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Characterization of two HIV-1 infectors during initial antiretroviral treatment, and the emergence of phenotypic resistance in reverse transcriptase-associated mutation patterns

Overview of attention for article published in Virology Journal, November 2015
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Title
Characterization of two HIV-1 infectors during initial antiretroviral treatment, and the emergence of phenotypic resistance in reverse transcriptase-associated mutation patterns
Published in
Virology Journal, November 2015
DOI 10.1186/s12985-015-0417-y
Pubmed ID
Authors

Wei Guo, Jingwan Han, Daomin Zhuang, Siyang Liu, Yongjian Liu, Lin Li, Hanping Li, Zuoyi Bao, Fujiang Wang, Jingyun Li

Abstract

Highly active antiretroviral therapy (HAART) is recommended to control the infection of HIV-1. HIV-1 drug resistance becomes an obstacle to HAART due to the accumulation of specific mutations in the RT coding region. The development of resistance mutations may be more complex than previously thought. We followed two HIV-1 infectors from a HIV-1 drug resistance surveillance cohort in Henan province and evaluated CD4+ T-cell number and viral load thereafter at ten time-periods and characterized their reverse transcriptase-associated mutation patterns at each time point. Then we constructed the recombinant virus strains with these mutation patterns to mimick the viruses and test the phenotypic resistance caused by the mutation patterns on TZM-b1 cells. CD4+ T-cell number initially increased and then decreased rapidly, while viral load decreased and then dropped sharply during initial antiretroviral treatment. The number of mutations and the combination patterns of mutations increased over time. According to the phenotypic resistance performed by recombinant virus strains, VirusT215Y/V179E/Y181C/H221Y exhibited high levels of resistance to EFV (5.57-fold), and T215Y/V179E-containing virus increased 20.20-fold in AZT resistance (p < 0.01). VirusT215Y/V179E/Y181C increased markedly in EFV resistance (p < 0.01). The IC50 for VirusT215Y/V179E/H221Y was similar to that for VirusT215Y/V179E/Y181C. VirusT215Y/K103N/Y181C/H221Y induced a dramatic IC50 increase of all the four agents (Efavirenz EFV, Zidovudine AZT, Lamivudine 3TC, and Stavudine d4T) (p < 0.01). As for VirusT215Y/K103N/Y181C, only the IC50 of EFV was significantly increased. T215Y/K103N resulted in a 26.36-fold increase in EFV (p < 0.01). T215Y/K103N/H221Y significantly increased the resistance to AZT and 3TC. The IC50 of EFV with T215Y/V179E was lower than with T215Y/K103N (F = 93.10, P < 0.0001). With T215Y/V179E, Y181C significantly increase in EFV resistance, while the interaction between 181 and 221 in EFV was not statistically significant (F = 1.20, P = 0.3052). With T215Y/K103N, neither H221Y nor Y181C showed a significant increase in EFV resistance, but the interaction between 181 and 221 was statistically significant (F = 38.12, P = 0.0003). Data in this study suggests that pathways of viral evolution toward drug resistance appear to proceed through distinct steps and at different rates. Phenotypic resistance using recombinant virus strains with different combination of mutation patterns reveals that interactions among mutations may provide information on the impact of these mutations on drug resistance. All the result provides reference to optimize clinical treatment schedule.

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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 %
Student > Master 4 18%
Researcher 3 14%
Student > Postgraduate 3 14%
Student > Ph. D. Student 2 9%
Professor > Associate Professor 1 5%
Other 1 5%
Unknown 8 36%
Readers by discipline Count As %
Medicine and Dentistry 4 18%
Biochemistry, Genetics and Molecular Biology 2 9%
Immunology and Microbiology 2 9%
Computer Science 1 5%
Environmental Science 1 5%
Other 2 9%
Unknown 10 45%
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 30 June 2016.
All research outputs
#20,335,423
of 22,880,230 outputs
Outputs from Virology Journal
#2,885
of 3,051 outputs
Outputs of similar age
#235,796
of 281,578 outputs
Outputs of similar age from Virology Journal
#57
of 59 outputs
Altmetric has tracked 22,880,230 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.
So far Altmetric has tracked 3,051 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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