Evidence map›Paper›PMID 32539747›Full record

ArticleGenome biology2020

Dynamic rewiring of the human interactome by interferon signaling.

Craig H Kerr, Michael A Skinnider, Daniel D T Andrews, Angel M Madero, Queenie W T Chan, R Greg Stacey, Nikolay Stoynov, Eric Jan, Leonard J Foster

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. The Effects ofBioMed research international · 2023
    Article
  12. Article
  13. Article
  14. The SARS-CoV-2 RNA interactome.Molecular cell · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 2 countries.

Craig H KerrMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Michael A SkinniderMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Daniel D T AndrewsDepartment of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
Angel M MaderoMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Queenie W T ChanMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
R Greg StaceyMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Nikolay StoynovMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Eric JanDepartment of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
Leonard J FosterMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada. foster@msl.ubc.ca.ORCID 0000-0001-8551-4817
University of British Columbia · CA

Funding

CIHR
6 · The paper itself

Abstract

backgroundThe type I interferon (IFN) response is an ancient pathway that protects cells against viral pathogens by inducing the transcription of hundreds of IFN-stimulated genes. Comprehensive catalogs of IFN-stimulated genes have been established across species and cell types by transcriptomic and biochemical approaches, but their antiviral mechanisms remain incompletely characterized. Here, we apply a combination of quantitative proteomic approaches to describe the effects of IFN signaling on the human proteome, and apply protein correlation profiling to map IFN-induced rearrangements in the human protein-protein interaction network.

resultsWe identify > 26,000 protein interactions in IFN-stimulated and unstimulated cells, many of which involve proteins associated with human disease and are observed exclusively within the IFN-stimulated network. Differential network analysis reveals interaction rewiring across a surprisingly broad spectrum of cellular pathways in the antiviral response. We identify IFN-dependent protein-protein interactions mediating novel regulatory mechanisms at the transcriptional and translational levels, with one such interaction modulating the transcriptional activity of STAT1. Moreover, we reveal IFN-dependent changes in ribosomal composition that act to buffer IFN-stimulated gene protein synthesis.

conclusionsOur map of the IFN interactome provides a global view of the complex cellular networks activated during the antiviral response, placing IFN-stimulated genes in a functional context, and serves as a framework to understand how these networks are dysregulated in autoimmune or inflammatory disease.

Indexed as

Protein Interaction MapsProteomeHost-Pathogen InteractionsHumansInterferon Type IProteomicsRibosomal ProteinsSignal TransductionVirus DiseasesInterferon Type IProteomeRibosomal ProteinsRPL28 protein, humanInnate immunityInteractomeInterferonInterferon-stimulated geneProtein complexesProtein correlation profilingProteomics

Identifiers

PMID32539747
PMCPMC7294662
OpenAlexW3035726067

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.