Integrated characterization of SARS-CoV-2 genome, microbiome, antibiotic resistance and host response from single throat swabs

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Abstract

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, poses a severe threat to humanity. Rapid and comprehensive analysis of both pathogen and host sequencing data is critical to track infection and inform therapies. In this study, we performed unbiased metatranscriptomic analysis of clinical samples from COVID-19 patients using a newly-developed RNA-seq library construction method (TRACE-seq), which utilizes tagmentation activity of Tn5 on RNA/DNA hybrids. This approach avoids the laborious and time-consuming steps in traditional RNA-seq procedure, and hence is fast, sensitive and convenient. We demonstrated that TRACE-seq allowed integrated characterization of full genome information of SARS-CoV-2, putative pathogens causing coinfection, antibiotic resistance and host response from single throat swabs. We believe that the integrated information will deepen our understanding of pathogenesis and improve diagnostic accuracy for infectious diseases.

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  1. SciScore for 10.1101/2020.10.15.340794: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics statement: The study and use of all samples were approved by the Ethics Committee of Wuhan Institue of Virology (No. WIVH17202001).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    preprocessing: Raw reads from sequencing were firstly subjected to Trim Galore (v0.6.4_dev) (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) for quality control and adaptor trimming.
    Trim Galore
    suggested: (Trim Galore, RRID:SCR_011847)
    Host transcriptional profiling analysis: Filtered reads were mapped to human genome (hg19) and transcriptome using STAR (v2.7.1a) (35).
    STAR
    suggested: (STAR, RRID:SCR_015899)
    Multidimensional scaling and differential gene expression analysis were conducted using EdgeR (v3.28.1) (37) with gene count data generated by HTSeq (v0.11.2) (38).
    EdgeR
    suggested: (edgeR, RRID:SCR_012802)
    HTSeq
    suggested: (HTSeq, RRID:SCR_005514)
    Gene Ontology Enrichment Analysis for biological processes was performed by DAVID (v6.8) (39) with all significantly up-regulated genes as input.
    DAVID
    suggested: (DAVID, RRID:SCR_001881)
    Due to the redundancy of enriched GO terms, GO terms and their p values were further summarized using REViGO (40).
    REViGO
    suggested: (REViGO, RRID:SCR_005825)
    Discrimination and de-novo assembly of SARS-CoV-2: After removal of human reads, the remaining data were aligned to the reference genome of Wuhan-Hu-1 (GenBank accession number: NC_045512) using Bowtie2 (v2.2.9) (41) for SARS-CoV-2 identification.
    Bowtie2
    suggested: (Bowtie 2, RRID:SCR_016368)
    The coverage and sequencing depth of SARS-CoV-2 genome were calculated by Samtools (v1.9) (42).
    Samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    On the other hand, to verify the method could screen for aetiologic agents and obtain pathogen genome, all non-human reads were processed for de-novo assembly using MEGAHIT (v1.2.9) with default parameters (43), and then all contigs were searched against NCBI nt database using blastn for classification(44).
    MEGAHIT
    suggested: (MEGAHIT, RRID:SCR_018551)
    blastn
    suggested: (BLASTN, RRID:SCR_001598)
    Microbiome analysis: After removing human reads, the remaining reads were subjected to microbial taxonomic classification using Kraken2 (v2.0.8-beta) (45) with a custom database.
    Kraken2
    suggested: None
    To build the custom database, standard RefSeq complete bacterial genomes were downloaded through “kraken2-build --download-library bacteria” and complete genomes of human viruses and genome assemblies of fungi were downloaded from NCBI’s RefSeq and added to the custom database’s genomic library using the “--add-to-library” switch.
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    Distances between samples were calculated using Morisita-horn dissimilarity index by vegdist command from vegan package version 2.5-6 (https://CRAN.R-project.org/package=vegan).
    vegan
    suggested: (vegan, RRID:SCR_011950)
    All corresponding graphs were plotted using R scripts by RStudio (v1.2.5033) (https://rstudio.com/).
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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.