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Detection of Zaire Ebola virus by real-time reverse transcription-polymerase chain reaction, Sierra Leone, 2014
Journal of Virological Methods 222 (2015) 62–65
Contents lists available at ScienceDirect
Journal of Virological Methods journal homepage: www.elsevier.com/locate/jviromet
Detection of Zaire Ebola virus by real-time reverse transcription-polymerase chain reaction, Sierra Leone, 2014 Licheng Liu a,1 , Yang Sun b,1 , Brima Kargbo c,1 , Chuntao Zhang d , Huahua Feng e , Huijun Lu b , Wenseng Liu b , Chengyu Wang b , Yi Hu b , Yongqiang Deng b , Jiafu Jiang b , Xiaoping Kang a , Honglei Yang e , Yongqiang Jiang a , Yinhui Yang a , David Kargbo c,∗ , Jun Qian b,∗∗ , Weijun Chen e,f,∗ ∗ ∗ a State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Dongdajie Road 20, Beijing 100071, China b The China Mobile Laboratory Testing Team in Sierra Leone, Sierra Leone c Ministry of Health and Sanitation, Freetown, Sierra Leone d National Institutes for Food and Drug Control, Beijing 100050, China e Beijing BGI-GBI Biotech Co., Ltd, Beijing 101300, China f CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, No. 1 Beichen West Road, Chaoyang District, Beijing 100101, China
a b s t r a c t Article history: Received 12 December 2014 Received in revised form 23 April 2015 Accepted 12 May 2015 Available online 27 May 2015 Keywords: Ebola virus disease Zaire Ebola virus Real-time reverse transcription polymerase chain reaction (rRT-PCR)
During the 2014 Ebola virus disease (EVD) outbreak, a real-time quantitative polymerase chain reaction was established to detect and identify the Zaire Ebola virus. We describe the use of this assay to screen 315 clinical samples from EVD suspected person in Sierra Leone. The detection rate in blood samples was 77.81% (207/266), and there were relatively higher detection rate (79.32% and 81.42%, respectively) during the first two weeks after onset of symptoms. In the two weeks that followed, the detection rate declined to 66.67% and 25.00%, respectively. There was the highest virus load at the first week and then decreased. The detection rate in swab samples was 89.79% (44/49). This may be benefit from the included patients. 46 of 49 swab samples were collected from died patients. Taken together, the results presented here indicate that the assay specifically and sensitively detects Zaire Ebola virus. © 2015 Elsevier B.V. All rights reserved.
The re-emergence of Ebola in 2013 leading to an epidemic in West Africa which is still ongoing in 2014, and has resulted in at least 17,145 suspected cases and 6070 confirmed deaths (WHO, 2014). The story of the current outbreak began in Gueckedouin (Guinea) where, on 6 December 2013, a 2-year-old boy was affected (Baize et al., 2014; Gire et al., 2014). What differentiates this outbreak from the previous ones is not only its magnitude (past outbreaks resulted in a maximum of a few hundred cases), but also
∗ Corresponding author. ∗∗ Corresponding author at: Institute of Military Veterinary, AMMS, Key Laboratory of Jilin Province for Zoonosis Prevention and Control, Changchun, China. ∗ ∗ ∗Corresponding author at: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, No. 1 Beichen West Road, Chaoyang District, Beijing 100101, China. Tel.: +86 10 80485404; fax: +86 10 80485404. E-mail addresses: [email protected] (D. Kargbo), [email protected] (J. Qian), [email protected] (W. Chen). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.jviromet.2015.05.005 0166-0934/© 2015 Elsevier B.V. All rights reserved.
its first ever appearance in west African countries (Guinea, Liberia, Sierra Leone and Nigeria). The ‘Guinea strain’ is a variant of the Zaire Ebola virus, but hemorrhagic manifestations are not as apparent this time around (Baize et al., 2014; Gire et al., 2014). The mortality also seems to be lower than usual, at (a still very high) 50–55% (Kuhn et al., 2011; WHO, 2014). Zaire Ebola virus is one of five known viruses within the genus Ebolavirus (Kuhn et al., 2010). Zaire Ebola virus causes a hemorrhagic fever in the humans and some other nonhuman primates. Exceptionally, in swine, Zaire Ebola virus causes a respiratory disease. It has been known as Ebola virus disease (EVD). The Ebola virus is transmitted only through close and direct contact with the blood or body fluids of human cases or affected animals. Aerosol transmission has not been reported. All these factors restrict its spread and it is unlikely that even a traveler to affected areas would be exposed to such situations, unless he visits a hospital or attends a funeral. No indigenous cases have been reported outside West Africa and cases diagnosed in other continents are due to importation of the virus through travel in this EVD outbreak. Those who have fever at the
L. Liu et al. / Journal of Virological Methods 222 (2015) 62–65
time of entry from the affected areas are being admitted to special facilities and tested. It is expected that the preventive measures will ensure the safety of our population as effectively as during the SARS epidemic and avian influenza. Therefore, developing a rapid diagnostic method for detecting Zaire Ebola virus is an urgent priority for controlling the spread of this disease. Although many documents about real-time RT-PCR assays for Ebola virus have already published (Drosten et al., 2002; Towner et al., 2004; Weidmann et al., 2004; Huang et al., 2012; Fajfr et al., 2014), the study has showed he ‘Guinea strain’ is a variant of the Zaire Ebola virus (Gire et al., 2014). Otherwise, all assays lack of internal control to monitor the whole process of detection. In this study, we describe a sensitive and specific real-time reverse transcription-polymerase chain reaction (rRT-PCR) assay that was developed for the detection of Zaire Ebola virus and report its use in a survey of more than 315 samples from persons diagnosed with probable EVD during the 2014 epidemic in Sierra Leone.
