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AIDS Res Ther. 2010 Feb 15;7:4. doi: 10.1186/1742-6405-7-4.

HIV-1 V3 envelope deep sequencing for clinical plasma specimens failing in phenotypic tropism assays.

Author information

  • 1Tibotec-Virco Virology BVBA, Mechelen, Belgium. ivanden3@its.jnj.com.

Abstract

BACKGROUND:

HIV-1 infected patients for whom standard gp160 phenotypic tropism testing failed are currently excluded from co-receptor antagonist treatment. To provide patients with maximal treatment options, massively parallel sequencing of the envelope V3 domain, in combination with tropism prediction tools, was evaluated as an alternative tropism determination strategy. Plasma samples from twelve HIV-1 infected individuals with failing phenotyping results were available. The samples were submitted to massive parallel sequencing and to confirmatory recombinant phenotyping using a fraction of the gp120 domain.

RESULTS:

A cut-off for sequence reads interpretation of 5 to10 times the sequencing error rate (0.2%) was implemented. On average, each sample contained 7 different V3 haplotypes. V3 haplotypes were submitted to tropism prediction algorithms, and 4/14 samples returned with presence of a dual/mixed (D/M) tropic virus, respectively at 3%, 10%, 11%, and 95% of the viral quasispecies. V3 tropism prediction was confirmed by gp120 phenotyping, except for two out of 4 D/M predicted viruses (with 3 and 95%) which were phenotypically R5-tropic. In the first case, the result was discordant due to the limit of detection for the phenotyping technology, while in the latter case the prediction algorithms were not computing the viral tropism correctly.

CONCLUSIONS:

Although only demonstrated on a limited set of samples, the potential of the combined use of "deep sequencing + prediction algorithms" in cases where routine gp160 phenotype testing cannot be employed was illustrated. While good concordance was observed between gp120 phenotyping and prediction of R5-tropic virus, the results suggest that accurate prediction of X4-tropic virus would require further algorithm development.

PMID:
20804564
[PubMed]
PMCID:
PMC2834596
Free PMC Article
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