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. 2020 Apr 22;127:104381. doi: 10.1016/j.jcv.2020.104381

Ad hoc laboratory-based surveillance of SARS-CoV-2 by real-time RT-PCR using minipools of RNA prepared from routine respiratory samples

Anna M Eis-Hübinger a, Mario Hönemann b, Jürgen J Wenzel c, Annemarie Berger d, Marek Widera d, Barbara Schmidt c, Souhaib Aldabbagh a, Benjamin Marx a, Hendrik Streeck a, Sandra Ciesek d, Uwe G Liebert b, Daniela Huzly e, Hartmut Hengel e, Marcus Panning e,*
PMCID: PMC7175872  PMID: 32344319

Highlights

  • A laboratory-based surveillance tool for SARS-CoV-2 was established.

  • It consists of minipool testing of nucleic acid preparations.

  • Limit of detection was 48 copies per reaction (95 % confidence interval: 33–184).

  • A protocol was distributed among five German university hospitals.

  • The approach proved its principle and one COVID-19 case was detected in 70 minipools.

Keywords: SARS-CoV-2, RT-PCR, Minipools, Surveillance, Laboratory

Abstract

Background

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China in late 2019 and subsequently caused a pandemic. Surveillance is important to better appreciate this evolving pandemic and to longitudinally monitor the effectiveness of public health measures.

Objectives

We aimed to provide a rapid, easy to establish and costeffective laboratory-based surveillance tool for SARS-CoV-2. Study design: We used minipools of RNA prepared from nucleic acid extractions of routine respiratory samples. We technically validated the assay and distributed the protocol within an informal network of five German university laboratories.

Results

We tested a total of 70 minipools resembling 700 samples shortly before the upsurge of cases in Germany from 17.02.2020 to 10.03.2020. One minipool reacted positive and after resolution one individual sample tested SARS-CoV-2 positive. This sample was from a hospitalized patient not suspected of having contracted SARS-CoV-2.

Conclusions

Our approach of a laboratory-based surveillance for SARSCoV-2 using minipools proved its concept is easily adaptable and resource-saving. It might assist not only public health laboratories in SARS-CoV-2 surveillance.

1. Background

As of 11 March 2020, WHO declared COVID-19 a pandemic [1]. Early case detection is crucial to contain the pandemic and symptom-based case definitions have been set up in many countries worldwide. However, there is evidence that transmission chains can be initiated by asymptomatic cases or only mildly diseased COVID-19 patients [2]. These cases will be missed by currently recommended symptom-based case definitions and may lead to unrecognized local spread, which has been seen in Italy, Iran and more recently in the US. To limit the pandemic an aggressive public health response has been set up in many countries worldwide. However, a resurgence of cases is anticipated whenever the strict public health isolation measures will be lifted. Therefore, one of the biggest challenges and unresolved issues for public health will be the surveillance and rapid identification of SARS-CoV-2 in the time between epidemic peaks.

2. Objectives

To rapidly identify unrecognized cases in hospitals in an efficient, resource-saving and cost effective manner we propose an ad hoc laboratory-based surveillance approach for SARS-CoV-2. It is based upon minipool (MP) testing of nucleic acid preparations of respiratory samples submitted to laboratories for routine diagnostics.

