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Updated: Nov 16, 2025
Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach
Published on: December 1, 2011
Adapting the geno2pheno[coreceptor] tool to HIV-1 subtype CRF01_AE by phenotypic validation using clinical isolates
Nina Marty1, Siriphan Saeng-Aroon2, Eva Heger3
1Molecular Virology, Department Biomedicine-Petersplatz, University of Basel, Petersplatz 10, 4055 Basel, Switzerland.
Objectives:
Geno2pheno[coreceptor] is a widely used tool for the prediction of coreceptor usage (viral tropism) of HIV-1 samples. For HIV-1 CRF01_AE, a significant overcalling of X4-tropism is observed when using the standard settings of Geno2pheno[coreceptor]. The aim of this study was to provide the experimental backing for adaptations to the geno2pheno[coreceptor] algorithm in order to improve coreceptor usage predictions of clinical HIV-1 CRF01_AE isolates STUDY DESIGN: V3-sequences of 20 clinical HIV-1 subtype CRF01_AE samples were sequenced and analyzed by geno2pheno[coreceptor]. In parallel, coreceptor usage was determined for these samples by replicative phenotyping in human cells in the presence of specific X4- or R5-inhibitors.
Results:
The sole introduction of the CRF01_AE V3 region into a full-length otherwise subtype B provirus failed to produce replication-competent viral progeny. A successive genome-replacement strategy revealed that also CRF01_AE derived gag and pol sequences are necessary to generate HIV genomes with sufficient replication competence. Subsequent phenotypic analysis confirmed overcalling of X4-tropism for CRF01_AE viruses using the current version and the standard cut-off at 10% false positive rate (FPR) of geno2pheno[coreceptor]. Lowering the FPR cut-off to 2.5% reduced the X4-overcalling in our sample collection, while still allowing a safe administration of Maraviroc (MCV).
Conclusion:
This study demonstrates the successful adjustment of geno2pheno[coreceptor] rules for subtype CRF01_AE. It also supports the unique strength of combining complementing methods, namely phenotyping and genotyping, for validating new bioinformatics tools prior to application in diagnostics.
