Literature DB >> 15030701

Real-time polymerase chain reaction for detecting SARS coronavirus, Beijing, 2003.

Junhui Zhai1, Thomas Briese, Erhei Dai, Xiaoyi Wang, Xin pang, Zongmin Du, Haihong Liu, Jin Wang, Hongxia Wang, Zhaobiao Guo, Zeliang Chen, Lingxiao Jiang, Dongsheng Zhou, Yanping Han, Omar Jabado, Gustavo Palacios, W Ian Lipkin, Ruifu Tang.   

Abstract

During the 2003 severe acute respiratory syndrome (SARS) outbreak, a real-time quantitative polymerase chain reaction, which targets the nucleocapsid gene at the 3' end of the viral genome, was established to detect and identify the SARS-associated coronavirus. We describe the use of this assay to screen >700 clinical samples.

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Year:  2004        PMID: 15030701      PMCID: PMC3322935          DOI: 10.3201/eid1002.030799

Source DB:  PubMed          Journal:  Emerg Infect Dis        ISSN: 1080-6040            Impact factor:   6.883


Severe acute respiratory syndrome (SARS) is a new infectious disease of humans, first recognized in late February 2003 in Hanoi, Vietnam. The disease spread rapidly, with cases reported from 29 countries on five continents over 4 months (–). By July 3, 2003, this epidemic resulted in 8,439 reported cases globally, of which 812 were fatal (). Rapid identification of the causal agent as a novel coronavirus (SARS-CoV) represents an extraordinary achievement in the history of global health and helped to contain the epidemic (). Nonetheless, the epidemiology and pathogenesis of SARS remain poorly understood, and definitive diagnostic tests or specific treatments are not established. Since the origin of the virus and its animal reservoirs remain to be defined, the potential for recurrence is unknown. This fact underscores the importance of establishing sensitive and efficient methods for diagnosis and surveillance. Immunofluorescence and enzyme-linked immunosorbent assays (ELISA) are reported to inconsistently detect antibodies to SARS-CoV before day 10 or 20 after the onset of symptoms, respectively (,). Thus, although helpful in tracking the course of infection at the population level, these serologic tools have less usefulness in detecting infection at early stages, when there may be potential to implement therapeutic interventions or measures, such as quarantine that may reduce the risk for transmission to naïve persons. In contrast, polymerase chain reaction (PCR)–based assays have the potential to detect infection at earlier time points. We describe a sensitive real-time PCR assay that can be readily standardized across laboratories and report its use in a survey of more than 700 samples from persons diagnosed with probable SARS during the 2003 epidemic in Beijing.

