Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray

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

doi:10.1073/pnas.0510921103

Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray

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

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

114 Citations (Scopus)

Abstract

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. © 2006 by The National Academy of Sciences of the USA.

Original language	English
Pages (from-to)	4011-4016
Journal	PNAS: Proceedings of the National Academy of Sciences of the United States of America
Volume	103
Issue number	11
DOIs	https://doi.org/10.1073/pnas.0510921103
Publication status	Published - 14 Mar 2006
Externally published	Yes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Keywords

Infectious disease
Protein chip
Virus diagnostics

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10.1073/pnas.0510921103

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Zhu, H., Hu, S., Jona, G., Zhu, X., Kreiswirth, N., Willey, B. M., Mazzulli, T., Liu, G., Song, Q., Chen, P., Cameron, M., Tyler, A., Wang, J., Wen, J., Chen, W., Compton, S., & Snyder, M. (2006). Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray. PNAS: Proceedings of the National Academy of Sciences of the United States of America, 103(11), 4011-4016. https://doi.org/10.1073/pnas.0510921103

@article{ec33690bf6984968ba666d87895cb715,

title = "Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray",

abstract = "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. {\textcopyright} 2006 by The National Academy of Sciences of the USA.",

keywords = "Infectious disease, Protein chip, Virus diagnostics",

author = "Heng Zhu and Shaohui Hu and Ghil Jona and Xiaowei Zhu and Nate Kreiswirth and Willey, {Barbara M.} and Tony Mazzulli and Guozhen Liu and Qifeng Song and Peng Chen and Mark Cameron and Andrea Tyler and Jian Wang and Jie Wen and Weijun Chen and Susan Compton and Michael Snyder",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected]. ",

year = "2006",

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doi = "10.1073/pnas.0510921103",

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journal = "PNAS: Proceedings of the National Academy of Sciences of the United States of America",

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Zhu, H, Hu, S, Jona, G, Zhu, X, Kreiswirth, N, Willey, BM, Mazzulli, T, Liu, G, Song, Q, Chen, P, Cameron, M, Tyler, A, Wang, J, Wen, J, Chen, W, Compton, S & Snyder, M 2006, 'Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray', PNAS: Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 11, pp. 4011-4016. https://doi.org/10.1073/pnas.0510921103

Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray. / Zhu, Heng; Hu, Shaohui; Jona, Ghil et al.
In: PNAS: Proceedings of the National Academy of Sciences of the United States of America, Vol. 103, No. 11, 14.03.2006, p. 4011-4016.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

TY - JOUR

T1 - Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray

AU - Zhu, Heng

AU - Hu, Shaohui

AU - Jona, Ghil

AU - Zhu, Xiaowei

AU - Kreiswirth, Nate

AU - Willey, Barbara M.

AU - Mazzulli, Tony

AU - Liu, Guozhen

AU - Song, Qifeng

AU - Chen, Peng

AU - Cameron, Mark

AU - Tyler, Andrea

AU - Wang, Jian

AU - Wen, Jie

AU - Chen, Weijun

AU - Compton, Susan

AU - Snyder, Michael

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2006/3/14

Y1 - 2006/3/14

N2 - 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. © 2006 by The National Academy of Sciences of the USA.

AB - 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. © 2006 by The National Academy of Sciences of the USA.

KW - Infectious disease

KW - Protein chip

KW - Virus diagnostics

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-33645225281&origin=recordpage

U2 - 10.1073/pnas.0510921103

DO - 10.1073/pnas.0510921103

M3 - RGC 21 - Publication in refereed journal

C2 - 16537477

SN - 0027-8424

VL - 103

SP - 4011

EP - 4016

JO - PNAS: Proceedings of the National Academy of Sciences of the United States of America

JF - PNAS: Proceedings of the National Academy of Sciences of the United States of America

IS - 11

ER -

Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray

Abstract

Bibliographical note

UN SDGs

Research Keywords

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