1. Genetic diversity in the partial sequence of the HIV-1 gag gene among people living with multidrug-resistant HIV-1 infection.
- Author
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Alencar CS, Sabino EC, Diaz RS, Mendrone-Junior A, and Nishiya AS
- Subjects
- Humans, Male, Female, Adult, Drug Resistance, Multiple, Viral genetics, Mutation, Genotype, Anti-HIV Agents therapeutic use, Anti-HIV Agents pharmacology, Middle Aged, Phylogeny, DNA, Viral genetics, HIV-1 genetics, HIV-1 drug effects, HIV Infections drug therapy, HIV Infections virology, Genetic Variation genetics, gag Gene Products, Human Immunodeficiency Virus genetics
- Abstract
The group-specific antigen (gag) plays a crucial role in the assembly, release, and maturation of HIV. This study aimed to analyze the partial sequence of the HIV gag gene to classify HIV subtypes, identify recombination sites, and detect protease inhibitor (PI) resistance-associated mutations (RAMs). The cohort included 100 people living with HIV (PLH) who had experienced antiretroviral treatment failure with reverse transcriptase/protease inhibitors. Proviral HIV-DNA was successfully sequenced in 96 out of 100 samples for gag regions, specifically matrix (p17) and capsid (p24). Moreover, from these 96 sequences, 82 (85.42%) were classified as subtype B, six (6.25%) as subtype F1, one (1.04%) as subtype C, and seven (7.29%) exhibited a mosaic pattern between subtypes B and F1 (B/F1), with breakpoints at p24 protein. Insertions and deletions of amino acid at p17 were observed in 51 samples (53.13%). The prevalence of PI RAM in the partial gag gene was observed in 78 out of 96 PLH (81.25%). Among these cases, the most common mutations were R76K (53.13%), Y79F (31.25%), and H219Q (14.58%) at non-cleavage sites, as well as V128I (10.42%) and Y132F (11.46%) at cleavage sites. While B/F1 recombination was identified in the p24, the p17 coding region showed higher diversity, where insertions, deletions, and PI RAM, were observed at high prevalence. In PLH with virological failure, the analysis of the partial gag gene could contribute to more accurate predictions in genotypic resistance to PIs. This can aid guide more effective HIV treatment strategies.
- Published
- 2024
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