The Study

Primers and probe were selected in the N (nucleocapsid protein) gene region at the 3′ end of the SARS-CoV genome by using Primer Express Software (PE Applied Biosystems, Foster City, CA). The primer set used was: Taq-772F 5′-AAGCCTCGCCAAAAACGTAC (forward) and Taq-1000R 5′-AAGTCAGCCATGTTCCCGAA (reverse), Taq-955T 5′-FAM-TCACGCATTGGCATGGAAGTCACAC-T-TAMRA (probe), labeled with the reporter FAM (6-carboxyfluorescein) and the quencher TAMRA (6-carboxytetramethylrhodamine) (TIB Molbiol, Berlin, Germany). A calibration standard was generated by PCR amplification of a 1,277–bp fragment comprising part of the N open reading frame (ORF) and the 3′ noncoding region (Co-STND-U275, 5′-CCCGACGAGTTCGTGGTGGTG; Co-STND-L1529, 5′-GCGTTACACATTAGGGCTCTTCCATA). The product was cloned into vector pGEM-Teasy (Invitrogen, Carlsbad, CA), and serial dilutions of linearized plasmid were used to optimize the assay. RNA standards were generated by in vitro transcription of linearized plasmid DNA using a mMESSAGE mMACHINE T7 kit as recommended by the manufacturer (Ambion, Austin, TX). A portion of the construct (nucleotides 682–1105 of the N ORF) was modified through site-directed mutagenesis, to distinguish plasmid-derived products from authentic products in diagnostic applications. Mutations introduced were an A to G change at position 845 of the N ORF, and an A to C change at position 866, creating a unique ApaI restriction site. Detection of live virus was assessed by using supernatant from virus-infected Vero E6 cells (isolate BJ01; 4th passage; 108 TCID50/mL) tenfold diluted to 10–12 in tissue culture media. RNA from 140-μL aliquots of each dilution was extracted and resuspended in 60 μL of DEPC-treated water for reverse transcription (9 μL RNA/20-μL reaction) and PCR (5 μL/assay). 20 μL of each virus dilution were spiked into 180 μL of clarified supernatant of a fecal preparation to simulate clinical specimens, and RNA from 140-μL aliquots was extracted and processed as above. Clinical materials, including 326 fecal and 426 whole blood samples, were collected from Chaoyang Hospital, 301 Hospital, You’an Hospital, and Xuanwu Hospital, Beijing. All persons had a diagnosis of probable SARS according to World Health Organization (WHO) criteria. For analysis of fecal samples, 1 g of stool was suspended in 1 mL of phosphate-buffered saline, mixed vigorously, and centrifuged for 10 min at 3,000 g, 4°C. Supernatant was collected for RNA extraction and PCR analysis. For analysis of blood samples, whole blood was fractionated using Ficoll Paque (Amersham Pharmacia, England). Plasma was collected and immunoglobulin (Ig) G and IgM levels were determined with an ELISA kit from the Beijing Genomics Institute (Beijing, China). Peripheral blood mononuclear cells were collected and RNA extracted by using the QiaAmp Viral RNA Mini Kit (Qiagen, Germany). Nine microliters total RNA was reverse transcribed (SuperScript II Transcriptase, Invitrogen), and 2 μL of cDNA subjected to PCR by using a TaqMan Universal Master Mix kit (PE Applied Biosystems) on an ABI Prism 7900 HT sequence detector (PE Applied Biosystems). Thermocycling conditions were: 2 min 50°C (AmpErase UNG), 10 min 95°C (polymerase activation); 45 cycles of 15s 95°C denaturation, and 1 min 60°C annealing/extension.

Conclusions

A standard curve of plasmid concentration versus threshold cycle was generated with a cloned version of the 3′ terminal portion of the viral genome. A correlation coefficient (r2) of 0.9913 showed a linear relationship between threshold cycle (Ct) and plasmid concentration (0–105 copies) (Figure 1A). The detection limit for plasmid DNA was <5 copies per assay (Ct = 42.66). A linear relationship was consistently obtained for input loads of 101–105 copies per assay.
Figure 1

Standard curve and amplification plot using serial dilutions of plasmid DNA (A) or of cRNA (B).

Standard curve and amplification plot using serial dilutions of plasmid DNA (A) or of cRNA (B). Standards for RT-PCR were generated by in vitro transcription of RNA from linearized plasmid template with T7 polymerase. Logarithmic dilutions of the synthesized RNA yielded results comparable to the DNA standards (r2 = 0.9950; Figure 1B). Supernatant from infected Vero E6 cells was serially diluted to determine the detection limit for live virus. Analysis of RNA extracted from logarithmic dilutions indicated a detection threshold of 0.0005 TCID50 (10–9 dilution; 0.1 TCID50/mL; 0.0005 TCID50 per assay well). The threshold for detection of SARS-CoV in spiked fecal samples was 0.005 TCID50 (10–7 dilution; 1 TCID50/mL; 0.005 TCID50 per assay well) (data not shown). Materials from persons who had probable SARS included 326 fecal samples and 426 blood samples. Control specimens collected during the outbreak from healthy persons included 16 fecal samples and 82 blood samples. The detection rate in fecal samples was 27% during the first 20 days after onset of symptoms (Table, Figure 2A). In the 20 days that followed, the detection rate declined to 16% to 18%, but even after >40 days, 9% of samples gave a positive reading. A similar time was observed in the analysis of blood samples; however, a higher the detection rate of 45% to 49% was obtained (note that only 11 of the samples were matched for blood and feces). During the first 20 days after onset of symptoms, the detection rate of RT-PCR in blood was significantly higher than that for IgM (10%–24%) or IgG antibodies (13%–15%) (Table, Figure 2B). Twenty-one to 40 days after onset of symptoms, serologic findings were more frequently positive than RT-PCR.
Table

Summary of clinical samplesa

SpecimensTotal patients1–10 d
11–20 d
21–30 d
31–40 d
>40 d
posnegposnegposnegposnegposneg
Feces PCR
326
10
27
19
52
12
65
12
55
7
67
Blood PCR
426
28
34
20
21
22
143
26
132
NA
NA
Blood IgG
426
6
56
10
31
82
83
138
20
NA
NA
Blood IgM426854635631028276NANA

apos, positive;eg, negative; PCR, polymerase chain reaction; Ig, immunoglobulin; NA, not available.

