Non-specific Primers Reveal False-negative Risk in Detection of COVID-19

  1. Wei Liu

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Abstract

Background

A novel coronavirus disease 2019 (COVID-19) broke out in Wuhan of Hubei province and had spread throughout the world since December 2019. Because the clinically diagnosed cases in Hubei province were reported for the first time on February 13, 2020, a very high peak of new cases in China was observed. The reason why so many clinically diagnosed cases appeared was not clear.

Methods

All data of new cases in China were acquired from WHO situation reports. Linear fitting was used to infer the ability to detect COVID-19 infections. Primer-BLAST and nucleotide blast were applied to check the specificity of primers. Expression data of human mRNA in different tissues was obtained from Human Protein Atlas.

Findings

Based on the data and analysis of changes of new laboratory-confirmed cases and new clinically diagnosed cases, it was inferred that there were many false-negative results in all clinically diagnosed cases in Hubei province. There were eight non-specific primers in dozens of primers used in clinical or research detection of COVID-19. Among them, a pair of primer for the ORF1ab regions of SARS-CoV-2 genome well matched some human mRNAs such as Cathepsin C transcripts. Compared to other transcripts, Cathepsin C mRNA had a high abundance in tonsil, lung and small intestine.

Interpretation

Some non-specific RT-PCR primers could cause the serious interference during RT-PCR amplification so as to increase the risk of false-negative diagnoses for COVID-19 infections.

Funding

Key Research Project of the Higher Education of Henan Province

Research in context

Evidence before this study

The author searched PubMed on April 15, 2020, for papers that describe false-negative RT-PCR detection of COVID-19 by using the search terms “COVID-19”, “false-negative” and “RT-PCR”, with no language or time restrictions. Eleven investigations only presented the rate of false-negative detection or the importance of positive chest CT finding. There were no reports referring the primer problems of false-negative detection in COVID-19 infections.

Added value of this study

The author had found that some primers could amplify the human mRNA in specimens, which mixed SARS-CoV-2 viral particles and other tissue cells. A pair of primer provided by China CDC could vastly match the sequences of human CTSC transcripts with high abundance. That could lead to false-negative results in detection of COVID-19 infections.

Implications of all the available evidence

Although there were so many false-negative results in detection of COVID-19 infections in China, the exact reason was not clear. Problems in sampling and test condition were discussed thoroughly, but conclusions were usually contradictory. Therefore, the work could promote the verification of the false-negative detection of COVID-19 infections in China.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.07.20056804: (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
    4 Among them, two sets of primers, including forward primer (F), reverse primer (R) and fluorescence probe, were designed by National Institute for Viral Disease Control and Prevention (IVDC), China CDC.5 Since the onset of the COVID-19 outbreak, two sets of primers had recommended to guide disease prevention and control in China.10,11 All mRNA expressions in different human organs were obtained from Human Protein Atlas (HPA, https://www.proteinatlas.org/).12 Analysis of primer specificity: Primer-BLAST (https://www.ncbi.nlm.nih.gov/tools/primer-blast/index.cgi) was applied to determine whether specific primers for SARS-CoV-2 virus show significant match with human RNA or not.
    Primer-BLAST
    suggested: (Primer-BLAST, RRID:SCR_003095)
    Nucleotide blast (https://blast.ncbi.nlm.nih.gov/Blast.cgi) was also used to check the specificity of primers, in which options Refseq RNA was chosen as database, word size was set to 7, and expect threshold was set to 1000.14
    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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 10.1101/2020.04.07.20056804v2 on medRxiv
  3. Version published to 10.1101/2020.04.07.20056804v1 on medRxiv