1. Study PCR primers and probes were designed using Primer Express Software (Applied Biosystems, Foster City, CA) based on an alignment of all previously published Zaire Ebola virus nucleoprotein (NP) gene sequences. The specific primers and probe set for NP gene was as follows: forward primer (KJ660348.2, nt 1394–1431), 5 -GAGCATGGTCTTTTCCCTCA-3 , reverse primer (KJ660348.2, nt 1554–1535), 5 -TCGCGAGACTCTGCATATTG-3 and probe (KJ660348.2, nt 1437–1456), 5 -FAM-TCGCCACAGCACACGGGAGTBQH1-3 . The probe was labeled with the reporter FAM (6-carboxyfluorescein) and the quencher BHQ1. The human ribonucleoprotein gene was employed as internal control (Forward primer: 5 -AGATTTGGACCTGCGTAGCG-3 , Reverse primer: 5 -GAGCGGCTGTCTCCACAAGT-3 , Probe: VIC 5 -TTCTGACCTGAAGGCTCTGCGCG-BHQ1-3 ). Primers and probes were synthesized by BGI (Beijing Genomics Institute, Beijing, China). A calibration standard was generated by diluting RNA transcription of Zaire Ebola virus partial NP gene. The fragment of NP gene was synthesized based on the published sequence of NP gene of Zaire Ebola virus (GenBank accession no. KF827427, nt 1191–1790) by BGI (Beijing Genomics Institute, Beijing, China). The resulting products were cloned into a pGEM-T Easy vector (Promega Shanghai, Shanghai, China) and linearized using a specific DNA restriction enzyme. RNA was generated by in vitro transcription of the linearized plasmid DNA using the RiboMax Express Large-Scale RNA Production System, according to the manufacturer’s instructions (Promega, Madison, WI, USA). After digestion of the template DNA with RNase-free DNase I, the transcribed RNA was purified with an RNeasy kit (Qiagen GmbH, Hilden, Germany). The purified RNA was quantified spectrophotometrically at 260 nm, divided into aliquots, and stored at −80 ◦ C for future use. Ten-fold serial dilutions of transcribed NP RNA (5 × 107 to 5 copies/l) and two-fold serial dilutions of transcribed NP RNA (5 to 0.625 copies/l) were subjected to rRT-PCR analyses. To evaluate cross-reaction with other close-phylogenic viruses of the family Filoviridae, RNA transcriptions of partial NP genes from Sudan ebolavirus (GenBank accession no. KC242783.2, nt 1131–1730), Reston ebolavirus (GenBank accession no. JX477165.1, nt 1171–1770), Taï Forest ebolavirus (GenBank accession no. NC 014372, nt 1181–1790), Bundibugyo ebolavirus (GenBank accession no. NC 014373, nt 1181–1790) and Marburg marburgvirus (MARV) (GenBank accession no. NC 001608, nt 821–1420) were tested. All RNA transcriptions were prepared as described above and diluted to approximately 106 copies/ml, respectively. The following 7 viruses were kindly provided by the Academy of Military Medical Science and Center for Disease Control and
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Prevention of Henan: Dengue viruses (DENV-1, DENV-2, DENV3 and DENV-4), Japanese encephalitis virus (JEV), Hantan virus and FTLS-bunyavirus. All virus concentrations were determined using Real-time Fluorescence Quantitative PCR after diluting samples to approximately 106 copies/ml (Bai et al., 2008; Huang et al., 2013; Yang et al., 2004). Total RNA was extracted from 100 l viral culture supernatant using a QIAamp Viral RNA Mini Kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer’s instruction. RNA was eluted from the columns with 50 l diethyl pyrocarbonate (DEPC)-treated water containing 1 U DNase I. Samples were incubated at 37 ◦ C for 15 min to eliminate human DNA, and then the DNase was inactivated by incubating at 95 ◦ C for 10 min. Clinical materials, including 49 throat swabs and 266 whole blood samples, were supplied by Ministry of Health and Sanitation. All persons had a diagnosis of suspected EVD according to World Health Organization (WHO) criteria. They all characterized with fever, diarrhea, vomiting, or hemorrhage and had contact with a confirmed or probable Ebola case. All patients provided written informed consent for the research use of their samples. This research was approved by the Review Board of the Institute of Microbiology and Epidemiology, Beijing Institute of Genomics, the National Institutes for Food and Drug Control, and Ministry of Health and Sanitation. Forty-six throat swabs were collected from died patients. 100 sera from Dengue Fever (100 samples), 50 sera from JEV (50 samples), 50 plasma from Hantan and 50 sera from FTLS patients were also involved, which collected from Guangzhou CDC and Henan CDC. For analysis of throat swab samples, the swabs were washed in 1 ml of phosphate-buffered saline (PBS), and centrifuged for 5 min at 3000 × g, 4 ◦ C. Supernatant was collected for RNA extraction and PCR analysis. For analysis of blood samples, whole blood was centrifuged for 5 min at 3000 × g, 4 ◦ C. Plasma was collected for RNA extraction and PCR analysis. Sera and plasma were directly used for RNA extraction. Total RNA was extracted from 100 l samples using a QIAamp Viral RNA Mini Kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer’s instruction. On receipt of the suspected EVD specimen, prior to any manipulation of the specimen, some aliquots were removed in a type III biological safety cabinet for analysis. RRT-PCR was performed in 20-l reaction volumes containing 4 l of the RNA dilution, 10 l 2× Taqman One-Step RT-PCR Master Mix Reagents (ABI 4309169; Applied Biosystems), 0.5 l 40× MultiScribe and RNase inhibitor mixture, 0.25 M forward primer, 0.25 M reverse primer, and 0.125 M probe using a fluorometric PCR instrument (ABI 7300; Applied Biosystems). Thermal cycling parameters were 30 min at 42 ◦ C followed by 10 min at 95 ◦ C and a 40 cycles of amplification (95 ◦ C for 15 s and 58 ◦ C for 45 s); fluorescence was collected during the 58 ◦ C step. Standard curves of serially diluted RNA transcripts versus threshold cycle were generated to determine both the efficiency of the rRT-PCR and the limit of detection. The assay exhibited a wide linear range, beginning at 20 copies of target RNA per reaction and extending through 2 × 107 copies/reaction (R2 = 0.9991) for the assay. To determine the detection limit of the assay, two-fold serial dilutions of transcribed NP RNA (5 to 0.625 copies/l) were tested 20 times, respectively. The detection rate of approximately 10 copies per reaction in the assay was 100% and lower dilutions could not be effectively detected. To evaluate the specificity of our assay, NP RNA transcription of 5 close-phylogenic viruses and 7 viruses which could result in fever or hemorrhagic fever were tested. No cross-reaction of the assay with any of the 11 viruses was observed. To further evaluate the specificity, 250 sera or plasma from patients were tested, including 100 from patients infected with Dengue viruses, 50 from patients infected with FTLS-virus, 50 from patients infected with JEV, and 50 from patients infected with Hantan virus. All blood samples tested negative, but all samples
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L. Liu et al. / Journal of Virological Methods 222 (2015) 62–65
Table 1 Summary of clinical samples by rRT-PCR. Specimens
Blood Swab
Total patients
266 49
1–7 d
8–14 d
15–21 d
>21 d
pos
neg
pos
neg
pos
neg
pos
neg
142 26
37 2
57 16
23 3
6 2
3 0
2 NA
6 NA
pos, positive; neg, negative; rRT-PCR, real-time reverse transcription polymerase chain reaction; NA, not available.
tested positive using ribonucleoprotein, which was employed as a control to monitor the whole process of detection. Materials from persons who had probable EVD included 266 blood samples and 49 swab samples. The detection rate in blood samples was 77.81% (207/266), and there were relatively higher detection rate (79.32% and 81.42%, respectively) during the first two weeks after onset of symptoms (Table 1). In the two weeks that followed, the detection rate declined to 66.67% and 25.00%, respectively, but even after 29 days, one sample gave a positive reading. Results also showed that virus loads were the highest at the first week and then decreased (Fig. 1A), while virus loads have not regular change between 1st and 8th day after onset of symptoms, while late 8th day after onset of symptoms, the virus loads significantly decrease (Fig. 1B). The pair samples from 16 patients were tested and the results also showed this index and virus loads were higher during the early phrase (Table 2). A similar
change of virus loads was observed in the analysis of swab samples (Fig. 1A). A higher detection rate of 89.79% (44/49) was obtained in swab samples. This may be benefit from the included patients. 46 of 49 swab samples were collected from died patients. The patients were employed according to the clinical symptoms including fever, diarrhea, vomiting and hemorrhage. However, fewer patients have the symptom of hemorrhage in this epidemic. Maybe some patients infected with other diseases with similar symptoms were involved. We also found there seem to be higher detection rate in blood samples (note that only 3 of the samples were matched for blood and swabs). These three blood samples and swab samples were collected at the same day. All blood samples tested positive (Ct value: 21.91, 32.54, 35.66, respectively) while only one swab tested positive (Ct value: 24.06, neg, neg, respectively). Moreover, it has lower virus loads than that in the blood sample.
Fig. 1. Virus loads variation with time after onset of symptoms. (A) Average virus loads in different week after onset of symptoms in blood and swab samples (n ≥ 6). (B) Average virus loads in different day after onset of symptoms in blood samples (n ≥ 6).
L. Liu et al. / Journal of Virological Methods 222 (2015) 62–65
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Table 2 Demographic and virologic characteristics of 16 patients with confirmed Ebola virus disease during the 2014 outbreak in Sierra Leone. Patient no.
Sex
Age (yr)
Date of symptom onset
Date of the first specimen collection (virus loads)a
Date of the second specimen collection (virus loads)a
Date of the third specimen collection (virus loads)a
Outcome
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
F M M M F F M M M F F M F F M F
35 55 50 36 14 25 20 11 18 27 20 29 18 27 19 18
27-Sep 2-Oct 28-Sep 29-Sep 10-Oct 8-Oct 6-Oct 9-Oct 9-Oct 8-Oct 10-Oct 15-Oct 16-Oct 15-Oct 18-Oct 6-Oct
29-Sep (2.44E+06) 5-Oct (6.40E+02) 6-Oct (2.77E+07) 9-Oct (2.67E+05) 13-Oct (4.61E+05) 13-Oct (1.11E+07) 13-Oct (1.01E+06) 14-Oct (1.65E+08) 14-Oct (5.26E+07) 15-Oct (1.12E+05) 16-Oct (3.08E+07) 17-Oct (1.47E+05) 17-Oct (5.08E+04) 20-Oct (7.01E+06) 21-Oct (5.64E+07) 21-Oct (1.70E+05)
25-Oct (N) 11-Oct (N) 14-Oct (N) 16-Oct (3.87E+03) 16-Oct (1.09E+08) 16-Oct (9.93E+04) 17-Oct (N) 16-Oct (2.05E+07) 24-Oct (N) 18-Oct (9.39E+03) 24-Oct (N) 21-Oct (4.30E+03) 20-Oct (2.20E+08) 24-Oct (5.68E+03) 25-Oct (3.64E+05) 25-Oct (N)
NA NA NA 24-Oct (N) NA NA NA NA NA NA NA NA NA NA NA NA
Survived Survived Survived Survived Died Died Survived ND Survived ND Survived ND ND ND ND Survived
Entries in bold denote that the virus loads were rising during the early phrase. NA, not available; N, undetectable; ND, denotes not determined. a Determined by rRT-PCR.
Although rRT-PCR analysis of blood was a less sensitive index of infection at later time points (21–29 days after onset of symptoms), our findings indicate that long-term monitoring may be required to control dissemination of disease. Taken together, the results presented here indicate that the assay specifically and sensitively detects Zaire Ebola virus. Acknowledgments The work was supported by grants from the Infectious Diseases Special Project (2013ZX10004802, 2013ZX10004803), the National Hi-Tech Research and Development (863) Program of China (2012AA022006), funded by the Ministry of Science and Technology of China. References Baize, S., Pannetier, D., Oestereich, L., Rieger, T., Koivogui, L., Magassouba, N., Soropogui, B., Sow, M.S., Keïta, S., De Clerck, H., Tiffany, A., Dominguez, G., Loua, M., Traoré, A., Kolié, M., Malano, E.R., Heleze, E., Bocquin, A., Mély, S., Raoul, H., Caro, V., Cadar, D., Gabriel, M., Pahlmann, M., Tappe, D., Schmidt-Chanasit, J., Impouma, B., Diallo, A.K., Formenty, P., Van Herp, M., Günther, S., 2014. Emergence of Zaire Ebola virus disease in Guinea. N. Engl. J. Med. 371 (15), 1418–1425, http://dx. doi.org/10.1056/NEJMoa1404505 Bai, Z.J., Liu, L.C., Tu, Z., Yao, L.S., Liu, J.W., Xu, B., Tang, B.H., Liu, J.H., Wan, Y.J., Fang, M.Y., Chen, W.J., 2008. Real-time PCR for detecting circulating dengue virus in the Guangdong Province of China in 2006. J. Med. Microbiol. 57, 1547–1552. Drosten, C., Göttig, S., Schilling, S., Asper, M., Panning, M., Schmitz, H., Günther, S., 2002. Rapid detection and quantification of RNA of Ebola and Marburg viruses, Lassa virus, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus, dengue virus, and yellow fever virus by real-time reverse transcription-PCR. J. Clin. Microbiol. 40 (7), 2323–2330. ˚ zek, D., 2014. Detection panel for Fajfr, M., Neubauerová, V., Pajer, P., Kubíˇcková, P., Ruˇ identification of twelve hemorrhagic viruses using real-time RT-PCR. Epidemiol. Mikrobiol. Imunol. 63 (3), 238–244.
