Coronaviruses Use ACE2 Monomers as Entry-Receptors.

The angiotensin-converting enzyme 2 (ACE2) has been identified as entry receptor on cells enabling binding and infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via trimeric spike (S) proteins protruding from the viral surface. It has been suggested that trimeric S proteins preferably bind to plasma membrane areas with high concentrations of possibly multimeric ACE2 receptors to achieve a higher binding and infection efficiency. Here we used direct stochastic optical reconstruction microscopy (dSTORM) in combination with different labeling approaches to visualize the distribution and quantify the expression of ACE2 on different cells. Our results reveal that endogenous ACE2 receptors are present as monomers in the plasma membrane with densities of only 1-2 receptors µm-2 . In addition, binding of trimeric S proteins does not induce the formation of ACE2 oligomers in the plasma membrane. Supported by infection studies using vesicular stomatitis virus (VSV) particles bearing S proteins our data demonstrate that a single S protein interaction per virus particle with a monomeric ACE2 receptor is sufficient for infection, which provides SARS-CoV-2 a high infectivity.

SIM imaging resolves endocytosis of SARS-CoV-2 spike RBD in living cells.

It is urgent to understand the infection mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for the prevention and treatment of COVID-19. The infection of SARS-CoV-2 starts when the receptor-binding domain (RBD) of viral spike protein binds to angiotensin-converting enzyme 2 (ACE2) of the host cell, but the endocytosis details after this binding are not clear. Here, RBD and ACE2 were genetically coded and labeled with organic dyes to track RBD endocytosis in living cells. The photostable dyes enable long-term structured illumination microscopy (SIM) imaging and to quantify RBD-ACE2 binding (RAB) by the intensity ratio of RBD/ACE2 fluorescence. We resolved RAB endocytosis in living cells, including RBD-ACE2 recognition, cofactor-regulated membrane internalization, RAB-bearing vesicle formation and transport, RAB degradation, and downregulation of ACE2. The RAB was found to activate the RBD internalization. After vesicles were transported and matured within cells, RAB was finally degraded after being taken up by lysosomes. This strategy is a promising tool to understand the infection mechanism of SARS-CoV-2.

Super-resolution using Deep Networks for Chest X-Ray Images

Super-resolution imaging is extensively deliberated in medical imaging modalities nowadays, there being a wide panic on the effect of COVID-19 virus impression. Generally, spatial resolutions of CXR are insufficient due to the constraints such as image acquisition time, hardware limits and physical limits. It is a clinically challenging task to recover the high resolution CXR images. A significant concern in CXR imaging is X-Ray contrast disparity and the demand to attain high quality images with adequate structural and imaging details. To address these problems, we propose an effective deep network for the super-resolution reconstruction method to recover high-resolution CXR images while retaining diagnostic capabilities. Specifically, the reinforcement subnetwork is hosted to generate sharp and informative qualitative features. The quantitative and qualitative assessments found that the proposed model based on the evaluation index improves the CXR super-resolution. In addition, the PSNR index of the proposed model has 0.30 higher than that of the SRCNN network. © 2021 IEEE.