scholarly journals Cellular factors that interact with the hepatitis B virus enhancer.

1989 ◽  
Vol 9 (4) ◽  
pp. 1804-1809 ◽  
Author(s):  
R Ben-Levy ◽  
O Faktor ◽  
I Berger ◽  
Y Shaul
Keyword(s):  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Phorbol Ester ◽  
Base Pair ◽  
Binding Sites ◽  
Globin Gene ◽  
Gene Promoter ◽  
Cellular Factors ◽  
B Virus ◽  
Dna Fragment

An 83-base-pair-long hepatitis B virus DNA fragment efficiently activates the transcription of the heterologous globin gene promoter. This fragment contains binding sites for at least four distinct cellular factors termed E, TGT3, EP, and NF-I. E is a positively acting factor, responsive to phorbol ester. EP is apparently identical to the factor EF-C that binds to the polyomavirus enhancer. The conservation of the binding site sequences for most of these factors in the genomes of other members of the hepadnavirus family suggests that these viruses share common enhancer elements.

Cellular factors that interact with the hepatitis B virus enhancer

1989 ◽  
Vol 9 (4) ◽  
pp. 1804-1809
Author(s):  
R Ben-Levy ◽  
O Faktor ◽  
I Berger ◽  
Y Shaul
Keyword(s):  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Phorbol Ester ◽  
Base Pair ◽  
Binding Sites ◽  
Globin Gene ◽  
Gene Promoter ◽  
Cellular Factors ◽  
B Virus ◽  
Dna Fragment

An 83-base-pair-long hepatitis B virus DNA fragment efficiently activates the transcription of the heterologous globin gene promoter. This fragment contains binding sites for at least four distinct cellular factors termed E, TGT3, EP, and NF-I. E is a positively acting factor, responsive to phorbol ester. EP is apparently identical to the factor EF-C that binds to the polyomavirus enhancer. The conservation of the binding site sequences for most of these factors in the genomes of other members of the hepadnavirus family suggests that these viruses share common enhancer elements.

Hepatitis B virus C gene promoter is under negative regulation

Virology ◽  
1992 ◽  
Vol 189 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Karen K. Gerlach ◽  
Robert H. Schloemer
Keyword(s):  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Gene Promoter ◽  
Negative Regulation ◽  
B Virus ◽  
Virus C

Identification of a promoter element located upstream from the hepatitis B virus X gene

1987 ◽  
Vol 7 (1) ◽  
pp. 545-548
Author(s):  
M Treinin ◽  
O Laub
Keyword(s):  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Gene Promoter ◽  
Maximal Activity ◽  
Enhancer Element ◽  
B Virus ◽  
X Gene ◽  
Rna Mapping ◽  
Active Promoter ◽  
Cat Gene

We have analyzed a series of plasmids in which the sequences located upstream from the hepatitis B virus (HBV) X gene were linked to the chloramphenicol acetyl transferase (CAT) gene. Expression of the marker CAT gene in transfected cells clearly demonstrated that sequences preceding the X gene contain an active promoter. RNA mapping by primer extension indicated that the RNA encoded by the X gene promoter initiates at multiple sites spanning nucleotides 1250 to 1350 on the HBV genome. Deletion within the adjacent HBV enhancer element region significantly reduced the activity of the X gene promoter, suggesting that the X gene promoter requires the enhancer element for maximal activity.

scholarly journals Prospero-related homeobox protein (Prox1) inhibits hepatitis B virus replication through repressing multiple cis regulatory elements

2009 ◽  
Vol 90 (5) ◽  
pp. 1246-1255 ◽  
Author(s):  
Jun Qin ◽  
Jianwei Zhai ◽  
Ran Hong ◽  
Shifang Shan ◽  
Yuying Kong ◽  
...  
Keyword(s):  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Core Promoter ◽  
Antigen Expression ◽  
Regulatory Elements ◽  
Genome Replication ◽  
Nuclear Factor ◽  
Cellular Factors ◽  
B Virus ◽  
Homeobox Protein

Hepatitis B virus (HBV) gene transcription is controlled by viral promoters and enhancers, the activities of which are regulated by a number of cellular factors as well as virally encoded proteins. Negative regulation of HBV cis-element activities by cellular factors has been reported less widely than their activation. In this study, we report that nuclear factor Prospero-related homeobox protein (Prox1) represses HBV antigen expression and genome replication in cultured hepatocytes. By using reporter-gene analysis, three of the four HBV promoters, namely the enhancer II/core promoter (ENII/Cp), preS1 promoter (Sp1) and enhancer I/X promoter, were identified as targets for Prox1-mediated repression. Mechanistic analysis then revealed that, for ENII/Cp, Prox1 serves as a corepressor of liver receptor homologue 1 (LRH-1) and downregulates LRH-1-mediated activation of ENII/Cp, whereas for Sp1, Prox1 partially represses Sp1 activity by interacting directly with hepatocyte nuclear factor 1. Identification of Prox1 as an HBV repressor will help in the understanding of detailed interactions between viral cis elements and host cellular factors and may also form the basis for new anti-HBV intervention therapeutics.

scholarly journals DeepHBV: A deep learning model to predict hepatitis B virus (HBV) integration sites.

2021 ◽  
Author(s):  
Canbiao Wu ◽  
Xiaofang Guo ◽  
Mengyuan Li ◽  
Xiayu Fu ◽  
Zeliang Hou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Binding Sites ◽  
Learning Model ◽  
Validation Dataset ◽  
B Virus ◽  
Integration Sites ◽  
Deep Learning Model ◽  
Pan Cancer

Hepatitis B virus (HBV) is one of the main causes for viral hepatitis and liver cancer. Previous studies showed HBV can integrate into host genome and further promote malignant transformation. In this study, we developed an attention-based deep learning model DeepHBV to predict HBV integration sites by learning local genomic features automatically. We trained and tested DeepHBV using the HBV integration sites data from dsVIS database. Initially, DeepHBV showed AUROC of 0.6363 and AUPR of 0.5471 on the dataset. Adding repeat peaks and TCGA Pan Cancer peaks can significantly improve the model performance, with an AUROC of 0.8378 and 0.9430 and an AUPR of 0.7535 and 0.9310, respectively. On independent validation dataset of HBV integration sites from VISDB, DeepHBV with HBV integration sequences plus TCGA Pan Cancer (AUROC of 0.7603 and AUPR of 0.6189) performed better than HBV integration sequences plus repeat peaks (AUROC of 0.6657 and AUPR of 0.5737). Next, we found the transcriptional factor binding sites (TFBS) were significantly enriched near genomic positions that were paid attention to by convolution neural network. The binding sites of AR-halfsite, Arnt, Atf1, bHLHE40, bHLHE41, BMAL1, CLOCK, c-Myc, COUP-TFII, E2A, EBF1, Erra and Foxo3 were highlighted by DeepHBV attention mechanism in both dsVIS dataset and VISDB dataset, revealing the HBV integration preference. In summary, DeepHBV is a robust and explainable deep learning model not only for the prediction of HBV integration sites but also for further mechanism study of HBV induced cancer.

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