title: Use of four next-generation sequencing platforms to determine HIV-1 coreceptor tropism.
abstract: HIV-1 coreceptor tropism assays are required to rule out the presence of CXCR4-tropic (non-R5) viruses prior treatment with CCR5 antagonists. Phenotypic (e.g., Trofile™, Monogram Biosciences) and genotypic (e.g., population sequencing linked to bioinformatic algorithms) assays are the most widely used. Although several next-generation sequencing (NGS) platforms are available, to date all published deep sequencing HIV-1 tropism studies have used the 454™ Life Sciences/Roche platform. In this study, HIV-1 co-receptor usage was predicted for twelve patients scheduled to start a maraviroc-based antiretroviral regimen. The V3 region of the HIV-1 env gene was sequenced using four NGS platforms: 454™, PacBio® RS (Pacific Biosciences), Illumina®, and Ion Torrent™ (Life Technologies). Cross-platform variation was evaluated, including number of reads, read length and error rates. HIV-1 tropism was inferred using Geno2Pheno, Web PSSM, and the 11/24/25 rule and compared with Trofile™ and virologic response to antiretroviral therapy. Error rates related to insertions/deletions (indels) and nucleotide substitutions introduced by the four NGS platforms were low compared to the actual HIV-1 sequence variation. Each platform detected all major virus variants within the HIV-1 population with similar frequencies. Identification of non-R5 viruses was comparable among the four platforms, with minor differences attributable to the algorithms used to infer HIV-1 tropism. All NGS platforms showed similar concordance with virologic response to the maraviroc-based regimen (75% to 80% range depending on the algorithm used), compared to Trofile (80%) and population sequencing (70%). In conclusion, all four NGS platforms were able to detect minority non-R5 variants at comparable levels suggesting that any NGS-based method can be used to predict HIV-1 coreceptor usage.
authors.affiliation: Computational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester, United Kingdom.
authors.forename: John
authors.initials: J
authors.lastname: Archer
authors.forename: Jan
authors.initials: J
authors.lastname: Weber
authors.forename: Kenneth
authors.initials: K
authors.lastname: Henry
authors.forename: Dane
authors.initials: D
authors.lastname: Winner
authors.forename: Richard
authors.initials: R
authors.lastname: Gibson
authors.forename: Lawrence
authors.initials: L
authors.lastname: Lee
authors.forename: Ellen
authors.initials: E
authors.lastname: Paxinos
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Arts
authors.forename: David L
authors.initials: DL
authors.lastname: Robertson
authors.forename: Larry
authors.initials: L
authors.lastname: Mimms
authors.forename: Miguel E
authors.initials: ME
authors.lastname: Quiñones-Mateu
mesh_terms: D001483:Base Sequence; D016000:Cluster Analysis; D015699:HIV Envelope Protein gp120 / Q000235:genetics; D015658:HIV Infections / Q000821:virology; D015497:HIV-1 / Q000235:genetics / Q000502:physiology*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008969:Molecular Sequence Data; D019713:Receptors, CCR5 / Q000235:genetics / Q000378:metabolism*; D019718:Receptors, CXCR4 / Q000235:genetics / Q000378:metabolism*; D016415:Sequence Alignment; D056189:Viral Tropism
chemical_list: D015699:HIV Envelope Protein gp120; D019713:Receptors, CCR5; D019718:Receptors, CXCR4