Single cell multi-omic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients

Front Immunol. 2024 Jul 4:15:1374828. doi: 10.3389/fimmu.2024.1374828. eCollection 2024.

Abstract

Introduction: Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing.

Methods: To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omics approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls.

Results: We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC.

Discussion: Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.

Keywords: COVID - 19; SARSCoV- 2; innate lymphocyte cells (ILCs); single cell RNA analysis; single cell immunology.

MeSH terms

  • Adult
  • Aged
  • COVID-19* / genetics
  • COVID-19* / immunology
  • Female
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Humans
  • Immunity, Innate*
  • Lymphocytes* / immunology
  • Lymphocytes* / metabolism
  • Male
  • Middle Aged
  • Multiomics
  • Single-Cell Analysis
  • Transcriptome

Associated data

  • Dryad/10.5061/dryad.8931zcrz4