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Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction

The interaction of human immunodeficiency virus with human cells is responsible for all stages of the viral life cycle, from the infection of CD4+ cells to reverse transcription, integration, and the assembly of new viral particles. To date, a large amount of OMICs data as well as information from f...

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Autores principales: Ivanov, Sergey, Lagunin, Alexey, Filimonov, Dmitry, Tarasova, Olga
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311653/
https://www.ncbi.nlm.nih.gov/pubmed/32625189
http://dx.doi.org/10.3389/fmicb.2020.01314
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author Ivanov, Sergey
Lagunin, Alexey
Filimonov, Dmitry
Tarasova, Olga
author_facet Ivanov, Sergey
Lagunin, Alexey
Filimonov, Dmitry
Tarasova, Olga
author_sort Ivanov, Sergey
collection PubMed
description The interaction of human immunodeficiency virus with human cells is responsible for all stages of the viral life cycle, from the infection of CD4+ cells to reverse transcription, integration, and the assembly of new viral particles. To date, a large amount of OMICs data as well as information from functional genomics screenings regarding the HIV–host interaction has been accumulated in the literature and in public databases. We processed databases containing HIV–host interactions and found 2910 HIV-1-human protein-protein interactions, mostly related to viral group M subtype B, 137 interactions between human and HIV-1 coding and non-coding RNAs, essential for viral lifecycle and cell defense mechanisms, 232 transcriptomics, 27 proteomics, and 34 epigenomics HIV-related experiments. Numerous studies regarding network-based analysis of corresponding OMICs data have been published in recent years. We overview various types of molecular networks, which can be created using OMICs data, including HIV–human protein–protein interaction networks, co-expression networks, gene regulatory and signaling networks, and approaches for the analysis of their topology and dynamics. The network-based analysis can be used to determine the critical pathways and key proteins involved in the HIV life cycle, cellular and immune responses to infection, viral escape from host defense mechanisms, and mechanisms mediating different susceptibility of humans to infection. The proteins and pathways identified in these studies represent a basis for developing new anti-HIV therapeutic strategies such as new drugs preventing infection of CD4+ cells and viral replication, effective vaccines, “shock and kill” and “block and lock” approaches to cure latent infection.
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spelling pubmed-73116532020-07-02 Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction Ivanov, Sergey Lagunin, Alexey Filimonov, Dmitry Tarasova, Olga Front Microbiol Microbiology The interaction of human immunodeficiency virus with human cells is responsible for all stages of the viral life cycle, from the infection of CD4+ cells to reverse transcription, integration, and the assembly of new viral particles. To date, a large amount of OMICs data as well as information from functional genomics screenings regarding the HIV–host interaction has been accumulated in the literature and in public databases. We processed databases containing HIV–host interactions and found 2910 HIV-1-human protein-protein interactions, mostly related to viral group M subtype B, 137 interactions between human and HIV-1 coding and non-coding RNAs, essential for viral lifecycle and cell defense mechanisms, 232 transcriptomics, 27 proteomics, and 34 epigenomics HIV-related experiments. Numerous studies regarding network-based analysis of corresponding OMICs data have been published in recent years. We overview various types of molecular networks, which can be created using OMICs data, including HIV–human protein–protein interaction networks, co-expression networks, gene regulatory and signaling networks, and approaches for the analysis of their topology and dynamics. The network-based analysis can be used to determine the critical pathways and key proteins involved in the HIV life cycle, cellular and immune responses to infection, viral escape from host defense mechanisms, and mechanisms mediating different susceptibility of humans to infection. The proteins and pathways identified in these studies represent a basis for developing new anti-HIV therapeutic strategies such as new drugs preventing infection of CD4+ cells and viral replication, effective vaccines, “shock and kill” and “block and lock” approaches to cure latent infection. Frontiers Media S.A. 2020-06-17 /pmc/articles/PMC7311653/ /pubmed/32625189 http://dx.doi.org/10.3389/fmicb.2020.01314 Text en Copyright © 2020 Ivanov, Lagunin, Filimonov and Tarasova. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Ivanov, Sergey
Lagunin, Alexey
Filimonov, Dmitry
Tarasova, Olga
Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction
title Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction
title_full Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction
title_fullStr Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction
title_full_unstemmed Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction
title_short Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction
title_sort network-based analysis of omics data to understand the hiv–host interaction
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311653/
https://www.ncbi.nlm.nih.gov/pubmed/32625189
http://dx.doi.org/10.3389/fmicb.2020.01314
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