SARS Coronavirus Detection Methods
Identifieur interne : 000866 ( Pmc/Corpus ); précédent : 000865; suivant : 000867SARS Coronavirus Detection Methods
Auteurs : Susanna K. P. Lau ; Xiao-Yan Che ; Patrick C. Y. Woo ; Beatrice H. L. Wong ; Vincent C. C. Cheng ; Gibson K. S. Woo ; Ivan F. N. Hung ; Rosana W. S. Poon ; Kwok-Hung Chan ; J. S. Malik Peiris ; Kwok-Yung YuenSource :
- Emerging Infectious Diseases [ 1080-6040 ] ; 2005.
Abstract
Using clinical samples from patients with severe acute respiratory syndrome, we showed that the sensitivities of a quantitative reverse transcription–polymerase chain reaction (80% for fecal samples and 25% for urine samples) were higher than those of the polyclonal (50% and 5%) and monoclonal (35% and 8%) antibody-based nucleocapsid antigen capture enzyme-linked immunosorbent assays.
Url:
DOI: 10.3201/eid1107.041045
PubMed: 16022791
PubMed Central: 3371792
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<author><name sortKey="Lau, Susanna K P" sort="Lau, Susanna K P" uniqKey="Lau S" first="Susanna K. P." last="Lau">Susanna K. P. Lau</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Che, Xiao Yan" sort="Che, Xiao Yan" uniqKey="Che X" first="Xiao-Yan" last="Che">Xiao-Yan Che</name>
<affiliation><nlm:aff id="aff2">First Military Medical University, Guangzhou, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Woo, Patrick C Y" sort="Woo, Patrick C Y" uniqKey="Woo P" first="Patrick C. Y." last="Woo">Patrick C. Y. Woo</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Wong, Beatrice H L" sort="Wong, Beatrice H L" uniqKey="Wong B" first="Beatrice H. L." last="Wong">Beatrice H. L. Wong</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Cheng, Vincent C C" sort="Cheng, Vincent C C" uniqKey="Cheng V" first="Vincent C. C." last="Cheng">Vincent C. C. Cheng</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
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<author><name sortKey="Woo, Gibson K S" sort="Woo, Gibson K S" uniqKey="Woo G" first="Gibson K. S." last="Woo">Gibson K. S. Woo</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Hung, Ivan F N" sort="Hung, Ivan F N" uniqKey="Hung I" first="Ivan F. N." last="Hung">Ivan F. N. Hung</name>
<affiliation><nlm:aff id="aff3">Queen Mary Hospital, Hong Kong Special Administrative Region, People's Republic of China</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Poon, Rosana W S" sort="Poon, Rosana W S" uniqKey="Poon R" first="Rosana W. S." last="Poon">Rosana W. S. Poon</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Chan, Kwok Hung" sort="Chan, Kwok Hung" uniqKey="Chan K" first="Kwok-Hung" last="Chan">Kwok-Hung Chan</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Peiris, J S Malik" sort="Peiris, J S Malik" uniqKey="Peiris J" first="J. S. Malik" last="Peiris">J. S. Malik Peiris</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Yuen, Kwok Yung" sort="Yuen, Kwok Yung" uniqKey="Yuen K" first="Kwok-Yung" last="Yuen">Kwok-Yung Yuen</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
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<author><name sortKey="Lau, Susanna K P" sort="Lau, Susanna K P" uniqKey="Lau S" first="Susanna K. P." last="Lau">Susanna K. P. Lau</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Che, Xiao Yan" sort="Che, Xiao Yan" uniqKey="Che X" first="Xiao-Yan" last="Che">Xiao-Yan Che</name>
<affiliation><nlm:aff id="aff2">First Military Medical University, Guangzhou, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Woo, Patrick C Y" sort="Woo, Patrick C Y" uniqKey="Woo P" first="Patrick C. Y." last="Woo">Patrick C. Y. Woo</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Wong, Beatrice H L" sort="Wong, Beatrice H L" uniqKey="Wong B" first="Beatrice H. L." last="Wong">Beatrice H. L. Wong</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Cheng, Vincent C C" sort="Cheng, Vincent C C" uniqKey="Cheng V" first="Vincent C. C." last="Cheng">Vincent C. C. Cheng</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Woo, Gibson K S" sort="Woo, Gibson K S" uniqKey="Woo G" first="Gibson K. S." last="Woo">Gibson K. S. Woo</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Hung, Ivan F N" sort="Hung, Ivan F N" uniqKey="Hung I" first="Ivan F. N." last="Hung">Ivan F. N. Hung</name>
