Porcine Epidemic Diarrhea Virus Replication in Human Intestinal Cells Reveals Potential Susceptibility to Cross-Species Infection.

Various coronaviruses have emerged as a result of cross-species transmission among humans and domestic animals. Porcine epidemic diarrhea virus (PEDV; family Coronaviridae, genus Alphacoronavirus) causes acute diarrhea, vomiting, dehydration, and high mortality in neonatal piglets. Porcine small intestinal epithelial cells (IPEC-J2 cells) can be used as target cells for PEDV infection. However, the origin of PEDV in pigs, the host range, and cross-species infection of PEDV remain unclear. To determine whether PEDV has the ability to infect human cells in vitro, human small intestinal epithelial cells (FHs 74 Int cells) were inoculated with PEDV LJX and PEDV CV777 strains. The results indicated that PEDV LJX, but not PEDV CV777, could infect FHs 74 Int cells. Furthermore, we observed M gene mRNA transcripts and N protein expression in infected FHs 74 Int cells. A one-step growth curve showed that the highest viral titer of PEDV occurred at 12 h post infection. Viral particles in vacuoles were observed in FHs 74 Int cells at 24 h post infection. The results proved that human small intestinal epithelial cells are susceptible to PEDV infection, suggesting the possibility of cross-species transmission of PEDV.

Transmissible Gastroenteritis Virus Nucleocapsid Protein Interacts with Na+/H+ Exchanger 3 To Reduce Na+/H+ Exchanger Activity and Promote Piglet Diarrhea.

Transmissible gastroenteritis virus (TGEV) is member of the family Coronaviridae and mainly causes acute diarrhea. TGEV infection is characterized by vomiting, watery diarrhea, and severe dehydration, resulting in high mortality rates in neonatal piglets. TGEV infection symptoms are related to an imbalance of sodium absorption in small intestinal epithelial cells; however, the etiology of sodium imbalance diarrhea caused by TGEV remains unclear. In this study, we performed transcriptomic analysis of intestinal tissues from infected and healthy piglets and observed that the expression of NHE3, encoding Na+/H+ exchanger 3 (NHE3), the main exchanger of electroneutral sodium in intestinal epithelial cells, was significantly reduced upon TGEV infection. We also showed that specific inhibition of intestinal NHE3 activity could lead to the development of diarrhea in piglets. Furthermore, we revealed an interaction between TGEV N protein and NHE3 near the nucleus. The binding of TGEV N to NHE3 directly affected the expression and activity of NHE3 on the cell surface and affected cellular electrolyte absorption, leading to diarrhea. Molecular docking and computer-aided screening techniques were used to screen for the blocker of the interaction between TGEV N and NHE3, which identified irinotecan. We then demonstrated that irinotecan was effective in relieving TGEV-induced diarrhea in piglets. These findings provide new insights into the mechanism of TGEV-induced sodium imbalance diarrhea and could lead to the design of novel antiviral strategies against TGEV. IMPORTANCE A variety of coronaviruses have been found to cause severe diarrhea in hosts, including TGEV; however, the pathogenic mechanism is not clear. Therefore, prompt determination of the mechanism and identification of efficient therapeutic agents are required, both for public health reasons and for economic development. In this study, we demonstrated that NHE3 is the major expressed protein of NHEs in the intestine, and its expression decreased by nearly 70% after TGEV infection. Also, specific inhibition of intestinal NHE3 resulted in severe diarrhea in piglets. This demonstrated that NHE3 plays an important role in TGEV-induced diarrhea. In addition, we found that TGEV N directly regulates NHE3 expression and activity through protein-protein interaction, which is essential to promote diarrhea. Molecular docking and other techniques demonstrated that irinotecan could block the interaction and diarrhea caused by TGEV. Thus, our results provide a basis for the development of novel therapeutic agents against TGEV and guidance for the development of drugs for other diarrhea-causing coronaviruses.

Bioinformatic analysis of the S protein of human respiratory coronavirus.

The present study aimed to apply bioinformatic methods to analyze the structure of the S protein of human respiratory coronaviruses, including severe respiratory disease syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), human coronavirus HKU1 (HCoV-HKU1), and severe respiratory disease syndrome coronavirus type 2 (SARS-CoV-2). We predicted and analyzed the physicochemical properties, hydrophilicity and hydrophobicity, transmembrane regions, signal peptides, phosphorylation and glycosylation sites, epitopes, functional domains, and motifs of the S proteins of human respiratory coronaviruses. All four S proteins contain a transmembrane region, which enables them to bind to host cell surface receptors. All four S proteins contain a signal peptide, phosphorylation sites, glycosylation sites, and epitopes. The predicted phosphorylation sites might mediate S protein activation, the glycosylation sites might affect the cellular orientation of the virus, and the predicted epitopes might have implications for the design of antiviral inhibitors. The S proteins of all four viruses have two structural domains, S1 (C-terminal and N-terminal domains) and S2 (homology region 1 and 2). Our bioinformatic analysis of the structural and functional domains of human respiratory coronavirus S proteins provides a basis for future research to develop broad-spectrum antiviral drugs, vaccines, and antibodies.

Tackling Explicit Material from Online Video Conferencing Software for Education Using Deep Attention Neural Architectures.

The spread of the COVID-19 pandemic affected all areas of social life, especially education. Globally, many states have closed schools temporarily or imposed local curfews. According to UNESCO estimations, approximately 1.5 billion students have been affected by the closure of schools and the mandatory implementation of distance learning. Although rigorous policies are in place to ban harmful and dangerous content aimed at children, there are many cases where minors, mainly students, have been exposed relatively or unfairly to inappropriate, especially sexual content, during distance learning. Ensuring minors' emotional and mental health is a priority for any education system. This paper presents a severe attention neural architecture to tackle explicit material from online education video conference applications to deal with similar incidents. This is an advanced technique that, for the first time in the literature, proposes an intelligent mechanism that, although it uses attention mechanisms, does not have a square complexity of memory and time in terms of the size of the input. Specifically, we propose the implementation of a Generative Adversarial Network (GAN) with the help of a local, sparse attention mechanism, which can accurately detect obscene and mainly sexual content in streaming online video conferencing software for education.