Immune cell profiling of COVID-19 patients in the recovery stage by single-cell sequencing
bioinformatics immunology/immunity
Wen et al.
https://www.medrxiv.org/content/10.1101/2020.03.23.20039362v1 (posted on 31/3/2020)
Summary
Wen et al characterised the immune cell composition and transcriptional changes of peripheral blood mononuclear cells (PBMCs) patients in early and late recovery stages (ERS and LRS) of COVID-19 plus controls (N=5 each), using single cell RNA-, BCR- and TCR-sequencing (10X). They identified an inflammatory signature in ERS with an accumulation of inflammatory monocytes. They describe common BCR sequences in ERS, without testing statistical significance. Using a not-well-established computational approach to predict cell-cell interactions, they claim an ‘inflammatory storm’ where inflammatory monocytes act as pivoting members in ERS. It is unclear if this differs from a usual post-infectious monocyte response.
Research highlights
1. Immune response is sustained more than 7 days after testing negative for COVID-19
2. Increased fraction of classical inflammatory monocytes (CD14++ IL1b+) in peripheral blood of post-COVID-19 infection patients
3. Increased fraction of CD4 central memory T cells in ERS patients, these are decreased close to healthy controls in LRS patients
4. Increased fraction of plasma cells in ERS patients, decreased in LRS
5. Class switch of IgA to IgM antibodies happens in the time period from ERS to LRS
6. Identification of dominant IGV genes in post-COVID-19 patients, this could be useful for vaccine development
Research Impact
For understanding the immune cell composition after clearance of SARS-COV-2 (from PBMCs)
For retrospectively understanding the immune cell response and informing possible vaccine designs/drug targets
For identifying immune signatures in recovery patients
Methodology
The authors distinguish patients into early recovery stage (n=5, ERS, < 7 days since testing negative for COVID19) and late recovery stage (n=5, LRS, > 14 days) and compared these to healthy controls (n=5)
Single cell RNA-sequencing of PBMCs
scBCR-seq and scTCR-seq to assess clonality of expanded B- and T-cell clones
Computational methods are not well described, therefore some figures are not directly highlighting the conclusions drawn
Some tools used are not standard workflow tools and would need further description in the methods
Strengths and weaknesses of the paper
Strengths:
· Use of human patients in different stages of disease (healthy controls, ERS and LRS)
· Robust numbers of patients and healthy controls (5 samples per group; age-matched)
· Combination of different approaches (scRNA-seq, scTCR-seq and scBCR-seq) for characterising immune cell composition and possible functionality
· Comparison of ERS to LRS for insights into immune clearance and therapeutic strategy
· BCR chain occurrence could be important for vaccine development
Weakness:
· Underlying data does not appear to be publicly available
· Only recovery patients à ongoing disease for mechanism
· Only blood, no lung tissue or lung fluid (BAL) à would be important for mechanism proposition
· Descriptive, no validation of results
· Unclear how the results differ from usual post-infectious changes (e.g. elevated monocyte-to-lymphocyte ratio is a general marker of infection)
· Computational methods used are not state-of-the-art or not well-described
· Methods not detailed enough to reproduce the analysis
· Poorly annotated figures make it difficult to draw conclusions
· No statistical tests given but findings claimed to be ‘significant’