Evidence map›Paper›PMID 23166726›Full record

ArticlePloS one2012

Use of four next-generation sequencing platforms to determine HIV-1 coreceptor tropism.

John Archer, Jan Weber, Kenneth Henry, Dane Winner, Richard Gibson, Lawrence Lee, Ellen Paxinos, Eric J Arts, David L Robertson, Larry Mimms and 1 more

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Next-generation sequencing of HIV-1 single genome amplicons.Biomolecular detection and quantification · 2019
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Blood CXCR3Frontiers in immunology · 2018
    Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

John ArcherComputational and Evolutionary Biology, Faculty of Life Sciences, The University of Manchester, Manchester, United Kingdom.
Jan Weber
Kenneth Henry
Dane Winner
Richard Gibson
Lawrence Lee
Ellen Paxinos
Eric J Arts
David L Robertson
Larry Mimms
Miguel E Quiñones-Mateu

Funding

Impact of HIV-1 Fitness on Disease ProgressionR01AI049170 · NIAID · UNIVERSITY OF WESTERN ONTARIO · PI ARTS, ERIC J · 2002 to 2024
$6.8M
Biotechnology and Biological Sciences Research Council BB/H012419/1Medical Research Council G1001806NIAID NIH HHS R01 AI049170
6 · The paper itself

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.

Indexed as

High-Throughput Nucleotide SequencingViral TropismBase SequenceCluster AnalysisHIV-1HIV Envelope Protein gp120HIV InfectionsHumansMolecular Sequence DataReceptors, CCR5Receptors, CXCR4Sequence AlignmentHIV Envelope Protein gp120Receptors, CCR5Receptors, CXCR4

Identifiers

PMID23166726
PMCPMC3498215

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.