Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View

Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View

Development of an effective HIV management is enticed by the fact that long-term non-progressors (LTNP) restrict viral replication spontaneously, but is hindered by HIV-1 latency. Given that the most overlapping characteristics found between HIV-1 LTNP and latency, detailed analysis of the differenc...

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Main Authors: Yang, Jin, Yang, Zongxing, Lv, Hangjun, Lou, Yi, Wang, Juan, Wu, Nanping
Format: Online
Language:English
Published: Public Library of Science 2013
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3581534/
id pubmed-3581534
recordtype oai_dc
spelling pubmed-35815342013-02-28 Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View Yang, Jin Yang, Zongxing Lv, Hangjun Lou, Yi Wang, Juan Wu, Nanping Research Article Development of an effective HIV management is enticed by the fact that long-term non-progressors (LTNP) restrict viral replication spontaneously, but is hindered by HIV-1 latency. Given that the most overlapping characteristics found between HIV-1 LTNP and latency, detailed analysis of the difference would disclose the essentials of latency. In this study, microarray data from our previous study was combined with HIV-1 latency and LTNP data obtained from NCBI GEO database. Principal variance component analysis and hierarchical clustering verified the removal of batch effect across platform. The analysis revealed a total of 456 differential expressed genes with >2-fold change and B-statistic >0. Bayesian inference was used to reconstitute the transcriptional network of HIV-1 latency or LTNP, respectively. Gene regulation was reprogrammed under different disease condition. By network interference, KPNA2 and ATP5G3 were identified as the hubs in latency network which mediate nuclear export and RNA processing. These data offer comparative insights into HIV-1 latency, which will facilitate the understanding of the genetic basis of HIV-1 latency in vivo and serve as a clue for future treatment dealing with key targets in HIV-1 latency. Public Library of Science 2013-02-25 /pmc/articles/PMC3581534/ /pubmed/23451031 http://dx.doi.org/10.1371/journal.pone.0055791 Text en © 2013 Yang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Yang, Jin
Yang, Zongxing
Lv, Hangjun
Lou, Yi
Wang, Juan
Wu, Nanping
spellingShingle Yang, Jin
Yang, Zongxing
Lv, Hangjun
Lou, Yi
Wang, Juan
Wu, Nanping
Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View
author_facet Yang, Jin
Yang, Zongxing
Lv, Hangjun
Lou, Yi
Wang, Juan
Wu, Nanping
author_sort Yang, Jin
title Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View
title_short Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View
title_full Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View
title_fullStr Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View
title_full_unstemmed Bridging HIV-1 Cellular Latency and Clinical Long-Term Non-Progressor: An Interactomic View
title_sort bridging hiv-1 cellular latency and clinical long-term non-progressor: an interactomic view
description Development of an effective HIV management is enticed by the fact that long-term non-progressors (LTNP) restrict viral replication spontaneously, but is hindered by HIV-1 latency. Given that the most overlapping characteristics found between HIV-1 LTNP and latency, detailed analysis of the difference would disclose the essentials of latency. In this study, microarray data from our previous study was combined with HIV-1 latency and LTNP data obtained from NCBI GEO database. Principal variance component analysis and hierarchical clustering verified the removal of batch effect across platform. The analysis revealed a total of 456 differential expressed genes with >2-fold change and B-statistic >0. Bayesian inference was used to reconstitute the transcriptional network of HIV-1 latency or LTNP, respectively. Gene regulation was reprogrammed under different disease condition. By network interference, KPNA2 and ATP5G3 were identified as the hubs in latency network which mediate nuclear export and RNA processing. These data offer comparative insights into HIV-1 latency, which will facilitate the understanding of the genetic basis of HIV-1 latency in vivo and serve as a clue for future treatment dealing with key targets in HIV-1 latency.
publisher Public Library of Science
publishDate 2013
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3581534/
_version_ 1611957432955699200

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