A single-cell atlas of the peripheral immune response to severe COVID-19
Download from source ↗Dataset overview
A single-cell atlas of the peripheral immune response in patients with severe COVID-19.
Abstract
There is an urgent need to better understand the pathophysiology of Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2, which has infected more than three million people worldwide<sup>1</sup>. Approximately 20% of patients with COVID-19 develop severe disease and 5% of patients require intensive care<sup>2</sup>. Severe disease has been associated with changes in peripheral immune activity, including increased levels of pro-inflammatory cytokines<sup>3,4</sup> that may be produced by a subset of inflammatory monocytes<sup>5,6</sup>, lymphopenia<sup>7,8</sup> and T cell exhaustion<sup>9,10</sup>. To elucidate pathways in peripheral immune cells that might lead to immunopathology or protective immunity in severe COVID-19, we applied single-cell RNA sequencing (scRNA-seq) to profile peripheral blood mononuclear cells (PBMCs) from seven patients hospitalized for COVID-19, four of whom had acute respiratory distress syndrome, and six healthy controls. We identify reconfiguration of peripheral immune cell phenotype in COVID-19, including a heterogeneous interferon-stimulated gene signature, HLA class II downregulation and a developing neutrophil population that appears closely related to plasmablasts appearing in patients with acute respiratory failure requiring mechanical ventilation. Importantly, we found that peripheral monocytes and lymphocytes do not express substantial amounts of pro-inflammatory cytokines. Collectively, we provide a cell atlas of the peripheral immune response to severe COVID-19.
doi:10.1038/s41591-020-0944-y ↗ PMID 32514174 ↗ PMC7382903 ↗
Study facts
- Organism
- Homo sapiens
- Platform
- Illumina NovaSeq 6000
- Age group
- —
- Disease groups
- —
- Anatomical sites
- peripheral blood
Data availability
- Raw counts
File types
RDS
Files and samples
- filelist.txt ↗
- GSE150728_RAW.tar ↗
- GSM4557327_555_1_cell.counts.matrices.rds.gz ↗
- GSM4557328_555_2_cell.counts.matrices.rds.gz ↗
- GSM4557329_556_cell.counts.matrices.rds.gz ↗
- GSM4557330_557_cell.counts.matrices.rds.gz ↗
- GSM4557331_558_cell.counts.matrices.rds.gz ↗
- GSM4557332_559_cell.counts.matrices.rds.gz ↗
- GSM4557333_561_cell.counts.matrices.rds.gz ↗
- GSM4557334_HIP002_cell.counts.matrices.rds.gz ↗
- GSM4557335_HIP015_cell.counts.matrices.rds.gz ↗
- GSM4557336_HIP023_cell.counts.matrices.rds.gz ↗
- GSM4557337_HIP043_cell.counts.matrices.rds.gz ↗
- GSM4557338_HIP044_cell.counts.matrices.rds.gz ↗
- GSM4557339_HIP045_cell.counts.matrices.rds.gz ↗
- index.html ↗
- PBMCs from COVID-19 sample7
- PBMCs from healthy control6
| Accession | Sample | Tissue | Molecule |
|---|---|---|---|
GSM4557327 |
PBMCs from COVID-19 sample covid_555_1 | PBMCs from COVID-19 sample | polyA RNA |
GSM4557328 |
PBMCs from COVID-19 sample covid_555_2 | PBMCs from COVID-19 sample | polyA RNA |
GSM4557329 |
PBMCs from COVID-19 sample covid_556 | PBMCs from COVID-19 sample | polyA RNA |
GSM4557330 |
PBMCs from COVID-19 sample covid_557 | PBMCs from COVID-19 sample | polyA RNA |
GSM4557331 |
PBMCs from COVID-19 sample covid_558 | PBMCs from COVID-19 sample | polyA RNA |
GSM4557332 |
PBMCs from COVID-19 sample covid_559 | PBMCs from COVID-19 sample | polyA RNA |
GSM4557333 |
PBMCs from COVID-19 sample covid_561 | PBMCs from COVID-19 sample | polyA RNA |
GSM4557334 |
PBMCs from healthy control HIP002 | PBMCs from healthy control | polyA RNA |
GSM4557335 |
PBMCs from healthy control HIP015 | PBMCs from healthy control | polyA RNA |
GSM4557336 |
PBMCs from healthy control HIP023 | PBMCs from healthy control | polyA RNA |
GSM4557337 |
PBMCs from healthy control HIP043 | PBMCs from healthy control | polyA RNA |
GSM4557338 |
PBMCs from healthy control HIP044 | PBMCs from healthy control | polyA RNA |
GSM4557339 |
PBMCs from healthy control HIP045 | PBMCs from healthy control | polyA RNA |
Strengths & limitations for reuse
Strengths
- Raw reads are advertised
- Raw counts are advertised
Limitations
- Not documented: processed matrices are advertised
- Not documented: cell metadata are advertised
- Not documented: participant counts are documented
Extraction evidence & provenance
Each extracted field is shown with the source excerpt and location used to resolve it.
Assay
| Field | Value | Evidence |
|---|---|---|
assay.assay_type |
single-cell RNA sequencing |
we applied single-cell RNA sequencing (scRNA-seq) Section |
assay.library_chemistry |
Nextera XT DNA library preparation kit |
Library preparation was performed with a Nextera XT DNA library preparation kit Section |
assay.platform |
Illumina NovaSeq 6000 |
Illumina NovaSeq 6000 Section |
assay.reference_genome |
GRCh37 |
Genome_build: GRCh37 including the complete genome sequences of all SARS-CoV-2 strains sequenced from California before March 24, 2020 Section |
assay.sequencing_type |
scrna_seq |
we applied single-cell RNA sequencing (scRNA-seq) Section |
Cohort
| Field | Value | Evidence |
|---|---|---|
cohort.non_ibd_controls |
6 |
6 healthy controls Section |
Data_Assets
| Field | Value | Evidence |
|---|---|---|
data_assets.raw_counts |
True |
cell.counts.matrices.rds.gz Section |
data_assets.raw_reads |
True |
GSE150728_RAW.tar Section |
Specimens
| Field | Value | Evidence |
|---|---|---|
specimens.anatomical_sites |
['peripheral blood'] |
peripheral blood mononuclear cells (PBMCs) Section |