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Evolutionary Analysis of HIV-1 Pol Proteins Reveals Representative Residues for Viral Subtype Differentiation

Overview of attention for article published in Frontiers in Microbiology, November 2017
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Title
Evolutionary Analysis of HIV-1 Pol Proteins Reveals Representative Residues for Viral Subtype Differentiation
Published in
Frontiers in Microbiology, November 2017
DOI 10.3389/fmicb.2017.02151
Pubmed ID
Authors

Shohei Nagata, Junnosuke Imai, Gakuto Makino, Masaru Tomita, Akio Kanai

Abstract

RNA viruses have been used as model systems to understand the patterns and processes of molecular evolution because they have high mutation rates and are genetically diverse. Human immunodeficiency virus 1 (HIV-1), the etiological agent of acquired immune deficiency syndrome, is highly genetically diverse, and is classified into several groups and subtypes. However, it has been difficult to use its diverse sequences to establish the overall phylogenetic relationships of different strains or the trends in sequence conservation with the construction of phylogenetic trees. Our aims were to systematically characterize HIV-1 subtype evolution and to identify the regions responsible for HIV-1 subtype differentiation at the amino acid level in the Pol protein, which is often used to classify the HIV-1 subtypes. In this study, we systematically characterized the mutation sites in 2,052 Pol proteins from HIV-1 group M (144 subtype A; 1,528 subtype B; 380 subtype C), using sequence similarity networks. We also used spectral clustering to group the sequences based on the network graph structures. A stepwise analysis of the cluster hierarchies allowed us to estimate a possible evolutionary pathway for the Pol proteins. The subtype A sequences also clustered according to when and where the viruses were isolated, whereas both the subtype B and C sequences remained as single clusters. Because the Pol protein has several functional domains, we identified the regions that are discriminative by comparing the structures of the domain-based networks. Our results suggest that sequence changes in the RNase H domain and the reverse transcriptase (RT) connection domain are responsible for the subtype classification. By analyzing the different amino acid compositions at each site in both domain sequences, we found that a few specific amino acid residues (i.e., M357 in the RT connection domain and Q480, Y483, and L491 in the RNase H domain) represent the differences among the subtypes. These residues were located on the surface of the RT structure and in the vicinity of the amino acid sites responsible for RT enzymatic activity or function.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 29%
Student > Bachelor 12 21%
Student > Ph. D. Student 3 5%
Professor 2 4%
Lecturer 2 4%
Other 3 5%
Unknown 18 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 21%
Agricultural and Biological Sciences 9 16%
Medicine and Dentistry 5 9%
Immunology and Microbiology 2 4%
Chemical Engineering 1 2%
Other 5 9%
Unknown 22 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 February 2019.
All research outputs
#14,097,173
of 24,569,575 outputs
Outputs from Frontiers in Microbiology
#10,242
of 27,905 outputs
Outputs of similar age
#161,632
of 334,546 outputs
Outputs of similar age from Frontiers in Microbiology
#302
of 554 outputs
Altmetric has tracked 24,569,575 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 27,905 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has gotten more attention than average, scoring higher than 61% 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 334,546 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 50% of its contemporaries.
We're also able to compare this research output to 554 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.