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Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray

2006; National Academy of Sciences; Volume: 103; Issue: 11 Linguagem: Inglês

10.1073/pnas.0510921103

1091-6490

Heng Zhu, Shaohui Hu, Ghil Jona, Xiaowei Zhu, Nate Kreiswirth, Barbara Willey, Tony Mazzulli, Guozhen Liu, Qifeng Song, Peng Chen, Mark J. Cameron, Andrea D. Tyler, Jian Wang, Jie Wen, Weijun Chen, Susan R Compton, M Snyder,

Biosensors and Analytical Detection

To monitor severe acute respiratory syndrome (SARS) infection, a coronavirus protein microarray that harbors proteins from SARS coronavirus (SARS-CoV) and five additional coronaviruses was constructed. These microarrays were used to screen ≈400 Canadian sera from the SARS outbreak, including samples from confirmed SARS-CoV cases, respiratory illness patients, and healthcare professionals. A computer algorithm that uses multiple classifiers to predict samples from SARS patients was developed and used to predict 206 sera from Chinese fever patients. The test assigned patients into two distinct groups: those with antibodies to SARS-CoV and those without. The microarray also identified patients with sera reactive against other coronavirus proteins. Our results correlated well with an indirect immunofluorescence test and demonstrated that viral infection can be monitored for many months after infection. We show that protein microarrays can serve as a rapid, sensitive, and simple tool for large-scale identification of viral-specific antibodies in sera.