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Identification of molecular sub-networks associated with cell survival in a chronically SIVmac-infected human CD4+ T cell line

Feng Q He18, Ulrike Sauermann2, Christiane Beer37, Silke Winkelmann3, Zheng Yu3, Sieghart Sopper245, An-Ping Zeng16 and Manfred Wirth3*

Author Affiliations

1 Group Systems Biology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, D-38124 Braunschweig, Germany

2 Infection models, German Primate Centre DPZ, Kellnerweg 4, D-37077 Göttingen, Germany

3 Epigenetic Regulation Mechanisms, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, 38124 Braunschweig, Germany

4 Tumor Immunology Lab, Hematology and Oncology, Medical University Innsbruck, Innsbruck, Austria

5 Tyrolean Cancer Research Institute, Innsbruck, Austria

6 Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, Dennickestr. 15, D-21073 Hamburg, Germany

7 Present address: Department of Molecular Biology, Aarhus University, C.F. Mollers Alle 130, Aarhus, Denmark

8 Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7, Avenue des Hauts Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg

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Virology Journal 2014, 11:152  doi:10.1186/1743-422X-11-152

Published: 27 August 2014

Abstract

Background

The deciphering of cellular networks to determine susceptibility to infection by HIV or the related simian immunodeficiency virus (SIV) is a major challenge in infection biology.

Results

Here, we have compared gene expression profiles of a human CD4+ T cell line at 24 h after infection with a cell line of the same origin permanently releasing SIVmac. A new knowledge-based-network approach (Inter-Chain-Finder, ICF) has been used to identify sub-networks associated with cell survival of a chronically SIV-infected T cell line. Notably, the method can identify not only differentially expressed key hub genes but also non-differentially expressed, critical, ‘hidden’ regulators. Six out of the 13 predicted major hidden key regulators were among the landscape of proteins known to interact with HIV. Several sub-networks were dysregulated upon chronic infection with SIV. Most prominently, factors reported to be engaged in early stages of acute viral infection were affected, e.g. entry, integration and provirus transcription and other cellular responses such as apoptosis and proliferation were modulated. For experimental validation of the gene expression analyses and computational predictions, individual pathways/sub-networks and significantly altered key regulators were investigated further. We showed that the expression of caveolin-1 (Cav-1), the top hub in the affected protein-protein interaction network, was significantly upregulated in chronically SIV-infected CD4+ T cells. Cav-1 is the main determinant of caveolae and a central component of several signal transduction pathways. Furthermore, CD4 downregulation and modulation of the expression of alternate and co-receptors as well as pathways associated with viral integration into the genome were also observed in these cells. Putatively, these modifications interfere with re-infection and the early replication cycle and inhibit cell death provoked by syncytia formation and bystander apoptosis.

Conclusions

Thus, by using the novel approach for network analysis, ICF, we predict that in the T cell line chronically infected with SIV, cellular processes that are known to be crucial for early phases of HIV/SIV replication are altered and cellular responses that result in cell death are modulated. These modifications presumably contribute to cell survival despite chronic infection.

Keywords:
Human T cell line; Chronic SIV/HIV infection; Virus-host-interaction; Transcriptome; Network analysis; Caveolin-1; CD4; Key gene prediction; Systems biology