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Gene expression patterns induced at different stages of rhinovirus infection in human alveolar epithelial cells

Overview of attention for article published in PLOS ONE, May 2017
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Title
Gene expression patterns induced at different stages of rhinovirus infection in human alveolar epithelial cells
Published in
PLOS ONE, May 2017
DOI 10.1371/journal.pone.0176947
Pubmed ID
Authors

Mohammad Reza Etemadi, King-Hwa Ling, Shahidee Zainal Abidin, Hui-Yee Chee, Zamberi Sekawi

Abstract

Human rhinovirus (HRV) is the common virus that causes acute respiratory infection (ARI) and is frequently associated with lower respiratory tract infections (LRTIs). We aimed to investigate whether HRV infection induces a specific gene expression pattern in airway epithelial cells. Alveolar epithelial cell monolayers were infected with HRV species B (HRV-B). RNA was extracted from both supernatants and infected monolayer cells at 6, 12, 24 and 48 hours post infection (hpi) and transcriptional profile was analyzed using Affymetrix GeneChip and the results were subsequently validated using quantitative Real-time PCR method. HRV-B infects alveolar epithelial cells which supports implication of the virus with LRTIs. In total 991 genes were found differentially expressed during the course of infection. Of these, 459 genes were up-regulated whereas 532 genes were down-regulated. Differential gene expression at 6 hpi (187 genes up-regulated vs. 156 down-regulated) were significantly represented by gene ontologies related to the chemokines and inflammatory molecules indicating characteristic of viral infection. The 75 up-regulated genes surpassed the down-regulated genes (35) at 12 hpi and their enriched ontologies fell into discrete functional entities such as regulation of apoptosis, anti-apoptosis, and wound healing. At later time points of 24 and 48 hpi, predominated down-regulated genes were enriched for extracellular matrix proteins and airway remodeling events. Our data provides a comprehensive image of host response to HRV infection. The study suggests the underlying molecular regulatory networks genes which might be involved in pathogenicity of the HRV-B and potential targets for further validations and development of effective treatment.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 19%
Researcher 6 19%
Student > Doctoral Student 4 13%
Student > Ph. D. Student 3 9%
Lecturer > Senior Lecturer 2 6%
Other 6 19%
Unknown 5 16%
Readers by discipline Count As %
Medicine and Dentistry 6 19%
Immunology and Microbiology 5 16%
Agricultural and Biological Sciences 4 13%
Engineering 2 6%
Computer Science 2 6%
Other 9 28%
Unknown 4 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 01 June 2017.
All research outputs
#8,963,459
of 11,218,652 outputs
Outputs from PLOS ONE
#93,837
of 125,783 outputs
Outputs of similar age
#191,201
of 266,427 outputs
Outputs of similar age from PLOS ONE
#2,913
of 4,053 outputs
Altmetric has tracked 11,218,652 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 125,783 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
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 266,427 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4,053 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.