Figure 2

(A) real-time polymerase chain reaction (PCR) analysis of fecal samples; (B) real-time PCR, immunoglobulin (Ig) M and IgG analysis of blood samples.

apos, positive;eg, negative; PCR, polymerase chain reaction; Ig, immunoglobulin; NA, not available. (A) real-time polymerase chain reaction (PCR) analysis of fecal samples; (B) real-time PCR, immunoglobulin (Ig) M and IgG analysis of blood samples. Of the 16 fecal and 82 blood samples obtained from healthy persons, one blood sample yielded a positive result in RT-PCR (confirmed by repeated assays). Because the sample was collected during the outbreak, it may represent a true infection in a person who was not yet symptomatic or who did not have classical symptoms (no clinical information for the period after sampling was available). We also analyzed 180 sputum and 76 throat-washing samples from an unrelated cohort of persons with a diagnosis of probable SARS, for which the time after onset of symptoms had not been reported. The RT-PCR detection rate obtained in these samples was 63% for sputa, and 15% for throat washing samples (data not shown). It was not possible during the Beijing outbreak to obtain clinical materials in a prospective serial fashion from a defined SARS-CoV–infected patient cohort. Thus, some samples represent persons with respiratory symptoms caused by pathogens other than SARS-CoV (). However, confidence in the clinical criteria is enhanced by an 87% seropositivity in samples taken 31–40 days after onset of symptoms. Current real-time RT-PCR assays allow sensitive detection of SARS-CoV nucleic acid in clinical specimens by targeting N gene sequence, as shown here, or pol gene sequence (–). A major advantage to real-time PCR platforms is that amplification and analysis are completed in a closed system. Thus, the risk of contamination, which can confound conventional (frequently nested) RT-PCR protocols (,,), is markedly reduced. Whether different positivity rates reported for various SARS-CoV assays (–,) reflect true differences in assay performance, or merely differences in specimen type or differences in sample preparation (), will only become apparent after comparative quality control tests using identical samples in the various assays and laboratories. Using calibrated DNA and RNA standards, we achieved comparable results with the assay reported here in the New York and Beijing laboratories. RNA integrity is a critical determinant of sensitivity in RT-PCR SARS-CoV assays. Samples were not collected at clinical sites with the objective of nucleic acid analysis. Additionally, protocols adopted by the various hospitals for sample collection, handling, and storage were not uniform. Nonetheless, RT-PCR analysis resulted in consistent results for all 11 cases of matching feces and blood samples. Furthermore, all blood samples seropositive during the first 20 days after onset of symptoms were also positive in RT-PCR. Of the 48 RT-PCR positive samples collected 21–40 days after onset of symptoms, 45 were also seropositive. RT-PCR analysis of blood was a less sensitive index of infection than immunologic assays at later time points (21–40 days after onset of symptoms). However, 16% of blood samples and 18% of fecal samples contained SARS-CoV RNA >31–40 days after onset of symptoms. A similar duration of persistence of SARS sequences in stool has been observed by Ren et al. (). Whether infectious virus is present at these later time points remains to be determined; nonetheless, our findings indicate that long-term monitoring may be required to control dissemination of disease.
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1.  Severe acute respiratory syndrome (SARS).

