Single-cell landscape of immunological responses in COVID-19 patients

  1. Ji-Yuan Zhang
  2. Xiang-Ming Wang
  3. Xudong Xing
  4. Zhe Xu
  5. Chao Zhang
  6. Jin-Wen Song
  7. Xing Fan
  8. Peng Xia
  9. Jun-Liang Fu
  10. Si-Yu Wang
  11. Ruo-Nan Xu
  12. Xiao-Peng Dai
  13. Lei Shi
  14. Lei Huang
  15. Tian-Jun Jiang
  16. Ming Shi
  17. Yuxia Zhang
  18. Alimuddin Zumla
  19. Markus Maeurer
  20. Fan Bai
  21. Fu-Sheng Wang

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Abstract

In COVID-19 caused by SARS-CoV-2 infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of five healthy donors and 13 COVID-19 patients including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in COVID-19 patients showed a strong interferon-alpha response, and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4 + Effector-GNLY (Granulysin), CD8 + Effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during the disease progression.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.23.217703: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Enrichment analysis for the functions of the DEGs was conducted using the Metascape webtool (www.metascape.org).
    Metascape
    suggested: (Metascape, RRID:SCR_016620)
    Gene sets were derived from the GO Biological Process Ontology.
    GO Biological
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are several limitations in this study. For example, it was very difficult to obtain the immune cells in bronchoalveolar lavage fluid due to biosafety reasons during the outbreak of COVID-19 when we performed this study. Also, the sample size is comparatively small. Therefore, future studies with longitudinal samples from more COVID-19 patients may help to determine the cause-and-effect relationships between immune characteristic of different cell types and disease outcome. Taken together, this integrated, multi-cellular description in our study lays the foundation for future characterization of the complex, dynamic immune responses to SARS-CoV-2 infection. The transcriptomic data, coupled with detailed TCR- and BCR-based lineage information, can serve as a rich resource for deeper understanding of peripheral lymphocytes in COVID-19 patients and pave the way for rationally designed therapies as well as development of SARS-CoV-2-specific vaccines.

    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

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  2. Version published to 10.1101/2020.07.23.217703 on bioRxiv