3. Study design

The workflow comprises individual nucleic acid (NA) extraction of respiratory samples, pooling of extracted NA samples in batches of 10 and SARS-CoV-2 specific real-time RT-PCR. In a first step, we analyzed the impact of minipool (MP) testing in batches of 10 samples per pool. Nucleic acid was extracted from 200 μL respiratory specimen (pharyngeal swabs in viral transport medium, sputum, broncho-alveolar lavage fluid) using the MinElute Virus kit (Qiagen, Hilden, Germany) on the QIAcube system as recommended. Elution was done in a volume of 100 μL. For setting up MP, 5 μL of each individual NA preparation was combined in pools of 10 (dilution factor of 10). We retrieved 40 left-over NA preparations of respiratory samples from 2019 representing a variety of non-SARS-CoV-2 viruses from our local biobank in Freiburg and set up MP. We tested four MP using the same RT-PCR as for individual patient testing as described [3]. To exclude possible unspecific reactions of the MP procedure these MP were also tested using the SARS-CoV-2 specific real-time RT-PCR as described below. To determine the analytical sensitivity of the MP approach, we used in vitro-transcribed RNA standards for the E gene obtained by the European virus archive global (EVAg), https://www.european-virus-archive.com, and the SARS-CoV-2 E gene RT-PCR assay as described [4]. RT-PCR was done on an ABI 7500 instrument (Applied Biosystems, Weiterstadt, Germany). We spiked different in vitro-transcribed RNA concentrations in stored NA preparations of respiratory samples from 2019 and established MP. Replicate testing was done to determine the limit of detection (LOD) as described [4]. Finally, we used NA preparations from three actual SARS-CoV-2 cases in Freiburg (containing 4 × 104 copies/mL; 3.2 × 107 copies/mL; 1.6 × 107 copies/mL, respectively) and set up three MP each containing one SARS-CoV-2 positive NA preparation and retested these samples.

We distributed the workflow within an informal network of 5 German laboratories (Table 2). All sites are tertiary care centers with a total of 1.600 (site A), 1.300 (site B), 1.400 (site C), 840 beds (site D), and 1.500 (site E), respectively.

Table 2.

Number of minipools tested for SARS-CoV-2 RNA at five different sites, Germany, February – March 2020.

Laboratory site Minipools tested (n=) Individual samples (n=) SARS-CoV-2 RT-PCR positive patients (n=)
A (Freiburg) 42 420 1
B (Bonn) 6 100 0
C (Leipzig) 9 90 0
D (Regensburg) 8 80 0
E (Frankfurt) 5 70 0
Total 70 700 0

Ethical approval for this study was not required since all activities are according to legal provisions defined by the German Infection Protection Act (IfSG). All samples have been submitted for routine patient care and diagnostics and written informed consent has been obtained by each patient. All data used in the current study was anonymized prior to being obtained by the authors.

4. Results

We were able to detect all non-SARS-CoV-2 pathogens in MP which tested positive in individual RT-PCR (Table 1 ). No unspecific reactions were seen in these samples from 2019 using the SARS-CoV-2 RT-PCR. The LOD for the MP approach was 48 copies per reaction (95 % confidence interval: 33–184) (Fig. 1 ). Testing of MP spiked with SARS-CoV-2 RNA showed that except for the MP containing the lowest concentrated sample both other MP tested SARS-CoV-2 RNA positive.

Table 1.

Detection of respiratory viruses in samples using individual RT-PCR and in four minipools of 10 individual samples (A1 – A4), Freiburg, Germany, December 2019.

Patient sample Pathogen Ct-value (Individual patient analysis) Minipool Pathogen Ct-value
(Minipool analysis)
1 Influenza B virus 29 A1 Influenza B virus 25
2 negative negative
3 negative negative
4 negative negative
5 negative negative
6 negative negative
7 negative negative
8 negative negative
9 negative negative
10 negative negative
11 negative A2 negative
12 RSVa 25 RSV 29
13 negative negative
14 negative negative
15 Influenza A virus 33 Influenza A virus 34
16 negative negative
17 negative negative
18 negative negative
19 negative negative
20 negative negative
21 negative A3 negative
22 Rhinovirus, HMPVb 24, 25 Rhinovirus, HMPV 31, 30
23 negative negative
24 Adenovirus 25 Adenovirus 29
25 negative negative
26 negative negative
27 negative negative
28 RSV 32 RSV 35
29 Negative negative
30 negative negative
31 negative A4 negative
32 RSV 34 RSV >35
33 Influenza A virus 37 Influenza A virus 33
34 negative negative
35 Influenza A virus 32 Influenza A virus 29
36 negative negative
37 negative negative
38 negative negative
39 negative negative
40 HMPV 32 HMPV 34
a

RSV: respiratory syncitial virus.

b

HMPV :human metapneumovirus.

Fig. 1.

Fig. 1

Probit analysis of SARS-CoV-2 RNA detection rate (y axes) in relation to viral RNA concentration at different copy numbers per reaction (x axes).