Gire, S.K., Goba, A., Andersen, K.G., Sealfon, R.S., Park, D.J., Kanneh, L., Jalloh, S., Momoh, M., Fullah, M., Dudas, G., Wohl, S., Moses, L.M., Yozwiak, N.L., Winnicki, S., Matranga, C.B., Malboeuf, C.M., Qu, J., Gladden, A.D., Schaffner, S.F., Yang, X., Jiang, P.P., Nekoui, M., Colubri, A., Coomber, M.R., Fonnie, M., Moigboi, A., Gbakie, M., Kamara, F.K., Tucker, V., Konuwa, E., Saffa, S., Sellu, J., Jalloh, A.A., Kovoma, A., Koninga, J., Mustapha, I., Kargbo, K., Foday, M., Yillah, M., Kanneh, F., Robert, W., Massally, J.L., Chapman, S.B., Bochicchio, J., Murphy, C., Nusbaum, C., Young, S., Birren, B.W., Grant, D.S., Scheiffelin, J.S., Lander, E.S., Happi, C., Gevao, S.M., Gnirke, A., Rambaut, A., Garry, R.F., Khan, S.H., Sabeti, P.C., 2014. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science 345, 1369–1372, http://dx.doi.org/10.1126/science.1259657 Huang, X.Y., Liu, L.C., Du, Y.H., Ma, H.X., Mu, Y.J., Wang, P.Z., Ma, H., Tang, X.Y., Wang, H.F., Kang, K., Zhang, S.Q., Wu, W.L., Chen, H.M., Liu, G.H., Yang, Y.H., Jiang, Y.Q., Xu, B.L., Chen, W.J., 2013. Detection of a novel bunyavirus associated with fever, thrombocytopenia and leukopenia syndrome in Henan Province, China, using real-time reverse transcription PCR. J. Med. Microbiol. 62, 1060–1064. Huang, Y., Wei, H., Wang, Y., Shi, Z., Raoul, H., Yuan, Z., 2012. Rapid detection of filoviruses by real-time TaqMan polymerase chain reaction assays. Virol. Sin. 27 (5), 273–277. Kuhn, J.H., Dodd, L.E., Wahl-Jensen, V., Radoshitzky, S.R., Bavari, S., Jahrling, P.B., 2011. Evaluation of perceived threat differences posed by filovirus variants. Biosecur. Bioterror. 9, 361–371. Kuhn, J.H., Stephan, B., Hideki, E., Thomas, W.G., Karl, M.J., Yoshihiro, K., Ian, W.L., Ana, I.N., 2010. Proposal for a revised taxonomy of the family Filoviridae: classification, names of taxa and viruses, and virus abbreviations. Arch. Virol. 155, 2083–2103. Towner, J.S., Rollin, P.E., Bausch, D.G., Sanchez, A., Crary, S.M., Vincent, M., Lee, W.F., Spiropoulou, C.F., Ksiazek, T.G., Lukwiya, M., Kaducu, F., Downing, R., Nichol, S.T., 2004. Rapid diagnosis of Ebola hemorrhagic fever by reverse transcription-PCR in an outbreak setting and assessment of patient viral load as a predictor of outcome. J. Virol. 78 (8), 4330–4341. Weidmann, M., Mühlberger, E., Hufert, F.T., 2004. Rapid detection protocol for filoviruses. J. Clin. Virol. 30 (1), 94–99. WHO, 2014. Ebola Response Roadmap Situation Report, http://apps.who.int/ (accessed iris/bitstream/10665/144806/1/roadmapsitrep 3Dec2014 eng.pdf 03.12.14). Yang, D.K., Kweon, C.H., Kim, B.H., Lim, S.I., Kim, S.H., Kwon, J.H., Han, H.R., 2004. TaqMan reverse transcription polymerase chain reaction for the detection of Japanese encephalitis virus. J. Vet. Sci. 5 (4), 345–351.
Contents lists available at ScienceDirect
Journal of Virological Methods journal homepage: www.elsevier.com/locate/jviromet
Detection of Zaire Ebola virus by real-time reverse transcription-polymerase chain reaction, Sierra Leone, 2014 Licheng Liu a,1 , Yang Sun b,1 , Brima Kargbo c,1 , Chuntao Zhang d , Huahua Feng e , Huijun Lu b , Wenseng Liu b , Chengyu Wang b , Yi Hu b , Yongqiang Deng b , Jiafu Jiang b , Xiaoping Kang a , Honglei Yang e , Yongqiang Jiang a , Yinhui Yang a , David Kargbo c,∗ , Jun Qian b,∗∗ , Weijun Chen e,f,∗ ∗ ∗ a State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Dongdajie Road 20, Beijing 100071, China b The China Mobile Laboratory Testing Team in Sierra Leone, Sierra Leone c Ministry of Health and Sanitation, Freetown, Sierra Leone d National Institutes for Food and Drug Control, Beijing 100050, China e Beijing BGI-GBI Biotech Co., Ltd, Beijing 101300, China f CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, No. 1 Beichen West Road, Chaoyang District, Beijing 100101, China
a b s t r a c t Article history: Received 12 December 2014 Received in revised form 23 April 2015 Accepted 12 May 2015 Available online 27 May 2015 Keywords: Ebola virus disease Zaire Ebola virus Real-time reverse transcription polymerase chain reaction (rRT-PCR)
During the 2014 Ebola virus disease (EVD) outbreak, a real-time quantitative polymerase chain reaction was established to detect and identify the Zaire Ebola virus. We describe the use of this assay to screen 315 clinical samples from EVD suspected person in Sierra Leone. The detection rate in blood samples was 77.81% (207/266), and there were relatively higher detection rate (79.32% and 81.42%, respectively) during the first two weeks after onset of symptoms. In the two weeks that followed, the detection rate declined to 66.67% and 25.00%, respectively. There was the highest virus load at the first week and then decreased. The detection rate in swab samples was 89.79% (44/49). This may be benefit from the included patients. 46 of 49 swab samples were collected from died patients. Taken together, the results presented here indicate that the assay specifically and sensitively detects Zaire Ebola virus. © 2015 Elsevier B.V. All rights reserved.
