A Viral Fragmentation Signature for SARS-CoV-2 in Clinical Samples Correlating with Contagiousness

  1. Yukti Choudhury
  2. Chae Yin Cher
  3. Zi Yi Wan
  4. Chao Xie
  5. Jing Shan Lim
  6. Ramandeep Kaur Virk
  7. Min Han Tan
  8. Alvin Kuo Jing Teo
  9. Li Yang Hsu

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Abstract

The viral load of SARS-CoV-2 in clinical samples as measured by the primary diagnostic tool of RT-PCR is an imperfect readout for infection potential as most targeted assays designed for sensitivity, indiscriminately detect short and long RNA fragments, although infectivity is embodied only in the whole virus and its intact genome. Here, we used next-generation sequencing (NGS) to characterize 155 clinical samples and show sensitive and quantitative detection of viral RNA which confirmed subgenomic RNA in 57.6% of samples and provided a novel method to determine relative integrity of viral RNA in samples. The relative abundance of long fragments quantified as a viral fragmentation score was positively associated with viral load and inversely related to time from disease onset. An empirically determined score cut-off for presence of substantially fragmented RNA was able to identify 100% of samples collected after 8 days of illness with poor infection potential in line with current clinical understanding of infectiousness of SARS-CoV-2. The quantification of longer fragments in addition to existing short targets in an NGS or RT-PCR-based assay could provide a valuable readout of infection potential simultaneous to the detection of any fragments of SARS-CoV-2 RNA in test samples.

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  1. ScreenIT

    SciScore for 10.1101/2021.01.11.21249265: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationEach forward primer additionally includes on the 5’ end, a random 10 nucleotide sequence to serve as molecular barcode.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    A total of 155 samples, corresponding to 48 individuals were analyzed by NGS.
    NGS
    suggested: (PM4NGS, RRID:SCR_019164)
    Barcode sequences were clustered based on sequence and amplicon identity, and consensus calling was done for each molecular tag (or barcode) cluster, by first performing global alignment among all associated reads using MAFFT.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Insert length analysis and calculation of viral fragmentation score: For each positive sample with sequencing data, SAMtools was used to capture insert sizes from alignment files with the following specifications: samtools view -f65 -F2048 SampleXYZ_consensus.bam | cut -f 1,4,9 > SampleXYZ_f65F2048.txt where f65 = filter in read paired, first in pair (Reads which are paired and insert sizes for first read in read pair and second in read in read pair will have same same insert size with “negative” length); F2048 = filter out reads with supplementary alignment (removes most subgenomic RNA reads which have part of reads with supplementary alignment and removes chimeric reads.
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Regression analysis and curve fitting was done using Prism 8.0.1.
    Prism
    suggested: (PRISM, RRID:SCR_005375)

    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: We detected the following sentences addressing limitations in the study:
    There are important limitations to this study. The use of the exact cut-off of VFS to categorize samples into clinical groups may not universally apply. Nonetheless, the basic premise of the argument that more intact virus would reflect in more longer fragments in a clinical sample would universally apply. As the study’s main conclusions are based on NGS, with some comparison to RT-PCR results, without evidence from virus culture studies it cannot be ruled out that some of the observed infectivity measures are correlated and result from a feature of the specific NGS method. In conclusion, we have applied NGS to comprehensively characterize longitudinal samples collected from different sites. NGS is an enabling tool that provides sequence-related information for which it is primarily designed, and also information from size and length dimensions. Based on this, we identify fragment length differences among clinical samples which are correlated to clinical features of infectiousness of SARS-CoV-2, quantification of which could be incorporated as relevant and straightforward measure to determine infection potential.

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2021.01.11.21249265v1 on medRxiv