Single-cell RNA-seq and V(D)J profiling of immune cells in COVID-19 patients

  1. Xiaoying Fan
  2. Xiangyang Chi
  3. Wenji Ma
  4. Suijuan Zhong
  5. Yunzhu Dong
  6. Wei Zhou
  7. Wenyu Ding
  8. Hongyan Fan
  9. Chonghai Yin
  10. Zhentao Zuo
  11. Yilong Yang
  12. Mengyao Zhang
  13. Qiang Ma
  14. Jianwei Liu
  15. Ting Fang
  16. Qian Wu
  17. Wei Chen
  18. Xiaoqun Wang

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Abstract

Coronavirus disease 2019 (COVID-19) has caused over 220,000 deaths so far and is still an ongoing global health problem. However, the immunopathological changes of key types of immune cells during and after virus infection remain unclear. Here, we enriched CD3+ and CD19+ lymphocytes from peripheral blood mononuclear cells of COVID-19 patients (severe patients and recovered patients at early or late stages) and healthy people (SARS-CoV-2 negative) and revealed transcriptional profiles and changes in these lymphocytes by comprehensive single-cell transcriptome and V(D)J recombination analyses. We found that although the T lymphocytes were decreased in the blood of patients with virus infection, the remaining T cells still highly expressed inflammatory genes and persisted for a while after recovery in patients. We also observed the potential transition from effector CD8 T cells to central memory T cells in recovered patients at the late stage. Among B lymphocytes, we analyzed the expansion trajectory of a subtype of plasma cells in severe COVID-19 patients and traced the source as atypical memory B cells (AMBCs). Additional BCR and TCR analyses revealed a high level of clonal expansion in patients with severe COVID-19, especially of B lymphocytes, and the clonally expanded B cells highly expressed genes related to inflammatory responses and lymphocyte activation. V-J gene usage and clonal types of higher frequency in COVID-19 patients were also summarized. Taken together, our results provide crucial insights into the immune response against patients with severe COVID-19 and recovered patients and valuable information for the development of vaccines and therapeutic strategies.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.24.20101238: (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
    The Human Peripheral Blood Mononuclear Cells (PBMCs) were obtained by Ficoll density gradient centrifugation (DakeweBiotech) according to the manufacturer’s instruction and then applied to the red blood cell lysis solution (Miltenyi Biotec) for 10 minutes at room temperature.
    DakeweBiotech
    suggested: None
    We used CellPhoneDB V2.041 to calculate ligand-receptor interactions between T cells and B cells in different states.
    CellPhoneDB
    suggested: (CellPhoneDB, RRID:SCR_017054)

    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 10.1101/2020.05.24.20101238 on medRxiv