In silico prediction of COVID-19 test efficiency with DinoKnot

  1. Tara Newman
  2. Hiu Fung Kevin Chang
  3. Hosna Jabbari

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Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus spreading across the world causing the disease COVID-19. The diagnosis of COVID-19 is done by quantitative reverse-transcription polymer chain reaction (qRT-PCR) testing which utilizes different primer-probe sets depending on the assay used. Using in silico analysis we aimed to determine how the secondary structure of the SARS-CoV-2 RNA genome affects the interaction between the reverse primer during qRT-PCR and how it relates to the experimental primer-probe test efficiencies. We introduce the program DinoKnot (Duplex Interaction of Nucleic acids with pseudoKnots) that follows the hierarchical folding hypothesis to predict the secondary structure of two interacting nucleic acid strands (DNA/RNA) of similar or different type. DinoKnot is the first program that utilizes stable stems in both strands as a guide to find the structure of their interaction. Using DinoKnot we predicted the interaction of the reverse primers used in four common COVID-19 qRT-PCR tests with the SARS-CoV-2 RNA genome. In addition, we predicted how 12 mutations in the primer/probe binding region may affect the primer/probe ability and subsequent SARS-CoV-2 detection. While we found all reverse primers are capable of interacting with their target area, we identified partial mismatching between the SARS-CoV-2 genome and some reverse primers. We predicted three mutations that may prevent primer binding, reducing the ability for SARS-CoV-2 detection. We believe our contributions can aid in the design of a more sensitive SARS-CoV-2 test.

Author summary

The current testing for the disease COVID-19 that is caused by the novel cornonavirus SARS-CoV-2 uses oligonucleotides called primers that bind to specific target regions on the SARS-CoV-2 genome to detect the virus. Our goal was to use computational tools to predict how the structure of the SARS-CoV-2 RNA genome affects the ability of the primers to bind to their target region. We introduce the program DinoKnot (Duplex interaction of nucleic acids with pseudoknots) that is able to predict the interactions between two DNA or RNA molecules. We used DinoKnot to predict the efficiency of four common COVID-19 tests, and the effect of mutations in the SARS-CoV-2 virus on ability of the COVID-19 tests in detecting those strains. We predict partial mismatching between some primers and the SARS-CoV-2 genome but that all primers are capable of interacting with their target areas. We also predict three mutations that prevent primer binding and thus SARS-CoV-2 detection. We discuss the limitations of the current COVID-19 testing and suggest the design of a more sensitive COVID-19 test that can be aided by our findings.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.11.292730: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    As is a limitation of this survey we cannot verify whether the respondents who believed they had COVID-19 were in fact infected with SARS-CoV-2. However, since they were tested later, this may support the hypothesis that the viral load may be below the limit of detection if the test is taken a greater number of days after symptom onset. Therefore false negative tests are likely an issue with having enough viral load in the sample rather than an issue with the primer interaction with the SARS-CoV-2 genome since DinoKnot predicted correct primer binding for most of the primers at the higher temperatures. We hypothesize that a SARS-CoV-2 aptamer test is beneficial to provide a lower limit of detection. Aptamers are single stranded RNA or DNA nucleotides (10-100nt) that are able to bind to targets such as viruses and proteins [36]. Aptamers’ binding specificity is ensured by their secondary and tertiary structure [36]. An RNA aptamer test designed for the SARS-CoV Nucleocapsid protein showed a detection limit of 2 pg/mL [37]. A recent aptamer test for Norovirus, a positive sense RNA virus, has a limit of detection of 200 viral copies/mL [38]. This is lower than the qRT-PCR limit of detection of determined by Vogels et al. by a magnitude of 103 [4]. The lower limit of detection that is possible with aptamer tests would be beneficial in testing patients later after symptom onset. We believe that an aptamer test can be designed for SARS-CoV-2 that both improves the detection sensiti...

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.09.11.292730 on bioRxiv