We prospectively analyzed 42 M P comprising 420 samples using the SARS-CoV-2 E gene assay. We used all available NA samples which had been sent for routine diagnostics to the Institute of Virology in Freiburg excluding samples with a specific request for SARS-CoV-2 diagnostics from 17.02.2020 to 10.03.2020 (Fig. 2 ). One out of 42 M P tested positive. The MP was resolved and individual testing confirmed SARS-CoV-2 infection in one individual patient.

Fig. 2.

Fig. 2

Number of minipools tested by date at five sites in Germany, February-March 2020. The star indicates the first SARS-CoV-2 RNA positive minipool detected.

Invited laboratories of our informal network rapidly adopted the MP screening strategy and a total of 70 M P were tested from 17.02.2020 to 10.03.2020 (Fig. 2). At sites B to E all MP tested SARS-CoV-2 negative. Of note, site B provided another 4 M P artificially spiked with SARS-CoV-2 positive NA samples from actual cases to further validate the procedure. The Ct-values of SARS-CoV-2 RT-PCR in individual patient samples were 26, 26, 15, and 35, respectively. All artificially spiked MP tested SARS-CoV-2 positive and Ct-values were 29, 29, 18, and 38 indicating a dilution factor of 10 as expected.

5. Discussion

We report a diagnostic workflow for the laboratory-based surveillance of SARS-CoV-2 in a rapid and cost effective manner. Shortly after the identification of SARS-CoV-2 specific real-time RT-PCR protocols were set up and have been distributed worldwide [4,5]. The availability of rapid and reliable diagnostics for early case detection is instrumental in an outbreak scenario [6]. From a public health perspective an easy to establish and cost effective laboratory-based screening strategy may assist in rapid case detection, surveillance and ultimately in a better understanding of this epidemic [7]. Technically, this can be done in parallel using samples from routine diagnostics which are subsequently tested for SARS-CoV-2 RNA [8]. However, with the circulation of influenza cases across Europe merging with the upsurge of SARS-CoV-2 many laboratories may lack the capacity and resources to perform additional single patient sample testing for SARS-CoV-2. In addition, a shortage of PCR reagents has become an issue of concern as huge numbers of additional SARS-CoV-2 molecular tests are performed globally in a relatively short period of time. To minimize work load, resources and costs a pooling approach of nucleic acid extractions might be considered. We used the assay described by Corman et al. and were able to demonstrate an almost exactly 10-fold higher LOD which is due to MP related dilution factor of 10 [4]. Data from China showed SARS-CoV-2 RNA concentrations in the range of 1,5 × 104 to 1,5 × 107 copies per milliliter giving rise to the notion that the MP procedure will be sensitive enough for most clinical samples [9]. Another study of only mildly disease patients showed an average of 3,4 × 105 copies per swab. However, at the moment there is a lack of comprehensive information on viral RNA concentrations in mildly diseased or asymptomatic cases. Critically, we were not able to detect one low concentrated samples diluted into a MP, which was close to the LOD of the pooling procedure.

Networks are paramount for an efficient response to emerging infections and we aimed to provide an easy to implement workflow [4,10]. We set up an informal network and were able to test a total of 70 M P covering different geographic regions of Germany. In perspective, this approach can be set up rather easily e. g. by public health laboratories, can be done on a daily basis and at reduced costs compared to individual patient testing. It could allow for longitudinally monitoring the effectiveness of contact reduction measures at the population level and early detection of epidemic waves.

In light of an evolving SARS-CoV-2 epidemic and the possibility of unrecognized spread within the population we propose a rapid and straightforward screening strategy for SARS-CoV-2. This approach proved its principle and might assist public health laboratories in Europe and elsewhere to rapidly detect SARS-CoV-2 cases which might otherwise remain undetected.

Ethical considerations

All samples have been submitted for routine patient care and diagnostics. Ethical approval for this study was not required since all activities are according to legal provisions defined by the German Infection Protection Act (IfSG). Written informed consent has been obtained by each patient. All data used in the current study was anonymized prior to being obtained by the authors.

Funding

None.

