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Single Cell Transcriptomic Re-analysis of Immune Cells in Bronchoalveolar Lavage Fluids Reveals the Correlation of B Cell Characteristics and Disease Severity of Patients with SARS-CoV-2 Infection

  • Chae Won Kim (Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)) ;
  • Ji Eun Oh (Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)) ;
  • Heung Kyu Lee (Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST))
  • Received : 2020.10.27
  • Accepted : 2021.01.13
  • Published : 2021.02.28
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Abstract

The coronavirus disease 2019 (COVID-19) pandemic (severe acute respiratory syndrome coronavirus 2) is a global infectious disease with rapid spread. Some patients have severe symptoms and clinical signs caused by an excessive inflammatory response, which increases the risk of mortality. In this study, we reanalyzed scRNA-seq data of cells from bronchoalveolar lavage fluids of patients with COVID-19 with mild and severe symptoms, focusing on Ab-producing cells. In patients with severe disease, B cells seemed to be more activated and expressed more immunoglobulin genes compared with cells from patients with mild disease, and macrophages expressed higher levels of the TNF superfamily member B-cell activating factor but not of APRIL (a proliferation-inducing ligand). In addition, macrophages from patients with severe disease had increased pro-inflammatory features and pathways associated with Fc receptor-mediated signaling, compared with patients with mild disease. CCR2-positive plasma cells accumulated in patients with severe disease, probably because of increased CCL2 expression on macrophages from patients with severe disease. Together, these results support the hypothesis that different characteristics of B cells might be associated with the severity of COVID-19 infection.

Keywords

Acknowledgement

This study was supported by the National Research Foundation of Korea (NRF-2019R1A2C2087490 and NRF-2019M3A9A8067236) funded by the Ministry of Science and ICT of Korea. This work was also supported by Mobile Clinic Module Project funded by KAIST and the 2020 Joint Research Project of Institutes of Science and Technology.

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