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Meta- and orthogonal integration of influenza "OMICs" data defines a role for UBR4 in virus budding

Abstract

Several systems-level datasets designed to dissect host-pathogen interactions during influenza A infection have been reported. However, apparent discordance among these data has hampered their full utility toward advancing mechanistic and therapeutic knowledge. To collectively reconcile these datasets, we performed a meta-analysis of data from eight published RNAi screens and integrated these data with three protein interaction datasets, including one generated within the context of this study. Further integration of these data with global virus-host interaction analyses revealed a functionally validated biochemical landscape of the influenza-host interface, which can be queried through a simplified and customizable web portal (http://www.metascape.org/IAV). Follow-up studies revealed that the putative ubiquitin ligase UBR4 associates with the viral M2 protein and promotes apical transport of viral proteins. Taken together, the integrative analysis of influenza OMICs datasets illuminates a viral-host network of high-confidence human proteins that are essential for influenza A virus replication.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Medical Virology
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Scopus Subject Areas:Life Sciences > Parasitology
Life Sciences > Microbiology
Life Sciences > Virology
Language:English
Date:9 December 2015
Deposited On:15 Feb 2016 15:21
Last Modified:14 Aug 2024 01:40
Publisher:Cell Press (Elsevier)
ISSN:1931-3128
Funders:NIAID research grant U19 AI106754, Swiss National Science Foundation (31003A_135278) to S. Stertz, doctoral grant from the AXA Research Fund, NIH P50 GM085764
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.chom.2015.11.002
Official URL:http://www.sciencedirect.com/science/article/pii/S1931312815004564
PubMed ID:26651948
Project Information:
  • Funder:
  • Grant ID:
  • Project Title: NIAID research grant U19 AI106754
  • Funder: SNSF
  • Grant ID:
  • Project Title: Swiss National Science Foundation (31003A_135278) to S. Stertz
  • Funder:
  • Grant ID:
  • Project Title: doctoral grant from the AXA Research Fund
  • Funder:
  • Grant ID:
  • Project Title: NIH P50 GM085764
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