Factor Xa cleaves SARS-CoV-2 spike protein to block viral entry and infection.

Serine proteases (SP), including furin, trypsin, and TMPRSS2 cleave the SARS-CoV-2 spike (S) protein, enabling the virus to enter cells. Here, we show that factor (F) Xa, an SP involved in blood coagulation, is upregulated in COVID-19 patients. In contrast to other SPs, FXa exerts antiviral activity. Mechanistically, FXa cleaves S protein, preventing its binding to ACE2, and thus blocking viral entry and infection. However, FXa is less effective against variants carrying the D614G mutation common in all pandemic variants. The anticoagulant rivaroxaban, a direct FXa inhibitor, inhibits FXa-mediated S protein cleavage and facilitates viral entry, whereas the indirect FXa inhibitor fondaparinux does not. In the lethal SARS-CoV-2 K18-hACE2 model, FXa prolongs survival yet its combination with rivaroxaban but not fondaparinux abrogates that protection. These results identify both a previously unknown function for FXa and an associated antiviral host defense mechanism against SARS-CoV-2 and suggest caution in considering direct FXa inhibitors for preventing or treating thrombotic complications in COVID-19 patients.

The K18-Human ACE2 Transgenic Mouse Model Recapitulates Non-severe and Severe COVID-19 in Response to an Infectious Dose of the SARS-CoV-2 Virus.

A comprehensive analysis and characterization of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection model that mimics non-severe and severe coronavirus disease 2019 (COVID-19) in humans is warranted for understating the virus and developing preventive and therapeutic agents. Here, we characterized the K18-hACE2 mouse model expressing human (h)ACE2 in mice, controlled by the human keratin 18 (K18) promoter, in the epithelia, including airway epithelial cells where SARS-CoV-2 infections typically start. We found that intranasal inoculation with higher viral doses (2 × 103 and 2 × 104 PFU) of SARS-CoV-2 caused lethality of all mice and severe damage of various organs, including lung, liver, and kidney, while lower doses (2 × 101 and 2 × 102 PFU) led to less severe tissue damage and some mice recovered from the infection. In this hACE2 mouse model, SARS-CoV-2 infection damaged multiple tissues, with a dose-dependent effect in most tissues. Similar damage was observed in postmortem samples from COVID-19 patients. Finally, the mice that recovered from infection with a low dose of virus survived rechallenge with a high dose of virus. Compared to other existing models, the K18-hACE2 model seems to be the most sensitive COVID-19 model reported to date. Our work expands the information available about this model to include analysis of multiple infectious doses and various tissues with comparison to human postmortem samples from COVID-19 patients. In conclusion, the K18-hACE2 mouse model recapitulates both severe and non-severe COVID-19 in humans being dose-dependent and can provide insight into disease progression and the efficacy of therapeutics for preventing or treating COVID-19. IMPORTANCE The pandemic of coronavirus disease 2019 (COVID-19) has reached nearly 240 million cases, caused nearly 5 million deaths worldwide as of October 2021, and has raised an urgent need for the development of novel drugs and therapeutics to prevent the spread and pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To achieve this goal, an animal model that recapitulates the features of human COVID-19 disease progress and pathogenesis is greatly needed. In this study, we have comprehensively characterized a mouse model of SARS-CoV-2 infection using K18-hACE2 transgenic mice. We infected the mice with low and high doses of SARS-CoV-2 to study the pathogenesis and survival in response to different infection patterns. Moreover, we compared the pathogenesis of the K18-hACE2 transgenic mice with that of the COVID-19 patients to show that this model could be a useful tool for the development of antiviral drugs and therapeutics.

Identifying Protein Complexes With Clear Module Structure Using Pairwise Constraints in Protein Interaction Networks.

The protein-protein interaction (PPI) networks can be regarded as powerful platforms to elucidate the principle and mechanism of cellular organization. Uncovering protein complexes from PPI networks will lead to a better understanding of the science of biological function in cellular systems. In recent decades, numerous computational algorithms have been developed to identify protein complexes. However, the majority of them primarily concern the topological structure of PPI networks and lack of the consideration for the native organized structure among protein complexes. The PPI networks generated by high-throughput technology include a fraction of false protein interactions which make it difficult to identify protein complexes efficiently. To tackle these challenges, we propose a novel semi-supervised protein complex detection model based on non-negative matrix tri-factorization, which not only considers topological structure of a PPI network but also makes full use of available high quality known protein pairs with must-link constraints. We propose non-overlapping (NSSNMTF) and overlapping (OSSNMTF) protein complex detection algorithms to identify the significant protein complexes with clear module structures from PPI networks. In addition, the proposed two protein complex detection algorithms outperform a diverse range of state-of-the-art protein complex identification algorithms on both synthetic networks and human related PPI networks.

COVID-19 pandemic: study on simple, easy, and practical relaxation techniques while wearing medical protective equipment.

BACKGROUND: No studies have reported on how to relieve distress or relax in medical health workers while wearing medical protective equipment in coronavirus disease 2019 (COVID-19) pandemic. The study aimed to establish which relaxation technique, among six, is the most feasible in first-line medical health workers wearing medical protective equipment. METHODS: This was a two-step study collecting data with online surveys. Step 1: 15 first-line medical health workers were trained to use six different relaxation techniques and reported the two most feasible techniques while wearing medical protective equipment. Step 2: the most two feasible relaxation techniques revealed by step 1 were quantitatively tested in a sample of 65 medical health workers in terms of efficacy, no space limitation, no time limitation, no body position requirement, no environment limitation to be done, easiness to learn, simplicity, convenience, practicality, and acceptance. RESULTS: Kegel exercise and autogenic relaxation were the most feasible techniques according to step 1. In step 2, Kegel exercise outperformed autogenic relaxation on all the 10 dimensions among the 65 participants while wearing medical protective equipment (efficacy: 24 v. 15, no space limitation: 30 v. 4, no time limitation: 31 v. 4, no body position requirement: 26 v. 4, no environment limitation: 30 v. 11, easiness to learn: 28 v. 5, simplicity: 29 v. 7, convenience: 29 v. 4, practicality: 30 v. 14, acceptance: 32 v. 6). CONCLUSION: Kegel exercise seems a promising self-relaxation technique for first-line medical health workers while wearing medical protective equipment among COVID-19 pandemic.