<affiliation><nlm:aff id="aff3">Queen Mary Hospital, Hong Kong Special Administrative Region, People's Republic of China</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Poon, Rosana W S" sort="Poon, Rosana W S" uniqKey="Poon R" first="Rosana W. S." last="Poon">Rosana W. S. Poon</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Chan, Kwok Hung" sort="Chan, Kwok Hung" uniqKey="Chan K" first="Kwok-Hung" last="Chan">Kwok-Hung Chan</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Peiris, J S Malik" sort="Peiris, J S Malik" uniqKey="Peiris J" first="J. S. Malik" last="Peiris">J. S. Malik Peiris</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Yuen, Kwok Yung" sort="Yuen, Kwok Yung" uniqKey="Yuen K" first="Kwok-Yung" last="Yuen">Kwok-Yung Yuen</name>
<affiliation><nlm:aff id="aff1">University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</nlm:aff>
</affiliation>
</author>
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<series><title level="j">Emerging Infectious Diseases</title>
<idno type="ISSN">1080-6040</idno>
<idno type="eISSN">1080-6059</idno>
<imprint><date when="2005">2005</date>
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<front><div type="abstract" xml:lang="en"><p>Using clinical samples from patients with severe acute respiratory syndrome, we showed that the sensitivities of a quantitative reverse transcription–polymerase chain reaction (80% for fecal samples and 25% for urine samples) were higher than those of the polyclonal (50% and 5%) and monoclonal (35% and 8%) antibody-based nucleocapsid antigen capture enzyme-linked immunosorbent assays.</p>
</div>
</front>
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<pmc article-type="brief-report"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Emerg Infect Dis</journal-id>
<journal-id journal-id-type="iso-abbrev">Emerging Infect. Dis</journal-id>
<journal-id journal-id-type="publisher-id">EID</journal-id>
<journal-title-group><journal-title>Emerging Infectious Diseases</journal-title>
</journal-title-group>
<issn pub-type="ppub">1080-6040</issn>
<issn pub-type="epub">1080-6059</issn>
<publisher><publisher-name>Centers for Disease Control and Prevention</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">16022791</article-id>
<article-id pub-id-type="pmc">3371792</article-id>
<article-id pub-id-type="publisher-id">04-1045</article-id>
<article-id pub-id-type="doi">10.3201/eid1107.041045</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Dispatch</subject>
</subj-group>
<subj-group subj-group-type="article-type"><subject>Dispatch</subject>
</subj-group>
</article-categories>
<title-group><article-title>SARS Coronavirus Detection Methods</article-title>
<alt-title alt-title-type="running-head">ELISA versus qRT-PCR for SARS-CoV detection</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Lau</surname>
<given-names>Susanna K.P.</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Che</surname>
<given-names>Xiao-Yan</given-names>
</name>
<xref ref-type="aff" rid="aff2">†</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Woo</surname>
<given-names>Patrick C.Y.</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Wong</surname>
<given-names>Beatrice H.L.</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Cheng</surname>
<given-names>Vincent C.C.</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Woo</surname>
<given-names>Gibson K.S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Hung</surname>
<given-names>Ivan F.N.</given-names>
</name>
<xref ref-type="aff" rid="aff3">‡</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Poon</surname>
<given-names>Rosana W.S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Chan</surname>
<given-names>Kwok-Hung</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Peiris</surname>
<given-names>J.S. Malik</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Yuen</surname>
<given-names>Kwok-Yung</given-names>
</name>
<xref ref-type="aff" rid="aff1">*</xref>
</contrib>
<aff id="aff1"><label>*</label>
University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China;</aff>
