ABSTRACT
Angiotensin I-converting enzyme 2 (ACE2), type II transmembrane serine protease 2 and 4 (TMPRSS2 and TMPRSS4) are important receptors for SARS-CoV-2 infection. In this study, the full-length tree shrewACE2 gene was cloned and sequenced, and its biological information was analyzed. The expression levels of ACE2, TMPRSS2 and TMPRSS4 in various tissues or organs of the tree shrew were detected. The results showed that the full-length ACE2 gene in tree shrews was 2,786 bp, and its CDS was 2,418 bp, encoding 805 amino acids. Phylogenetic analysis based on the CDS of ACE2 revealed that tree shrews were more similar to rabbits (85.93%) and humans (85.47%) but far from mice (82.81%) and rats (82.58%). In silico analysis according to the binding site of SARS-CoV-2 with the ACE2 receptor of different species predicted that tree shrews had potential SARS-CoV-2 infection possibility, which was similar to that of rabbits, cats and dogs but significantly higher than that of mice and rats. In addition, various tissues or organs of tree shrews expressed ACE2, TMPRSS2 and TMPRSS4. Among them, the kidney most highly expressed ACE2, followed by the lung and liver. The esophagus, lung, liver, intestine and kidney had relatively high expression levels of TMPRSS2 and TMPRSS4. In general, we reported for the first time the expression of ACE2, TMPRSS2 and TMPRSS4 in various tissues or organs in tree shrews. Our results revealed that tree shrews could be used as a potential animal model to study the mechanism underlying SARS-CoV-2 infection.
Disclosure Statement
No potential conflict of interest was reported by the author(s).
Consent for publication
All the authors agreed to publish the final version of this manuscript.
Data availability statement
All the involved data had been included in the present manuscript, and the original raw data could be obtained from the corresponding author upon reasonable request.
Author contributions
Data curation, Caixia Lu and Yuanyuan Han; Formal analysis, Wenguang Wang; Investigation, Xiaomei Sun; Methodology, Wenpeng Gu and Yuanyuan Han; Resources, Na Li, Wenpeng Gu and Pinfen Tong; Software, Yuanyuan Han; Supervision, Xiaomei Sun, Wenguang Wang and Jiejie Dai; Validation, Wenguang Wang; Visualization, Jiejie Dai; Writing – original draft, Jiejie Dai.