Analysis of the upper respiratory tract microbiota in mild and severe COVID-19 patients

  1. V. Babenko
  2. R. Bakhtyev
  3. V. Baklaushev
  4. L. Balykova
  5. P. Bashkirov
  6. J. Bespyatykh
  7. A. Blagonravova
  8. D. Boldyreva
  9. D. Fedorov
  10. I. Gafurov
  11. R. Gaifullina
  12. J. Galeeva
  13. E. Galova
  14. A. Gospodaryk
  15. E. Ilina
  16. K. Ivanov
  17. D. Kharlampieva
  18. P. Khromova
  19. K. Klimina
  20. K. Kolontarev
  21. N. Kolyshkina
  22. A. Koritsky
  23. V. Kuropatkin
  24. V. Lazarev
  25. A. Manolov
  26. V. Manuvera
  27. D. Matyushkina
  28. M. Morozov
  29. E. Moskaleva
  30. V. Musarova
  31. O. Ogarkov
  32. E. Orlova
  33. A. Pavlenko
  34. A. Petrova
  35. N. Pozhenko
  36. D. Pushkar
  37. A. Rumyantsev
  38. S. Rumyantsev
  39. V. Rumyantsev
  40. L. Rychkova
  41. A. Samoilov
  42. I. Shirokova
  43. V. Sinkov
  44. S. Solovieva
  45. E. Starikova
  46. P. Tikhonova
  47. G. Trifonova
  48. A. Troitsky
  49. A. Tulichev
  50. Y. Udalov
  51. A. Varizhuk
  52. A. Vasiliev
  53. R. Vereshchagin
  54. V. Veselovsky
  55. A. Volnukhin
  56. G. Yusubalieva
  57. V. Govorun

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

The microbiota of the respiratory tract remains a relatively poorly studied subject. At the same time, like the intestinal microbiota, it is involved in modulating the immune response to infectious agents in the host organism. A causal relationship between the composition of the respiratory microbiota and the likelihood of development and the severity of COVID-19 may be hypothesized. We analyze biomaterial from nasopharyngeal smears from 336 patients with a confirmed diagnosis of COVID-19, selected during the first and second waves of the epidemic in Russia. Sequences from a similar study conducted in Spain were also included in the analysis. We investigated associations between disease severity and microbiota at the level of microbial community (community types) and individual microbes (differentially represented species). To search for associations, we performed multivariate analysis, taking into account comorbidities, type of community and lineage of the virus. We found that two out of six community types are associated with a more severe course of the disease, and one of the community types is characterized by high stability (very similar microbiota profiles in different patients) and low level of lung damage. Differential abundance analysis with respect to comorbidities and community type suggested association of Rothia and Streptococcus genera representatives with more severe lung damage, and Leptotrichia , unclassified Lachnospiraceae and Prevotella with milder forms of the disease.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.09.20.461025: (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

    No key resources detected.

    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.

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

    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 10.1101/2021.09.20.461025v2 on bioRxiv
  3. Version published to 10.1101/2021.09.20.461025v1 on bioRxiv