scholarly journals The 5′ Untranslated Region of the Capsid Protein 2 Gene of Mink Enteritis Virus Is Essential for Its Expression

2018 ◽  
Vol 92 (18) ◽  
Author(s):  
Shuang-Shuang Yang ◽  
Jigui Wang ◽  
Zhaoda Li ◽  
Shangjin Cui ◽  
Weiquan Liu

ABSTRACTMink enteritis virus (MEV), as a parvovirus, is among the smallest of the animal DNA viruses. The limited genome leads to multifunctional sequences and complex gene expression regulation. Here, we show that the expression of viral capsid protein 2 (VP2) of MEV requires its 5′ untranslated regions (5′ UTR) which promote VP2 gene expression at both transcriptional and translational levels. The expression of VP2 was inhibited in several common eukaryotic expression vectors. Our data showed that the 5′ UTR of VP2 enhanced capsid gene transcription but not increased stability or promotes nucleocytoplasmic export of VP2 mRNA. Analysis of the functions of 5′ UTR fragments showed that the proximal region (nucleotides [nt] 1 to 270; that is, positions +1 to +270 relative to the transcription initiation site, nt 2048 to 2317 of MEV-L) of 5′ UTR of VP2 was necessary for VP2 transcription and also promoted the activity of P38 promoter. Unexpectedly, further analysis showed that deletion of the distal region (nt 271 to 653) of the 5′ UTR of VP2 almost completely abolished VP2 translation in the presence of P38, whereas the transcription was still induced significantly. Furthermore, using a luciferase reporter bicistronic system, we identified that the 5′ UTR had an internal ribosome entry site-like function which could be enhanced by NS1 via the site at nt 382 to 447. Mutation of the 5′ UTR in the MEV full-length clones further showed that the 5′ UTR was required for VP2 gene expression. Together, our data reveal an undiscovered function of 5′ UTR of MEV VP2 in regulating viral gene expression.IMPORTANCEMEV, a parvovirus, causes acute enteritis in mink. In the present report, we describe an untranslated sequence-dependent mechanism by which MEV regulates capsid gene expression. Our results highlight the roles of untranslated sequences in regulating the transcriptional activity of P38 promoter and translation of capsid genes. These data also reveal the possibility of an unusual translation mechanism in capsid protein expression and the multiple functions of nonstructural protein. A better understanding of the gene expression regulation mechanism of this virus will help in the design of new vaccines and targets for antiviral agents against MEV.

2019 ◽  
Vol 78 ◽  
pp. 01002
Author(s):  
Zhou-Tong Dai ◽  
Ao Yao ◽  
Yuan Xiang ◽  
Jia Peng Li ◽  
Wei Guo ◽  
...  

CD44, cluster of differentiation 44 is a typical marker of stem cells. At present, it has been found that CD44 is prevalent in various human malignant tumors, but its expression regulation mechanism is still not clear. The initiation of gene expression, the modification of RNA levels, and the regulation of protein levels are the main factors affecting the expression level of genes, and the most critical one is the regulation of gene expression by signaling pathways. Up to now, there has been no report on the role of MKL-1 in the cloning of the cd44 promoter. Therefore, this study intends to clone the cd44 gene promoter, construct its luciferase reporter gene vector, transfect the MKL-1 overexpression vector, and analyze how it affects transcriptional activity, in order to further study the expression regulation of cd44. The mechanism provides a powerful tool in the future.


2021 ◽  
Vol 16 ◽  
Author(s):  
Min Yao ◽  
Caiyun Jiang ◽  
Chenglong Li ◽  
Yongxia Li ◽  
Shan Jiang ◽  
...  

Background: Mammalian genes are regulated at the transcriptional and post-transcriptional levels. These mechanisms may involve the direct promotion or inhibition of transcription via a regulator or post-transcriptional regulation through factors such as micro (mi)RNAs. Objective: This study aimed to construct gene regulation relationships modulated by causality inference-based miRNA-(transition factor)-(target gene) networks and analyze gene expression data to identify gene expression regulators. Methods: Mouse gene expression regulation relationships were manually curated from literature using a text mining method which was then employed to generate miRNA-(transition factor)-(target gene) networks. An algorithm was then introduced to identify gene expression regulators from transcriptome profiling data by applying enrichment analysis to these networks. Results: A total of 22,271 mouse gene expression regulation relationships were curated for 4,018 genes and 242 miRNAs. GEREA software was developed to perform the integrated analyses. We applied the algorithm to transcriptome data for synthetic miR-155 oligo-treated mouse CD4+ T-cells and confirmed that miR-155 is an important network regulator. The software was also tested on publicly available transcriptional profiling data for Salmonella infection, resulting in the identification of miR-125b as an important regulator. Conclusion: The causality inference-based miRNA-(transition factor)-(target gene) networks serve as a novel resource for gene expression regulation research, and GEREA is an effective and useful adjunct to the currently available methods. The regulatory networks and the algorithm implemented in the GEREA software package are available under a free academic license at website : http://www.thua45.cn/gerea.


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