Targeted Hybridization Capture of SARS-CoV-2 and Metagenomics Enables Genetic Variant Discovery and Nasal Microbiome Insights

  1. Dorottya Nagy-Szakal
  2. Mara Couto-Rodriguez
  3. Heather L. Wells
  4. Joseph E. Barrows
  5. Marilyne Debieu
  6. Kristin Butcher
  7. Siyuan Chen
  8. Agnes Berki
  9. Courteny Hager
  10. Robert J. Boorstein
  11. Mariah K. Taylor
  12. Colleen B. Jonsson
  13. Christopher E. Mason
  14. Niamh B. O’Hara

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Abstract

This is the first FDA emergency-use-authorized hybridization capture-based next-generation sequencing (NGS) assay to detect the SARS-CoV-2 genome. Viral metagenomics and the novel hybrid capture NGS-based assay, along with its research-use-only analysis, can provide important genetic insights into SARS-CoV-2 and other emerging pathogens and improve surveillance and early detection, potentially preventing or mitigating new outbreaks.

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  1. Version published to 10.1128/spectrum.00197-21
  2. ScreenIT

    SciScore for 10.1101/2021.03.16.21252988: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    VERO E6 cells [ATCC CRL-1586] spiked into VTM were used as a negative extraction control (NEC) to monitor for any cross-contamination that occurs during the extraction process, as well as an extraction control to validate extraction reagents and successful RNA extraction.
    VERO E6
    suggested: None
    Software and Algorithms
    SentencesResources
    We performed BLASTn alignments using all 994 probes found in the SARS-CoV-2 Research Panel, with the PolyA tail removed, against the parallelized database.
    BLASTn
    suggested: (BLASTN, RRID:SCR_001598)
    Quality analysis was performed with FastQC (v0.11.3) (55) with default settings to validate the quality of the raw sequencing data.
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    In order to remove all human reads, Bowtie2 (v2.3.4.1) (57) and samtools (v1.9) (58) were used to align the quality filtered reads to Homo sapiens reference genome (GCF_000001405.39_GRCh38.p13).
    Bowtie2
    suggested: (Bowtie 2, RRID:SCR_016368)
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Processed reads were analyzed utilizing MetaPhlAn2 (59) to identify the relative abundance of microbial species.
    MetaPhlAn2
    suggested: None
    To explore functional genomic profiling, we used HUMAnN2 (61) to characterize microbial pathways linked to the presented microbial species.
    HUMAnN2
    suggested: (HUMAnN2 , RRID:SCR_016280)

    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:
    The limitations of amplicon-based sequencing have resulted in discordant single nucleotide variants as well as frequently missed variants (10, 31), and capture-based methods represent an important tool for addressing any missing variation. As the COVID-19 pandemic is still ongoing and new variants are emerging, global implementation of robust SARS-CoV-2 sequencing programs is needed to further characterize the viral genome and to inform public health responses (9). Profiling the SARS-CoV-2 Microbiome: Only a few studies evaluating the microbiome associated with COVID-19 patients have been conducted to date. Overall, our microbial profiling overlaps with previous studies using shotgun sequencing and metagenomic analysis on nasopharyngeal bacterial composition (32, 33) with commensal respiratory species detected such as Streptococcus, Veillonella, Prevotella, Rothia, Actinomyces, Haemophilus, and Neisseria species. While one study found decreased diversity in SARS-CoV-2 positive specimens, reporting the vast majority of reads mapped to a single organism in each sample, which could be explained by the necessity of the higher coverage of Nanopore sequencing (13), we found no significant difference in richness or evenness between CVP and CVN samples; however, CVN samples exhibited a trend of lower richness. In addition, Mostafa et al. reported higher abundance of Corynebacterium accolens and decreased abundance of Propionibacteriaceae in CVP, which are common skin commensals, resp...

    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 10.1101/2021.03.16.21252988 on medRxiv