Comparative in silico design and validation of GPS™ CoVID-19 dtec-RT-qPCR test

  1. A. Martínez-Murcia
  2. G. Bru
  3. A. Navarro
  4. P. Ros-Tárraga
  5. A. García-Sirera
  6. L. Pérez

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Abstract

Aims

Providing a ready-to-use reverse transcriptase qPCR (RT-qPCR) method fully validated to detect the SARS-CoV-2 with a higher exclusivity than this shown by early published RT-qPCR designs.

Methods and Results

The specificity of the GPS™ CoVID-19 dtec-RT-qPCR test by analysis of sequence alignments was approached and compared with other RT-qPCR designs. The GPS™ CoVID-19 dtec-RT-qPCR test was validated following criteria of UNE/EN ISO 17025:2005 and ISO/IEC 15189:2012. Diagnostic validation was achieved by two independent reference laboratories, the Instituto de Salud Carlos III, (Madrid, Spain), the Public Health England (Colindale, London, UK), and received the label CE-IVD. The GPS design showed the highest exclusivity and passed all parameters of validation with strict acceptance criteria. Results from reference laboratories 100% correlated with these obtained by using reference methods and showed 100% of diagnostic sensitivity and specificity.

Conclusions

The CE-IVD GPS™ CoVID-19 dtec-RT-qPCR test, available worldwide with full analytical and diagnostic validation, is the more exclusive for SARS-CoV-2 by far.

Significance and Impact of the Study

Considering the CoVID-19 pandemic status, the exclusivity of RT-qPCR tests is crucial to avoid false positives due to related coronaviruses. This work provides of a highly specific and validated RT-qPCR method for detection of SARS-CoV-2, which represents a case of efficient transfer of technology successfully used since the pandemic was declared.

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  1. Version published to 10.1111/jam.14781
  2. ScreenIT

    SciScore for 10.1101/2020.04.27.065383: (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
    GENOME SEQUENCES ALIGNMENT AND PHYLOGENETIC ANALYSIS: Partial alignments of ten SARS-CoV-2 genomic sequences and these from strains of Bat-CoV, Bat SARS-like-CoV, SARS-CoV, Pangolin-CoV (ca. 18,141 bp) and the corresponding phylogenetic tree (Figure 1) was obtained by Neighbour joining method [20], with bootstrap values for 1000 replicates, using the MEGA 5.2.2 software [21]. 2.2.
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    IN SILICO COMPARATIVE ANALYSIS OF PRIMERS/PROBES SPECIFICITY: The primers and probes of GPS™ COVID-19 dtec-RT-qPCR Test and the RT-qPCR designs recently published [12–19] were aligned to the corresponding homologous regions of 63 SARS-CoV-2 strains and closely related Betacoronavirus using the Basic Local Alignment Search Tool (BLAST) software available on the National Center for Biotechnology Information (NCBI, https://blast.ncbi.nlm.nih.gov/Blast.cgi) website databases (Bethesda, MD, USA).
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    https://blast.ncbi.nlm.nih.gov/Blast.cgi
    suggested: (TBLASTX, RRID:SCR_011823)

    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.
    • No funding statement was detected.
    • 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.

  3. Version published to 10.1101/2020.04.27.065383v2 on bioRxiv
  4. Version published to 10.1101/2020.04.27.065383v1 on bioRxiv