High expression of angiotensin-converting enzyme-2 (ACE2) on tissue macrophages that may be targeted by virus SARS-CoV-2 in COVID-19 patients
Song, X.; Hu, W.; Yu, H.; Zhao, L.; Zhao, Y.; Zhao, Y.
Show abstract
Angiotensin-converting enzyme-2 (ACE2) has been recognized as the binding receptor for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that infects host cells, causing the development of the new coronavirus infectious disease (COVID-19). To better understand the pathogenesis of COVID-19 and build up the host anti-viral immunity, we examined the levels of ACE2 expression on different types of immune cells including tissue macrophages. Flow cytometry demonstrated that there was little to no expression of ACE2 on most of the human peripheral blood-derived immune cells including CD4+ T, CD8+ T, activated CD4+ T, activated CD8+ T, CD4+CD25+CD127low/- regulatory T cells (Tregs), Th17 cells, NKT cells, B cells, NK cells, monocytes, dendritic cells (DCs), and granulocytes. Additionally, there was no ACE2 expression (< 1%) found on platelets. Compared with interleukin-4-treated type 2 macrophages (M2), the ACE2 expression was markedly increased on the activated type 1 macrophages (M1) after the stimulation with lipopolysaccharide (LPS). Immunohistochemistry demonstrated that high expressions of ACE2 were colocalized with tissue macrophages, such as alveolar macrophages found within the lungs and Kupffer cells within livers of mice. Flow cytometry confirmed the very low level of ACE2 expression on human primary pulmonary alveolar epithelial cells. These data indicate that alveolar macrophages, as the frontline immune cells, may be directly targeted by the SARS-CoV-2 infection and therefore need to be considered for the prevention and treatment of COVID-19.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Transcriptome analysis of PBMCs reveals distinct immune response in the asymptomatic and re-detectable positive COVID-19 patients 96%
- Prophylactic treatment of Glycyrrhiza glabra mitigates COVID-19 pathology through inhibition of pro-inflammatory cytokines in the hamster model and NETosis. 96%
- Plasma gradient of soluble urokinase-type plasminogen activator receptor is linked to pathogenic plasma proteome and immune transcriptome and stratifies outcomes in severe COVID-19 96%
Similar papers in this journal
- SARS-CoV-2 infection induces mixed M1/M2 phenotype in circulating monocytes and alterations in both dendritic cell and monocyte subsets 96%
- TGF-β expressed by M2 macrophages promotes wound healing by inhibiting TSG-6 expression by mesenchymal stem cells 96%
- Novel prognostic determinants of COVID-19-related mortality: a pilot study on severely-ill patients in Russia 95%
Similar papers in this journal
- Hematopoietic growth factors Regulate Entry of Monocytes into the Adult Brain via Chemokine Receptor CCR5 96%
- RIPK2 is crucial for the microglial inflammatory response to bacterial muramyl dipeptide but not to lipopolysaccharide 96%
- Myogenetic oligodeoxynucleotide induces myocardial differentiation of murine pluripotent stem cells 95%
Similar papers in this journal
- Increased LPS levels coexist with systemic inflammation and result in monocyte activation in severe COVID-19 patients 96%
- SARS-CoV-2 immune complex triggers human monocyte necroptosis 94%
- Aucubin promoted neuron functional recovery by suppressing inflammation and neuronal apoptosis in a spinal cord injury model 93%
Similar papers in this journal
- The Spike protein of SARS-CoV-2 impairs lipid metabolism and increases susceptibility to lipotoxicity: implication for a role of Nrf2 94%
- Differential modulation of miR-122 transcription by TGFbeta1/BMP6: implications for nonresolving inflammation and hepatocarcinogenesis 94%
- Stem cell factor and granulocyte colony-stimulating factor promote remyelination in the chronic phase of severe traumatic brain injury 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.