Lack of integrase inhibitors associated resistance mutations among HIV-1C isolates

HIV-1C分离株中缺乏整合酶抑制剂与耐药突变相关

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Abstract

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

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