antibody pairs that have been translated into rapid immunochromatography tests to specifically detect the viral nonstructural 1 (NS1) protein antigen and distinguish the four DENV serotypes (DENV1–4) and ZIKV without cross-reaction. To complement visual test analysis and remove user subjectivity in reading test results, we used image processing and data analysis for data capture and test result quantification. Using a 30-μl serum sample, the sensitivity and specificity values of the DENV1–4 tests and the pan-DENV test, which detects all four dengue serotypes, ranged from 0.76 to 1.00. Sensitivity/specificity for the ZIKV rapid test was 0.81/0.86, respectively, using a 150-μl serum input. Serum ZIKV NS1 protein concentrations were about 10-fold lower than corresponding DENV NS1 concentrations in infected patients; moreover, ZIKV NS1 protein was not detected in polymerase chain reaction–positive patient urine samples. Our rapid immunochromatography approach and reagents have immediate application in differential clinical diagnosis of acute ZIKV and DENV cases, and the platform can be applied toward developing rapid antigen diagnostics for emerging viruses.
Materialart:
Online-Ressource
ISSN:
1946-6234
,
1946-6242
DOI:
10.1126/scitranslmed.aan1589
Sprache:
Englisch
Verlag:
American Association for the Advancement of Science (AAAS)
Publikationsdatum:
2017
