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J Virol ; 95(16): e0018721, 2021 07 26.
Article in English | MEDLINE | ID: covidwho-1486048


Subversion of the host cell cycle to facilitate viral replication is a common feature of coronavirus infections. Coronavirus nucleocapsid (N) protein can modulate the host cell cycle, but the mechanistic details remain largely unknown. Here, we investigated the effects of manipulation of porcine epidemic diarrhea virus (PEDV) N protein on the cell cycle and the influence on viral replication. Results indicated that PEDV N induced Vero E6 cell cycle arrest at S-phase, which promoted viral replication (P < 0.05). S-phase arrest was dependent on the N protein nuclear localization signal S71NWHFYYLGTGPHADLRYRT90 and the interaction between N protein and p53. In the nucleus, the binding of N protein to p53 maintained consistently high-level expression of p53, which activated the p53-DREAM pathway. The key domain of the N protein interacting with p53 was revealed to be S171RGNSQNRGNNQGRGASQNRGGNN194 (NS171-N194), in which G183RG185 are core residues. NS171-N194 and G183RG185 were essential for N-induced S-phase arrest. Moreover, small molecular drugs targeting the NS171-N194 domain of the PEDV N protein were screened through molecular docking. Hyperoside could antagonize N protein-induced S-phase arrest by interfering with interaction between N protein and p53 and inhibit viral replication (P < 0.05). The above-described experiments were also validated in porcine intestinal cells, and data were in line with results in Vero E6 cells. Therefore, these results reveal the PEDV N protein interacts with p53 to activate the p53-DREAM pathway, and subsequently induces S-phase arrest to create a favorable environment for virus replication. These findings provide new insight into the PEDV-host interaction and the design of novel antiviral strategies against PEDV. IMPORTANCE Many viruses subvert the host cell cycle to create a cellular environment that promotes viral growth. PEDV, an emerging and reemerging coronavirus, has led to substantial economic loss in the global swine industry. Our study is the first to demonstrate that PEDV N-induced cell cycle arrest during the S-phase promotes viral replication. We identified a novel mechanism of PEDV N-induced S-phase arrest, where the binding of PEDV N protein to p53 maintains consistently high levels of p53 expression in the nucleus to mediate S-phase arrest by activating the p53-DREAM pathway. Furthermore, a small molecular compound, hyperoside, targeted the PEDV N protein, interfering with the interaction between the N protein and p53 and, importantly, inhibited PEDV replication by antagonizing cell cycle arrest. This study reveals a new mechanism of PEDV-host interaction and also provides a novel antiviral strategy for PEDV. These data provide a foundation for further research into coronavirus-host interactions.

Antiviral Agents/pharmacology , Coronavirus Nucleocapsid Proteins/chemistry , Host-Pathogen Interactions/drug effects , Porcine epidemic diarrhea virus/drug effects , Quercetin/analogs & derivatives , Tumor Suppressor Protein p53/chemistry , Amino Acid Sequence , Animals , Antiviral Agents/chemistry , Binding Sites , Cell Line , Chlorocebus aethiops , Coronavirus Infections/drug therapy , Coronavirus Infections/genetics , Coronavirus Infections/metabolism , Coronavirus Infections/virology , Coronavirus Nucleocapsid Proteins/antagonists & inhibitors , Coronavirus Nucleocapsid Proteins/genetics , Coronavirus Nucleocapsid Proteins/metabolism , Epithelial Cells/drug effects , Epithelial Cells/virology , Gene Expression Regulation , High-Throughput Screening Assays , Host-Pathogen Interactions/genetics , Molecular Docking Simulation , Nuclear Localization Signals , Porcine epidemic diarrhea virus/genetics , Porcine epidemic diarrhea virus/metabolism , Protein Binding , Protein Conformation , Protein Interaction Domains and Motifs , Quercetin/chemistry , Quercetin/pharmacology , S Phase Cell Cycle Checkpoints/drug effects , S Phase Cell Cycle Checkpoints/genetics , Signal Transduction , Swine , Swine Diseases/drug therapy , Swine Diseases/genetics , Swine Diseases/metabolism , Swine Diseases/virology , Tumor Suppressor Protein p53/antagonists & inhibitors , Tumor Suppressor Protein p53/genetics , Tumor Suppressor Protein p53/metabolism , Vero Cells , Virus Replication/drug effects
ISPRS International Journal of Geo-Information ; 10(10):696, 2021.
Article in English | ProQuest Central | ID: covidwho-1480790


A spatial co-location pattern denotes a subset of spatial features whose instances frequently appear nearby. High influence co-location pattern mining is used to find co-location patterns with high influence in specific aspects. Studies of such pattern mining usually rely on spatial distance for measuring nearness between instances, a method that cannot be applied to an influence propagation process concluded from epidemic dispersal scenarios. To discover meaningful patterns by using fruitful results in this field, we extend existing approaches and propose a mining framework. We first defined a new concept of proximity to depict semantic nearness between instances of distinct features, thus applying a star-shaped materialized model to mine influencing patterns. Then, we designed attribute descriptors to perceive attributes of instances and edges from time series data, and we calculated the attribute weights via an analytic hierarchy process, thereby computing the influence between instances and the influence of features in influencing patterns. Next, we constructed influencing metrics and set a threshold to discover high influencing patterns. Since the metrics do not satisfy the downward closure property, we propose two improved algorithms to boost efficiency. Extensive experiments conducted on real and synthetic datasets verified the effectiveness, efficiency, and scalability of our method.

Pathog Dis ; 78(3)2020 04 01.
Article in English | MEDLINE | ID: covidwho-616784


The coronavirus disease 2019 (COVID-2019) that emerged in Wuhan, China, has rapidly spread to many countries across all six WHO regions. However, its pathobiology remains incompletely understood and many efforts are underway to study it worldwide. To clarify its pathogenesis to some extent, it will inevitably require lots of COVID-2019-associated pathological autopsies. Pathologists from all over the world have raised concerns with pathological autopsy relating to COVID-2019. The issue of whether a person died from COVID-2019 infection or not is always an ambiguous problem in some cases, and ongoing epidemiology from China may shed light on it. This review retrospectively summarizes the research status of pathological autopsy for COVID-2019 deaths in China, which will be important for the cause of death, prevention, control and clinical strategies of COVID-2019. Moreover, it points out several challenges at autopsy. We believe pathological studies from China enable to correlate clinical symptoms and pathological features of COVID-2019 for doctors and provide an insight into COVID-2019 disease.

Autopsy , Coronavirus Infections/pathology , Pneumonia, Viral/pathology , Betacoronavirus , COVID-19 , Cause of Death , China , Coronavirus Infections/mortality , Humans , Pandemics , Pneumonia, Viral/mortality , SARS-CoV-2