<aff id="aff2"><label>†</label>
First Military Medical University, Guangzhou, People's Republic of China;</aff>
<aff id="aff3"><label>‡</label>
Queen Mary Hospital, Hong Kong Special Administrative Region, People's Republic of China</aff>
</contrib-group>
<author-notes><corresp id="cor1">Address for correspondence: Kwok-Yung Yuen, Department of Microbiology, University of Hong Kong, University Pathology Building, Queen Mary Hospital, Hong Kong, People's Republic of China; fax: 852-2855-1241; email: <email xlink:href="hkumicro@hkucc.hku.hk">hkumicro@hkucc.hku.hk</email>
</corresp>
</author-notes>
<pub-date pub-type="ppub"><month>7</month>
<year>2005</year>
</pub-date>
<volume>11</volume>
<issue>7</issue>
<fpage>1108</fpage>
<lpage>1111</lpage>
<abstract><p>Using clinical samples from patients with severe acute respiratory syndrome, we showed that the sensitivities of a quantitative reverse transcription–polymerase chain reaction (80% for fecal samples and 25% for urine samples) were higher than those of the polyclonal (50% and 5%) and monoclonal (35% and 8%) antibody-based nucleocapsid antigen capture enzyme-linked immunosorbent assays.</p>
</abstract>
<kwd-group kwd-group-type="author"><title>Keywords: </title>
<kwd>SARS-Cov</kwd>
<kwd>qRT-PCR</kwd>
<kwd>nucleocapsid</kwd>
<kwd>capture ELISA</kwd>
</kwd-group>
</article-meta>
</front>
<body><p>The epidemic of severe acute respiratory syndrome (SARS) in 2003, caused by SARS-associated coronavirus (SARS-CoV), has affected 30 countries, with 8,098 cases and 774 deaths (<xref ref-type="bibr" rid="R1">1</xref>
–<xref ref-type="bibr" rid="R8">8</xref>
). Early diagnosis of SARS-CoV infection, which involves viral detection, is important for preventing future epidemics. Since culturing of SARS-CoV is difficult and insensitive, the reverse transcription–polymerase chain reaction (RT-PCR) and quantitative RT-PCR (qRT-PCR) has been the working standard in diagnosis (<xref ref-type="bibr" rid="R2">2</xref>
,<xref ref-type="bibr" rid="R9">9</xref>
). Nevertheless, these techniques are relatively expensive and rely on the availability of equipment and expertise. We recently reported the development of 2 sandwich enzyme-linked immunosorbent assays (ELISAs) for detection of SARS-CoV nucleocapsid protein in clinical specimens of SARS patients (<xref ref-type="bibr" rid="R10">10</xref>
,<xref ref-type="bibr" rid="R11">11</xref>
). However, no studies have been conducted to compare the sensitivities of ELISA with those of RT-PCR. Although PCR assays are generally more sensitive, ELISAs are less expensive and easier to conduct (<xref ref-type="bibr" rid="R12">12</xref>
,<xref ref-type="bibr" rid="R13">13</xref>
). To evaluate the potential usefulness of ELISA in diagnosing SARS-CoV infections, we compared the performance of ELISA and qRT-PCR and studied the correlation between their results.</p>
<sec><title>The Study</title>
<p>Fecal specimens (n = 40, from 40 patients 1–27 days after symptom onset) and urine specimens (n = 133, from 101 patients 2–57 days after symptom onset) were collected from SARS patients hospitalized in Hong Kong from March to May 2003. SARS was confirmed by the presence of serum immunoglobulin (Ig) G against SARS-CoV by an immunofluorescence assay (<xref ref-type="bibr" rid="R4">4</xref>
). Specimens were tested with polyclonal and monoclonal antibody–based capture ELISAs for SARS-CoV nucleocapsid protein and real-time qRT-PCR. Control urine (n = 100) and fecal (n = 100) specimens were obtained from hospitalized patients without SARS.</p>
<p>SARS-CoV nucleocapsid protein was detected by polyclonal antibody–based ELISA according to published protocols (<xref ref-type="bibr" rid="R7">7</xref>
,<xref ref-type="bibr" rid="R11">11</xref>
). SARS-CoV nucleocapsid protein was detected by monoclonal antibody–based ELISA using a modified protocol for serum samples (<xref ref-type="bibr" rid="R10">10</xref>