The re-emergence of Ebola in 2013 leading to an epidemic in West Africa which is still ongoing in 2014, and has resulted in at least 17,145 suspected cases and 6070 confirmed deaths (WHO, 2014). The story of the current outbreak began in Gueckedouin (Guinea) where, on 6 December 2013, a 2-year-old boy was affected (Baize et al., 2014; Gire et al., 2014). What differentiates this outbreak from the previous ones is not only its magnitude (past outbreaks resulted in a maximum of a few hundred cases), but also
∗ Corresponding author. ∗∗ Corresponding author at: Institute of Military Veterinary, AMMS, Key Laboratory of Jilin Province for Zoonosis Prevention and Control, Changchun, China. ∗ ∗ ∗Corresponding author at: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, No. 1 Beichen West Road, Chaoyang District, Beijing 100101, China. Tel.: +86 10 80485404; fax: +86 10 80485404. E-mail addresses: [email protected] (D. Kargbo), [email protected] (J. Qian), [email protected] (W. Chen). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.jviromet.2015.05.005 0166-0934/© 2015 Elsevier B.V. All rights reserved.
its first ever appearance in west African countries (Guinea, Liberia, Sierra Leone and Nigeria). The ‘Guinea strain’ is a variant of the Zaire Ebola virus, but hemorrhagic manifestations are not as apparent this time around (Baize et al., 2014; Gire et al., 2014). The mortality also seems to be lower than usual, at (a still very high) 50–55% (Kuhn et al., 2011; WHO, 2014). Zaire Ebola virus is one of five known viruses within the genus Ebolavirus (Kuhn et al., 2010). Zaire Ebola virus causes a hemorrhagic fever in the humans and some other nonhuman primates. Exceptionally, in swine, Zaire Ebola virus causes a respiratory disease. It has been known as Ebola virus disease (EVD). The Ebola virus is transmitted only through close and direct contact with the blood or body fluids of human cases or affected animals. Aerosol transmission has not been reported. All these factors restrict its spread and it is unlikely that even a traveler to affected areas would be exposed to such situations, unless he visits a hospital or attends a funeral. No indigenous cases have been reported outside West Africa and cases diagnosed in other continents are due to importation of the virus through travel in this EVD outbreak. Those who have fever at the
L. Liu et al. / Journal of Virological Methods 222 (2015) 62–65
time of entry from the affected areas are being admitted to special facilities and tested. It is expected that the preventive measures will ensure the safety of our population as effectively as during the SARS epidemic and avian influenza. Therefore, developing a rapid diagnostic method for detecting Zaire Ebola virus is an urgent priority for controlling the spread of this disease. Although many documents about real-time RT-PCR assays for Ebola virus have already published (Drosten et al., 2002; Towner et al., 2004; Weidmann et al., 2004; Huang et al., 2012; Fajfr et al., 2014), the study has showed he ‘Guinea strain’ is a variant of the Zaire Ebola virus (Gire et al., 2014). Otherwise, all assays lack of internal control to monitor the whole process of detection. In this study, we describe a sensitive and specific real-time reverse transcription-polymerase chain reaction (rRT-PCR) assay that was developed for the detection of Zaire Ebola virus and report its use in a survey of more than 315 samples from persons diagnosed with probable EVD during the 2014 epidemic in Sierra Leone.