Authors: 
Journal:  Wkly Epidemiol Rec       Date:  2003-03-21

2.  Identification of a novel coronavirus in patients with severe acute respiratory syndrome.

Authors:  Christian Drosten; Stephan Günther; Wolfgang Preiser; Sylvie van der Werf; Hans-Reinhard Brodt; Stephan Becker; Holger Rabenau; Marcus Panning; Larissa Kolesnikova; Ron A M Fouchier; Annemarie Berger; Ana-Maria Burguière; Jindrich Cinatl; Markus Eickmann; Nicolas Escriou; Klaus Grywna; Stefanie Kramme; Jean-Claude Manuguerra; Stefanie Müller; Volker Rickerts; Martin Stürmer; Simon Vieth; Hans-Dieter Klenk; Albert D M E Osterhaus; Herbert Schmitz; Hans Wilhelm Doerr
Journal:  N Engl J Med       Date:  2003-04-10       Impact factor: 91.245

3.  A major outbreak of severe acute respiratory syndrome in Hong Kong.

Authors:  Nelson Lee; David Hui; Alan Wu; Paul Chan; Peter Cameron; Gavin M Joynt; Anil Ahuja; Man Yee Yung; C B Leung; K F To; S F Lui; C C Szeto; Sydney Chung; Joseph J Y Sung
Journal:  N Engl J Med       Date:  2003-04-07       Impact factor: 91.245

4.  Identification of severe acute respiratory syndrome in Canada.

Authors:  Susan M Poutanen; Donald E Low; Bonnie Henry; Sandy Finkelstein; David Rose; Karen Green; Raymond Tellier; Ryan Draker; Dena Adachi; Melissa Ayers; Adrienne K Chan; Danuta M Skowronski; Irving Salit; Andrew E Simor; Arthur S Slutsky; Patrick W Doyle; Mel Krajden; Martin Petric; Robert C Brunham; Allison J McGeer
Journal:  N Engl J Med       Date:  2003-03-31       Impact factor: 91.245

5.  [Identification and molecular cloning and sequence analysis of a novel coronavirus from patients with SARS by RT-PCR].

Authors:  Bo-ping Zhou; Xin-chun Chen; Huo-sheng Wang; Mei-zhong Li; Yi-wen Hu; Fan Du; Liu-mei Xu; Gui-lin Yang
Journal:  Zhonghua Shi Yan He Lin Chuang Bing Du Xue Za Zhi       Date:  2003-06

6.  Establishment of a fluorescent polymerase chain reaction method for the detection of the SARS-associated coronavirus and its clinical application.

Authors:  Xinwei Wu; Gang Cheng; Biao Di; Aihua Yin; Yunshao He; Ming Wang; Xinyu Zhou; Lijuan He; Kai Luo; Lin Du
Journal:  Chin Med J (Engl)       Date:  2003-07       Impact factor: 2.628

7.  Viral aetiology of acute respiratory illnesses in patients with a suspicion of severe acute respiratory syndrome (SARS) in Switzerland.

Authors:  L Kaiser; C Deffernez; Y Thomas; D Koch; V Masserey Spicher; I Uckay; D Schultze; G Siegl; L Perrin; H C Matter; W Wunderli
Journal:  Swiss Med Wkly       Date:  2003-07-12       Impact factor: 2.193

8.  Evaluation of reverse transcription-PCR assays for rapid diagnosis of severe acute respiratory syndrome associated with a novel coronavirus.

Authors:  W C Yam; K H Chan; L L M Poon; Y Guan; K Y Yuen; W H Seto; J S M Peiris
Journal:  J Clin Microbiol       Date:  2003-10       Impact factor: 5.948

9.  [Detection of SARS-CoV RNA in stool samples of SARS patients by nest RT-PCR and its clinical value].

Authors:  Yi Ren; Hui-guo Ding; Qing-fa Wu; Wei-jun Chen; Dong Chen; Zhi-ying Bao; Ling Yang; Chun-hui Zhao; Jian Wang
Journal:  Zhongguo Yi Xue Ke Xue Yuan Xue Bao       Date:  2003-06

10.  A multicentre collaboration to investigate the cause of severe acute respiratory syndrome.

Authors: 
Journal:  Lancet       Date:  2003-05-17       Impact factor: 79.321

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1.  Monoclonal antibody-based antigen capture enzyme-linked immunosorbent assay reveals high sensitivity of the nucleocapsid protein in acute-phase sera of severe acute respiratory syndrome patients.