CRediT authorship contribution statement

Anna M. Eis-Hübinger: Investigation, Data curation, Writing - review & editing. Mario Hönemann: Investigation, Formal analysis, Methodology, Writing - review & editing. Jürgen J. Wenzel: Investigation, Formal analysis, Methodology, Writing - review & editing. Annemarie Berger: Investigation, Formal analysis, Methodology, Writing - review & editing. Marek Widera: Investigation, Formal analysis, Methodology, Writing - review & editing. Barbara Schmidt: Investigation, Formal analysis, Methodology, Writing - review & editing. Souhaib Aldabbagh: Investigation, Formal analysis, Methodology, Writing - review & editing. Benjamin Marx: Investigation, Formal analysis, Methodology, Writing - review & editing. Hendrik Streeck: Investigation, Formal analysis, Methodology, Writing - review & editing. Sandra Ciesek: Investigation, Formal analysis, Methodology, Writing - review & editing. Uwe G. Liebert: Investigation, Formal analysis, Methodology, Writing - review & editing. Daniela Huzly: Investigation, Formal analysis, Methodology, Writing - review & editing. Hartmut Hengel: Investigation, Formal analysis, Methodology, Writing - review & editing. Marcus Panning: Conceptualization, Supervision, Writing - review & editing.

Declaration of Competing Interest

All authors have no conflict of interest to declare.

Acknowledgements

We are grateful to Claudia Ehret, Monika Häffner, Verena Schillinger and the team in Freiburg and the entire molecular diagnostic teams in Bonn, Frankfurt, Leipzig, and Regensburg for expert technical assistance.

References

  • 1.World Health Organization . 2020. Director-General’s Opening Remarks at the Media Briefing on COVID-19 - 11 March 2020. [Google Scholar]
  • 2.Li R., Pei S., Chen B., Song Y., Zhang T., Yang W. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2) Science. 2020 doi: 10.1126/science.abb3221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Huzly D., Korn K., Bierbaum S., Eberle B., Falcone V., Knoll A. Influenza A virus drift variants reduced the detection sensitivity of a commercial multiplex nucleic acid amplification assay in the season 2014/15. Arch. Virol. 2016;161(9):2417–2423. doi: 10.1007/s00705-016-2930-8. [DOI] [PubMed] [Google Scholar]
  • 4.Corman V.M., Landt O., Kaiser M., Molenkamp R., Meijer A., Chu D.K. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill. 2020;25(3) doi: 10.2807/1560-7917.ES.2020.25.3.2000045. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Reusken C., Broberg E.K., Haagmans B., Meijer A., Corman V.M., Papa A. Laboratory readiness and response for novel coronavirus (2019-nCoV) in expert laboratories in 30 EU/EEA countries, January 2020. Euro Surveill. 2020;25(6) doi: 10.2807/1560-7917.ES.2020.25.6.2000082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Johnson H.C., Gossner C.M., Colzani E., Kinsman J., Alexakis L., Beauté J. Potential scenarios for the progression of a COVID-19 epidemic in the European Union and the European Economic Area, March 2020. Euro Surveill. 2020;25(9) doi: 10.2807/1560-7917.ES.2020.25.9.2000202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Lipsitch M., Swerdlow D.L., Finelli L. Defining the epidemiology of Covid-19 – studies needed. N. Engl. J. Med. 2020;382:1194–1196. doi: 10.1056/NEJMp2002125. [DOI] [PubMed] [Google Scholar]
  • 8.Bordi L., Nicastri E., Scorzolini L., Di Caro A., Capobianchi M.R., Castilletti C. Differential diagnosis of illness in patients under investigation for the novel coronavirus (SARS-CoV-2), Italy, February 2020. Euro Surveill. 2020;25(8) doi: 10.2807/1560-7917.ES.2020.25.8.2000170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Zou L., Ruan F., Huang M., Liang L., Huang H., Hong Z. SARS-CoV-2 viral load in upper respiratory specimens of infected patients. N. Engl. J. Med. 2020;382:1177–1179. doi: 10.1056/NEJMc2001737. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Panning M., Eickmann M., Landt O., Monazahian M., Olschlager S., Baumgarte S. Detection of influenza A(H1N1)v virus by real-time RT-PCR. Euro Surveill. 2009;14(36) [PubMed] [Google Scholar]

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