Novel SARS-CoV-2 Whole-genome sequencing technique using Reverse Complement PCR enables easy, fast and accurate outbreak analysis in hospital and community settings

  1. Femke Wolters
  2. Jordy P.M. Coolen
  3. Alma Tostmann
  4. Lenneke F.J. van Groningen
  5. Chantal P. Bleeker-Rovers
  6. Edward C.T.H. Tan
  7. Nannet van der Geest-Blankert
  8. Jeannine L.A. Hautvast
  9. Joost Hopman
  10. Heiman F.L. Wertheim
  11. Janette C. Rahamat-Langendoen
  12. Marko Storch
  13. Willem J.G. Melchers

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Abstract

Background

Current transmission rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are still increasing and many countries are facing second waves of infections. Rapid SARS-CoV-2 whole-genome sequencing (WGS) is often unavailable but could support public health organizations and hospitals in monitoring and determining transmission links. Here we report the use of reverse complement polymerase chain reaction (RC-PCR), a novel technology for WGS of SARS-CoV-2 enabling library preparation in a single PCR saving time, resources and enables high throughput screening. Additionally, we show SARS-CoV-2 diversity and possible transmission within the Radboud university medical center (Radboudumc) during September 2020 using RC-PCR WGS.

Methods

A total of 173 samples tested positive for SARS-CoV-2 between March and September 2020 were selected for whole-genome sequencing. Ct values of the samples ranged from 16 to 42. They were collected from 83 healthcare workers and three patients at the Radboudumc, in addition to 64 people living in the area around the hospital and tested by the local health services. For validation purposes, nineteen of the included samples were previously sequenced using Oxford Nanopore Technologies and compared to RC-PCR WGS results. The applicability of RC-PCR WGS in outbreak analysis for public health service and hospitals was tested on six suspected clusters containing samples of healthcare workers and patients with an epidemiological link.

Findings

RC-PCR resulted in sequencing data for 146 samples. It showed a genome coverage of up to 98,2% for samples with a maximum Ct value of 32. Comparison to Oxford Nanopore technologies gives a near-perfect agreement on 95% of the samples (18 out of 19). Three out of six clusters with a suspected epidemiological link were fully confirmed, in the others, four healthcare workers were not associated. In the public health service samples, a previously unknown chain of transmission was confirmed.

Significance statement

SAR-CoV-2 whole-genome sequencing using RC-PCR is a reliable technique and applicable for use in outbreak analysis and surveillance. Its ease of use, high-trough screening capacity and wide applicability makes it a valuable addition or replacement during this ongoing SARS-CoV-2 pandemic.

Funding

None

Research in context

Evidence before this study

At present whole genome sequencing techniques for SARS-CoV-2 have a large turnover time and are not widely available. Only a few laboratories are currently able to perform large scale SARS-CoV-2 sequencing. This restricts the use of sequencing to aid hospital and community infection prevention.

Added value of this study

Here we present clinical and technical data on a novel Whole Genome Sequencing technology, implementing reverse-complement PCR. It is able to obtain high genome coverage of SARS-CoV-2 and confirm and exclude epidemiological links in 173 healthcare workers and patients. The RC-PCR technology simplifies the workflow thereby reducing hands on time. It combines targeted PCR and sequence library construction in a single PCR, which normally takes several steps. Additionally, this technology can be used in concordance with the widely available range of Illumina sequencers.

Implications of all the available evidence

RC-PCR whole genome sequencing technology enables rapid and targeted surveillance and response to an ongoing outbreak that has great impact on public health and society. Increased use of sequencing technologies in local laboratories can help prevent increase of SARS-CoV-2 spreading by better understanding modes of transmission.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.10.29.360578: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationThey were randomly selected for the first run, but were also part of an IPC identified cluster and therefore included in the second run.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All consensus sequences and reference NC_045512.2 were aligned using MUSCLE (version 3.8.1551) using default settings.
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    A maximum-likelihood phylogenetic tree was inferred using IQ-TREE (version 2.0.3) under the GTR□+□F□+□I□+□G4 model with the ultrafast bootstrap option set to 1,000.
    IQ-TREE
    suggested: (IQ-TREE, RRID:SCR_017254)
    Phylogenetic tree visualization and annotation was performed using iTOL (version 5.6.3) or FigTree (version 1.4.4) (http://tree.bio.ed.ac.uk/software/figtree/).10 SNP distances between samples was calculated using snp-dists (version 0.7.0) (https://github.com/tseemann/snp-dists).
    FigTree
    suggested: (FigTree, RRID:SCR_008515)
    The clinical validation consisted of a comparison of the epidemiological information of the community and hospital samples and the WGS findings to see whether sequencing confirmed or dismissed the suspected links between the samples.
    WGS
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.10.29.360578 on bioRxiv