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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-06-01
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| Series: | Frontiers in Microbiology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fmicb.2020.01314/full |
| _version_ | 1811222922570760192 |
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| author | Sergey Ivanov Sergey Ivanov Alexey Lagunin Alexey Lagunin Dmitry Filimonov Olga Tarasova |
| author_facet | Sergey Ivanov Sergey Ivanov Alexey Lagunin Alexey Lagunin Dmitry Filimonov Olga Tarasova |
| author_sort | Sergey Ivanov |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-12T08:24:26Z |
| format | Article |
| id | doaj.art-6dde30fed07640d7b03873bc05a79afc |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-04-12T08:24:26Z |
| publishDate | 2020-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-6dde30fed07640d7b03873bc05a79afc2022-12-22T03:40:28ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2020-06-011110.3389/fmicb.2020.01314550549Network-Based Analysis of OMICs Data to Understand the HIV–Host InteractionSergey Ivanov0Sergey Ivanov1Alexey Lagunin2Alexey Lagunin3Dmitry Filimonov4Olga Tarasova5Department of Bioinformatics, Institute of Biomedical Chemistry, Moscow, RussiaDepartment of Bioinformatics, Pirogov Russian National Research Medical University, Moscow, RussiaDepartment of Bioinformatics, Institute of Biomedical Chemistry, Moscow, RussiaDepartment of Bioinformatics, Pirogov Russian National Research Medical University, Moscow, RussiaDepartment of Bioinformatics, Institute of Biomedical Chemistry, Moscow, RussiaDepartment of Bioinformatics, Institute of Biomedical Chemistry, Moscow, RussiaThe 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.https://www.frontiersin.org/article/10.3389/fmicb.2020.01314/fullvirus–host interactionhuman immunodeficiency virusprotein–protein interactionsOMICstranscriptomicsnetwork analysis |
| spellingShingle | Sergey Ivanov Sergey Ivanov Alexey Lagunin Alexey Lagunin Dmitry Filimonov Olga Tarasova Network-Based Analysis of OMICs Data to Understand the HIV–Host Interaction Frontiers in Microbiology virus–host interaction human immunodeficiency virus protein–protein interactions OMICs transcriptomics network analysis |
| 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 | virus–host interaction human immunodeficiency virus protein–protein interactions OMICs transcriptomics network analysis |
| url | https://www.frontiersin.org/article/10.3389/fmicb.2020.01314/full |
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