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Computational analysis of HIV-1 resistance based on gene expression profiles and the virus-host interaction network

Authors :
Xiangyin Kong
Yu-Dong Cai
Lei Chen
Tao Huang
Zhongping Xu
Source :
PLoS ONE, Vol 6, Iss 3, p e17291 (2011), PLoS ONE
Publication Year :
2011
Publisher :
Public Library of Science (PLoS), 2011.

Abstract

A very small proportion of people remain negative for HIV infection after repeated HIV-1 viral exposure, which is called HIV-1 resistance. Understanding the mechanism of HIV-1 resistance is important for the development of HIV-1 vaccines and Acquired Immune Deficiency Syndrome (AIDS) therapies. In this study, we analyzed the gene expression profiles of CD4+ T cells from HIV-1-resistant individuals and HIV-susceptible individuals. One hundred eighty-five discriminative HIV-1 resistance genes were identified using the Minimum Redundancy-Maximum Relevance (mRMR) and Incremental Feature Selection (IFS) methods. The virus protein target enrichment analysis of the 185 HIV-1 resistance genes suggested that the HIV-1 protein nef might play an important role in HIV-1 infection. Moreover, we identified 29 infection information exchanger genes from the 185 HIV-1 resistance genes based on a virus-host interaction network analysis. The infection information exchanger genes are located on the shortest paths between virus-targeted proteins and are important for the coordination of virus infection. These proteins may be useful targets for AIDS prevention or therapy, as intervention in these pathways could disrupt communication with virus-targeted proteins and HIV-1 infection.

Details

Language :
English
ISSN :
19326203
Volume :
6
Issue :
3
Database :
OpenAIRE
Journal :
PLoS ONE
Accession number :
edsair.doi.dedup.....0bce46dc7b403fbe1ad73166509bbf7b