1. Study PCR primers and probes were designed using Primer Express Software (Applied Biosystems, Foster City, CA) based on an alignment of all previously published Zaire Ebola virus nucleoprotein (NP) gene sequences. The specific primers and probe set for NP gene was as follows: forward primer (KJ660348.2, nt 1394–1431), 5 -GAGCATGGTCTTTTCCCTCA-3 , reverse primer (KJ660348.2, nt 1554–1535), 5 -TCGCGAGACTCTGCATATTG-3 and probe (KJ660348.2, nt 1437–1456), 5 -FAM-TCGCCACAGCACACGGGAGTBQH1-3 . The probe was labeled with the reporter FAM (6-carboxyfluorescein) and the quencher BHQ1. The human ribonucleoprotein gene was employed as internal control (Forward primer: 5 -AGATTTGGACCTGCGTAGCG-3 , Reverse primer: 5 -GAGCGGCTGTCTCCACAAGT-3 , Probe: VIC 5 -TTCTGACCTGAAGGCTCTGCGCG-BHQ1-3 ). Primers and probes were synthesized by BGI (Beijing Genomics Institute, Beijing, China). A calibration standard was generated by diluting RNA transcription of Zaire Ebola virus partial NP gene. The fragment of NP gene was synthesized based on the published sequence of NP gene of Zaire Ebola virus (GenBank accession no. KF827427, nt 1191–1790) by BGI (Beijing Genomics Institute, Beijing, China). The resulting products were cloned into a pGEM-T Easy vector (Promega Shanghai, Shanghai, China) and linearized using a specific DNA restriction enzyme. RNA was generated by in vitro transcription of the linearized plasmid DNA using the RiboMax Express Large-Scale RNA Production System, according to the manufacturer’s instructions (Promega, Madison, WI, USA). After digestion of the template DNA with RNase-free DNase I, the transcribed RNA was purified with an RNeasy kit (Qiagen GmbH, Hilden, Germany). The purified RNA was quantified spectrophotometrically at 260 nm, divided into aliquots, and stored at −80 ◦ C for future use. Ten-fold serial dilutions of transcribed NP RNA (5 × 107 to 5 copies/l) and two-fold serial dilutions of transcribed NP RNA (5 to 0.625 copies/l) were subjected to rRT-PCR analyses. To evaluate cross-reaction with other close-phylogenic viruses of the family Filoviridae, RNA transcriptions of partial NP genes from Sudan ebolavirus (GenBank accession no. KC242783.2, nt 1131–1730), Reston ebolavirus (GenBank accession no. JX477165.1, nt 1171–1770), Taï Forest ebolavirus (GenBank accession no. NC 014372, nt 1181–1790), Bundibugyo ebolavirus (GenBank accession no. NC 014373, nt 1181–1790) and Marburg marburgvirus (MARV) (GenBank accession no. NC 001608, nt 821–1420) were tested. All RNA transcriptions were prepared as described above and diluted to approximately 106 copies/ml, respectively. The following 7 viruses were kindly provided by the Academy of Military Medical Science and Center for Disease Control and
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Prevention of Henan: Dengue viruses (DENV-1, DENV-2, DENV3 and DENV-4), Japanese encephalitis virus (JEV), Hantan virus and FTLS-bunyavirus. All virus concentrations were determined using Real-time Fluorescence Quantitative PCR after diluting samples to approximately 106 copies/ml (Bai et al., 2008; Huang et al., 2013; Yang et al., 2004). Total RNA was extracted from 100 l viral culture supernatant using a QIAamp Viral RNA Mini Kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer’s instruction. RNA was eluted from the columns with 50 l diethyl pyrocarbonate (DEPC)-treated water containing 1 U DNase I. Samples were incubated at 37 ◦ C for 15 min to eliminate human DNA, and then the DNase was inactivated by incubating at 95 ◦ C for 10 min. Clinical materials, including 49 throat swabs and 266 whole blood samples, were supplied by Ministry of Health and Sanitation. All persons had a diagnosis of suspected EVD according to World Health Organization (WHO) criteria. They all characterized with fever, diarrhea, vomiting, or hemorrhage and had contact with a confirmed or probable Ebola case. All patients provided written informed consent for the research use of their samples. This research was approved by the Review Board of the Institute of Microbiology and Epidemiology, Beijing Institute of Genomics, the National Institutes for Food and Drug Control, and Ministry of Health and Sanitation. Forty-six throat swabs were collected from died patients. 100 sera from Dengue Fever (100 samples), 50 sera from JEV (50 samples), 50 plasma from Hantan and 50 sera from FTLS patients were also involved, which collected from Guangzhou CDC and Henan CDC. For analysis of throat swab samples, the swabs were washed in 1 ml of phosphate-buffered saline (PBS), and centrifuged for 5 min at 3000 × g, 4 ◦ C. Supernatant was collected for RNA extraction and PCR analysis. For analysis of blood samples, whole blood was centrifuged for 5 min at 3000 × g, 4 ◦ C. Plasma was collected for RNA extraction and PCR analysis. Sera and plasma were directly used for RNA extraction. Total RNA was extracted from 100 l samples using a QIAamp Viral RNA Mini Kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer’s instruction. On receipt of the suspected EVD specimen, prior to any manipulation of the specimen, some aliquots were removed in a type III biological safety cabinet for analysis. RRT-PCR was performed in 20-l reaction volumes containing 4 l of the RNA dilution, 10 l 2× Taqman One-Step RT-PCR Master Mix Reagents (ABI 4309169; Applied Biosystems), 0.5 l 40× MultiScribe and RNase inhibitor mixture, 0.25 M forward primer, 0.25 M reverse primer, and 0.125 M probe using a fluorometric PCR instrument (ABI 7300; Applied Biosystems). Thermal cycling parameters were 30 min at 42 ◦ C followed by 10 min at 95 ◦ C and a 40 cycles of amplification (95 ◦ C for 15 s and 58 ◦ C for 45 s); fluorescence was collected during the 58 ◦ C step. Standard curves of serially diluted RNA transcripts versus threshold cycle were generated to determine both the efficiency of the rRT-PCR and the limit of detection. The assay exhibited a wide linear range, beginning at 20 copies of target RNA per reaction and extending through 2 × 107 copies/reaction (R2 = 0.9991) for the assay. To determine the detection limit of the assay, two-fold serial dilutions of transcribed NP RNA (5 to 0.625 copies/l) were tested 20 times, respectively. The detection rate of approximately 10 copies per reaction in the assay was 100% and lower dilutions could not be effectively detected. To evaluate the specificity of our assay, NP RNA transcription of 5 close-phylogenic viruses and 7 viruses which could result in fever or hemorrhagic fever were tested. No cross-reaction of the assay with any of the 11 viruses was observed. To further evaluate the specificity, 250 sera or plasma from patients were tested, including 100 from patients infected with Dengue viruses, 50 from patients infected with FTLS-virus, 50 from patients infected with JEV, and 50 from patients infected with Hantan virus. All blood samples tested negative, but all samples
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Table 1 Summary of clinical samples by rRT-PCR. Specimens
Blood Swab
Total patients
266 49
1–7 d
8–14 d
15–21 d
>21 d
pos
neg
pos
neg
pos
neg
pos
neg
142 26
37 2
57 16
23 3
6 2
3 0
2 NA
6 NA
pos, positive; neg, negative; rRT-PCR, real-time reverse transcription polymerase chain reaction; NA, not available.