Authors:  Biao Di; Wei Hao; Yang Gao; Ming Wang; Ya-di Wang; Li-wen Qiu; Kun Wen; Duan-hua Zhou; Xin-wei Wu; En-jie Lu; Zhi-yong Liao; Ya-bo Mei; Bo-jian Zheng; Xiao-yan Che
Journal:  Clin Diagn Lab Immunol       Date:  2005-01

2.  Detection of respiratory viruses and subtype identification of influenza A viruses by GreeneChipResp oligonucleotide microarray.

Authors:  Phenix-Lan Quan; Gustavo Palacios; Omar J Jabado; Sean Conlan; David L Hirschberg; Francisco Pozo; Philippa J M Jack; Daniel Cisterna; Neil Renwick; Jeffrey Hui; Andrew Drysdale; Rachel Amos-Ritchie; Elsa Baumeister; Vilma Savy; Kelly M Lager; Jürgen A Richt; David B Boyle; Adolfo García-Sastre; Inmaculada Casas; Pilar Perez-Breña; Thomas Briese; W Ian Lipkin
Journal:  J Clin Microbiol       Date:  2007-06-06       Impact factor: 5.948

Review 3.  Severe acute respiratory syndrome coronavirus as an agent of emerging and reemerging infection.

Authors:  Vincent C C Cheng; Susanna K P Lau; Patrick C Y Woo; Kwok Yung Yuen
Journal:  Clin Microbiol Rev       Date:  2007-10       Impact factor: 26.132

4.  Nucleocapsid protein as early diagnostic marker for SARS.

Authors:  Xiao-Yan Che; Wei Hao; Yadi Wang; Biao Di; Kai Yin; Yin-Chao Xu; Chang-Sen Feng; Zhuo-Yue Wan; Vincent C C Cheng; Kwok-Yung Yuen
Journal:  Emerg Infect Dis       Date:  2004-11       Impact factor: 6.883

5.  SARS molecular detection external quality assurance.

Authors:  Christian Drosten; Hans Wilhelm Doerr; Wilina Lim; Klaus Stöhr; Matthias Niedrig
Journal:  Emerg Infect Dis       Date:  2004-12       Impact factor: 6.883

6.  Using patient-collected clinical samples and sera to detect and quantify the severe acute respiratory syndrome coronavirus (SARS-CoV).

Authors:  Zhongping He; Hui Zhuang; Chunhui Zhao; Qingming Dong; Guoai Peng; Dominic E Dwyer
Journal:  Virol J       Date:  2007-03-27       Impact factor: 4.099

7.  Development of SARS-CoV-2 Nucleocapsid Specific Monoclonal Antibodies.

Authors:  James S Terry; Loran Br Anderson; Michael S Scherman; Carley E McAlister; Rushika Perera; Tony Schountz; Brian J Geiss
Journal:  bioRxiv       Date:  2020-09-03

8.  Viral load quantitation of SARS-coronavirus RNA using a one-step real-time RT-PCR.

Authors:  Els Keyaerts; Leen Vijgen; Piet Maes; Griet Duson; Johan Neyts; Marc Van Ranst
Journal:  Int J Infect Dis       Date:  2005-07-14       Impact factor: 3.623

9.  Panmicrobial oligonucleotide array for diagnosis of infectious diseases.

Authors:  Gustavo Palacios; Phenix-lan Quan; Omar J Jabado; Sean Conlan; David L Hirschberg; Yang Liu; Junhui Zhai; Neil Renwick; Jeffrey Hui; Hedi Hegyi; Allen Grolla; James E Strong; Jonathan S Towner; Thomas W Geisbert; Peter B Jahrling; Cornelia Büchen-Osmond; Heinz Ellerbrok; Maria Paz Sanchez-Seco; Yves Lussier; Pierre Formenty; M Stuart T Nichol; Heinz Feldmann; Thomas Briese; W Ian Lipkin
Journal:  Emerg Infect Dis       Date:  2007-01       Impact factor: 6.883

10.  Wrestling SARS from uncertainty.

Authors:  Jairam R Lingappa; L Clifford McDonald; Patricia Simone; Umesh D Parashar
Journal:  Emerg Infect Dis       Date:  2004-02       Impact factor: 6.883

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