). Briefly, fecal and urine specimens were inactivated with 2% and 0.5% phenol, respectively, for 15 min before centrifugation and dilution in phosphate-buffered saline with 2% skim milk. One hundred microliters of 1:10 diluted fecal specimens or 1:2 diluted urine specimens was added to wells previously coated with antinucleocapsid monoclonal antibodies. Plates were incubated, washed, treated with antinucleocapsid rabbit monoclonal antibodies, and analyzed as described previously (<xref ref-type="bibr" rid="R10">10</xref>
,<xref ref-type="bibr" rid="R11">11</xref>
). RNA extraction and real-time qPCR assay specific for the 1b region of SARS-CoV were conducted as described previously (<xref ref-type="bibr" rid="R3">3</xref>
,<xref ref-type="bibr" rid="R9">9</xref>
).</p>
<p>We compared the detection rates of 2 ELISAs and real-time qRT-PCR using the McNemar test and studied the correlation between the optical density values at 450 nm (OD<sub>450</sub>
) of the 2 ELISAs and log<sub>10</sub>
viral concentrations, as determined by real-time qRT-PCR, by linear regression (SPSS version 11.0, SPSS Inc., Chicago, IL, USA). A p value <0.05 was regarded as significant.</p>
<p>A comparison of the 2 ELISAs is shown in the <xref ref-type="fig" rid="F1">Figure</xref>
and <xref ref-type="table" rid="T1">Table 1</xref>
. The cutoffs of the polyclonal antibody–based ELISA have been determined previously, with specificities of 96% and 99% for fecal and urine specimens, respectively (<xref ref-type="bibr" rid="R11">11</xref>
). The baselines of the monoclonal antibody–based ELISA were determined by using 100 control fecal and urine specimens, with mean OD<sub>450</sub>
values of 0.089 and 0.05 and standard deviation (SD) values of 0.074 and 0.03, respectively. The specificities of the monoclonal antibody–based ELISA were 93% for fecal specimens and 98% for urine specimens, as determined using cutoffs defined as the mean + 2 SD. Of 40 fecal samples obtained from SARS patients, 20 (50%) obtained on days 9 to 23 after onset of symptoms were positive by the polyclonal antibody–based ELISA, and 14 (35%) obtained on days 2 to 21 were positive by the monoclonal antibody–based ELISA. Of 133 urine samples, 6 (5%) obtained on days 16 to 32 after onset of symptoms were positive by the polyclonal antibody–based ELISA, and 11 (8%) obtained on days 6 to 45 were positive by the monoclonal antibody–based ELISA. Results of the polyclonal antibody–based ELISA were comparable with our previous data on different specimens (<xref ref-type="bibr" rid="R11">11</xref>
). The OD<sub>450</sub>
values of both fecal (Pearson correlation 0.610, p<0.0005) and urine specimens (Pearson correlation 0.475, p<0.0005) detected by the 2 ELISAs were significantly correlated.</p>
<fig id="F1" fig-type="figure" position="float"><label>Figure</label>
<caption><p>Evaluation of polyclonal and monoclonal antibody–based enzyme-linked immunosorbent assays (ELISAs) for detecting nucleocapsid protein in fecal and urine specimens. The dashed horizontal lines represent the corresponding cutoff optical density values at 450 nm (OD<sub>450</sub>
). SARS, severe acute respiratory syndrome.</p>
</caption>
<graphic xlink:href="04-0883-F"></graphic>
</fig>
<table-wrap id="T1" position="float"><label>Table 1</label>
<caption><title>Detection of SARS-CoV in clinical specimens by qRT-PCR and ELISA in relation to time from onset of symptoms*</title>
</caption>
<table frame="hsides" rules="groups"><col width="111" span="1"></col>
<col width="60" span="1"></col>
<col width="38" span="1"></col>
<col width="125" span="1"></col>
<col width="131" span="1"></col>
<thead><tr><th rowspan="2" valign="bottom" align="left" scope="col" colspan="1">Days from onset of symptoms</th>
<th rowspan="2" valign="bottom" align="center" scope="col" colspan="1">No. specimens</th>
<th valign="bottom" colspan="3" align="center" scope="colgroup" rowspan="1">No. positive specimens (%)<hr></hr>
</th>
</tr>
<tr><th valign="bottom" colspan="1" align="center" scope="colgroup" rowspan="1">qRT-PCR</th>
<th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">Polyclonal antibody–based ELISA</th>
<th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">Monoclonal antibody–based ELISA</th>
</tr>
</thead>
<tbody><tr><td colspan="5" valign="top" align="left" scope="col" rowspan="1">Fecal specimens</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">1–5</td>
