Effects of SARS-CoV-2 Membrane Glycoprotein on Host Pre-mRNA 3' Processing

Objective To investigate the effect of SARS-CoV-2 membrane protein on the processing of the 3' untranslated region (UTR) of the mRNA precursor (pre-mRNA) in host cells. Methods Based on the cell model of human lung epithelial cells A549, over-expression of the SARS-CoV-2 membrane protein was performed. The RNA-Seq high-throughput sequencing technique and bioinformatics methods was employed to analyze the systematic characterization of alternative polyadenylation (APA) events in host cells. Genes with significant APA events were uploaded to the Metascape database for functional enrichment analysis. In addition, alternative 3'UTR length of genes with APA events was verified by RT-qPCR. Then the target protein expression level was detected by Western blot. Results A total of 813 genes that were significant dynamic APA events in host cells that over-expressed SARS-CoV-2 membrane protein. These genes were enriched in cell biologicial processes such as the mitotic cell cycle and regulation of cellular response to stress. We further screened AKT1, which encodes a critical regulator involved in the above biological process, showing a 3'UTR lengthening in IGV software. RT-qPCR verified the trend of 3'UTR length changes of AKT1. Western blot showed the increased level of phosphorylated AKT1 protein in over-expressed group of M protein. Conclusion SARS-CoV-2 membrane protein potentially affects the 3' processing of host pre-mRNAs. AKT1, which is involved in a variety of viral biological processes, with 3'UTR lengthening, and its protein function was activated intracellularly. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.

Effects of SARS-CoV-2 Membrane Glycoprotein on Host Pre-mRNA 3 ' Processing

Objective To investigate the effect of SARS-CoV-2 membrane protein on the processing of the 3' untranslated region (UTR) of the mRNA precursor (pre-mRNA) in host cells. Methods Based on the cell model of human lung epithelial cells A549, over-expression of the SARS-CoV-2 membrane protein was performed. The RNA-Seq high-throughput sequencing technique and bioinformatics methods was employed to analyze the systematic characterization of alternative polyadenylation (APA) events in host cells. Genes with significant APA events were uploaded to the Metascape database for functional enrichment analysis. In addition, alternative 3'UTR length of genes with APA events was verified by RT-qPCR. Then the target protein expression level was detected by Western blot. Results A total of 813 genes that were significant dynamic APA events in host cells that overexpressed SARS-CoV-2 membrane protein. These genes were enriched in cell biologicial processes such as the mitotic cell cycle and regulation of cellular response to stress. We further screened AKT1, which encodes a critical regulator involved in the above biological process, showing a 3'UTR lengthening in IGV software. RT-qPCR verified the trend of 3'UTR length changes of AKT1. Western blot showed the increased level of phosphorylated AKT1 protein in over-expressed group of M protein. Conclusion SARS-CoV-2 membrane protein potentially affects the 3' processing of host pre-mRNAs. AKT1, which is involved in a variety of viral biological processes, with 3'UTR lengthening, and its protein function was activated intracellularly.

Characterizations and Optimization for Resilient Manufacturing Systems With Considerations of Process Uncertainties

The recent COVID-19 pandemic reveals the vulnerability of global supply chains: the unforeseen supply crunches and unpredictable variability in customer demands lead to catastrophic disruption to production planning and management, causing wild swings in productivity for most manufacturing systems. Therefore, a smart and resilient manufacturing system (S & RMS) is promised to withstand such unexpected perturbations and adjust promptly to mitigate their impacts on the system's stability. However, modeling the system's resilience to the impacts of disruptive events has not been fully addressed. We investigate a generalized polynomial chaos (gPC) expansion-based discrete-event dynamic system (DEDS) model to capture uncertainties and irregularly disruptive events for manufacturing systems. The analytic approach allows a real-time optimization for production planning to mitigate the impacts of intermittent disruptive events (e.g., supply shortages) and enhance the system's resilience. The case study on a hybrid bearing manufacturing workshop suggests that the proposed approach allows a timely intervention in production planning to significantly reduce the downtime (around one-fifth of the downtime compared to the one without controls) while guaranteeing maximum productivity under the system perturbations and uncertainties.

China's Exports during the Global COVID-19 Pandemic

The global COVID-19 pandemic caused various economic contraction in most countries, including all of China's major trading partners. Using a difference-in-differences model, this study examines the impact of the COVID-19 pandemic on China's monthly exports from January 2019 to May 2020. We find strong and robust evidence that China's exports to countries at high risk from the pandemic experienced a larger decline than exports to low-risk countries after the onset of the pandemic, with the prices of exports increasing significantly. Furthermore, the results of a triple differences model show heterogeneous effects across different industries and goods. Chinese industries located upstream in the global value chain are more vulnerable than those located downstream. Industries with high labor and contract intensity (proxies for processing trade) experienced greater declines than other industries. Exports of goods with high import elasticity of substitution experienced higher prices and moderate volume losses due to the pandemic.