Literature DB >> 24821496

Deep sequencing of HIV: clinical and research applications.

Shiven B Chabria1, Shaili Gupta, Michael J Kozal.   

Abstract

Human immunodeficiency virus (HIV) exhibits remarkable diversity in its genomic makeup and exists in any given individual as a complex distribution of closely related but nonidentical genomes called a viral quasispecies, which is subject to genetic variation, competition, and selection. This viral diversity clinically manifests as a selection of mutant variants based on viral fitness in treatment-naive individuals and based on drug-selective pressure in those on antiretroviral therapy (ART). The current standard-of-care ART consists of a combination of antiretroviral agents, which ensures maximal viral suppression while preventing the emergence of drug-resistant HIV variants. Unfortunately, transmission of drug-resistant HIV does occur, affecting 5% to >20% of newly infected individuals. To optimize therapy, clinicians rely on viral genotypic information obtained from conventional population sequencing-based assays, which cannot reliably detect viral variants that constitute <20% of the circulating viral quasispecies. These low-frequency variants can be detected by highly sensitive genotyping methods collectively grouped under the moniker of deep sequencing. Low-frequency variants have been correlated to treatment failures and HIV transmission, and detection of these variants is helping to inform strategies for vaccine development. Here, we discuss the molecular virology of HIV, viral heterogeneity, drug-resistance mutations, and the application of deep sequencing technologies in research and the clinical care of HIV-infected individuals.

Entities:  

Keywords:  HIV quasispecies; deep sequencing; low-frequency variants; mutant variants; transmitted drug resistance

Mesh:

Year:  2014        PMID: 24821496     DOI: 10.1146/annurev-genom-091212-153406

Source DB:  PubMed          Journal:  Annu Rev Genomics Hum Genet        ISSN: 1527-8204            Impact factor:   8.929


  9 in total

1.  Establishing Genotypic Cutoff Values To Measure Antimicrobial Resistance in Salmonella.

Authors:  Gregory H Tyson; Shaohua Zhao; Cong Li; Sherry Ayers; Jonathan L Sabo; Claudia Lam; Ron A Miller; Patrick F McDermott
Journal:  Antimicrob Agents Chemother       Date:  2017-02-23       Impact factor: 5.191

2.  Measurement error and variant-calling in deep Illumina sequencing of HIV.

Authors:  Mark Howison; Mia Coetzer; Rami Kantor
Journal:  Bioinformatics       Date:  2019-06-01       Impact factor: 6.937

3.  HIV Drug Resistance Mutations (DRMs) Detected by Deep Sequencing in Virologic Failure Subjects on Therapy from Hunan Province, China.

Authors:  Xi Chen; Xiaobai Zou; Jianmei He; Jun Zheng; Jennifer Chiarella; Michael J Kozal
Journal:  PLoS One       Date:  2016-02-19       Impact factor: 3.240

4.  High levels of pre-treatment HIV drug resistance and treatment failure in Nigerian children.

Authors:  Ragna S Boerma; T Sonia Boender; Kim C E Sigaloff; Tobias F Rinke de Wit; Michael Boele van Hensbroek; Nicaise Ndembi; Titilope Adeyemo; Edamisan O Temiye; Akin Osibogun; Pascale Ondoa; Job C Calis; Alani Sulaimon Akanmu
Journal:  J Int AIDS Soc       Date:  2016-11-10       Impact factor: 5.396

5.  Pre-treatment minority HIV-1 drug resistance mutations and long term virological outcomes: is prediction possible?

Authors:  M L Mzingwane; C T Tiemessen; K L Richter; S H Mayaphi; G Hunt; S M Bowyer
Journal:  Virol J       Date:  2016-10-12       Impact factor: 4.099

6.  Big data or bust: realizing the microbial genomics revolution.

Authors:  Sobia Raza; Leila Luheshi
Journal:  Microb Genom       Date:  2016-02-05

7.  A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

Authors:  Yuri Kravatsky; Vladimir Chechetkin; Daria Fedoseeva; Maria Gorbacheva; Galina Kravatskaya; Olga Kretova; Nickolai Tchurikov
Journal:  Viruses       Date:  2017-11-23       Impact factor: 5.048

8.  High prevalence of HIV-1 transmitted drug-resistance mutations from proviral DNA massively parallel sequencing data of therapy-naïve chronically infected Brazilian blood donors.

Authors:  Rodrigo Pessôa; Sabri S Sanabani
Journal:  PLoS One       Date:  2017-09-27       Impact factor: 3.240

9.  The impact of within-host ecology on the fitness of a drug-resistant parasite.

Authors:  Silvie Huijben; Brian H K Chan; William A Nelson; Andrew F Read
Journal:  Evol Med Public Health       Date:  2018-06-27
  9 in total

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