Differences in Chemokine Coreceptor Usage between Genetic Subtypes of HIV-1

Tscherning, Charlotte; Alaeus, Annette; Fredriksson, Robert; Björndal, Åsa; Deng, Hongkui; Littman, Dan R.; Fenyõ, Éva Mária; Albert, Jan

doi:10.1006/viro.1997.8980

Cited by 233 publications

(174 citation statements)

References 39 publications

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“…More importantly, most genotypic predictors have been designed based on the genetic characteristics of HIV-1 clade B (25,33). Since non-B subtypes show a wide genetic variability in the V3 region and since X4 viruses might be more prevalent in some clades than others (1,17,22,34,35), there is an urgent need to know the reliability of genotypic tools for inferring HIV-1 tropism in non-B subtypes, especially in regions where these HIV-1 variants are quite prevalent and may soon have access to CCR5 antagonists.…”

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confidence: 99%

Evaluation of Eight Different Bioinformatics Tools To Predict Viral Tropism in Different Human Immunodeficiency Virus Type 1 Subtypes

et al. 2008

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Human immunodeficiency virus type 1 (HIV-1) tropism can be assessed using phenotypic assays, but this is quite laborious, expensive, and time-consuming and can be made only in sophisticated laboratories. More accessible albeit reliable tools for testing of HIV-1 tropism are needed in view of the prompt introduction of CCR5 antagonists in clinical practice. Bioinformatics tools based on V3 sequences might help to predict HIV-1 tropism; however, most of these methods have been designed by taking only genetic information derived from HIV-1 subtype B into consideration. The aim of this study was to evaluate the performances of several genotypic tools to predict HIV-1 tropism in non-B subtypes, as data on this issue are scarce. Plasma samples were tested using a new phenotypic tropism assay (Phenoscript-tropism; Eurofins), and results were compared with estimates of coreceptor usage using eight different genotypic predictor softwares (Support Vector Machine [SVM], C4.5, C4.5 with positions 8 to 12 only, PART, Charge Rule, geno2pheno coreceptor, Position-Specific Scoring Matrix X4R5 [PSSM X4R5 ], and PSSM sinsi ). A total of 150 samples were tested, with 115 belonging to patients infected with non-B subtypes and 35 drawn from subtype B-infected patients, which were taken as controls. When non-B subtypes were tested, the concordances between the results obtained using the phenotypic assay and distinct genotypic tools were as follows: 78.8% for SVM, 77.5% for C4.5, 82.5% for C4.5 with positions 8 to 12 only, 82.5% for PART, 82.5% for Charge Rule, 82.5% for PSSM X4R5 , 83.8% for PSSM sinsi , and 71.3% for geno2pheno. When clade B viruses were tested, the best concordances were seen for PSSM X4R5 (91.4%), PSSM sinsi (88.6%), and geno2pheno (88.6%). The sensitivity for detecting X4 variants was lower for non-B than for B viruses, especially in the case of PSSM sinsi (38.4% versus 100%, respectively), SVM wetcat (46% versus 100%, respectively), and PART (30% versus 90%, respectively). In summary, while inferences of HIV-1 coreceptor usage using genotypic tools seem to be reliable for clade B viruses, their performances are poor for non-B subtypes, in which they particularly fail to detect X4 variants.

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confidence: 99%

Evaluation of Eight Different Bioinformatics Tools To Predict Viral Tropism in Different Human Immunodeficiency Virus Type 1 Subtypes

et al. 2008

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“…The V3 loop of HIV-1 is critical for co-receptor binding and is the main determinant of which of the cellular co-receptors, CCR5 or CXCR4, the viruses use for cell entry [21]. Most HIV clades cause disease by assuming the CCR5+/NSI phenotype during early disease and the CXCR4/SI phenotype during the end stage of the disease [22].…”

Section: Discussionmentioning

confidence: 99%

Viral Subtypes, Coreceptor Usage and Phylogenetic Relationships of Hiv-1 Isolates in Discordant Positive and Concordant Couples

Hambissa¹,

Mengistu²,

Howe³

et al. 2017

J Clin Cell Immunol

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Ethiopian HIV viruses were mainly HIV type C in all discordant positives and HIV/AIDS subjects. But other subtypes such as subtype A, B and recombinant A/G subtypes were also observed. Co-receptor utilization of discordant positive isolated viruses was both CCR5 and CXCR4 in equal proportion. The majority of HIV/AIDS patients used CXCR4, although about one third used CCR5 and a few also used dual co receptors. Our study showed that the majority of subtype C viruses were CXCR4/SI high/rapid subtype. And about one third was CCR5/NSI subtypes. The phylogenetic or evolutionary relationship showed that the majority of the viruses isolated from discordant positives showed sub clustering in one region and those isolated from concordant couples in another region, showing that discordant positive isolated viruses were evolving independently and were related with each other but this was not seen in viruses of concordant couples and HIV/AIDS subjects.

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“…There are other positions in Env but outside of V3 that also contribute to the X4 phenotype, but the specific contribution of these other sites is not clear (Hoffman et al 2002;Pastore et al 2006;Huang et al 2008Huang et al , 2011. There also seem to be differences among the subtypes for their propensity to evolve X4 variants, with X4 variants being more common in subtype D isolates (Tscherning et al 1998;Huang et al 2007). The reason for this difference is unclear, although the evolutionary distance between R5 and X4 variants of each subtype might be different.…”

Section: Target Cells T-cell Subsetsmentioning

confidence: 99%