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MicroRNAs01:22

MicroRNAs

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MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After...
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MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
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Viruses with RNA Genomes

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RNA viruses are categorized into positive-strand, negative-strand, or double-stranded groups based on their genomic structure and replication mechanisms. This classification dictates how they exploit host cellular machinery for protein synthesis and replication. Some RNA viruses also utilize reverse transcription as part of their life cycle, further diversifying their replication strategies.Positive-Strand RNA VirusesPositive-strand RNA viruses have genomes that function directly as messenger...
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RNA Interference01:23

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RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions
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Developing a virus-microRNA interactome using cytoscape.

Meredith Hill1, Dayna Mason1, Tânia Monteiro Marques2

  • 1School Biomedical Engineering, University of Technology Sydney, NSW, Australia.

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|January 30, 2020
PubMed
Summary
This summary is machine-generated.

This study presents a method to analyze oncogenic virus-protein-miRNA interactions using Cytoscape. This approach helps identify cellular pathways altered by viruses, aiding in cancer diagnosis and treatment.

Keywords:
Developing a virus-microRNA interactomeGene expressionMicroRNANetwork analysisRegulatory networksVisualisation

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Area of Science:

  • Molecular biology
  • Virology
  • Bioinformatics

Background:

  • Oncogenic viruses significantly impact mammalian cell pathways, but their global effects are poorly understood.
  • Identifying molecular targets is crucial for developing early diagnosis, prevention, and treatment strategies for virus-associated cancers.
  • Current methods lack comprehensive approaches to map viral interactions and their downstream effects on cellular regulation.

Purpose of the Study:

  • To provide a step-by-step guide for uncovering viral-protein-miRNA interactions using public datasets and Cytoscape.
  • To enable the identification of specific cellular pathways dysregulated by oncogenic viruses.
  • To demonstrate the utility of this method by constructing a gene regulatory interactome for Human Papillomavirus Type 16 (HPV16).

Main Methods:

  • Utilizing publicly available datasets to identify viral proteins and their interacting microRNAs (miRNAs).
  • Employing the network visualization and analysis software Cytoscape to build gene regulatory interactomes.
  • Integrating data to map the interactions between viral proteins, miRNAs, and host cell genes.

Main Results:

  • A gene regulatory interactome for HPV16 and its regulated miRNAs was successfully constructed.
  • The method demonstrated the ability to visualize and analyze complex molecular interactions.
  • The approach facilitates the mapping of viral regulatory functions and their impact on host gene expression.

Conclusions:

  • The developed method offers a robust framework for analyzing viral-host interactions at the molecular level.
  • This approach can be broadly applied to study other oncogenic viruses and their roles in cellular transformation.
  • Understanding these interactions is key to identifying novel therapeutic targets and improving cancer management strategies.