Epidemiological and Genomic Analysis of SARS-CoV-2 in 10 Patients From a Mid-Sized City Outside of Hubei, China in the Early Phase of the COVID-19 Outbreak

  1. Jinkun Chen
  2. Evann E. Hilt
  3. Fan Li
  4. Huan Wu
  5. Zhuojing Jiang
  6. Qinchao Zhang
  7. Jiling Wang
  8. Yifang Wang
  9. Ziqin Li
  10. Jialiang Tang
  11. Shangxin Yang

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Abstract

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  1. Version published to 10.3389/fpubh.2020.567621
  2. ScreenIT

    SciScore for 10.1101/2020.04.16.20058560: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Since the patient identification was removed and the samples used in this study were remnant and otherwise would be discarded, the Shaoxing Center for Disease Control and Prevention had determined that the institutional review boards (IRB) approval was waived for this project, and the informed consent form was not required.
    Consent: Since the patient identification was removed and the samples used in this study were remnant and otherwise would be discarded, the Shaoxing Center for Disease Control and Prevention had determined that the institutional review boards (IRB) approval was waived for this project, and the informed consent form was not required.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data Analysis: Quality control and trimming of paired-end reads was performed using custom Python scripts as follows: 1) trim 3’ adapters; 2) trim reads at ambiguous bases; 3) filter reads shorter than 40bp; 4) filter reads with average quality score < 20.
    Python
    suggested: (IPython, RRID:SCR_001658)
    Host-derived reads were removed by alignment against the GRCh38.p13 genome reference using bowtie2 (v2.3.4.3) with default parameters.
    bowtie2
    suggested: (Bowtie 2, RRID:SCR_016368)
    snippy (v4.5.0) was used for variant calling and core SNP alignment against the Wuhan-Hu-1 reference, FastTree (v2.1.3) was used for tree construction using default parameters, and Figtree (v1.4.4) was used to visualize the resulting phylogenetic tree.
    FastTree
    suggested: (FastTree, RRID:SCR_015501)
    Figtree
    suggested: (FigTree, RRID:SCR_008515)
    Additional statistical analyses and visualizations were performed using custom Python scripts with the pandas (v0.25.0) and matplotlib (v3.1.1) modules.
    matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The major limitation of this study is that we only had 10 samples analyzed due to the requirement of sufficient SARS-CoV-2 RNA from a metagenomic sample. However, with the development of a SARS-CoV-2 probe enrichment or multiplex PCR protocols, this type of viral sequencing analysis may be applied to samples with lower viral loads, thereby enabling more complete molecular epidemiological surveillance. In addition, the Ct value cut-off of 28 established in this study may not be directly applicable to other real-time PCR assays due to the technical differences. In summary, we demonstrated that a full viral genomic analysis is feasible via metagenomics sequencing directly on nasopharyngeal samples, which allows retrospective molecular surveillance on SARS-CoV-2 to understand the dynamics of the outbreak in the early phase. The identical virus found in patients in Shaoxing, a mid-sized city outside of Hubei, China, and patients in Europe and Australia was striking. Our analysis added to the growing body of evidence that SARS-CoV-2 spread extremely quickly around the globe as early as January. Although only ten patients were included in this study, we found both lineages (A & B) /types (L & S) of viruses with numerous mutations (both synonymous and non-synonymous) across the entire viral genome. Our study contributed to the understanding of the SARS-CoV-2 evolution in the early phase of the COVID-19 pandemic.

    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.

  3. Version published to 10.1101/2020.04.16.20058560 on medRxiv