Dysbiosis and structural disruption of the respiratory microbiota in COVID-19 patients with severe and fatal outcomes

  1. Alejandra Hernández-Terán
  2. Fidencio Mejía-Nepomuceno
  3. María Teresa Herrera
  4. Omar Barreto
  5. Emma García
  6. Manuel Castillejos
  7. Celia Boukadida
  8. Margarita Matias-Florentino
  9. Alma Rincón-Rubio
  10. Santiago Avila-Rios
  11. Mario Mújica-Sánchez
  12. Ricardo Serna-Muñoz
  13. Eduardo Becerril-Vargas
  14. Cristobal Guadarrama-Pérez
  15. Víctor Hugo Ahumada-Topete
  16. Sebastián Rodríguez-Llamazares
  17. José Arturo Martínez-Orozco
  18. Jorge Salas-Hernández
  19. Rogelio Pérez-Padilla
  20. Joel Armando Vázquez-Pérez

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Abstract

The COVID-19 outbreak has caused over three million deaths worldwide. Understanding the pathology of the disease and the factors that drive severe and fatal clinical outcomes is of special relevance. Studying the role of the respiratory microbiota in COVID-19 is especially important as the respiratory microbiota is known to interact with the host immune system, contributing to clinical outcomes in chronic and acute respiratory diseases. Here, we characterized the microbiota in the respiratory tract of patients with mild, severe, or fatal COVID-19, and compared it to healthy controls and patients with non-COVID-19-pneumonia. We comparatively studied the microbial composition, diversity, and microbiota structure between the study groups and correlated the results with clinical data. We found differences in the microbial composition for COVID-19 patients, healthy controls, and non-COVID-19 pneumonia controls. In particular, we detected a high number of potentially opportunistic pathogens associated with severe and fatal levels of the disease. Also, we found higher levels of dysbiosis in the respiratory microbiota of patients with COVID-19 compared to the healthy controls. In addition, we detected differences in diversity structure between the microbiota of patients with mild, severe, and fatal COVID-19, as well as the presence of specific bacteria that correlated with clinical variables associated with increased risk of mortality. In summary, our results demonstrate that increased dysbiosis of the respiratory tract microbiota in patients with COVID-19 along with a continuous loss of microbial complexity structure found in mild to fatal COVID-19 cases may potentially alter clinical outcomes in patients. Taken together, our findings identify the respiratory microbiota as a factor potentially associated with the severity of COVID-19.

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  1. Version published to 10.1038/s41598-021-00851-0
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    SciScore for 10.1101/2021.05.19.21257485: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethics statement: The Science, Biosecurity and Bioethics Committee of the Instituto Nacional de
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The Amplicon Sequence Variants (ASVs) were aligned with MAFFT 40 and used to construct a phylogeny with fasttree2 41.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    ASVs taxonomy was assigned with the Näive Bayes classifier sklearn 42 using the Greengenes 13.8 database 43
    Greengenes
    suggested: (Greengenes, RRID:SCR_002830)
    Raw data were deposited in the NCBI Sequence Read Archive (SRA) (PRNAJ726205)
    NCBI Sequence Read Archive
    suggested: (NCBI Sequence Read Archive (SRA, RRID:SCR_004891)
    Subsequently, we constructed Kaplan-Meier survival curves in SPSS Statistics (version 21) (Chicago, Illinois, USA) by using the hospitalization days as time variable, the mortality status (either deceased or alive) as a dependent variable, and the specific clinical qualitative variables as exposure variable.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    To further characterize the structure, we computed metrics of the topology of each network using the NetworkAnalyzer plug-in in Cytoscape 51 and visualized them with a spider chart constructed in R program.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)

    Results from OddPub: Thank you for sharing your data.

    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.
    • No funding statement was detected.
    • 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.

  3. Version published to 10.1101/2021.05.19.21257485v1 on medRxiv