tested positive using ribonucleoprotein, which was employed as a control to monitor the whole process of detection. Materials from persons who had probable EVD included 266 blood samples and 49 swab samples. The detection rate in blood samples was 77.81% (207/266), and there were relatively higher detection rate (79.32% and 81.42%, respectively) during the first two weeks after onset of symptoms (Table 1). In the two weeks that followed, the detection rate declined to 66.67% and 25.00%, respectively, but even after 29 days, one sample gave a positive reading. Results also showed that virus loads were the highest at the first week and then decreased (Fig. 1A), while virus loads have not regular change between 1st and 8th day after onset of symptoms, while late 8th day after onset of symptoms, the virus loads significantly decrease (Fig. 1B). The pair samples from 16 patients were tested and the results also showed this index and virus loads were higher during the early phrase (Table 2). A similar
change of virus loads was observed in the analysis of swab samples (Fig. 1A). A higher detection rate of 89.79% (44/49) was obtained in swab samples. This may be benefit from the included patients. 46 of 49 swab samples were collected from died patients. The patients were employed according to the clinical symptoms including fever, diarrhea, vomiting and hemorrhage. However, fewer patients have the symptom of hemorrhage in this epidemic. Maybe some patients infected with other diseases with similar symptoms were involved. We also found there seem to be higher detection rate in blood samples (note that only 3 of the samples were matched for blood and swabs). These three blood samples and swab samples were collected at the same day. All blood samples tested positive (Ct value: 21.91, 32.54, 35.66, respectively) while only one swab tested positive (Ct value: 24.06, neg, neg, respectively). Moreover, it has lower virus loads than that in the blood sample.
Fig. 1. Virus loads variation with time after onset of symptoms. (A) Average virus loads in different week after onset of symptoms in blood and swab samples (n ≥ 6). (B) Average virus loads in different day after onset of symptoms in blood samples (n ≥ 6).
L. Liu et al. / Journal of Virological Methods 222 (2015) 62–65
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Table 2 Demographic and virologic characteristics of 16 patients with confirmed Ebola virus disease during the 2014 outbreak in Sierra Leone. Patient no.
Sex
Age (yr)
Date of symptom onset
Date of the first specimen collection (virus loads)a
Date of the second specimen collection (virus loads)a
Date of the third specimen collection (virus loads)a
Outcome
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
F M M M F F M M M F F M F F M F
35 55 50 36 14 25 20 11 18 27 20 29 18 27 19 18
27-Sep 2-Oct 28-Sep 29-Sep 10-Oct 8-Oct 6-Oct 9-Oct 9-Oct 8-Oct 10-Oct 15-Oct 16-Oct 15-Oct 18-Oct 6-Oct
29-Sep (2.44E+06) 5-Oct (6.40E+02) 6-Oct (2.77E+07) 9-Oct (2.67E+05) 13-Oct (4.61E+05) 13-Oct (1.11E+07) 13-Oct (1.01E+06) 14-Oct (1.65E+08) 14-Oct (5.26E+07) 15-Oct (1.12E+05) 16-Oct (3.08E+07) 17-Oct (1.47E+05) 17-Oct (5.08E+04) 20-Oct (7.01E+06) 21-Oct (5.64E+07) 21-Oct (1.70E+05)
25-Oct (N) 11-Oct (N) 14-Oct (N) 16-Oct (3.87E+03) 16-Oct (1.09E+08) 16-Oct (9.93E+04) 17-Oct (N) 16-Oct (2.05E+07) 24-Oct (N) 18-Oct (9.39E+03) 24-Oct (N) 21-Oct (4.30E+03) 20-Oct (2.20E+08) 24-Oct (5.68E+03) 25-Oct (3.64E+05) 25-Oct (N)
NA NA NA 24-Oct (N) NA NA NA NA NA NA NA NA NA NA NA NA
Survived Survived Survived Survived Died Died Survived ND Survived ND Survived ND ND ND ND Survived
Entries in bold denote that the virus loads were rising during the early phrase. NA, not available; N, undetectable; ND, denotes not determined. a Determined by rRT-PCR.
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