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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Lack of integrase inhibitors associated resistance mutations among HIV-1C isolates
|
|---|---|
| Published in |
Journal of Translational Medicine, December 2015
|
| DOI | 10.1186/s12967-015-0734-3 |
| Pubmed ID | |
| Authors |
Andargachew Mulu, Melanie Maier, Uwe Gerd Liebert |
| Abstract |
Although biochemical analysis of HIV-1 integrase enzyme suggested the use of integrase inhibitors (INIs) against HIV-1C, different viral subtypes may favor different mutational pathways potentially leading to varying levels of drug resistance. Thus, the aim of this study was to search for the occurrence and natural evolution of integrase polymorphisms and/or resistance mutations in HIV-1C Ethiopian clinical isolates prior to the introduction of INIs. Plasma samples from chronically infected drug naïve patients (N = 45), of whom the PR and RT sequence was determined previously, were used to generate population based sequences of HIV-1 integrase. HIV-1 subtype was determined using the REGA HIV-1 subtyping tool. Resistance mutations were interpreted according to the Stanford HIV drug resistance database ( http://hivdb.stanford.edu ) and the updated International Antiviral Society (IAS)-USA mutation lists. Moreover, rates of polymorphisms in the current isolates were compared with South African and global HIV-1C isolates. All subjects were infected with HIV-1C concordant to the protease (PR) and reverse transcriptase (RT) regions. Neither major resistance-associated IN mutations (T66I/A/K, E92Q/G, T97A, Y143HCR, S147G, Q148H/R/K, and N155H) nor silent mutations known to change the genetic barrier were observed. Moreover, the DDE-catalytic motif (D64G/D116G/E152 K) and signature HHCC zinc-binding motifs at codon 12, 16, 40 and 43 were found to be highly conserved. However, compared to other South African subtype C isolates, the rate of polymorphism was variable at various positions. Although the sample size is small, the findings suggest that this drug class could be effective in Ethiopia and other southern African countries where HIV-1C is predominantly circulating. The data will contribute to define the importance of integrase polymorphism and to improve resistance interpretation algorithms in HIV-1C isolates. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 32% |
| Student > Master | 6 | 24% |
| Student > Doctoral Student | 3 | 12% |
| Other | 1 | 4% |
| Student > Postgraduate | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 6 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 28% |
| Immunology and Microbiology | 6 | 24% |
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Agricultural and Biological Sciences | 3 | 12% |
| Unknown | 6 | 24% |
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 17 June 2016.
All research outputs
#20,333,181
of 22,877,793 outputs
Outputs from Journal of Translational Medicine
#3,320
of 4,004 outputs
Outputs of similar age
#324,972
of 387,674 outputs
Outputs of similar age from Journal of Translational Medicine
#70
of 73 outputs
Altmetric has tracked 22,877,793 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.