Dataset Information

Proteomic Analysis of Measles Virus Protein C-Host Interactions in an Infectious Context Using Recombinant Viruses

ABSTRACT: Viruses manipulate central machineries of host cells to their advantage. They prevent host cell antiviral responses in order to create a favourable environment for their survival and propagation. Measles virus (MV) encodes two non-structural proteins MV-V and MV-C, proposed to counteract the host interferon response and to regulate cell death pathways in various functional assays. Several molecular mechanisms underlining MV-V regulation of innate immunity and cell death responses have been proposed, whereas MV-C host protein partners are less studied. We suggest that some cellular factors that are controlled by MV-C protein during viral replication could be components of innate immunity and the cell death pathways. In order to determine which host factors are hijacked by MV-C, we captured both direct and indirect host protein partners of MV-C protein. For this we used a strategy based on recombinant viruses expressing tagged viral proteins followed by affinity purification and a bottom-up mass spectrometry analysis. A list of host proteins specifically interacting with MV-C protein in different cell lines was identified.

INSTRUMENT(S): Q Exactive Plus

ORGANISM(S): Homo Sapiens (human) Viruses

TISSUE(S): Epithelial Cell, Cell Culture, Embryonic Stem Cell

SUBMITTER: Thibaut Douché

LAB HEAD: Frédéric TANGY

PROVIDER: PXD015316 | Pride | 2021-01-19

REPOSITORIES: Pride

ACCESS DATA

Similar Datasets

Project description:Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. These complementary approaches together result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer. We profiled the transcriptome of human cells expressing tumor virus proteins, in order to trace pathways through which viral proteins could alter cellular states. To examine transcriptome network perturbations directly in human cells, we generated expression constructs fusing each viral ORF (open reading frame) to a tandem epitope tag and introduced each construct into IMR-90 normal human diploid fibroblasts. Total RNA was isolated from IMR-90 cells expressing viORFs and gene expression was assayed on Human Gene 1.0 ST arrays.

Dataset Information

Proteomic Analysis of Measles Virus Protein C-Host Interactions in an Infectious Context Using Recombinant Viruses

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure