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Currently, there is no consensus on the genotypic tools to be used for tropism analysis in HIV-1 subtype C strains. Thus, the aim of the study was to evaluate the performance of the different V3 loop-based genotypic algorithms available. We compiled a dataset of 645 HIV-1 subtype C V3 loop sequences of known coreceptor phenotypes (531 R5-tropic/non-syncytium-inducing and 114 X4-tropic/R5X4-tropic/syncytium-inducing sequences) from the Los Alamos database (http://www.hiv.lanl.gov/) and previously published literature. Coreceptor usage was predicted based on this dataset using different software-based machine-learning algorithms as well as simple classical rules. All the sophisticated machine-learning methods showed a good concordance of above 85%. Geno2Pheno (false-positive rate cutoff of 5-15%) and CoRSeqV3-C were found to have a high predicting capability in determining both HIV-1 subtype C X4-tropic and R5-tropic strains. The current sophisticated genotypic tropism tools based on V3 loop perform well for tropism prediction in HIV-1 subtype C strains and can be used in clinical settings. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Objectives Genotypic tropism testing (GTT) of HIV is increasingly used prior to the initiation of CCR5 antagonist therapy in HIV-infected individuals. Normally performed on plasma-derived virus, the test is challenging when performed in patients with suppressed viraemia. We aimed to evaluate the performance of cell-associated proviral DNA against plasma-derived viral RNA as the genetic material for GTT in an Indian clinical setting. Methods From 52 HIV-1-infected individuals, the env V3 region was successfully amplified and sequenced from both proviral DNA and plasma RNA paired samples having a viral load >2500 copies/mL (n = 42) and from proviral DNA only in 10 antiretroviral therapy (ART)-experienced patients with a viral load <500 copies/mL. GTT was performed using the Geno2Pheno algorithm with the interpretative false positive rate (FPR) cut-off of 10%. Results Among paired samples, 40 of 42 patients harboured subtype C strains. Plasma RNA tropism prediction revealed X4 tropism in 4 of 42 (9.5%). A high concordance of 97.6% in tropism prediction was noted in simultaneous RNA/DNA samples (38 R5 and 3 X4). Discordance was observed in one sample showing R5 tropism in proviral DNA and X4 tropism in plasma RNA. Comparison of Geno2Pheno FPRs in both the plasma and proviral compartments showed good correlation (overall, r = 0.87; ART-naive patients, r = 0.79; ART-failing patients, r = 0.97). GTT was successfully performed in all 10 whole blood DNA samples having a viral load <500 copies/mL, all showing R5 tropism. Conclusions High concordance in tropism prediction from proviral DNA and plasma-viral RNA suggests that prediction of viral tropism using proviral DNA is accurate and feasible in resource-limited clinical settings, particularly in patients with low or suppressed viraemia. [ABSTRACT FROM PUBLISHER]