MassMark: A Highly Scalable Multiplex NGS-based Method for High-Throughput, Accurate and Sensitive Detection of SARS-CoV-2 for Mass Testing

  1. Kao Chin Ngeow
  2. Chao Xie
  3. Alvin Kuo Jing Teo
  4. Li Yang Hsu
  5. Min Han Tan
  6. Yukti Choudhury

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Abstract

Mass testing has been proposed as a strategy to address and contain the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic 1,2 . We have developed MassMark, a novel and highly scalable multiplex method that employs next generation sequencing for high-throughput, accurate and sensitive detection of SARS-CoV-2, while minimizing handling complexity and resources by utilizing a serial pooling strategy to accommodate over 9,000 samples per workflow. Analytical validation showed that MassMark was able to detect SARS-CoV-2 RNA down to a level of 100 copies per reaction. We evaluated the clinical performance of MassMark in a simulated screening testing with 22 characterized samples from three different sources (nasopharyngeal swabs, nasal swabs and saliva), comprising of 12 SARS-CoV-2 positive samples with mid to late Ct values (range: 22.98-32.72) and 10 negative samples. There was one false negative and no false positives, giving an overall sensitivity and specificity of 91.67% and 100% respectively, when compared against an optimized RT-PCR test with a target size within 70 bp (CDC 2019-nCoV Real-Time RT-PCR Diagnostic Panel 3 ).

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  1. ScreenIT

    SciScore for 10.1101/2021.01.08.20249017: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Specificity/Exclusivity Testing: In Silico Analysis: BLASTn analysis queries of the primer pairs used in MassMark were performed against a public domain nucleotide sequence database (updated on 07/12/2020) consisting of GenBank+EMBL+DDBJ+PDB+RefSeq sequences, but excluding EST, STS, GSS, WGS, TSA, patent sequences as well as phase 0, 1, and 2 HTGS sequences and sequences longer than 100Mb.
    BLASTn
    suggested: (BLASTN, RRID:SCR_001598)
    WGS
    suggested: None
    Libraries were quantified using a KAPA Library Quantification Kit (Roche, Basel, Switzerland) on a CFX96 Touch Real-Time PCR Detection System, before sequencing on a MiniSeq (Illumina, San Diego, CA, USA) or NextSeq 550 (Illumina) depending on the sample load (Table S2). 35,000 reads are allocated per individual sample.
    MiniSeq
    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

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  2. Version published to 10.1101/2021.01.08.20249017v1 on medRxiv