Use of Four Next-Generation Sequencing Platforms to Determine HIV-1 Coreceptor Tropism

0383618 - ÚOCHB 2013 RIV US eng J - Článek v odborném periodiku
Archer, J. - Weber, Jan - Henry, K. - Winner, D. - Gibson, R. - Lee, L. - Paxinos, E. - Arts, E. J. - Robertson, D. L. - Mimms, L. - Quinones-Mateu, M. E.
Use of Four Next-Generation Sequencing Platforms to Determine HIV-1 Coreceptor Tropism.
PLoS ONE. Roč. 7, č. 11 (2012), e49602/1-e49602/17. ISSN 1932-6203. E-ISSN 1932-6203
Grant CEP: GA MŠMT(CZ) LK11207
Výzkumný záměr: CEZ:AV0Z40550506
Klíčová slova: HIV-1 tropism * V3 region * deep sequencing
Kód oboru RIV: EE - Mikrobiologie, virologie
Impakt faktor: 3.730, rok: 2012
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0049602

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 (TM), 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 (TM) 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 (TM), PacBio (R) RS (Pacific Biosciences), Illumina (R), and Ion Torrent (TM) (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 (TM) 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.
Trvalý link: http://hdl.handle.net/11104/0213500