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Sci Rep. 2019 Jan 18;9(1):213. doi: 10.1038/s41598-018-36135-3.

Proteo-Transcriptomic Dynamics of Cellular Response to HIV-1 Infection.

Author information

1
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
2
SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
3
Institute of Microbiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
4
InvivoGen, Toulouse, France.
5
Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
6
Computational Systems Biology Team, Institut de Biologie de I'Ecole Normale Supérieure, CNRS UMR8197, INSERM U1024, ENS, PSL Université, Paris, France.
7
Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, (CA), USA.
8
Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, (CA), USA. atelenti@scripps.edu.
9
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland. niko.beerenwinkel@bsse.ethz.ch.
10
SIB Swiss Institute of Bioinformatics, Basel, Switzerland. niko.beerenwinkel@bsse.ethz.ch.
11
Institute of Microbiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. angela.ciuffi@chuv.ch.

Abstract

Throughout the HIV-1 replication cycle, complex host-pathogen interactions take place in the infected cell, leading to the production of new virions. The virus modulates the host cellular machinery in order to support its life cycle, while counteracting intracellular defense mechanisms. We investigated the dynamic host response to HIV-1 infection by systematically measuring transcriptomic, proteomic, and phosphoproteomic expression changes in infected and uninfected SupT1 CD4+ T cells at five time points of the viral replication process. By means of a Gaussian mixed-effects model implemented in the new R/Bioconductor package TMixClust, we clustered host genes based on their temporal expression patterns. We identified a proteo-transcriptomic gene expression signature of 388 host genes specific for HIV-1 replication. Comprehensive functional analyses of these genes confirmed the previously described roles of some of the genes and revealed novel key virus-host interactions affecting multiple molecular processes within the host cell, including signal transduction, metabolism, cell cycle, and immune system. The results of our analysis are accessible through a freely available, dedicated and user-friendly R/Shiny application, called PEACHi2.0. This resource constitutes a catalogue of dynamic host responses to HIV-1 infection that provides a basis for a more comprehensive understanding of virus-host interactions.

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