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Authors: Chen et al.

Link to paper:

Journal/ Pre-Print: medRxiv

Tags: Immunology/Immunity, Bioinformatics, Inflammation, Transcriptomics

Research Highlights

1. In COVID-19 patients, there was an increased ACE2 expression in ciliated, club, and basal cells of lung epithelium.

2. Transcriptomic analysis showed that SARS-CoV-2 promotes pro-inflammatory signalling pathways, including interferon and cytokine signalling.

3. Severe COVID-19 patients were shown to have a significantly higher neutrophil count in the lungs, lower macrophage number, and an increased expression of interferon and cytotoxic granule contents in T and NK cells.


The authors re-analyse previously published single-cell RNA-seq data collected from lung bronchoalveolar lavage fluid of COVID-19 patients (three mild, six severe) and eight healthy controls. They compared the expression of ACE2 and TMPRSS2 and found increased ACE2 on lung epithelial cells of patients. Increased pro-inflammatory cytokine production was observed in immune cells, as well as increased neutrophil count, T and NK cell activation and a decrease in macrophages. The authors note stronger correlations between epithelial cell gene expression and the counts of various immune cells (macrophages, T and NK) in patients, suggesting stronger epithelial-immune cell interactions during infection. The authors do not explicitly compare their analysis results to the original published analysis of this data.

Impact for SARS-CoV2/COVID19 Research Effort

· Understand the immune response to SARS-CoV2/COVID19

Study Type

· In silico study / bioinformatics study

· Patient Case study

Strengths and Limitations of the Paper

Novelty: Similar results have been shown in other scRNA-sequencing analyses. The authors do not compare their results to the previous analysis of this data, which makes it is hard to assess what is new.

Standing in the field: The increase in ACE2 expression in COVID-19 patients is in agreement with a previous observation linking ACE2 expression to interferon response (Ziegler et al, 2020, Cell). The induction of interferon and cytokines signalling pathways after SARS-CoV-2 infection is also in agreement with what is currently known.

Appropriate statistics: The data was analysed with a commonly used pipeline, Seurat. The interaction/correlation analysis between different cell types seems ad hoc and does not appear to control for differential sample size, variance or expression.

Viral model used: SARS-CoV-2 patient data

Translatability: . Observed changes in the lung immune landscape could help further understand the link between SARS-CoV-2 infection and cytokine storms.

Main limitations: In the case of scRNA-seq, the authors did not have access to the raw data and ran their analysis from the count quantification matrix instead, thus they did not have any control over the pre-processing steps. The number of samples is also quite small. The authors re-analysed data (scRNA-seq and bulk RNA-seq) previously published in different manuscripts which can be problem for cross-sample comparisons:

- Differences in samples preparation (BALF for COVID-19 patients and lung tissues for non-COVID-19 patients) can impact recovered cell type populations and the subsequent analysis.

- Differences in demographic characteristics (Chinese for COVID-19 patients and five African American, two White, and one Asian for non-COVID-19 patients) could impact gene expression levels and therefore the differential gene expression analysis results.