<td valign="top" align="center" rowspan="1" colspan="1">4</td>
<td valign="top" align="center" rowspan="1" colspan="1">3 (75)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (25)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">6–10</td>
<td valign="top" align="center" rowspan="1" colspan="1">4</td>
<td valign="top" align="center" rowspan="1" colspan="1">3 (75)</td>
<td valign="top" align="center" rowspan="1" colspan="1">2 (50)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">11–15</td>
<td valign="top" align="center" rowspan="1" colspan="1">13</td>
<td valign="top" align="center" rowspan="1" colspan="1">9 (69)</td>
<td valign="top" align="center" rowspan="1" colspan="1">7 (54)</td>
<td valign="top" align="center" rowspan="1" colspan="1">5 (38)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">16–20</td>
<td valign="top" align="center" rowspan="1" colspan="1">14</td>
<td valign="top" align="center" rowspan="1" colspan="1">13 (93)</td>
<td valign="top" align="center" rowspan="1" colspan="1">9 (64)</td>
<td valign="top" align="center" rowspan="1" colspan="1">7 (50)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">21–25</td>
<td valign="top" align="center" rowspan="1" colspan="1">4</td>
<td valign="top" align="center" rowspan="1" colspan="1">3 (75)</td>
<td valign="top" align="center" rowspan="1" colspan="1">2 (50)</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (25)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">26–30</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (100)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td colspan="5" valign="top" align="left" scope="col" rowspan="1">Urine specimens</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">1–5</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">6–10</td>
<td valign="top" align="center" rowspan="1" colspan="1">13</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (8)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">2 (15)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">11–15</td>
<td valign="top" align="center" rowspan="1" colspan="1">19</td>
<td valign="top" align="center" rowspan="1" colspan="1">3 (16)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">16–20</td>
<td valign="top" align="center" rowspan="1" colspan="1">67</td>
<td valign="top" align="center" rowspan="1" colspan="1">24 (36)</td>
<td valign="top" align="center" rowspan="1" colspan="1">5 (7)</td>
<td valign="top" align="center" rowspan="1" colspan="1">7 (10)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">21–25</td>
<td valign="top" align="center" rowspan="1" colspan="1">10</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (10)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (10)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">26–30</td>
<td valign="top" align="center" rowspan="1" colspan="1">11</td>
<td valign="top" align="center" rowspan="1" colspan="1">2 (18)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">31–40</td>
<td valign="top" align="center" rowspan="1" colspan="1">5</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (20)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">41–50</td>
<td valign="top" align="center" rowspan="1" colspan="1">5</td>
<td valign="top" align="center" rowspan="1" colspan="1">2 (40)</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">1 (20)</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">51–60</td>
<td valign="top" align="center" rowspan="1" colspan="1">2</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
</tbody>
</table>
<table-wrap-foot><p>*SARS-CoV, severe acute respiratory syndrome coronavirus; qRT-PCR, quantitative reverse transcription–polymerase chain reaction; ELISA, enzyme-linked immunosorbent assay.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec sec-type="conclusions"><title>Conclusions</title>
<p>The method of choice for early diagnosis of SARS-CoV infection should be the qRT-PCR. The sensitivity of qRT-PCR is superior to that of both ELISAs. Moreover, qRT-PCR can detect SARS-CoV earlier in fecal specimens (<xref ref-type="table" rid="T1">Tables 1</xref>
and <xref ref-type="table" rid="T2">2</xref>
