Persistent bacterial coinfection of a COVID-19 patient caused by a genetically adapted Pseudomonas aeruginosa chronic colonizer

  1. Jiuxin Qu
  2. Zhao Cai
  3. Yumei Liu
  4. XiangKe Duan
  5. Shuhong Han
  6. Yuao Zhu
  7. Zhaofang Jiang
  8. Yingdan Zhang
  9. Chao Zhuo
  10. Yang Liu
  11. Yingxia Liu
  12. Lei Liu
  13. Liang Yang

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Abstract

This study characterized a genetically adapted Pseudomonas aeruginosa small colony variant isolated from a COVID-19 patient who suffered persistent bacterial coinfection and eventually recovered from critical illness. Specification and modification of the isolates discovered at genomic and transcriptomic levels with aligned phenotypic observations indicated that these isolates formed excessive biofilm with elevated quorum sensing systems.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.05.238998: (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.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    Sample collection: Two isolates of P. aeruginosa were collected from sputum samples of one COVID-19 patient with 10 days interval (Isolate 1 on 12 February 2020 and Isolate 2 on 22 February 2020) during routine clinical tests.
    P. aeruginosa
    suggested: None

    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.

  2. Version published to 10.1101/2020.08.05.238998 on bioRxiv