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Iron overload down-regulates the expression of the HIV-1 Rev cofactor eIF5A in infected T lymphocytes

Overview of attention for article published in Proteome Science, August 2017
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Title
Iron overload down-regulates the expression of the HIV-1 Rev cofactor eIF5A in infected T lymphocytes
Published in
Proteome Science, August 2017
DOI 10.1186/s12953-017-0126-0
Pubmed ID
Authors

Carmine Mancone, Alessio Grimaldi, Giulia Refolo, Isabella Abbate, Gabriella Rozera, Dario Benelli, Gian Maria Fimia, Vincenzo Barnaba, Marco Tripodi, Mauro Piacentini, Fabiola Ciccosanti

Abstract

Changes in iron metabolism frequently accompany HIV-1 infection. However, while many clinical and in vitro studies report iron overload exacerbates the development of infection, many others have found no correlation. Therefore, the multi-faceted role of iron in HIV-1 infection remains enigmatic. RT-qPCR targeting the LTR region, gag, Tat and Rev were performed to measure the levels of viral RNAs in response to iron overload. Spike-in SILAC proteomics comparing i) iron-treated, ii) HIV-1-infected and iii) HIV-1-infected/iron treated T lymphocytes was performed to define modifications in the host cell proteome. Data from quantitative proteomics were integrated with the HIV-1 Human Interaction Database for assessing any viral cofactors modulated by iron overload in infected T lymphocytes. Here, we demonstrate that the iron overload down-regulates HIV-1 gene expression by decreasing the levels of viral RNAs. In addition, we found that iron overload modulates the expression of many viral cofactors. Among them, the downregulation of the REV cofactor eIF5A may correlate with the iron-induced inhibition of HIV-1 gene expression. Therefore, we demonstrated that eiF5A downregulation by shRNA resulted in a significant decrease of Nef levels, thus hampering HIV-1 replication. Our study indicates that HIV-1 cofactors influenced by iron metabolism represent potential targets for antiretroviral therapy and suggests eIF5A as a selective target for drug development.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 18%
Professor > Associate Professor 4 18%
Student > Ph. D. Student 3 14%
Student > Master 2 9%
Student > Bachelor 2 9%
Other 2 9%
Unknown 5 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 23%
Medicine and Dentistry 3 14%
Agricultural and Biological Sciences 2 9%
Engineering 2 9%
Computer Science 1 5%
Other 3 14%
Unknown 6 27%
Attention Score in Context

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 02 January 2018.
All research outputs
#18,581,651
of 23,015,156 outputs
Outputs from Proteome Science
#133
of 192 outputs
Outputs of similar age
#243,123
of 317,452 outputs
Outputs of similar age from Proteome Science
#4
of 5 outputs
Altmetric has tracked 23,015,156 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 192 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.