Systemic analysis of tissue cells potentially vulnerable to SARS-CoV-2 infection by the protein-proofed single-cell RNA profiling of ACE2, TMPRSS2 and Furin proteases
Authors: Lulin Zhou et al. Link to paper: https://www.biorxiv.org/content/10.1101/2020.04.06.028522v1
Journal/ Pre-Print: bioRxiv
Key Words: ACE2, TMPRSS2, Furin, viral entry
1. Lists tissues and cell types within these tissues that express ACE2, TMPRSS2 and FURIN and are possibly more susceptible to SARS-CoV-2 infection
2. Identified lung AT2 cells, lung macrophages and stromal cells in the adrenal gland as potential targets for SARS-CoV-2 infection, due to co-expression of ACE2 and the proteases TMPRSS2 and Furin
The authors aimed to characterise the distribution of the putative receptor for SARS-CoV-2 (ACE2) and two proteases (TMPRSS2 & FURIN) that have been shown to be important for viral spike protein processing and subsequent membrane fusion. Using bulk RNA-seq and proteomic datasets, they found that there is tissue-specific distribution of ACE2 and TMPRSS2, and that ACE2 RNA and protein expression does not always correlate. They also show by single-cell RNA profiling that ACE2 co-expresses with TMPRSS2 and Furin in only a few cell types, including lung AT2 cells, lung macrophages and adrenal gland stromal cells.
Impact for SARS-CoV2/COVID19 research efforts
Understand the virology and/or cell biology of SARS-CoV2/COVID19
Clinical symptoms and pathogenesis of SARS-Cov2/COVID19
· In silico study/bioinformatics study – bulk and single-cell RNA-seq
Strengths and limitations of the paper
Novelty: Investigate co-expression of ACE2, TMPRSS2 and Furin across different cell types, and combine RNA and protein expression data for these three targets (see figure 1).
Standing in the field: Provide evidence that could begin to explain the tissue/organ system distribution of COVID-19 symptoms. Due to low expression in the lung, provides some support for the concept that receptors other than ACE2 and other proteases may be involved in viral entry.
Appropriate statistics: Single-cell RNA-seq datasets were based on single or low numbers of human donors. Could have used further statistical analysis to compare ACE2 expression across different tissues.
Viral model used: N/A
Translatability: Not much, but some potential clinical use in identifying tissues vulnerable for SARS-CoV-2 infection.
Main limitations: Methods sections not very informative, particularly in explaining human datasets and bioinformatics techniques used. Lots of emphasis on correlational data, with no follow-up experiments (e.g. testing ACE2 functionality in cell types identified in vitro). Difficult to follow in pre-print form (e.g. text not always clear).