tailieunhanh - Báo cáo y học: "HIV-1 V3 envelope deep sequencing for clinical plasma specimens failing in phenotypic tropism assays"

HIV-1 V3 envelope deep sequencing for clinical plasma specimens failing in phenotypic tropism assays | Vandenbroucke et al. AIDS Research and Therapy 2010 7 4 http content 7 1 4 AIDS RESEARCH AND THERAPY RESEARCH Open Access HIV-1 V3 envelope deep sequencing for clinical plasma specimens failing in phenotypic tropism assays 1 1 1 1 11 Ina Vandenbroucke Herwig Van Marck Wendy Mostmans Veerle Van Eygen Evelien Rondelez Kim Thys 1 r- 3 r y4 lA it4 CI M xr 5 Kurt Van Baelen Katrien Fransen Dolores Vaira Kabamba Kabeya Stephane De Wit Eric Florence Michel Moutschen3 Linos Vandekerckhove6 7 Chris Verhofstede6 Lieven J Stuyver 1 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 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