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J Antimicrob Chemother. 2018 May 1;73(5):1152-1157. doi: 10.1093/jac/dky003.

HIV-1 genotypic resistance testing using the Vela automated next-generation sequencing platform.

Author information

1
INSERM, U1043, Toulouse F-31300, France.
2
CHU de Toulouse, Hôpital Purpan, Laboratoire de Virologie, Toulouse F-31300, France.
3
Université Toulouse III Paul-Sabatier, Faculté de Médecine Toulouse-Purpan, Toulouse F-31300, France.
4
CHU de Toulouse, Hôpital Purpan, Service des Maladies Infectieuses et Tropicales, Toulouse F-31300, France.

Abstract

Objectives:

To evaluate the diagnostic performance of the Vela next-generation sequencing (NGS) system in conjunction with the Sentosa SQ HIV Genotyping Assay for genotyping HIV-1.

Methods:

Plasma RNA was extracted and templates prepared with the Sentosa SX instrument before sequencing the HIV-1 polymerase on the Sentosa SQ301 Sequencer (PGM IonTorrent). The Vela NGS System was compared with direct sequencing and the 454 GS-FLX (Roche) and MiSeq (Illumina) systems for genotypic resistance testing on clinical samples.

Results:

The Vela NGS system detected majority resistance mutations in subtype B and CRF02-AG samples at 500 copies/mL and minority variants with a sensitivity of 5% at 100 000 copies/mL. The Vela NGS system and direct sequencing identified resistance mutations with 97% concordance in 46 clinical samples. Vela identified 1/20 of the 1%-5% mutations identified by 454, 5/12 of the 5%-20% mutations and 60/61 of the >20% mutations. Vela identified 3/14 of the 1%-5% mutations identified by MiSeq, 0/2 of the 5%-20% mutations and 47/47 of the >20% mutations. The resistance mutation quantifications by Vela and 454 were concordant (bias: 2.31%), as were those by Vela and MiSeq (bias: 1.06%).

Conclusions:

The Vela NGS system provides automated nucleic acid extraction, PCR reagent distribution, library preparation and bioinformatics analysis. The analytical performance was very good when compared with direct sequencing, but was less sensitive than two other NGS platforms for detecting minority variants.

PMID:
29444253
DOI:
10.1093/jac/dky003
[Indexed for MEDLINE]

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