Global Dynamics of Porcine Enteric Coronavirus PEDV Epidemiology, Evolution, and Transmission.

With a possible origin from bats, the alphacoronavirus Porcine epidemic diarrhea virus (PEDV) causes significant hazards and widespread epidemics in the swine population. However, the ecology, evolution, and spread of PEDV are still unclear. Here, from 149,869 fecal and intestinal tissue samples of pigs collected in an 11-year survey, we identified PEDV as the most dominant virus in diarrheal animals. Global whole genomic and evolutionary analyses of 672 PEDV strains revealed the fast-evolving PEDV genotype 2 (G2) strains as the main epidemic viruses worldwide, which seems to correlate with the use of G2-targeting vaccines. The evolving pattern of the G2 viruses presents geographic bias as they evolve tachytely in South Korea but undergo the highest recombination in China. Therefore, we clustered six PEDV haplotypes in China, whereas South Korea held five haplotypes, including a unique haplotype G. In addition, an assessment of the spatiotemporal spread route of PEDV indicates Germany and Japan as the primary hubs for PEDV dissemination in Europe and Asia, respectively. Overall, our findings provide novel insights into the epidemiology, evolution, and transmission of PEDV, and thus may lay a foundation for the prevention and control of PEDV and other coronaviruses.

Poly(A)-Binding Protein Cytoplasmic 1 Inhibits Porcine Epidemic Diarrhea Virus Replication by Interacting with Nucleocapsid Protein.

Porcine epidemic diarrhea virus (PEDV) is the etiological agent of porcine epidemic diarrhea (PED) characterized by vomit, watery diarrhea, dehydration and high mortality. Outbreaks of highly pathogenic variant strains of PEDV have resulted in extreme economic losses to the swine industry all over the world. The study of host-virus interaction can help to better understand the viral pathogenicity. Many studies have shown that poly(A)-binding proteins are involved in the replication process of various viruses. Here, we found that the infection of PEDV downregulated the expression of poly(A)-binding protein cytoplasmic 1 (PABPC1) at the later infection stage in Vero cells. The overexpression of PABPC1 inhibited the proliferation of PEDV at transcription and translation level, and siRNA-mediated depletion of PABPC1 promoted the replication of PEDV. Furthermore, mass spectrometry analysis and immunoprecipitation assay confirmed that PABPC1 interacted with the nucleocapsid (N) protein of PEDV. Confocal microscopy revealed the co-localizations of PABPC1 with N protein in the cytoplasm. Taken together, these results demonstrate the antiviral effect of PABPC1 against PEDV replication by interacting with N protein, which increases understanding of the interaction between PEDV and host.

K-SEIR-Sim: A simple customized software for simulating the spread of infectious diseases.

Infectious disease is a great enemy of humankind. The ravages of COVID-19 are leading to profound crises across the world. There is an urgent requirement for analyzing the current pandemic situation, predicting trends over time, and assessing the effectiveness of containment measures. Thus, numerous statistical models, primarily based on the susceptible-exposed-infected-recovered or removed (SEIR) model, have been established. However, these models are highly technical, which are difficult for the public and governing bodies to understand and use. To address this issue, we developed a simple operating software based on our improved K-SEIR model termed as the kernelkernel SEIR simulator (K-SEIR-Sim). This software includes natural propagation parameters, containment measure parameters, and certain characteristic parameters that can deduce the effects of natural propagation and containment measures. Further, the applicability of the proposed software was demonstrated using the example of the COVID-19 outbreak in the United States and the city of Wuhan, China. Operating results verified the potency of the proposed software in evaluating the epidemic situation and human intervention during COVID-19. Importantly, the software can perform real-time, backward-looking, and forward-looking analysis by functioning in data-driven and model-driven ways. All of them have considerable practical values in their applications according to the actual needs of personal use. Conclusively, K-SEIR-Sim is the first simple customized operating software that is highly valuable for the global fight against COVID-19 and other infectious diseases.