Optimizing SARS-CoV-2 molecular diagnostic using N gene target: insights about reinfection

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Abstract

Introduction

Molecular diagnosis of SARS-CoV-2 is a huge challenge to many countries around the world. The cost of tests to check infected people is inaccessible since specialized teams and equipment are not disposable in remote locations. Herein, we compared the fitness of two primers sets to the SARS-CoV-2 N gene in the molecular diagnosis of COVID-19.

Materials and Methods

The 1029 patient samples were tested to presense/abscence molecular test using in house US CDC protocol. We compared the fitness of two primers sets to two different regions of N gene targets.

Results

Both targets, N1 and N2 displayed similar fitness during testing with no differences between Ct or measurable viral genome copies. In addition, we verified security ranges Cts related to positive diagnostic with Ct above 35 value failuring in 66,6% after retesting of samples.

Main conclusion

Our data suggest that it is secure to use just one primer set to the N gene to identify SARS-CoV-2 in samples and the labs should be careful to set positive samples in high Ct values using high cutoffs.

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  1. SciScore for 10.1101/2020.12.06.20244905: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethic statement: The Research Ethics Committee of UFOB approved this study in 2020 (license number: 30629520.6.0000.0008).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All data was analyzed using GraphPad Prism 5.0 (GraphPad Software Inc).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.