). Among the 40 fecal samples from SARS patients, 32 (80%) were positive by qRT-PCR, which was significantly higher than that of the polyclonal (50%) and monoclonal (35%) antibody-based ELISAs (McNemar test, p<0.005 and p<0.001, respectively). Of the 133 urine samples from SARS patients, 33 (25%) were positive by qRT-PCR, which was also significantly higher than that of the polyclonal (5%) and monoclonal (8%) antibody-based ELISAs (McNemar test, p<0.001 for both comparisons). When qRT-PCR was used as a standard, the sensitivities of the polyclonal and monoclonal antibody–based ELISAs were 53.1% (17/32) and 43.8% (14/32) in fecal specimens, and 12.1% (4/33) and 15.2% (5/33) in urine specimens, respectively. The qRT-PCR can detect SARS-CoV in fecal specimens obtained on days 1 to 27 after onset of symptoms and in urine specimens obtained on days 9 to 45. Moreover, 6 (75%) of the 8 fecal specimens obtained on days 1 to 10 were positive by qRT-PCR. All 3 tests had the highest detection rates in fecal specimens collected on days 16 to 20, which suggested that this was the period of peak viral shedding in stool. The detection rates in urine specimens were much lower than those in fecal specimens in all 3 assays.</p>
<table-wrap id="T2" position="float"><label>Table 2</label>
<caption><title>Detection of SARS-CoV by qRT-PCR and ELISA in clinical specimens of patients with SARS*</title>
</caption>
<table frame="hsides" rules="groups"><col width="68" span="1"></col>
<col width="46" span="1"></col>
<col width="75" span="1"></col>
<col width="80" span="1"></col>
<col width="46" span="1"></col>
<col width="75" span="1"></col>
<col width="80" span="1"></col>
<thead><tr><th rowspan="2" valign="bottom" align="left" scope="col" colspan="1">RNA concentration (copies/mL)</th>
<th valign="bottom" colspan="3" align="center" scope="colgroup" rowspan="1">Fecal specimens<hr></hr>
</th>
<th valign="bottom" colspan="3" align="center" scope="colgroup" rowspan="1">Urine specimens<hr></hr>
</th>
</tr>
<tr><th valign="bottom" colspan="1" align="center" scope="colgroup" rowspan="1">No. specimens</th>
<th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">No. positive by polyclonal antibody–based ELISA</th>
<th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">No. positive by monoclonal antibody–based ELISA</th>
<th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">No. specimens</th>
<th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">No. positive by polyclonal antibody–based ELISA</th>
<th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">No. positive by monoclonal antibody–based ELISA</th>
</tr>
</thead>
<tbody><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><3 × 10<sup>2</sup>
</td>
<td valign="top" align="center" rowspan="1" colspan="1">8</td>
<td valign="top" align="center" rowspan="1" colspan="1">3</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">100</td>
<td valign="top" align="center" rowspan="1" colspan="1">2</td>
<td valign="top" align="center" rowspan="1" colspan="1">6</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">3 × 10<sup>2</sup>
–<10<sup>4</sup>
</td>
<td valign="top" align="center" rowspan="1" colspan="1">5</td>
<td valign="top" align="center" rowspan="1" colspan="1">3</td>
<td valign="top" align="center" rowspan="1" colspan="1">3</td>
<td valign="top" align="center" rowspan="1" colspan="1">16</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">10<sup>4</sup>
–<10<sup>6</sup>
</td>
<td valign="top" align="center" rowspan="1" colspan="1">3</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">10</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">10<sup>6</sup>
–<10<sup>8</sup>
</td>
<td valign="top" align="center" rowspan="1" colspan="1">9</td>
<td valign="top" align="center" rowspan="1" colspan="1">5</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">7</td>
<td valign="top" align="center" rowspan="1" colspan="1">2</td>
<td valign="top" align="center" rowspan="1" colspan="1">3</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">10<sup>8</sup>
–<10<sup>10</sup>
</td>
<td valign="top" align="center" rowspan="1" colspan="1">13</td>
<td valign="top" align="center" rowspan="1" colspan="1">8</td>
