Targeted deep sequencing of HIV-1 using the IonTorrentPGM platform

Gustavo H. Kijak*, Eric Sanders-Buell, Elizabeth A. Harbolick, Phuc Pham, Agnes L. Chenine, Leigh Anne Eller, Kathleen Rono, Merlin L. Robb, Nelson L. Michael, Jerome H. Kim, Sodsai Tovanabutra

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The characterization of mixed HIV-1 populations is a key question in clinical and basic research settings. This can be achieved through targeted deep sequencing (TDS), where next-generation sequencing is used to examine in depth a sub-genomic region of interest. This study explores the suitability of IonTorrent PGM(LifeTechnologies) for the TDS-based analysis of HIV-1 evolution. Using laboratory reagents and primary specimens sampled at pre-peak viremia the error rates from misincorporation and in vitro recombination were <0.5%. The sequencing error rate was 2- to 3-fold higher in/around homopolymeric tracts, and could be discerned from true polymorphism using bidirectional sequencing. The limit of detection of complex variants was further lowered by using haplotyping. The application of this system was illustrated on primary samples from an individual infected with HIV-1 followed from pre-peak viremia through six months post-acquisition. TDS provided an augmented view of the extent of genetic diversity, the covariation among polymorphisms, the evolutionary pathways, and the boundaries of the mutational space explored by the viral swarm. Based on its performance, the system can be applied for the characterization of minor viral variants in support of studies of viral evolution, which can inform the rational design of the next generation of vaccines and therapeutics.

Original languageEnglish
Pages (from-to)7-16
Number of pages10
JournalJournal of Virological Methods
Volume205
DOIs
StatePublished - 1 Sep 2014
Externally publishedYes

Keywords

  • HIV-1
  • IonTorrent
  • Molecular evolution
  • Next-generation sequencing
  • Targeted deep sequencing

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