A combined genotypic and phenotypic human immunodeficiency virus type 1 recombinant virus assay for the reverse transcriptase and integrase genes
Virco BVBA, Generaal De Wittelaan L11 B3, Mechelen, Belgium. Journal of virological methods
(Impact Factor: 1.78).
07/2009; 161(2):231-9. DOI: 10.1016/j.jviromet.2009.06.015
With the approval of the first HIV-1 integrase inhibitor raltegravir and a second one in phase III clinical development (elvitegravir), genotypic and phenotypic resistance assays are required to guide antiretroviral therapy and to investigate treatment failure. In this study, a genotypic and phenotypic recombinant virus assay was validated for determining resistance against integrase inhibitors. The assays are based on the amplification of a region encompassing not only HIV-1 integrase, but also reverse transcriptase and RNAseH. The overall amplification success was 85% (433/513) and increased to 93% (120/129) for samples with a viral load above 3 log(10) copies/ml. Both B and non-B HIV-1 subtypes could be genotyped successfully (93%; 52/56 and 100%; 49/49, respectively) and reproducibly. The phenotypic assay showed a high success rate (96.5%; 139/144) for subtype B (100%; 19/19) and non-B subtypes (92%; 45/49), and was found to be accurate and reproducible as assessed using well-characterized integrase mutants. Using both assays, baseline resistance to raltegravir and elvitegravir in subtype B and non-B HIV-1 strains selected at random was not observed, although integrase polymorphisms were present at varying prevalence. Biological cutoff values were found to be 2.1 and 2.0 for raltegravir and elvitegravir, respectively. In summary, a genotypic and phenotypic integrase resistance assay was validated successfully for accuracy, reproducibility, analytical and clinical sensitivity, and dynamic range.
Available from: Maxim Feyaerts
- "In this article, as the number of patients failing INI treatment was limited, our primary objective was to develop a methodology for training a linear regression model on a relatively small dataset. We increased the quality of the correlative genotype-phenotype data by taking multiple clones for each of the clinical isolates , allowing to more accurately model the resistance contribution of IN mutations or mutation pairs. Moreover, to avoid overfitting, we generated an INI model by consensus linear regression modeling, using a GA for selection of IN mutations [29,30]. "
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Integrase inhibitors (INI) form a new drug class in the treatment of HIV-1 patients. We developed a linear regression modeling approach to make a quantitative raltegravir (RAL) resistance phenotype prediction, as Fold Change in IC50 against a wild type virus, from mutations in the integrase genotype.
We developed a clonal genotype-phenotype database with 991 clones from 153 clinical isolates of INI naïve and RAL treated patients, and 28 site-directed mutants.We did the development of the RAL linear regression model in two stages, employing a genetic algorithm (GA) to select integrase mutations by consensus. First, we ran multiple GAs to generate first order linear regression models (GA models) that were stochastically optimized to reach a goal R2 accuracy, and consisted of a fixed-length subset of integrase mutations to estimate INI resistance. Secondly, we derived a consensus linear regression model in a forward stepwise regression procedure, considering integrase mutations or mutation pairs by descending prevalence in the GA models.
The most frequently occurring mutations in the GA models were 92Q, 97A, 143R and 155H (all 100%), 143G (90%), 148H/R (89%), 148K (88%), 151I (81%), 121Y (75%), 143C (72%), and 74M (69%). The RAL second order model contained 30 single mutations and five mutation pairs (p < 0.01): 143C/R&97A, 155H&97A/151I and 74M&151I. The R2 performance of this model on the clonal training data was 0.97, and 0.78 on an unseen population genotype-phenotype dataset of 171 clinical isolates from RAL treated and INI naïve patients.
We describe a systematic approach to derive a model for predicting INI resistance from a limited amount of clonal samples. Our RAL second order model is made available as an Additional file for calculating a resistance phenotype as the sum of integrase mutations and mutation pairs.
Available from: Marie-line L Andreola
- "We used an HXB2-based HIV backbone in which the integrase region was deleted (pHXB2-ΔIN) , . IN amplicons were then recombined intracellularly in MT4 cells with the pHXB2-ΔIN backbone by Amaxa nucleofection (Amaxa Biosystems) according to the manufacturer's recommendations. "
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ABSTRACT: Resistance to HIV-1 integrase (IN) inhibitor raltegravir (RAL), is encoded by mutations in the IN region of the pol gene. The emergence of the N155H mutation was replaced by a pattern including the Y143R/C/H mutations in three patients with anti-HIV treatment failure. Cloning analysis of the IN gene showed an independent selection of the mutations at loci 155 and 143. Characterization of the phenotypic evolution showed that the switch from N155H to Y143C/R was linked to an increase in resistance to RAL. Wild-type (WT) IN and IN with mutations Y143C or Y143R were assayed in vitro in 3'end-processing, strand transfer and concerted integration assays. Activities of mutants were moderately impaired for 3'end-processing and severely affected for strand transfer. Concerted integration assay demonstrated a decrease in mutant activities using an uncleaved substrate. With 3'end-processing assay, IC(50) were 0.4 microM, 0.9 microM (FC = 2.25) and 1.2 microM (FC = 3) for WT, IN Y143C and IN Y143R, respectively. An FC of 2 was observed only for IN Y143R in the strand transfer assay. In concerted integration, integrases were less sensitive to RAL than in ST or 3'P but mutants were more resistant to RAL than WT.
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ABSTRACT: An HIV-1 subtype C specific assay was established for integrase genotyping from 51 integrase inhibitor-naive patient plasma samples and 22 antiretroviral drug-naive primary viral isolates from South Africa. Seventy-one of the 73 samples were classified as HIV-1 subtype C and two samples were unique AC and CG recombinants in integrase. Amino acid sequence analysis revealed there were no primary mutations (Y143R/C/H, Q148H/R/K, and N155H/S) associated with reduced susceptibility to the integrase inhibitors raltegravir and elvitegravir. However, one sample had the T97A mutation, three samples had the E157Q and V165I mutations, and the majority of samples contained the polymorphic mutation V72I. The expected finding of no major integrase mutations conferring resistance to integrase inhibitors suggests that this new antiretroviral drug class will be effective in our region where HIV-1 subtype C predominates. However, the impact of E157Q and other naturally occurring polymorphisms warrants further phenotypic investigation.
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