Nanotrap Particles Improve Nanopore Sequencing of SARS-CoV-2 and Other Respiratory Viruses

  1. P Andersen
  2. S Barksdale
  3. RA Barclay
  4. N Smith
  5. J Fernandes
  6. K Besse
  7. D Goldfarb
  8. R Barbero
  9. R Dunlap
  10. T Jones-Roe
  11. R Kelly
  12. S Miao
  13. C Ruhunusiri
  14. A Munns
  15. S Mosavi
  16. L Sanson
  17. D Munns
  18. S Sahoo
  19. O Swahn
  20. K Hull
  21. D White
  22. K Kolb
  23. F Noroozi
  24. J Seelam
  25. A Patnaik
  26. B Lepene

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Abstract

Presented here is a magnetic hydrogel particle enabled workflow for capturing and concentrating SARS-CoV-2 from diagnostic remnant swab samples that significantly improves sequencing results using the Oxford Nanopore Technologies MinION sequencing platform. Our approach utilizes a novel affinity-based magnetic hydrogel particle, circumventing low input sample volumes and allowing for both rapid manual and automated high throughput workflows that are compatible with nanopore sequencing. This approach enhances standard RNA extraction protocols, providing up to 40x improvements in viral mapped reads, and improves sequencing coverage by 20-80% from lower titer diagnostic remnant samples. Furthermore, we demonstrate that this approach works for contrived influenza virus and respiratory syncytial virus samples, suggesting that it can be used to identify and improve sequencing results of multiple viruses in VTM samples. These methods can be performed manually or on a KingFisher Apex system.

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  1. Version published to 10.1101/2021.12.08.471814v2 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2021.12.08.471814: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Bioinformatics and Data Analysis: To analyze and process the sequencing data generated by the ONT Mk1C platform, the following tools were used: live basecalling and demultiplexing was performed using the ONT MinKnow software integrated into the ONT Mk1C MinION device; general classification and viral mapped reads were generated using the 3/9/2020 W.I.M.P protocol through ONT’s Epi2me web tool; further coverage analysis was conducted using Minimap2 and Samtools through the UseGalaxy.org web portal.
    ONT MinKnow
    suggested: None
    Samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Statistical analyses were performed and figures were generated using Graphpad Prism 9.
    Graphpad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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:
    Although this technology has many appealing advantages, the usable clinical sample pool is restricted to higher titer samples due to sensitivity and accuracy limitations 28–30. We saw this limitation as an opportunity to examine potential enrichment strategies to enhance the amount of nucleic acid material being sequenced, increasing the available pool of clinical samples. To that end, we applied the Nanotrap particle front-end virus capture and concentration method to both contrived VTM and diagnostic remnant samples. Nanotrap Particles significantly improved sequencing results by capturing and concentrating SARS-CoV-2 from contrived samples, improving the output of two standard RNA extraction methods. Furthermore, we identified a general working concentration range of SARS-CoV-2 in which Nanotrap particles were shown to significantly increase the viral mapped reads of the ONT Mk1C sequencing platform. Sequencing and RT-PCR improvements were seen for both Nanotrap Particle Workflows 1 and 2. Relative to the results delivered by the RNA extraction kits without Nanotrap particle pre-processing, both workflows significantly improved total viral mapped reads of SARS-Cov-2 at multiple concentrations. Of the two workflows, greater improvements were seen with the column-based Nanotrap Particle Workflow 1 over its comparator. This workflow employed a larger sample volume, allowing for a more significant amount of enrichment relative to the comparator. For the magnetic bead-based RNA...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2021.12.08.471814v1 on bioRxiv