Evidence map›Paper›PMID 27959928›Full record

ArticlePloS one2016

An Efficient Microarray-Based Genotyping Platform for the Identification of Drug-Resistance Mutations in Majority and Minority Subpopulations of HIV-1 Quasispecies.

Verónica Martín, Celia Perales, María Fernández-Algar, Helena G Dos Santos, Patricia Garrido, María Pernas, Víctor Parro, Miguel Moreno, Javier García-Pérez, José Alcamí and 4 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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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

14 authors at 6 institutions in 1 country.

Verónica MartínCentro de Biología Molecular 'Severo Ochoa' (CBMSO, CSIC-UAM). Campus de Cantoblanco, Madrid, Spain.
Celia PeralesCentro de Biología Molecular 'Severo Ochoa' (CBMSO, CSIC-UAM). Campus de Cantoblanco, Madrid, Spain.
María Fernández-AlgarDepartment of Molecular Evolution, Centro de Astrobiología (CAB, CSIC-INTA). Torrejón de Ardoz, Madrid, Spain.
Helena G Dos SantosCentro de Biología Molecular 'Severo Ochoa' (CBMSO, CSIC-UAM). Campus de Cantoblanco, Madrid, Spain.
Patricia GarridoBiotherapix, SLU. Parque Tecnológico de Madrid, Tres Cantos, Madrid. Spain.
María PernasBiotherapix, SLU. Parque Tecnológico de Madrid, Tres Cantos, Madrid. Spain.
Víctor ParroDepartment of Molecular Evolution, Centro de Astrobiología (CAB, CSIC-INTA). Torrejón de Ardoz, Madrid, Spain.
Miguel MorenoDepartment of Molecular Evolution, Centro de Astrobiología (CAB, CSIC-INTA). Torrejón de Ardoz, Madrid, Spain.
Javier García-PérezAIDS Immunopathogenesis Unit, Instituto de Salud Carlos III. Majadahonda, Madrid, Spain.
José AlcamíAIDS Immunopathogenesis Unit, Instituto de Salud Carlos III. Majadahonda, Madrid, Spain.
José Luis ToránBiotherapix, SLU. Parque Tecnológico de Madrid, Tres Cantos, Madrid. Spain.
David AbiaCentro de Biología Molecular 'Severo Ochoa' (CBMSO, CSIC-UAM). Campus de Cantoblanco, Madrid, Spain.
Esteban DomingoCentro de Biología Molecular 'Severo Ochoa' (CBMSO, CSIC-UAM). Campus de Cantoblanco, Madrid, Spain.
Carlos BrionesCentro de Investigación Biomédica en Red de enfermedades hepáticas y digestivas (CIBERehd), Spain.ORCID http://orcid.org/0000-0003-2213-8353
Centro de Astrobiología · ESCentro de Biología Molecular Severo Ochoa · ESTiGenix (Spain) · ESInstituto de Salud Carlos III · ESCentro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas · ESUniversitat Autònoma de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The response of human immunodeficiency virus type 1 (HIV-1) quasispecies to antiretroviral therapy is influenced by the ensemble of mutants that composes the evolving population. Low-abundance subpopulations within HIV-1 quasispecies may determine the viral response to the administered drug combinations. However, routine sequencing assays available to clinical laboratories do not recognize HIV-1 minority variants representing less than 25% of the population. Although several alternative and more sensitive genotyping techniques have been developed, including next-generation sequencing (NGS) methods, they are usually very time consuming, expensive and require highly trained personnel, thus becoming unrealistic approaches in daily clinical practice. Here we describe the development and testing of a HIV-1 genotyping DNA microarray that detects and quantifies, in majority and minority viral subpopulations, relevant mutations and amino acid insertions in 42 codons of the pol gene associated with drug- and multidrug-resistance to protease (PR) and reverse transcriptase (RT) inhibitors. A customized bioinformatics protocol has been implemented to analyze the microarray hybridization data by including a new normalization procedure and a stepwise filtering algorithm, which resulted in the highly accurate (96.33%) detection of positive/negative signals. This microarray has been tested with 57 subtype B HIV-1 clinical samples extracted from multi-treated patients, showing an overall identification of 95.53% and 89.24% of the queried PR and RT codons, respectively, and enough sensitivity to detect minority subpopulations representing as low as 5-10% of the total quasispecies. The developed genotyping platform represents an efficient diagnostic and prognostic tool useful to personalize antiviral treatments in clinical practice.

Indexed as

MutationAnti-HIV AgentsDrug Resistance, ViralGenotyping TechniquesHIV-1Oligonucleotide Array Sequence AnalysisAnti-HIV Agents

Identifiers

PMID27959928
PMCPMC5154500
OpenAlexW2564837112

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.