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Influenza A Virus Induces Autophagosomal Targeting of Ribosomal Proteins*

Overview of attention for article published in Molecular and Cellular Proteomics, July 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#50 of 3,226)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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7 news outlets
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3 X users

Citations

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23 Dimensions

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34 Mendeley
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Title
Influenza A Virus Induces Autophagosomal Targeting of Ribosomal Proteins*
Published in
Molecular and Cellular Proteomics, July 2018
DOI 10.1074/mcp.ra117.000364
Pubmed ID
Authors

Andrea C. Becker, Monique Gannagé, Sebastian Giese, Zehan Hu, Shadi Abou-Eid, Carole Roubaty, Petra Paul, Lea Bühler, Christine Gretzmeier, Veronica I. Dumit, Stéphanie Kaeser-Pebernard, Martin Schwemmle, Christian Münz, Jörn Dengjel

Abstract

Seasonal epidemics of influenza A virus are a major cause of severe illness and are of high socio-economic relevance. For the design of effective anti-viral therapies, a detailed knowledge of pathways perturbed by virus infection is critical. We performed comprehensive expression and organellar proteomics experiments to study the cellular consequences of influenza A virus infection using three human epithelial cell lines derived from human lung carcinomas: A549, Calu-1 and NCI-H1299. As a common response, the type I interferon pathway was upregulated upon infection. Interestingly, influenza A virus infection led to numerous cell line-specific responses affecting both protein abundance as well as subcellular localization. In A549 cells, the vesicular compartment appeared expanded after virus infection. In particular, the composition of autophagsomes was altered by targeting of ribosomes, viral mRNA and proteins to these double membrane vesicles. Thus, autophagy may support viral protein translation by promoting the clustering of the respective molecular machinery in autophagosomes in a cell line-dependent manner.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 21%
Student > Ph. D. Student 5 15%
Other 3 9%
Student > Bachelor 2 6%
Professor 2 6%
Other 5 15%
Unknown 10 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 21%
Biochemistry, Genetics and Molecular Biology 7 21%
Immunology and Microbiology 4 12%
Veterinary Science and Veterinary Medicine 2 6%
Medicine and Dentistry 1 3%
Other 0 0%
Unknown 13 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 52. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 October 2018.
All research outputs
#814,067
of 25,508,813 outputs
Outputs from Molecular and Cellular Proteomics
#50
of 3,226 outputs
Outputs of similar age
#17,440
of 341,260 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#6
of 46 outputs
Altmetric has tracked 25,508,813 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,226 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,260 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.