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Position-specific automated processing of V3 env ultra-deep pyrosequencing data for predicting HIV-1 tropism.

Authors :
Jeanne N
Saliou A
Carcenac R
Lefebvre C
Dubois M
Cazabat M
Nicot F
Loiseau C
Raymond S
Izopet J
Delobel P
Source :
Scientific reports [Sci Rep] 2015 Nov 20; Vol. 5, pp. 16944. Date of Electronic Publication: 2015 Nov 20.
Publication Year :
2015

Abstract

HIV-1 coreceptor usage must be accurately determined before starting CCR5 antagonist-based treatment as the presence of undetected minor CXCR4-using variants can cause subsequent virological failure. Ultra-deep pyrosequencing of HIV-1 V3 env allows to detect low levels of CXCR4-using variants that current genotypic approaches miss. However, the computation of the mass of sequence data and the need to identify true minor variants while excluding artifactual sequences generated during amplification and ultra-deep pyrosequencing is rate-limiting. Arbitrary fixed cut-offs below which minor variants are discarded are currently used but the errors generated during ultra-deep pyrosequencing are sequence-dependant rather than random. We have developed an automated processing of HIV-1 V3 env ultra-deep pyrosequencing data that uses biological filters to discard artifactual or non-functional V3 sequences followed by statistical filters to determine position-specific sensitivity thresholds, rather than arbitrary fixed cut-offs. It allows to retain authentic sequences with point mutations at V3 positions of interest and discard artifactual ones with accurate sensitivity thresholds.

Details

Language :
English
ISSN :
2045-2322
Volume :
5
Database :
MEDLINE
Journal :
Scientific reports
Publication Type :
Academic Journal
Accession number :
26585833
Full Text :
https://doi.org/10.1038/srep16944