<td valign="top" align="center" rowspan="1" colspan="1">10</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">≥10<sup>10</sup>
</td>
<td valign="top" align="center" rowspan="1" colspan="1">2</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
<td valign="top" align="center" rowspan="1" colspan="1">1</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
<td valign="top" align="center" rowspan="1" colspan="1">0</td>
</tr>
<tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Total</td>
<td valign="top" align="center" rowspan="1" colspan="1">40</td>
<td valign="top" align="center" rowspan="1" colspan="1">20</td>
<td valign="top" align="center" rowspan="1" colspan="1">14</td>
<td valign="top" align="center" rowspan="1" colspan="1">133</td>
<td valign="top" align="center" rowspan="1" colspan="1">6</td>
<td valign="top" align="center" rowspan="1" colspan="1">11</td>
</tr>
</tbody>
</table>
<table-wrap-foot><p>*SARS-CoV, severe acute respiratory syndrome coronavirus; qRT-PCR, quantitative reverse transcription–polymerase chain reaction; ELISA, enzyme-linked immunosorbent assay.</p>
</table-wrap-foot>
</table-wrap>
<p>SARS-CoV can be detected during the late phase of illness. Since SARS-CoV cannot be readily isolated from SARS patients after week 3 of illness (<xref ref-type="bibr" rid="R14">14</xref>
), the detection of SARS-CoV beyond this time may be due to prolonged shedding of nonviable viruses in these patients or the presence of neutralizing immunoglobulins in clinical specimens, which has prevented viral replication in cell cultures.</p>
<p>SARS-CoV RNA concentration and ELISA results were correlated. Higher detection rates by both ELISAs were found in specimens with higher viral concentrations (<xref ref-type="table" rid="T2">Table 2</xref>
). There was also a significant correlation between viral load and ELISA OD<sub>450</sub>
values in fecal specimens tested with the monoclonal antibody–based ELISA (Pearson correlation 0.424, p = 0.003), and in urine specimens tested with both the polyclonal and monoclonal antibody–based ELISAs (Pearson correlation 0.386 and 0.331, respectively, p<0.0005 in both analysis). Although the correlation between viral load and ELISA OD<sub>450</sub>
values in fecal specimens tested with the polyclonal antibody–based ELISA was not significant, there was a trend for such a correlation (Pearson correlation 0.229, p = 0.078).</p>
<p>In this study, fecal and urine samples were used because they are easier and safer to obtain and more readily available. In our previous reports, nucleocapsid protein was detected by the polyclonal antibody–based ELISA in 83% of nasopharyngeal aspirates collected on days 11 to 15 after symptom onset and by the monoclonal antibody–based ELISA in 85% of serum obtained during the first 10 days (<xref ref-type="bibr" rid="R10">10</xref>
,<xref ref-type="bibr" rid="R11">11</xref>
). These findings suggest that ELISA may be more useful when used with nasopharyngeal aspirate and serum specimens. However, these specimens were not included in the current study because only small amounts were available. Similar studies should be conducted if such samples are available.</p>
<p>This study was supported by the Research Grant Council Grant (HKU 7532/03M); Vice-Chancellor SARS Research Fund (21395035/39839/20700/420/01 and 21395061/27944/20700/420/01), The University of Hong Kong; and Suen Chi Sun Charitable Foundation SARS Research Fund.</p>
</sec>
</body>
<back><fn-group><fn fn-type="citation"><p><italic>Suggested citation for this article:</italic>
Lau SK, Che XY, Woo PC, Wong BH, Cheng VC, Woo GK, et al. SARS coronavirus detection methods. Emerg Infect Dis [serial on the Internet]. 2005 Jul [<italic>date cited</italic>
]. <ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.3201/eid1107.041045">http://dx.doi.org/10.3201/eid1107.041045</ext-link>
</p>
</fn>
</fn-group>
<bio id="d34e691"><p>Dr. Lau is assistant professor in the Department of Microbiology, University of Hong Kong. Her research interests include emerging infectious diseases and novel pathogens.</p>
</bio>
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