Scalable workflow for characterization of cell-cell communication in COVID-19 patients

PLoS Comput Biol. 2022 Oct 5;18(10):e1010495. doi: 10.1371/journal.pcbi.1010495. eCollection 2022 Oct.


COVID-19 patients display a wide range of disease severity, ranging from asymptomatic to critical symptoms with high mortality risk. Our ability to understand the interaction of SARS-CoV-2 infected cells within the lung, and of protective or dysfunctional immune responses to the virus, is critical to effectively treat these patients. Currently, our understanding of cell-cell interactions across different disease states, and how such interactions may drive pathogenic outcomes, is incomplete. Here, we developed a generalizable and scalable workflow for identifying cells that are differentially interacting across COVID-19 patients with distinct disease outcomes and use this to examine eight public single-cell RNA-seq datasets (six from peripheral blood mononuclear cells, one from bronchoalveolar lavage and one from nasopharyngeal), with a total of 211 individual samples. By characterizing the cell-cell interaction patterns across epithelial and immune cells in lung tissues for patients with varying disease severity, we illustrate diverse communication patterns across individuals, and discover heterogeneous communication patterns among moderate and severe patients. We further illustrate patterns derived from cell-cell interactions are potential signatures for discriminating between moderate and severe patients. Overall, this workflow can be generalized and scaled to combine multiple scRNA-seq datasets to uncover cell-cell interactions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19*
  • Cell Communication
  • Humans
  • Leukocytes, Mononuclear
  • SARS-CoV-2
  • Workflow

Grant support

The following sources of funding for each author, and for the manuscript preparation, are gratefully acknowledged: Australian Research Council Discovery Project grant (DP170100654) to JYHY; AIR@innoHK programme of the Innovation and Technology Commission of Hong Kong to YL and JYHY; Research Training Program Tuition Fee Offset and Stipend Scholarship and Chen Family Research Scholarship to YL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.