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Whole transcriptome analysis reveals differential gene expression profile reflecting macrophage polarization in response to influenza A H5N1 virus infection

Overview of attention for article published in BMC Medical Genomics, February 2018
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

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5 tweeters

Citations

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10 Dimensions

Readers on

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34 Mendeley
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Title
Whole transcriptome analysis reveals differential gene expression profile reflecting macrophage polarization in response to influenza A H5N1 virus infection
Published in
BMC Medical Genomics, February 2018
DOI 10.1186/s12920-018-0335-0
Pubmed ID
Authors

Na Zhang, Yun-Juan Bao, Amy Hin-Yan Tong, Scott Zuyderduyn, Gary D. Bader, J. S. Malik Peiris, Si Lok, Suki Man-Yan Lee

Abstract

Avian influenza A H5N1 virus can cause lethal disease in humans. The virus can trigger severe pneumonia and lead to acute respiratory distress syndrome. Data from clinical, in vitro and in vivo suggest that virus-induced cytokine dysregulation could be a contributory factor to the pathogenesis of human H5N1 disease. However, the precise mechanism of H5N1 infection eliciting the unique host response are still not well understood. To obtain a better understanding of the molecular events at the earliest time points, we used RNA-Seq to quantify and compare the host mRNA and miRNA transcriptomes induced by the highly pathogenic influenza A H5N1 (A/Vietnam/3212/04) or low virulent H1N1 (A/Hong Kong/54/98) viruses in human monocyte-derived macrophages at 1-, 3-, and 6-h post infection. Our data reveals that two macrophage populations corresponding to M1 (classically activated) and M2 (alternatively activated) macrophage subtypes respond distinctly to H5N1 virus infection when compared to H1N1 virus or mock infection, a distinction that could not be made from previous microarray studies. When this confounding variable is considered in our statistical model, a clear set of dysregulated genes and pathways emerges specifically in H5N1 virus-infected macrophages at 6-h post infection, whilst was not found with H1N1 virus infection. Furthermore, altered expression of genes in these pathways, which have been previously implicated in viral host response, occurs specifically in the M1 subtype. We observe a significant up-regulation of genes in the RIG-I-like receptor signaling pathway. In particular, interferons, and interferon-stimulated genes are broadly affected. The negative regulators of interferon signaling, the suppressors of cytokine signaling, SOCS-1 and SOCS-3, were found to be markedly up-regulated in the initial round of H5N1 virus replication. Elevated levels of these suppressors could lead to the eventual suppression of cellular antiviral genes, contributing to pathophysiology of H5N1 virus infection. Our study provides important mechanistic insights into the understanding of H5N1 viral pathogenesis and the multi-faceted host immune responses. The dysregulated genes could be potential candidates as therapeutic targets for treating H5N1 disease.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

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 %
Student > Ph. D. Student 13 38%
Researcher 6 18%
Student > Bachelor 4 12%
Student > Master 2 6%
Student > Doctoral Student 2 6%
Other 2 6%
Unknown 5 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 32%
Agricultural and Biological Sciences 5 15%
Medicine and Dentistry 4 12%
Immunology and Microbiology 4 12%
Veterinary Science and Veterinary Medicine 3 9%
Other 2 6%
Unknown 5 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 31 May 2019.
All research outputs
#8,340,162
of 15,149,790 outputs
Outputs from BMC Medical Genomics
#363
of 796 outputs
Outputs of similar age
#128,698
of 276,971 outputs
Outputs of similar age from BMC Medical Genomics
#5
of 16 outputs
Altmetric has tracked 15,149,790 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 796 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 52% 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 276,971 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.